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Acinetobacter baumannii, a notorious opportunistic pathogen, presents a formidable challenge in both clinical and environmental fields due to its resilience and ability to acquire resistance. This study undertook a comprehensive analysis of 183 A. baumannii isolates collected between 2019 and 2022 from intra-hospital infections (IHI), hospital sewages (Hs), wastewater treatment plants (WWTP), and adjacent river waters from two Southern cities, focusing on their resistome, virulome, and mobilome through isolation on chromogenic media, identification by MALDI-TOF-MS and antibiotic susceptibility testing by disk diffusion) followed by genotypic characterization [Whole Genome Sequencing (WGS), 3rd generation sequencing through the MinION (ONT) platform, pangenome description, and respectively horizontal gene transfer through conjugation assays]. Our findings reveal significant genomic plasticity and the prevalence of high-risk international clones, underlining the potential of these isolates to act as reservoirs for antibiotic resistance genes (ARGs) that could be dynamically exchanged between clinical and environmental settings through mobile genetic elements (MGEs) such as the pMAL1 plasmids and the critical role of WWTPs in the persistence and spread of A. baumannii. Moreover, our study presents the first report of the co-occurrence of blaOXA-23 and blaOXA-72 in A. baumannii ST2 clone. Thus, our research underscores the necessity for integrated surveillance and targeted interventions across healthcare and environmental sectors to mitigate the risk posed by this adaptable pathogen.

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The substantial heterogeneity exhibited by head and neck cancer (HNC), encompassing diverse cellular origins, anatomical locations, and etiological contributors, combined with the prevalent late-stage diagnosis, poses significant challenges for clinical management. Genomic sequencing endeavors have revealed extensive alterations in key signaling pathways that regulate cellular proliferation and survival. Initiatives to engineer therapies targeting these dysregulated pathways are underway, with several candidate molecules progressing to clinical evaluation phases, including FDA approval for agents like the EGFR-targeting monoclonal antibody cetuximab for K-RAS wild-type, EGFR-mutant HNSCC treatment. Non-coding RNAs (ncRNAs), owing to their enhanced stability in biological fluids and their important roles in intracellular and intercellular signaling within HNC contexts, are now recognized as potent biomarkers for disease management, catalyzing further refined diagnostic and therapeutic strategies, edging closer to the personalized medicine desideratum. Enhanced comprehension of the genomic and immunological landscapes characteristic of HNC is anticipated to facilitate a more rigorous assessment of targeted therapies benefits and limitations, optimize their clinical deployment, and foster innovative advancements in treatment approaches. This review presents an update on the molecular mechanisms and mutational spectrum of HNC driving the oncogenesis of head and neck malignancies and explores their implications for advancing diagnostic methodologies and precision therapeutics.

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Background The European Union (EU) faces many health-related challenges. Burden of diseases information and the resulting trends over time are essential for health planning. This paper reports estimates of disease burden in the EU and individual 27 EU countries in 2019, and compares them with those in 2010.Methods We used the Global Burden of Disease 2019 study estimates and 95% uncertainty intervals for the whole EU and each country to evaluate age-standardised death, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) rates for Level 2 causes, as well as life expectancy and healthy life expectancy (HALE).Results In 2019, the age-standardised death and DALY rates in the EU were 465.8 deaths and 20,251.0 DALYs per 100,000 inhabitants, respectively. Between 2010 and 2019, there were significant decreases in age-standardised death and YLL rates across EU countries. However, YLD rates remained mainly unchanged. The largest decreases in age-standardised DALY rates were observed for HIV/AIDS and sexually transmitted diseases and transport injuries (each -19%). Diabetes and kidney diseases showed a significant increase for age-standardised DALY rates across the EU (3.5%). In addition, mental disorders showed an increasing age-standardised YLL rate (14.5%).Conclusions There was a clear trend towards improvement in the overall health status of the EU but with differences between countries. EU health policymakers need to address the burden of diseases, paying specific attention to causes such as mental disorders. There are many opportunities for mutual learning among otherwise similar countries with different patterns of disease. center dot This article, systematically analysing GBD 2019 study estimates, presents an overview of the state of health in the European Union in 2019, compared to 2010.center dot There was an improvement in the overall health status of the EU, despite substantial differences between Member States.center dot Cardiovascular diseases and neoplasms are the major contributors to the overall burden of diseases in the EU in 2019.center dot The age-standardised rate of years lived with disability due to mental disorders has been increasing and is expected to increase even more because of the COVID-19 pandemic.center dot This report provides a framework upon which to base further region- and country-specific health policies and interventions, to support health planning and priority setting.

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Introduction: The ESCPM group ( Enterobacter species including Klebsiella aerogenes - formerly Enterobacter aerogenes, Serratia species, Citrobacter freundii complex, Providencia species and Morganella morganii ) has not yet been incorporated into systematic surveillance programs. Methods: We conducted a multicentre retrospective observational study analysing all ESCPM strains isolated from blood cultures in 27 European hospitals over a 3 -year period (2020-2022). Diagnostic approach, epidemiology, and antimicrobial susceptibility were investigated. Results: Our study comprised 6,774 ESCPM isolates. MALDI-TOF coupled to mass spectrometry was the predominant technique for bacterial identification. Susceptibility to new beta -lactam/ beta -lactamase inhibitor combinations and confirmation of AmpC overproduction were routinely tested in 33.3% and 29.6% of the centres, respectively. The most prevalent species were E. cloacae complex (4 4.8%) and S. marcescens (22.7%). Overall, third -generation cephalosporins (3GC), combined third- and fourthgeneration cephalosporins (3GC + 4GC) and carbapenems resistance phenotypes were observed in 15.7%, 4.6%, and 9.5% of the isolates, respectively. AmpC overproduction was the most prevalent resistance mechanism detected (15.8%). Among carbapenemase-producers, carbapenemase type was provided in 44.4% of the isolates, VIM- (22.9%) and OXA-48-enzyme (16%) being the most frequently detected. E. cloacae complex, K. aerogenes and Providencia species exhibited the most notable cumulative antimicrobial resistance profiles, with the former displaying 3GC, combined 3GC + 4GC and carbapenems resistance phenotypes in 15.2%, 7.4%, and 12.8% of the isolates, respectively. K. aerogenes showed the highest rate of both 3GC resistant phenotype (29.8%) and AmpC overproduction (32.1%), while Providencia species those of both carbapenems resistance phenotype (42.7%) and carbapenemase production (29.4%). ESCPM isolates exhibiting both 3GC and combined 3GC + 4GC resistance phenotypes displayed high susceptibility to ceftazidime/avibactam (98.2% and 95.7%, respectively) and colistin (90.3% and 90.7%, respectively). Colistin emerged as the most active drug against ESCPM species (except those intrinsically resistant) displaying both carbapenems resistance phenotype (85.8%) and carbapenemase production (97.8%). Conclusions: This study presented a current analysis of ESCPM species epidemiology in Europe, providing insights to inform current antibiotic treatments and guide strategies for antimicrobial stewardship and diagnostics. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

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We define the jump complexity of a finite automaton with translucent letters as a function that computes the smallest upper bound on the number of jumps needed by the automaton in order to accept each word of length n, for any positive integer n. We prove that a sufficient condition for a finite automaton with translucent letters to accept a regular language is to have a jump complexity bounded by a constant. Along the same lines, we show that there are languages which require a jump complexity in Omega(n) of any finite automaton with translucent letters accepting one of these languages. We also show that there exist nondeterministic finite automata with translucent letters of jump complexity in O(log n) and O(root n) that accept non-regular languages. Several open problems and directions for further developments are finally discussed.

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Mammalians sense antigenic messages from infectious agents that penetrate the respiratory and digestive epithelium, as well as signals from damaged host cells through membrane and cytosolic receptors. The transduction of these signals triggers a personalized response, depending on the nature of the stimulus and the host's genetics, physiological condition, and comorbidities. Interferons (IFNs) are the primary effectors of the innate immune response, and their synthesis is activated in most cells within a few hours after pathogen invasion. IFNs are primarily synthesized in infected cells, but their anti-infective effect is extended to the neighboring cells by autocrine and paracrine action. The emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in 2019 was a stark reminder of the potential threat posed by newly emerging viruses. This pandemic has also triggered an overwhelming influx of research studies aiming to unveil the mechanisms of protective versus pathogenic host immune responses induced by SARS-CoV-2. The purpose of this review is to describe the role of IFNs as vital players in the battle against SARS-CoV-2 infection. We will briefly characterize and classify IFNs, present the inductors of IFN synthesis, their sensors, and signaling pathways, and then discuss the role of IFNs in controlling the evolution of SARS-CoV-2 infection and its clinical outcome. Finally, we will present the perspectives and controversies regarding the prophylactic and therapeutic potential of IFNs in SARS-CoV-2 infection.

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The imbalance of microbial composition and diversity in favor of pathogenic microorganisms combined with a loss of beneficial gut microbiota taxa results from factors such as age, diet, antimicrobial administration for different infections, other underlying medical conditions, etc. Probiotics are known for their capacity to improve health by stimulating the indigenous gut microbiota, enhancing host immunity resistance to infection, helping digestion, and carrying out various other functions. Concurrently, the metabolites produced by these microorganisms, termed postbiotics, which include compounds like bacteriocins, lactic acid, and hydrogen peroxide, contribute to inhibiting a wide range of pathogenic bacteria. This review presents an update on using probiotics in managing and treating various human diseases, including complications that may emerge during or after a COVID-19 infection.

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We consider networks whose nodes host splicing processors, that is processors that are able to simulate the DNA recombination by splicing. Several topologies for the underlying graph of these networks are investigated. More precisely, we show that each network of splicing processors with some underlying graph can be directly converted into an equivalent network having an underlying graph of a different topology. Several common topologies are considered: full-mesh, star, grid, and wheel (ring-star). We also investigate the time and size complexity of each of these simulations.

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We consider networks whose nodes host splicing processors, that is processors that are able to simulate the DNA recombination by splicing. Several topologies for the underlying graph of these networks are investigated. More precisely, we show that each network of splicing processors with some underlying graph can be directly converted into an equivalent network having an underlying graph of a different topology. Several common topologies are considered: full-mesh, star, grid, and wheel (ring-star). We also investigate the time and size complexity of each of these simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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Motivated by the need of reducing the huge amount of data navigating simultaneously through a network of polarized splicing processors, we look to the possibility of introducing probabilities which theoretically could decrease this amount, at a price of some loss of certainty. We imagined two possible situations regarding the splicing step: to associate either fixed or dynamically computed probabilities with splicing rules in every node. Similarly to the splicing step, two situations could be considered for the communication step depending on the way the probabilities are associated: statically or dynamically. We believe that this new feature together with the communication protocol based on polarization might facilitate software simulations or hardware implementations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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We propose a simulation of an arbitrary network of evolutionary processors by a network having a special underlying graph, namely a wheel (ring-star) graph. This work continues a series of papers devoted to simulations between networks of evolutionary processors with various topologies. Somehow unexpected, the simulation is time complexity preserving at the price of a much larger network.

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Networks of splicing processors are one of the theoretical computational models that take inspiration from nature to efficiently solve problems that our current computational knowledge is not able to. One of the issues restricting/hindering is practical implementation is the arbitrariness of the underlying graph, since our computational systems usually conform to a predefined topology. We propose simulations of networks of splicing processors having arbitrary underlying graphs by networks whose underlying graphs are of a predefined topology: complete, star, and grid graphs. We show that all of these simulations are time efficient in the meaning that they preserve the time complexity of the original network: each computational step in that network is simulated by a fixed number of computational steps in the new topologic networks. Moreover, these simulations do not modify the order of magnitude of the network size.

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Multidrug-resistant Gram-negative bacteria such as Acinetobacter baumannii, Pseudomonas aeruginosa, and members of the Enterobacterales order are a challenging multi-sectorial and global threat, being listed by the WHO in the priority list of pathogens requiring the urgent discovery and development of therapeutic strategies. We present here an overview of the antibiotic resistance profiles and epidemiology of Gram-negative pathogens listed in the ESCAPE group circulating in Romania. The review starts with a discussion of the mechanisms and clinical significance of Gram-negative bacteria, the most frequent genetic determinants of resistance, and then summarizes and discusses the epidemiological studies reported for A. baumannii, P. aeruginosa, and Enterobacterales-resistant strains circulating in Romania, both in hospital and veterinary settings and mirrored in the aquatic environment. The Romanian landscape of Gram-negative pathogens included in the ESCAPE list reveals that all significant, clinically relevant, globally spread antibiotic resistance genes and carrying platforms are well established in different geographical areas of Romania and have already been disseminated beyond clinical settings.

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Simple Summary Despite its small size, the vermiform appendix is an organ with several physiological roles and various pathologies, the most common of which is acute appendicitis. The other pathologies of the vermiform appendix, especially its neoplasia are rare and often go unnoticed and are accidentally identified during appendectomies performed for other reasons. In the early stages, most appendiceal neoplasms are not detected; however, in the advanced stages, they may mimic the symptoms of acute appendicitis. In addition, due to massive mucus production, mucinous neoplasms, especially adenocarcinomas, may fistulize into adjacent structures, some identified after perforated organ pathology. The general treatment for appendiceal pathologies, including neoplasms, is complete surgical excision of the appendix, with or without the right hemicolectomy. Life expectancy is somewhat longer for low-grade mucinous tumors and peaks for well-differentiated, small, metastasis-free neuroendocrine tumors of the appendix occurring in children. The vermiform appendix is a muscular cylindrical structure originating near the junction of the cecum and ileum, averaging 9 cm (5-35 cm) in size. As the most mobile viscera, it can adopt several positions, the most common being the retrocecal position. Perceived as an atavistic organ lacking physiological relevance, the vermiform appendix appears to be involved in immune function, serving in the maturation of B lymphocytes and the production of immunoglobulin A, in endocrine function, excreting amines and hormones in the 2-3 mL of mucus secreted daily, and in digestive function, by storing beneficial bacteria from where they can recolonize the colon. With a lumen of about 6 mm, the vermiform appendix has a reduced storage capacity, so any blockage of the appendix with fecoliths (fecaliths), seeds derailed from the colon, or enlarged lymph nodes prevents drainage and intraluminal accumulation of secreted mucus. Unable to relax, the appendix wall severely limits its intraluminal volume, so mucus accumulation leads to inflammation of the appendix, known generically as appendicitis. In addition, the vermiform appendix may be the site of the development of neoplastic processes, which may or may not involve mucus production, some of which can significantly affect the standard of living and ultimately lead to death. In general, mucinous tumors may have a better prognosis than non-mucinous tumors. This review takes a comprehensive path, starting by describing the anatomy and embryology of the vermiform appendix and further detailing its inflammatory pathologies, pathologies related to congenital anomalies, and appendix tumors, thus creating an up-to-date framework for better understanding, diagnosis, and treatment of these health problems.

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Simple Summary An analysis of the presence of mutations of 105 genes in appendiceal cancers through the lens of the reviewed literature supports the view that in most of them, the inactivation of tumor suppressor genes, such as TP53 and SMAD4, is required in parallel with the reactivation of genes with oncogenic potentials, such as KRAS, GNAS, and BRAF, which support the main tumor processes, cell proliferation, angiogenesis, and evasion of apoptosis. Of all appendiceal cancers, the most mutated genes are reported in mucinous neoplasms of the appendix, not including those in the RAS-RAF-MEK-ERK signaling pathway, followed by low-grade appendiceal mucinous neoplasms, appendiceal goblet cell adenocarcinomas, and mucinous adenocarcinomas of the appendix, in which this signaling pathway is most frequently affected, showing its importance in their tumorigenesis. Microsatellite instability rarely occurs in appendix cancers, being reported only in adenocarcinomas. In appendiceal cancers, the most frequently mutated genes are (i) KRAS, which, when reactivated, restores signal transduction via the RAS-RAF-MEK-ERK signaling pathway and stimulates cell proliferation in the early stages of tumor transformation, and then angiogenesis; (ii) TP53, whose inactivation leads to the inhibition of programmed cell death; (iii) GNAS, which, when reactivated, links the cAMP pathway to the RAS-RAF-MEK-ERK signaling pathway, stimulating cell proliferation and angiogenesis; (iv) SMAD4, exhibiting typical tumor-suppressive activity, blocking the transmission of oncogenic TGFB signals via the SMAD2/SMAD3 heterodimer; and (v) BRAF, which is part of the RAS-RAF-MEK-ERK signaling pathway. Diverse mutations are reported in other genes, which are part of secondary or less critical signaling pathways for tumor progression, but which amplify the phenotypic diversity of appendiceal cancers. In this review, we will present the main genetic mutations involved in appendix tumors and their roles in cell proliferation and survival, and in tumor invasiveness, angiogenesis, and acquired resistance to anti-growth signals.

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Background The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic; characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic; and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings In 2019, at the onset of the COVID-19 pandemic, US$9 center dot 2 trillion (95% uncertainty interval [UI] 9 center dot 1-9 center dot 3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7 center dot 3 trillion (95% UI 7 center dot 2-7 center dot 4) in 2019; 293 center dot 7 times the $24 center dot 8 billion (95% UI 24 center dot 3-25 center dot 3) spent by low-income countries in 2019. That same year, $43 center dot 1 billion in development assistance was provided to maintain or improve health. The pandemic led to an unprecedented increase in development assistance targeted towards health; in 2020 and 2021, $1 center dot 8 billion in DAH contributions was provided towards pandemic preparedness in LMICs, and $37 center dot 8 billion was provided for the health-related COVID-19 response. Although the support for pandemic preparedness is 12 center dot 2% of the recommended target by the High-Level Independent Panel (HLIP), the support provided for the health -related COVID-19 response is 252 center dot 2% of the recommended target. Additionally, projected spending estimates suggest that between 2022 and 2026, governments in 17 (95% UI 11-21) of the 137 LMICs will observe an increase in national government health spending equivalent to an addition of 1% of GDP, as recommended by the HLIP. Interpretation There was an unprecedented scale-up in DAH in 2020 and 2021. We have a unique opportunity at this time to sustain funding for crucial global health functions, including pandemic preparedness. However, historical patterns of underfunding of pandemic preparedness suggest that deliberate effort must be made to ensure funding is maintained.

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This work is a survey of the main results reported for the degree of extension of two models defining non-regular languages, namely the context-free grammar and the extended automaton over groups. More precisely, we recall the main results regarding the degree on non-regularity of a context-free grammar as well as the degree of extension of finite automata over groups. Finally, we consider a similar measure for the finite automata with translucent letters and present some preliminary results. This measure could be considered for many mechanisms that extend a less expressive one. © V. Mitrana, M. Păun This work is licensed under the Creative Commons Attribution License.

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Head and neck cancer (HNC) is the sixth most common type of cancer, with more than half a million new cases annually. This review focuses on the role of oral dysbiosis and HPV infection in HNCs, presenting the involved taxons, molecular effectors and pathways, as well as the HPV-associated particularities of genetic and epigenetic changes and of the tumor microenvironment occurred in different stages of tumor development. Oral dysbiosis is associated with the evolution of HNCs, through multiple mechanisms such as inflammation, genotoxins release, modulation of the innate and acquired immune response, carcinogens and anticarcinogens production, generation of oxidative stress, induction of mutations. Thus, novel microbiome-derived biomarkers and interventions could significantly contribute to achieving the desideratum of personalized management of oncologic patients, regarding both early diagnosis and treatment. The results reported by different studies are not always congruent regarding the variations in the abundance of different taxons in HNCs. However, there is a consistent reporting of a higher abundance of Gram-negative species such as Fusobacterium, Leptotrichia, Treponema, Porphyromonas gingivalis, Prevotella, Bacteroidetes, Haemophilus, Veillonella, Pseudomonas, Enterobacterales, which are probably responsible of chronic inflammation and modulation of tumor microenvironment. Candida albicans is the dominant fungi found in oral carcinoma being also associated with shorter survival rate. Specific microbial signatures (e.g., F. nucleatum, Bacteroidetes and Peptostreptococcus) have been associated with later stages and larger tumor, suggesting their potential to be used as biomarkers for tumor stratification and prognosis. On the other hand, increased abundance of Corynebacterium, Kingella, Abiotrophia is associated with a reduced risk of HNC. Microbiome could also provide biomarkers for differentiating between oropharyngeal and hypopharyngeal cancers as well as between HPV-positive and HPV-negative tumors. Ongoing clinical trials aim to validate non-invasive tests for microbiome-derived biomarkers detection in oral and throat cancers, especially within high-risk populations. Oro-pharyngeal dysbiosis could also impact the HNCs therapy and associated side-effects of radiotherapy, chemotherapy, and immunotherapy. HPV-positive tumors harbor fewer mutations, as well as different DNA methylation pattern and tumor microenvironment. Therefore, elucidation of the molecular mechanisms by which oral microbiota and HPV infection influence the HNC initiation and progression, screening for HPV infection and vaccination against HPV, adopting a good oral hygiene, and preventing oral dysbiosis are important tools for advancing in the battle with this public health global challenge.

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This study aims to demonstrate the effectiveness of silver nanoparticles (Ag NPs) on multidrug-resistant (MDR) Acinetobacter baumannii (AB) strains isolated from the clinical and aquatic environment. Three types of Ag NPs were investigated for their antimicrobial, antibiofilm, and antivirulence properties on a total number of 132 AB strains isolated in the same temporal sequence from intra-hospital infections (IHIs), wastewater (WW), and surface water (SW) samples between 2019 and 2022 from different Romanian locations and characterized at the phenotypic and genotypic levels. The comparative analysis of the antimicrobial resistance (AR) profiles according to the isolation source and the geographical location demonstrated a decrease in MDR level in AB recovered from WW samples in 2022 from north-eastern/central/southern regions (N-E/C-W/analyzed strains S): 87.5/60/32.5%. The AB strains were lecithinase, caseinase, amylase, and lipase producers, had variable biofilm formation ability, and belonged to six genotypes associated with the presence of different virulence genes (ompA, csuE, bap, and bfmS). The Ag NPs synthesized with the solvothermal method exhibited an inhibitory effect on microbial growth, the adherence capacity to the inert substratum, and on the production of soluble virulence factors. We report here the first description of a powerful antibacterial agent against MDR AB strains circulating between hospitals and anthropically polluted water in Romania.

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Nowadays, intensive agriculture correlated with the impact of climate change has led to nutrient soil depletion and the salinization of agricultural lands, making them unsuitable for conventional agricultural crops, with a direct impact on the food industry. Therefore, it is necessary to find sustainable alternative solutions that satisfy the needs of both consumers and food production. One such solution may be represented by salt-tolerant species that can fulfill food requirements. One of the most promising salt-tolerant plant species that can be used is Salicornia europaea L. The present work was conducted in greenhouse conditions, and the adaptability of the species on different cultivation substrates was investigated by means of monitoring the plant indicators such as cuticle, epidermis, parenchyma, polyphenols content, and minerals. Moreover, the correlation between the polyphenol and mineral contents was highlighted. Therefore, three cultivation substrates with different levels of salinity/electrical conductivity were used. The reference (I) for biochemical indicators was represented by the plant grown in natural salinity conditions in the Southeast region of Romania. The results indicate that Salicornia europaea L. can be grown on different cultivation substrates other than salted soils, the plant showing the capacity to accumulate bioactive compounds similar to natively grown ones.

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We continue here the theoretical study initiated approximately twenty years ago on the possibility of using living cells for computing. In this paper, we reconsider the formal operations inspired by the intramolecular DNA rearrangements in the evolution of the macronucleus from the micronucleus in a group of ciliates. After introducing the concept of a valid string, we propose an efficient algorithm for checking this property for a given string. Then we investigate which of the considered operations preserve the property of a string to be valid. We also show that just one of the operations can be simulated by a finite transducer. The important problem regarding the order of applying the operations is then investigated showing that one operation can commute with the other two. Finally, we introduce the iterated variants and investigate a few properties. A sort of a normal form for the gene assembly in ciliates is obtained. The paper ends by a short discussion about open problems and further directions of research.

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The modernization of official statistics involves the use of new data sources, such as data collected through remote sensing. The document contains a description of how an urban green index, derived from the SDG 11.7 objective, was obtained for Romania's 41 county seat cities based on free data sets collected by remote sensing from the European and North American space agencies. The main result is represented by an estimate of the areas of surfaces covered with vegetation for the 40 county seat towns and the municipality of Bucharest, relative to the total surface. To estimate the area covered with vegetation, we used two data sets obtained by remote sensing, namely data provided by the MODIS mission, the TERRA satellite, and data provided by the Sentinel 2 mission from the Copernicus space program. Based on the results obtained, namely the surface area covered with vegetation, estimated in square kilometers, and the percentage of the total surface area or urban green index, we have created a national top of the county seat cities.

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This study aims to demonstrate the effectiveness of silver nanoparticles (Ag NPs) on multidrug-resistant (MDR) Acinetobacter baumannii (AB) strains isolated from the clinical and aquatic environment. Three types of Ag NPs were investigated for their antimicrobial, antibiofilm, and antivirulence properties on a total number of 132 AB strains isolated in the same temporal sequence from intra-hospital infections (IHIs), wastewater (WW), and surface water (SW) samples between 2019 and 2022 from different Romanian locations and characterized at the phenotypic and genotypic levels. The comparative analysis of the antimicrobial resistance (AR) profiles according to the isolation source and the geographical location demonstrated a decrease in MDR level in AB recovered from WW samples in 2022 from north-eastern/central/southern regions (N-E/C-W/analyzed strains S): 87.5/60/32.5%. The AB strains were lecithinase, caseinase, amylase, and lipase producers, had variable biofilm formation ability, and belonged to six genotypes associated with the presence of different virulence genes (ompA, csuE, bap, and bfmS). The Ag NPs synthesized with the solvothermal method exhibited an inhibitory effect on microbial growth, the adherence capacity to the inert substratum, and on the production of soluble virulence factors. We report here the first description of a powerful antibacterial agent against MDR AB strains circulating between hospitals and anthropically polluted water in Romania. © 2023 by the authors.

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We introduce an accepting splicing system based on a type of splicing, multiple splicing, which has never considered so far for accepting systems. This type of splicing differs from the usual operation in that several (not necessarily distinct) rules can be applied simultaneously to the same string. We first consider accepting multiple splicing systems where the number of splicing sites is a predefined constant. We prove that this model is computationally complete, if the constant is 2, by simulating a 2-tag system. Moreover, we show that the simulation is time-complexity preserving, and discuss also the descriptional complexity of the accepting splicing system given by our construction. We then consider the accepting multiple splicing systems where the number of sites has either an upper bound or a lower bound. The computational power of these systems is also investigated. We finally discuss some open problems. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.

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The current paper estimated the physico-chemical properties of water in the Danube Delta (Romania), based on Sentinel 2 remote sensing data. Eleven sites from the Danube Delta were sampled in spring and autumn for three years (2018-2020) and 21 water physico-chemical parameters were measured in laboratory. Several families of machine learning algorithms, translated into hundreds of models with different parameterizations for each machine learning algorithm, based on remote sensing data input from Sentinel 2 spectral bands, were employed to find the best models that predicted the values measured in laboratory. This was a novel approach, reflected in the types of selected models that minimised the values of performance metrics for the tested parameters. For alkalinity, calcium, chloride, carbon dioxide, hardness, potassium, sodium, ammonium, dissolved oxygen, sulphates, and suspended matter the results were promising, with an overall percentage bias of the estimates of +/- 10% from the observed values. For copper, magnesium, nitrites, nitrates, turbidity and zinc the estimates were fairly accurate, with percentage biases in the interval +/- 10% - 20%, whereas for detergents, led, and phosphates the percentage bias was higher than 20%. Overall, the results of the current study showed fairly good estimates between remote sensing based estimates and laboratory measured values for most water physico-chemical parameters.

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The aim of this work is to optimize the supercritical liquefaction process of rapeseeds in order to produce a bio-oil with low viscosity. Reaction parameters, such as reaction temperature, residence time, and solvent to biomass ratio, were studied. Response surface methodology (RSM) based on central composite design (CCD) was used to determine the optimum operating conditions to minimize the bio-oil viscosity. The low bio-oil viscosity of 5.90 mPa.s was obtained at the optimal operating conditions of 280 degrees C, 40 min, and methanol/biomass mass ratio of 5.5/1, at pressure within the batch reactor of 124.59 bars. At these optimal conditions, the bio-oil yield was high and reached around 80wt%, while its heating value was about 38.36MJ/kg. It was proved that the reaction temperature and methanol/biomass ratio were the most influencing parameters on bio-oil viscosity according to the ANOVA results. The predicted values from the RSM model was in good agreement with the experimental results. The GC-MS analysis showed that the bio-oil is mainly composed of methyl esters, which are the main components of biodiesel. This study revealed the complete supercritical transesterification of lipid into alkyl esters resulting in a low amount of triglycerides, monoglycerides, diglycerides, and glycerin, identified by GC-FID. The results will provide useful guidance for predicting other physical properties of bio-oil following a similar methodology to that used in this work. In addition, bio-oil could be used for biodiesel fuel production but after hydrodeoxygenation treatment.

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Considering the broad impact of applied research on the economy, RDI funding evaluations are required both in terms of the number of allocated resources and the management of these resources. RDI efficacy depends on human resources productivity and the financing instruments established through national priorities. This paper offers an analysis of the RDI investments in Romania allocated through the Competitiveness Operational Programme 2014-2020, covering the European Structural and Investment Funds, namely the European regional development fund. The analysis of the funded projects highlighted the common trends among the beneficiaries of RDI projects, their options in managing resources in relation to the eligibility of costs, and their national distribution between the seven development regions of Romania. The amount of funding was discussed in terms of the smart specialization domains established by the national strategy. The conclusions of the study, correlated with the objectives set by the SNCDI 2014-2020, are relevant for the management of the future funding instruments allocated to RDI by the ERDF in the period 2021-2027.

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This paper aimed to investigate the conversion of sunflower seeds to bio-char through hydrothermal liquefaction (HTL) process. The effect of reaction temperature (X-1, 240-320 degrees C), residence time (X-2, 10-60 min) and biomass/solvent ratio (X-3 , 20-80%) was analyzed and optimized using full factorial design of response surface methodology. The developed regression model gave accurate predictions and fitted well with the experimental results with a determination coefficient R-2 of 92.89%. The optimized conditions for bio-char production have been found to be 240 degrees C, 60 min and 20%, temperature, time and biomass to solvent ratio, respectively. These optimum values were validated by experimental runs which produced a bio-char yield of 32.24 wt% with higher heating value of 32.24 MJ/kg and high carbon content of 65.45%. The quadratic model revealed a strong interaction between reaction temperature and residence time, as well as, reaction temperature and biomass/solvent ratio. Based on the thermal decomposition mechanism of bio-char, derivative thermogravimetry revealed two major peaks were observed at 275 and 400 degrees C indicating the improvement in thermal stability of the bio-char after HTL process. In addition, the obtained bio-chars were different in terms of their organic and ash content depending on the HTL operating conditions.

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Since 2021, the National Evaluation exam in Romania (the exam aimed to assess 14- to 15-year-old students' knowledge at the end of lower secondary education and just before high school) has presented a novel examination structure that resembles PISA tests. The current investigation analyses the 2021 National Evaluation exam results compared to the results obtained in the previous two years (2019-2020) as an evaluation of upper education institutions' effectiveness in Romania. The results put forward the same conclusions as proposed by extant literature on Bucharest high schools. Even though the educational institutions show apparent progress and great adaptability to change, a more in-depth analysis reveals great inequality between educational institutions. As in the case of Bucharest, nationally there are only a small number of top-performing high schools in Romania, with the majority of high schools ranking in the lowest category as conceptualised in the study. The current investigation puts together a novel methodology for classification based on the main instruments proposed in literature: a letter grade classification and Turner's f-index. The results and the methodological proposal are especially relevant considering the latest PISA (2018) conclusions on Romania characterising the national educational system as underperforming.

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To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

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Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

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Background: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). Interpretation: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

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Impact on aquatic ecosystems from intensive agriculture can be mitigated through a variety of structural and management conservation practices. This article provides an overview of the main Best Management Practices (BMP) for reducing direct or indirect detrimental impact from agriculture on inland waters’ quality and ecological status. The BMP's have been shown to be more efficient compared to conventional ones and comprise a set of recommendations that should be considered carefully by environmental scientists, stakeholders, farmers and land-owners alike. © 2022 Elsevier Inc. All rights reserved

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New global directions align agricultural land resources towards food production; therefore, marginal lands could provide opportunities for second-generation energy crops, assuming that in the difficult conditions of plant development, productivity can be maintained at relatively high levels. Sustainable bioenergy production on marginal lands represents an ambitious objective, offering high-quality biofuels without competing with the agri-food industry, since it allows successful feedstock production to be performed on unmanaged areas. However, marginal land feedstock production generally shows several agronomic, techno-economic, and methodological challenges, leading to decreases in the obtained quantities of biomass and profitability. Sweet Sorghum is a technical plant that has the needed qualities to produce large amounts of biofuels on marginal lands. It is a high biomass-and sugar-yielding crop, characterized by a high photosynthetic efficiency and low fertilizer requirement, is resistant to drought, and adapts well to different climate areas. Marginal lands and contaminated soils provide a favorable development environment for plants such as sweet sorghum; however, in-depth research studies on biomass productivity must be carried out, as well as advanced quality evaluation of the products, in order to develop combined technologies that use resources efficiently. The present study starts with a comparative evaluation of two sweet sorghum crops established on both marginal and regular lands, assessing plant development characteristics and juice production, and an evaluation of bioethanol generation potential. The vegetal wastes resulting from the processing were treated by pyrolysis, with the aim of maximizing the productivity of high-quality liquid biofuels and chemicals. The charcoal obtained in the thermal processes was considered as an amendment of the soil so that marginal land quality could be improved over time. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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Networks of splicing processors (NSP for short) embody a subcategory among the new computational models inspired by natural phenomena with theoretical potential to handle unsolvable problems efficiently. Current literature considers three variants in the context of networks managed by random-context filters. Despite the divergences on system complexity and control degree over the filters, the three variants were proved to hold the same computational power through the simulations of two computationally complete systems: Turing machines and 2-tag systems. However, the conversion between the three models by means of a Turing machine is unattainable because of the huge computational costs incurred. This research paper addresses this issue with the proposal of direct and efficient simulations between the aforementioned paradigms. The information about the nodes and edges (i.e., splicing rules, random-context filters, and connections between nodes) composing any network of splicing processors belonging to one of the three categories is used to design equivalent networks working under the other two models. We demonstrate that these new networks are able to replicate any computational step performed by the original network in a constant number of computational steps and, consequently, we prove that any outcome achieved by the original architecture can be accomplished by the constructed architectures without worsening the time complexity.

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The paper presents the biological variation in biochemical compounds of fruits belonging to Ribes nigrum L. species during the maturation process. The fruits from two varieties were collected in the following phenological stages: early first fruits (SIII), advanced first fruit (SIV), harvesting maturity (SV), and consumption maturity (SVI). The extracts were subjected to analysis. Total phenolic content (TPC) expressed as gallic acid equivalent (GAE), total flavonoid content (TFC) expressed as rutin equivalent (RE), and free radical scavenging activity (FRSA) expressed as mg/mL ascorbic acid equivalent (AAE), and gas-chromatographic profile were determined. The phenolic content differed considerably during the maturation process. Thus, the maximum value of TPC was achieved by 'Kzvana' fruits in the SV stage with 7.36 mM GAE/ml extract. The flavonoid content was highlighted in 'Roxia' fruits in the SVI stage with 1.24 mM RE/mL extract. With regard to FRSA, 'Kzvana' fruits have better activity. Also, the aromatic profile was characterized using gas chromatographic analysis.

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To avoid the transformation of the dependent variable, which introduces bias when back-transformed, complex nonlinear forest models have the parameters estimated with heuristic techniques, which can supply erroneous values. The solution for accurate nonlinear models provided by Strimbu et al. (Ecosphere 8:e01945, 2017) for 11 functions (i.e., power, trigonometric, and hyperbolic) is not based on heuristics but could contain a Taylor series expansion. Therefore, the objectives of the present study are to present the unbiased estimates for variance following the transformation of the predicted variable and to identify an expansion of the Taylor series that does not induce numerical bias for mean and variance. We proved that the Taylor series expansion present in the unbiased expectation of mean and variance depends on the variance. We illustrated the new modeling approach on two problems, one at the ecosystem level, namely site productivity, and one at individual tree level, namely stem taper. The two models are unbiased, more parsimonious, and more precise than the existing less parsimonious models. This study focuses on research methods, which could be applied in similar studies of other species, ecosystem, as well as in behavioral sciences and econometrics.

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Currently, the entire world is facing major challenges related to agricultural practices and heavy metals contaminations of agricultural systems and food production. On the other hand, the structure, texture, and properties of the soil have deteriorated as a result of intensive conventional agriculture based on the addition of different inputs. Along with these, toxic metals affect agricultural soils, crops, food chain, becoming a major threat to living systems. Among these is chromium (Cr), an element naturally occurring in rocky soils and volcanic dust. The increased use of chromium in several multiple activities causes soil and water contamination. Differently from other heavy metals like lead, cadmium, and copper, chromium presents different degrees of toxicity depending on its chemical form. In the present review, we present data regarding chromium abundance in agricultural systems, factors favouring the absorption in the plant and bioaccumulation in different organs and tissues, bioaccumulation and translocation factors, its toxicity in plants, animals, and human through the food chain, and how it can be quantified using different types of analysis.

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Bio-oil production from sunflower seeds, as model components, was carried out in supercritical hydrothermal liquefaction conditions. The effects of operating parameters such as temperature, time, and biomass/solvent mass ratio were investigated. Response surface methodology based on full factorial design was utilized to optimize the operating conditions using Design Expert software. From the analysis of variance, the most influential factor of each experimental design response was identified and a regression model was derived. The results show that the quadratic polynomial model provided accurate predictions for bio-oil yield and its viscosity, with a determination coefficient R-2 of 0.9120 and 0.9351, respectively. The optimum condition was 286.21 degrees C, a reaction time of 12 min, and 20% of biomass/solvent mass ratio. These conditions led to obtain 79.96 wt.% of bio-oil with a viscosity of 18.09 mPa s. The produced bio-oil was subjected to different analyses and characterized by gas chromatography-mass spectrometry. Besides, ether esters were identified as major components. Bio-oil properties were evaluated according to standard norms, and the results suggest the need of further upgrading step to improve its quality.

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Current advances in computational modelling and simulation have led to the inclusion of computer scientists as partners in the process of engineering of new nanomaterials and nanodevices. This trend is now, more than ever, visible in the field of deoxyribonucleic acid (DNA)-based nanotechnology, as DNA's intrinsic principle of self-assembly has been proven to be highly algorithmic and programmable. As a raw material, DNA is a rather unremarkable fabric. However, as a way to achieve patterns, dynamic behavior, or nano-shape reconstruction, DNA has been proven to be one of the most functional nanomaterials. It would thus be of great potential to pair up DNA's highly functional assembly characteristics with the mechanic properties of other well-known bio-nanomaterials, such as graphene, cellulos, or fibroin. In the current study, we perform projections regarding the structural properties of a fibril mesh (or filter) for which assembly would be guided by the controlled aggregation of DNA scaffold subunits. The formation of such a 2D fibril mesh structure is ensured by the mechanistic assembly properties borrowed from the DNA assembly apparatus. For generating inexpensive pre-experimental assessments regarding the efficiency of various assembly strategies, we introduced in this study a computational model for the simulation of fibril mesh assembly dynamical systems. Our approach was based on providing solutions towards two main circumstances. First, we created a functional computational model that is restrictive enough to be able to numerically simulate the controlled aggregation of up to 1000s of elementary fibril elements yet rich enough to provide actionable insides on the structural characteristics for the generated assembly. Second, we used the provided numerical model in order to generate projections regarding effective ways of manipulating one of the the key structural properties of such generated filters, namely the average size of the openings (gaps) within these meshes, also known as the filter's aperture. This work is a continuation of Amarioarei et al., 2018, where a preliminary version of this research was discussed.

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This paper is part of the investigation of some operations on words and languages with motivations coming from DNA biochemistry, namely three variants of hairpin completion and three variants of hairpin reduction. Since not all the hairpin completions or reductions of semilinear languages remain semilinear, we study sufficient conditions for semilinear languages to preserve their semilinearity property after applying the non-iterated hairpin completion or hairpin reduction. A similar approach is then applied to the iterated variants of these operations. Along these lines, we define the hairpin reduction root of a language and show that the hairpin reduction root of a semilinear language is not necessarily semilinear except the universal language. A few open problems are finally discussed.

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Many experiments cannot feasibly be conducted as factorials. Simulations using synthetically generated data are viable alternatives to such factorial experiments. The main objective of the present research is to develop a methodology and platform to synthetically generate spatially explicit forest ecosystems represented by points with a predefined spatial pattern. Using algorithms with polynomial complexity and parameters that control the number of clusters, the degree of clusterization, and the proportion of nonrandom trees, we show that spatially explicit forest ecosystems can be generated time efficiently, which enables large factorial simulations. The proposed method was tested on 1200 synthetically generated forest stands, each of 25 ha, using 10 spatial indices: Clark-Evans aggregation index; Ripley's K; Besag's L; Morisita's dispersion index; Greig-Smith index; the size dominance index of Hui; index of nonrandomness of Pielou; directional index and mean directional index of Corral-Rivas; and size differentiation index of Von Gadow. The size of individual trees was randomly generated aiming at variograms such as real forests. We obtained forest stands with the expected spatial arrangement and distribution of sizes in less than 1 h. To ensure replicability of the study, we have provided free, fully functional software that executes the stated tasks.

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We define and investigate a complexity measure defined for extended finite automata over groups (EFA). Roughly, an EFA is a finite automaton augmented with a register storing an element of a group, initially the identity element. When a transition is performed, not only the state, but the register contents are updated. A word is accepted if, after reading completely the word, the automaton reached a final state, and the register returned to the identity element. The group memory complexity of an EFA over a group is a function from N to N which associates with each n the value 0, if there is no word of length n accepted by the automaton, or the minimal integer c such that for every word x of length n accepted by the automaton, there is a computation on x such that the number of transitions labeled by non-neutral element of the group used in that computation is at most c. We prove that a language is regular if and only if it is accepted by an EFA with a finite group memory complexity. In particular, any EFA over a group such that all its finitely generated subgroups are finite accepts a regular language. We then provide examples of EFA over some groups that accept non-regular languages and have a sublinear group memory complexity, namely a function in O(root n) or O(log n). There are non-regular languages such that any EFA over some group that accepts that language has a group memory complexity in Omega(n). (C) 2020 Elsevier Inc. All rights reserved.

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Due to the wide worldwide spread the COVID-19 pandemic has reached at the beginning of 2020, many countries have imposed strict measures of social distancing, the result of which was a sudden shift towards the online environment for most institutions of each state. This study explores students' perception of the quality of online education during the COVID-19 pandemic, right after the shift from traditional face-to-face learning to online education. Using an online questionnaire, feedback from the respondents regarding their perception of online education, sources of information used and preventive behavior is collected. A total of 238 students from different levels and fields participated in the study which concludes with a general opinion reflecting that although in favor of online education, students are unsure if the quality of it matches the quality of the traditional face-to-face education.

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We investigated the computational power of a new variant of network of splicing processors, which simplifies the general model such that filters remain associated with nodes but the input and output filters of every node coincide. This variant, callednetwork of uniform splicing processors, might be implemented more easily. Although the communication in the new variant seems less powerful, the new variant is sufficiently powerful to be computationally complete. Thus, nondeterministic Turing machines were simulated by networks of uniform splicing processors whose size depends linearly on the alphabet of the Turing machine. Furthermore, the simulation was time efficient. We argue that the network size can be decreased to a constant, namely six nodes. We further show that networks with only two nodes are able to simulate 2-tag systems. After these theoretical results, we discuss a possible software implementation of this model by proposing a conceptual architecture and describe all its components.

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The parameters of nonlinear forest models are commonly estimated with heuristic techniques, which can supply erroneous values. The use of heuristic algorithms is partially rooted in the avoidance of transformation of the dependent variable, which introduces bias when back-transformed to original units. Efforts were placed in computing the unbiased estimates for some of the power, trigonometric, and hyperbolic functions since only few transformations of the predicted variable have the corrections for bias estimated. The approach that supplies unbiased results when the dependent variable is transformed without heuristic algorithms, but based on a Taylor series expansion requires implementation details. Therefore, the objective of our study is to investigate the efficient expansion of the Taylor series that should be included in applications, such that numerical bias is not present. We found that five functions require more than five terms, whereas the arcsine, arccosine, and arctangent did not. Furthermore, the Taylor series expansion depends on the variance. We illustrated the results on two forest modeling problems, one at the stand level, namely site productivity, and one at individual tree level, namely taper. The models that are presented in the paper are unbiased, more parsimonious, and they have a RMSE comparable with existing less parsimonious models.

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Antimicrobial resistance (AMR) is a significant global threat to both public health and the environment. The emergence and expansion of AMR is sustained by the enormous diversity and mobility of antimicrobial resistance genes (ARGs). Different mechanisms of horizontal gene transfer (HGT), including conjugation, transduction, and transformation, have facilitated the accumulation and dissemination of ARGs in Gram-negative and Gram-positive bacteria. This has resulted in the development of multidrug resistance in some bacteria. The most clinically significant ARGs are usually located on different mobile genetic elements (MGEs) that can move intracellularly (between the bacterial chromosome and plasmids) or intercellularly (within the same species or between different species or genera). Resistance plasmids play a central role both in HGT and as support elements for other MGEs, in which ARGs are assembled by transposition and recombination mechanisms. Considering the crucial role of MGEs in the acquisition and transmission of ARGs, a potential strategy to control AMR is to eliminate MGEs. This review discusses current progress on the development of chemical and biological approaches for the elimination of ARG carriers.

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The present study is part of a comprehensive study dedicated to the cultivation of halophytes species on salt affected soils, aiming on new value chains development from obtained biomass. The work is conducted on the monitoring the degree of soil purification, the biomass production and seeds yield, and their chemical composition. In this context, the paper contains information related to the oil content of Portulaca saliva sp. seeds, in order to produce 2nd generation biofuels. Extraction of oil from seeds via traditional method (Saxhlet method) and accelerated solvent extraction (ASE) were carried out. ASE method was applied because requires small quantities of solvent, sample and operating time. ASE appear to be the most suitable method and the optimal conditions were: pressure - 10.34 AlPa, temperature - 105 degrees C, residence time - 10 min, solvent - petroleum ether, extraction ratio of 1:40, dynamic extraction time - 30 min. and 0.3 g diatomaceous earth. The highest oil recovery achieved was 33.4%.

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Since its introduction in the early 2000s, DNA origami had a big impact on the development of nanotechnology by gathering numerous applications. During this time, many tools were designed and used to generate arbitrary shapes capable of self-assembly which make this technique more approachable. In this paper, we have created the map of Romania at nanoscale dimensions by using a new open-source software - PERDIX. For this purpose, we used a scaffold strand with a length of 6959 nucleotides and 162 staple strands with a variable length ranging between 20 and 63 nucleotides. All the computational tools that were used in this experiment are open-source and user-friendly.

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We define a variant of accepting splicing system that can be used as a problem solver. A condition for halting the computation on a given input as well as a condition for making a decision as soon as the computation has stopped is considered. An algorithm based on this accepting splicing system that solves a well-known NP-complete problem, namely the 3-colorability problem is presented. We discuss an efficient solution in terms of running time and additional resources (axioms, supplementary symbols, number of splicing rules. More precisely, for a given graph with n vertices and m edges, our solution runs in O (nm) time, and needs O (mn(2)) other resources. Two variants of this algorithm of a reduced time complexity at an exponential increase of the other resources are finally discussed.

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An intriguing problem in computer science is the formal description of dynamics in cell populations. We propose here a multi-agent-based model that could be used in this respect. The model proposed in this paper consists of biological entities (cells) as agents and a biochemical environment. Both are represented by multisets of symbols. The environment evolution is regulated by multiset Lindenmayer rules depending on the current state of all agents, while the evolution of each agent, which depends on the environment current state, is defined by means of multiset patterns. We discuss some algorithmic problems related to the dynamics of the proposed multi-agent model: infinite and stationary evolution, environment, and agent reachability.

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We continue the investigation of three operations on words and languages with motivations coming from DNA biochemistry, namely unbounded and bounded hairpin completion and hairpin lengthening. We first show that each of these operations can be used for replacing the third step, the most laborious one, of the solution to the CNF-SAT reported in [28]. As not all the bounded/unbounded hairpin completion or lengthening of semilinear languages remain semilinear, we study sufficient conditions for semilinear languages to preserve their semilinearity property after applying once either the bounded or unbounded hairpin completion, or lengthening. A similar approach is then started for the iterated variants of the three operations. A few open problems are finally discussed.

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In this moment plastics provide a fundamental contribution in all activity fields: cars, aircraft, electronics, building, domestic daily activities, packing, etc. so the consumption of plastics has increased drastically. The disposal of plastic composite wastes is a serious environmental problem as they are not biodegradable. As a consequence, our work is focused in recycling of carbon fibers and glass fibers from waste composites through pyrolysis and partial oxidation.

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The Tile Assembly Model, and its many variants, is one of the most fundamental algorithmic assembly formalism within DNA nanotechnology. Most of the research in this field is focused on the complexity of assembling different shapes and patterns. In many cases, the assembly process is intrinsically deterministic and the final product is unique, while the assembly process might evolve through several possible assembly strategies. In this study we consider the controlled assembly of one dimensional tile structures according to predefined assembly graphs. We provide algorithmic approaches for developing such controlled assembly protocols, using the signal-passing Tile Assembly Model, as well as probabilistic approaches for investigating the assembly of such tile-based one-dimensional structures. As a byproduct, we build a generalized TAS (tile assembly system) which generate specific non-local non-associative algebraic computations and we assamble n x n squares using only one tile, which is a better efficiency compared to the staged assembly model. (C) 2019 The Authors. Published by Elsevier B.V.

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Applied pyrolysis is used in this work as a treatment technique for hydrocarbon fraction recovery of used lubricating oils (ULO) with the aim of its further energetic valorisation. Applied pyrolysis bring also the advantage of a better management of metallic compounds that will be concentrated in the solid residue. In this work, technical parameters have been evaluated to establish their influence on the process evolution with the aim of identifying the adequate parameters for obtaining the maximum liquid fraction. It was found that, for an equilibrated energy balance, the final pyrolysis temperature should not exceed 460 degrees C and the main parameter that affect the pyrolysis oil yield and its physical-chemical properties is the heating rate in the thermal range of decomposition. Activated Zeolites (HZSM-5 type) and Na2CO3 were used as catalysts. The catalysed pyrolysis tests were performed using direct contact between ULO and catalyst, the materials being mixed before processing. Experimental results showed that in non-catalysed pyrolysis an increasing heating rate is slightly reducing the yield of liquid fraction. On the other hand, by using catalysts, the liquid fraction is decreasing. Thus, the highest liquid ratio (81 wt. %) was obtained when the Na2O3 is used and the process is run under a heating rate of 3-5 degrees C/min. But then, the zeolite HZSM-5 is leading to the highest overall conversion, 95 wt. % at 15-17 degrees C/min, and is positively influence the formation of gas fractions.

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This paper presents the elemental content found in two saline soil samples with a certain electrical conductivity and the differences between two variants of extraction. The soil samples collected from a region in South-East of Romania affected by salinization process were investigated using a semi quantitative (SMA) inductively coupled plasma with mass spectrometry analysis (ICP-MS). Thus, the multi-elemental analysis of soil samples was preceded by one-step digestion in a high-pressure microwave system. For matrix destruction two mixtures of reagents were used: A - HNO3, HCl and H2O2 in 3:1:1 (v/v), and B - HNO3, HCl 3:1 (v/v). The electrical conductivity was realized using an adapted method, and the value was up to 10000 dS/m. Following semiquantitative analysis, the results showed that both of extraction methods showed the same elemental composition, the difference being only of the quantity of each element. Regarding the extraction efficiency, mixture A was more suitable for this type of soil.

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A plethora of forest models were developed by transforming the dependent variable, which introduces bias if appropriate corrections are not applied when back-transformed. Many recognized models are still biased and the original data sets are no longer available, which suggests ad hoc bias corrections. The present research presents a procedure for bias correction in the absence of needed information from summary statistics. Additionally, we developed a realistic correction of the square root transformation based on a truncated normal distribution. The transformations considered in this study are the logarithm, the square root and arcsine square root. Using simulated data we found that uncorrected back-transformation created biases by as much as 100 percent. The generated data revealed that depending on available information, that bias can still be present after correction. In addition to generated data we corrected the site index of Douglas-fir and ponderosa pine in Oregon USA, tree volume of 27 species from Romania, stand merchantable volume for longleaf pine in Louisiana and East Texas USA, and canopy fuel weight in Washington USA. Using only the available information, the unbiased back-transformed estimates can change from <= 1 percent (i.e. the site index and canopy fuel weight) to >= 1/3 (tree and stand volume).

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Advancements in information technology led environmental scientists to the illusion that efforts should be mainly focused on developing models that reduce uncertainty rather than on models adjusted to the existing uncertainty. As a result, environmental relationships are represented by non-parsimonious and suboptimal models, which in many instances could be even wrong. The objective of this research was to provide scientists focused on modeling ecosystem processes with a procedure that supplies parsimonious correct results. The procedure transforms the response variable to achieve a linear model and the normality of the residuals. After the parameters of the transformed model are estimated, the bias induced by back-transforming is corrected. We have computed the bias corrections for 11 of the most popular functions from the power, trigonometric, and hyperbolic families by considering the truncated normal distribution, when necessary. Using generated data, we have shown that the proposed procedure supplies unbiased results. We have identified a sample size artifact of data generation such that when the variance increases the truncation of distribution starts altering the corrections of predicted values, sometimes by more than 50% from the actual values. Our results indicate that uncertainty, measured by variance, impacts the analysis in a non-intuitive way when the defining domain of the response variable is restricted. The subtle way of influencing the development of complex nonlinear models by uncertainty advocates the usage of parsimonious linear models, which are less sensitive to the method of processing data. Finally, ecosystem processes should be modeled with strategies that consider not only processes and computation aspects, but also uncertainty, in particularly reducing variance to levels with no significant impact on the results.

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In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. With two more nodes we can simulate every nondeterministic Turing machine without increasing the time complexity. Particularly, we prove that NPSP of size 4 can accept all languages in NP in polynomial time. Furthermore, another computational model that is universal, namely the 2-tag system, can be simulated by NPSP of size 3 preserving the time complexity. All these results can be obtained with NPSPs with valuations in the set as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of this simulation.

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The tree species composition of a forest ecosystem is commonly represented with weights that measure the importance of one species with respect to the other species. Inclusion of weight in practical applications is difficult because of the inherent multidimensional perspective on composition. Scalar indices overcome the multidimensional challenges, and, consequently, are commonly present in complex ecosystem modeling. However, scalar indices face two major issues, namely non-uniqueness and non-measurability, which limit their ability to be generalized. The objective of this study is to identify the conditions for developing a univariate true measure of composition from weights. We argue that six conditions define a scalar measure of species mixture: (1) usefulness, (2) all species have equal importance, (3) all individuals have the same importance, (4) the measurements expressing importance of an individual are consistent and appropriate, (5) the function measuring composition is invertible, and (6) the function is a true-measure. We support our argument by formally proving all the conditions. To illustrate the applicability of the scalar measure we develop a rectilinear-based measure, and apply it in yield modeling and assessment of ecosystem dynamics. (C) 2018 Elsevier B.V. All rights reserved.

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The aim of this paper is to discuss two possible ways of introducing some features based on probabilistic concepts and methods in networks of polarized evolutionary processors (NPEP). We associate probabilities with rules in every node such that together with the communication protocol, which is based on the compatibility between the polarization of each node and data navigating through the network, might facilitate the study of biological phenomena as well as software simulations or hardware implementations. The probability associated with rules may be a priori defined and fixed or may be computed dynamically. Probabilities will also appear when communicating data between nodes; these probabilities may be statically or dynamically defined. This note also proposes the study of the impact of these characteristics and see how these new features reduce the gap between the formal model and its practical applicability. Introducing probabilities in NPEP is aimed to decrease the exponential expansion of the number of strings which appear in the computations used to solve NP-problems in a polynomial time. A decreasing of the exponential expansion of this number is achieved with a loss of certainty of the final result which is reached with some error probability.

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This paper presents the latest trends and approaches used for constructing nanoscale structures of 2D objects through DNA folding based on the DNA origami technology developed by Rothemund. The Rothemund method has been used in the construction of various shapes, such as the development of the nanoscale structure for the United States map. Following the steps of Rothemund's technique, we simulate the construction of the Romanian map nanoscale 2D structure, embedding the number 100 into it.

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Investigation of the lake systems can provide a variety of information that can lead to the development of general concepts about how lakes function and respond to environmental changes. The purpose of this study is to assess the current classification of therapeutic lakes based on supervised learning methods applied to several biochemical characteristics of such lakes. In order to classify the therapeutic lakes in a separate class, a dataset consisting of 45 observations from 9 different basins and from three different altitude categories was analysed using clustering and classification methods.

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The TAM (Model Tile Assembly Model) is a mathematical paradigm for modeling DNA self-assembling according to various given shapes, using DNA-tiles (rectangular shape) with sticky ends on each of the four edges that bound together on various shapes desired by the researcher. Although there are various models in the literature, the focus in this manuscript is on a rule based model, specifically the authors present an overview of the one-dimensional hierarchical self-assembly model of DNA tiles. The authors also present the evolution of number of tiles in partial assemblies, the average assembly size and of the number of partial assemblies of sizes 2 through 10 over the total running time. All simulations were run using the NFSim simulator on a preset period of time.

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Screening of 1,000-years old ice layers from the perennial ice block of Scarisoara Ice Cave (NW Romania) revealed the presence of fungal communities. Using culture-dependent methods and molecular techniques based on DGGE fingerprinting of 18S rRNA gene fragments and sequencing, we identified 50 cultured and 14 uncultured fungi in presently-forming, 400 and 900 years old ice layers, corresponding to 28 distinct operational taxonomic units (OTUs). The dominant ice-contained fungal OTUs were related to Ascomycota, Basidiomycota and Cryptomycota phyla. Representatives of Mucoromycota and Chytridiomycota were also isolated from recent and 400 years old ice samples. The cryophilic Mrakia stokesii was the most abundant fungal species found in the cave ice samples of all prospected ages, alongside other cryophilic fungi also identified in various glacial environments. Ice deposits formed during the Little Ice Age (dated between AD 1,250 and 1,850) appeared to have a higher fungal diversity than the ice layer formed during the Medieval Warm Period (prior to AD 1,250). A more complex fungal community adapted to low temperatures was obtained from all analyzed ice layers when cultivated at 4 degrees C as compared to 15 degrees C, suggesting the dominance of cold-adapted fungi in this glacial habitat. The fungal distribution in the analyzed cave ice layers revealed the presence of unique OTUs in different aged-formed ice deposits, as a first hint for putative further identification of fungal biomarkers for climate variations in this icy habitat. This is the first report on fungi from a rock-hosted cave ice block.

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Screening of 1,000-years old ice layers from the perennial ice block of Scǎrişoara Ice Cave (NW Romania) revealed the presence of fungal communities. Using culture-dependent methods and molecular techniques based on DGGE fingerprinting of 18S rRNA gene fragments and sequencing, we identified 50 cultured and 14 uncultured fungi in presently-forming, 400 and 900 years old ice layers, corresponding to 28 distinct operational taxonomic units (OTUs). The dominant ice-contained fungal OTUs were related to Ascomycota, Basidiomycota and Cryptomycota phyla. Representatives of Mucoromycota and Chytridiomycota were also isolated from recent and 400 years old ice samples. The cryophilic Mrakia stokesii was the most abundant fungal species found in the cave ice samples of all prospected ages, alongside other cryophilic fungi also identified in various glacial environments. Ice deposits formed during the Little Ice Age (dated between AD 1,250 and 1,850) appeared to have a higher fungal diversity than the ice layer formed during the Medieval Warm Period (prior to AD 1,250). A more complex fungal community adapted to low temperatures was obtained from all analyzed ice layers when cultivated at 4 °C as compared to 15 °C, suggesting the dominance of cold-adapted fungi in this glacial habitat. The fungal distribution in the analyzed cave ice layers revealed the presence of unique OTUs in different aged-formed ice deposits, as a first hint for putative further identification of fungal biomarkers for climate variations in this icy habitat. This is the first report on fungi from a rock-hosted cave ice block. © 2018 The Author(s).

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this paper we present an improvement of the Segment Based Contours (SBC) method by implementing a higher order of finite difference schemes in the partial differential equation used in our mathematical model. Two methods are presented: one is a 4th order method and the other a 8th order method. The 4th order method could be applied to segment both the cDNA microarray images and the Affymetrix GeneChips, while the 8th order method could only be applied to processing the cDNA microarray images, due to the limitation of the current image resolution. Additionally, we provide both the mathematical derivations for the partial. differential equations (their 4th or 8th order approximations) as well as the validation trough simulations of the microarray images by using real images as seeds for the Nykter's 2006 methodology. We conclude by showing that both the 4th order method as well as the 8th order one are superior to the SBC and the widely used GOGAC method implemented in the Affymetrix standard processing package for microarrays. (C) 2017 Elsevier B.V. All rights reserved.

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In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. We prove that NPSP of size 4 can accept all languages in NP in polynomial time. All these results can be obtained with NPSPs with valuations in the set {-1, 0, 1} as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of these simulations.

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In the last few decades, due to the global industrialization and population expansion the level of pollutants has largely increased, being one of the main environmental problems faced worldwide. Consequently, phytoremediation research had been gathering more and more interest. A study of data selected from Scopus is presented by the authors, identifying trends in publication number, collaboration and impact. The trends are identified at the global level followed by a discussion of how Romania performs with respect to the identified trends. When evaluating the research produced by the Romanian institutions, two characteristics are considered: phytoremediation potential of the plants in the Danube Delta and the coastal region and the phytoremediation research temporal evolution and international impact. The paper presents a quantitative analysis without adding variable weights to citations and publications based on the publications ranks offering an overview of the national research status in this research area.

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In this paper, catalyzed pyrolysis of scrap tires was studied in order to identify the influence of catalysts on gas composition during the main thermal range of the decomposition process. The aim is related to gas fraction optimization in terms of yield, composition, and distribution during the pyrolysis process. This is an original work using for the first time powder catalysts (MgO, Al2O3, CaCO3, and zeolite ZSM-5) uniformly distributed on a single layer of oyster shells (OSs) particles. The catalyst/tires mass ratio was kept for all the tests at 1/30. Depending on used catalyst, pyrolysis products yields ranged from 39 to 42 wt.% for char, from 26 to 38 wt.% for oils, and from 16 to 30 wt.% for gas. Compared to the thermal pyrolysis, it was found that the liquid yield increases in the presence of MgO/OS, while the use of Al2O3/OS decreases it significantly. The gas yield grows in the presence of Al2O3/OS ranging from 24.6 wt.% (thermal pyrolysis) to 30.6 wt.%. On the other hand, ZSM-5/OS and CaCO3/OS did not bring significant changes in products yield, but there are considerable influences on the evolution of gas composition during the tires decomposition. Also, two important advantages of using these new catalytic systems are identified. These relate to the formation of gaseous species throughout the waste decomposition, thus harmonizing the calorific value for the entire thermal range, and the disappearance of heavy molecules in liquid fractions, simplifying or canceling further upgrading processes.

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The treatment and disposal of tyres from vehicles has long been of considerable environmental importance. Studies have been undertaken to reduce their environmental impact. In this study, an alternative gas was produced from automobile tyre wastes by the means of a controlled pyrolysis. To do so, a novel catalytic system was designed with the aim of increasing the rate of conversion and improving the quality of the pyrolysis products. This work aimed also to reduce the severity of the overall reactions, by using powder catalysts (MgO, Al2O3, CaCO3, and zeolite ZSM-5) uniformly distributed on two layers of oyster shells (OS) particles. The catalyst/tyres mass ratio was kept for all the tests at 1/30. The pyrolysis reactor was maintained at 500 degrees C and the influence of each catalyst and of the number of shell beds (0, 1 or 2), on the yield and composition of the derived products, was examined. The gas yields could contribute by 1.2% of total consumption in Tunisia. Furthermore, some combinations could upgrade the derived gas and made it possible to use it as such or with the minimum of post-treatment. It was found that, with the use of supported catalyst, the gas produced is 45% greater compared to classical thermal pyrolysis. The Heating value of the produced gas was also improved by the use of supported catalysts; it was found 16% greater with the use of Al2O3/OS compared to non-catalytic pyrolysis. When compared to the gas obtained from only one catalytic supported bed, the sulfur content was reduced by 80% with the use of CaCO3/OS on two catalytic beds. (C) 2017 Elsevier Ltd. All rights reserved.

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In this article, correlation between the influence of catalysts on waste tires pyrolysis at. small- and laboratory-scale installation are highlighted. Kinetic and thermodynamic parameters of tires rubber thermochemical tranformations were evaluated using thermogravimetric analyses (TGA). For that purpose, Zeolite (ZSM-5), alumina (Al2O3, calcium carbonate (CaCO3, and magnesium oxide (MgO) were used as catalyst. It was found that all catalysts induce a delayed onset of pyrolytic process and MgO and. CaCO(3 )significantly reduced the activation energy (E-a from 246.89 kJ.mole(-1) (thermal pyrolysis) to 121.82 and 128.34 kJ.mole(-1), respectively. At laboratory scale, a fixed-bed. reactor was used to distinguish how the contact manner between tires and catalysts influences the yield of pyrolysis products as well as the gas quality. It. was proved that CaCO3 and Al2O3 are the most suitable catalysis for increasing the gas fraction, while the MgO promotes the formation of liquid fraction. (C) 2017 American Institute of Chemical Engineers.

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Evaluation of funded research, by measuring the outcomes of the grants publications, journals, and citations is not always done comparatively and publicised. Bibliometric indicators were employed and applied to the 2009-2014 publications authored by academicians funded by European research grants that are indexed in the Web of Science. Citation based approaches, such as the h-index or the impact factor, have been widely used to evaluate researchers or journals. In this study we use the aforementioned H-index to evaluate the funded research grants and to provide a ranking in terms of the most successful ones. The ranking results can be used by evaluators in determining how successful an applicant has potential to be, but also by researchers to choose their publication outlets, or to pursue future collaborations.

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The paper deals with the cellulase-mediated hydrolysis applied to several residual biomass resulting after extraction of biologically active principles from three medicinal plants: Melissa officinalis L., Melilotus officinalis L., Viola tricolor L. The yield of hydrolysis to hexoses was determined based on the amount of free glucose in the reaction mixture identified by spectrophotometric analysis, and total conversion of biomass residues was calculated. It was found that biomass resulted from Viola tricolor L. exhibits best glucose amount (10.35%) after 1 h of enzymatic hydrolysis, while that sourced from Melissa officinalis L. gives the highest total conversion of solid biomass (82.13%).

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The aim of this study was to develop a new variant of membranes based on collagen (COL), chitosan (CHI) and alkaline phosphatase (ALP) immobilized and cross-linking with glutaraldehyde (GA) at different concentrations. The biodegradation in the presence of collagenase was investigated. Biocompatibility was evaluated by MTT assay using a mouse fibroblast cell culture type NCTC (clone 929). Non-cross-linked samples were biocompatible and membranes cross-linked with low concentrations of GA (0.04, 0.08%) were also biocompatible. However, high concentrations of GA lead to a decreased biocompatibility. The adsorption behaviour of Ca2+ ions to all membranes were evaluated using the Freundlich isotherms. Haemolytic studies were performed in order to consider their applications in biomineralization process. By the addition of collagen and ALP to chitosan, the haemolytic index decreases, the COL-CHI-ALP membrane being in the non-haemolytic domain, while the COL-CHI-ALP-GA membrane has a haemolytic index greater than 2, and is slightly haemolytic.

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The paper presents a method for elaboration and characterization some chitosan-gelatine membranes with different collagen gelatine mass ratio, cross-linked with glutaraldehyde (GA) and coupled with extract plants. The aqueous extracts obtained from these plants were analyzed in terms of biologically active substances content (amino acids, polyphenols and phytosterols). The investigation for all obtained membranes involves: SEM microscopy, porosity, degradation test, contact angles measurement, hemolisys and antibacterian index determination.

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This paper conducts an examination of log files originating from High Performance Computing (HPC) applications with known reliability problems. The results of this study further the maturation and adoption of meaningful metrics representing HPC system and application failure characteristics. Quantifiable metrics representing the reliability of HPC applications are foundational for building an application resilience methodology critical in the realization of exascale supercomputing. In this examination, statistical inequality methods originating from the study of economics are applied to health and status information contained in HPC application log files. The main result is the derivation of a new failure index metric for HPC a normalized representation of parallel application volatility and/or resiliency to complement existing reliability metrics such as mean time between failure (MTBF), which aims for a better presentation of HPC application resilience. This paper provides an introduction to a Failure Index (FI) for HPC reliability and takes the reader through a use-case wherein the H is used to expose various run-time fluctuations in the failure rate of applications running on a collection of HPC platforms. (C) 2016 Elsevier Inc. All rights reserved.

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The Danube River-Danube Delta-Black Sea (DBS) region has witnessed major political, social and economic changes during the past three decades, which have profoundly affected the riverine, coastal and marine systems, their water management situation and the development of related research programmes. We reviewed the research activities in the DBS system of the past twenty years to determine the main funding bodies and to assess key research areas and how they varied over time and geographic region. As data basis we used a metadatabase filled with 478 projects addressing environmental and water management issues in the Danube River Basin, covering also the Danube Delta and the north-western Black Sea. As overall outcome extensive research efforts in the field of water management could be proven for the past two decades, despite the tumultuous times of political and economic transformations. One of the main findings was that EU funded projects played a key role for the development of transboundary research collaboration and were also the scientifically most productive one's. Historically, nutrient pollution was the main problem addressed, shifting to pollution in a broader sense and hydromorphological alterations in recent years. The newly arising challenges of climate change impacts and sediment management became important research questions in the last years, too. Most research was performed in the thematic field of navigation, followed by restoration and biodiversity issues. To meet all of the already

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There is much interest in producing hydrogen from various materials, including rubbery wastes to help in the fulfilment of the predicted hydrogen economy of the future. In this paper thermal and catalyzed cracking processes have been investigated for their suitability in producing gaseous compounds during thermochemical decomposition of polymer-based materials. Hydrogen and hydrogen-carriers production through rubbery wastes cracking was carried out into a laboratory bench scale installation using a fixed bed reaction system. Experiments were conducted at 500 degrees C with a catalyst/waste ratio of 1/30. Catalysts influences on rubber decomposition were characterized using a variety of methods, including thermogravimetric analysis (TGA). The results indicated that the gas yield varied from 17 to 31 wt.% with addition of different catalysts. The potential of H-2 production was significantly increased from 14 to 32 wt.% by using MgO-based catalytic bed. Moreover, it was found that the higher heating value (HHV) of gases varied from 10 to 44 MJ/Nm(3), and the use of catalysts led to an increasing HHV especially in the first stage of cracking (250-350 degrees C). This work highlights the evolution of hydrogen and hydrogen-carriers during thermal and catalyzed cracking, too.

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In this paper both kinetic and thermodynamic parameters of thermochemical transformation of waste tires are evaluated by using thermogravimetric analysis (TGA). For rubber thermochemical decomposition, individually and in the presence of other tires components, some kinetic and thermodynamic parameters such as energy of activation (Ea), frequency factor (A), reaction enthalpy (Delta H), entropy (Delta S) and free energy (Delta G) have been calculated by using the integration method. The experimental data was used to highlight the influence of textile and metal tire compounds and provided worthy and substantive information on the issues to conduct and manage thermochemical process at larger scale in order to maximize the interest product yield. Kinetic parameters values show that tested materials exhibit different thermal degradation patterns during pyrolysis process at different heating rates. Two distinct areas of weight loss and a shift of thermal degradation peaks at higher temperatures and increasing heating rate have been identified. Also, it was established that both individual fiber and metal induce an important decreasing in Ea and Delta H values during tire rubber pyrolysis.

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In this paper the products obtained through thermochemical processing of several polymer-based wastes are characterised. The influence of chemical composition of raw materials on the characteristics of obtained products has been investigated by using fixed bed reactor. The aim of this work is to identify the best use of products recovered after pyrolysis of plastic wastes collected from chemical and biochemical laboratories. This work is developed in a laboratory bench installation design to perform O-2-free processing at atmospheric pressure. The process parameters such as pyrolysis temperature and adapted heating rate have been determined through the transposition of thermal and kinetic information provided by thermogravimetric analysis (TGA). Gas-chromatography techniques have been used to identify the chemical composition of gases (GC/TCD) and liquids (GC/FID-MS). It was established that polymer wastes can led to a valuable liquid products, with encouraging energetic properties that allow their blending with fuels currently used without altering the performances of burning devices.

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The Danube River–Danube Delta–Black Sea (DBS) region has witnessed major political, social and economic changes during the past three decades, which have profoundly affected the riverine, coastal and marine systems, their water management situation and the development of related research programmes. We reviewed the research activities in the DBS system of the past twenty years to determine the main funding bodies and to assess key research areas and how they varied over time and geographic region. As data basis we used a metadatabase filled with 478 projects addressing environmental and water management issues in the Danube River Basin, covering also the Danube Delta and the north-western Black Sea. As overall outcome extensive research efforts in the field of water management could be proven for the past two decades, despite the tumultuous times of political and economic transformations. One of the main findings was that EU funded projects played a key role for the development of transboundary research collaboration and were also the scientifically most productive one's. Historically, nutrient pollution was the main problem addressed, shifting to pollution in a broader sense and hydromorphological alterations in recent years. The newly arising challenges of climate change impacts and sediment management became important research questions in the last years, too. Most research was performed in the thematic field of navigation, followed by restoration and biodiversity issues. To meet all of the already identified and newly emerging challenges in the DBS System, cross-border and integrated (river-delta-sea) research activities are of major importance and have to be further promoted. We thus suggest drawing up a regional DBS Research Agenda linked to key challenges in water management to strengthen research collaboration and advance targeted scientific projects, an approach fostering also the scientific capacity in the region. © 2015 Elsevier B.V.

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One issue that has become more important over the years is to evaluate the capability for worldwide research networks on different areas of research, especially in the areas that are identified as being worldwide significant. The study investigated the research output, citations impact and collaborations on publications listed in Scopus authored by researchers all over the world, research published between 1999-2014, selected by a group of keywords identified by authors. The results of the analysis identified an increasing trend in scientific publications starting with 2006, especially on three of the analyzed keywords. We also found differences in the citations patterns for the Black Sea and Danube Delta keywords in the contributing countries. The results of this study revealed a steady increase of the collaboration output and an increasing trend in the collaboration behavior, both at the European and national level. Additionally, at the national level the study identified the collaboration network between Romanian institutions per counties.

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The paper is focused on elaboration and physical chemical and biological characterization of new membranes based on chitosan and gelatine. The membranes were prepared using two gels chitosan and gelatin, in molar ratio 1:1 and 1:3. The surface characterization includes scaning electronic microscopy (SEM), water absorbtion, and determination of contact angles. As biological tests hemolysis and biodegradation were performed.

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The paper summarises the results of the 478 projects from the FP7-ENVIRONMENT proiect, DANube macroregion: Capacity building and Excellence in River Systems (basin, delta and sea) DANCERS database considering different attributes recorded for these projects. An analysis is performed on the recorded data and the significant characteristics are presented. The analysis performs a research output assessment in order to quantify the success of the projects. Trends are identified not only by thematic area and region of implementation, but also by coordinating country region and level of financing. A need to homogenising the level of financing as well as the level of funding efforts among the EU Strategy for the Danube Region (EUSDR) countries and not only, transpires at the end of the analysis. A concentrated effort towards inter and intra disciplinary collaboration as well as within and between institutional collaboration and knowledge sharing is also apparent.

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High Performance Computing applications on Cloud are of significance because of cost-effectiveness and elasticity. Reliability analysis of HPC applications on Cloud is an important areof study to better utilize infrastructure while dealing fault tolerant issues in a Cloud environment. In this work, we present a reliability model of a Cloud system under four scenarios: 1) Hardware components fail independently and software components fail independently; 2) software components fail independently and hardware components are correlated in failure; 3) correlated software failure and independent hardware failure; 4) dependent software and hardware failures. Moreover, we propose an optimal checkpoint placement technique based on reliability information for each scenario. Results show that if failure of the nodes and/or software in the system possesses a degree of dependency, the system becomes less reliable, which means that the failure rate increases and the mean time to failure decreases. Also, an increase in the number of nodes decreases there liability of the system. Moreover, the optimal checkpoint interval decreases when the reliability of the system decreases.

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In this work we describe a new segmentation technique for the Affymetrix microarray images. We prove that our method can offer better predictions on the gene levels as opposed to the standard Affymetrix segmentation implemented in the Affymetrix GeneChip Operating Software (GCOS). To check the accuracy and show the benefits of the new segmentation method we use a previously implemented methodology to simulate microarray images with realistic features. Using such an artificial image provides us with the actual levels for each spot and each gene investigated in the microarray. Using this information we then proceed to segment the same image twice (with GCOS and our new method). The two segmentations will produce two sets of gene levels that are then compared to the known gene levels (known since the moment of generating the artificial image). Using this methodology we are able to show statistically (using 50 replicates of the same steps of generating the image, segmenting, comparing the results) that in some cases our new method greatly outperforms the GCOS implemented segmentation method, while in the rest of the cases performs in similar fashion. (C) 2015 Elsevier B.V. All rights reserved.

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Thinking on environmental hazards, images of chemicals in waters, or air pollution coming out of industrial furnaces are most often seen. There are some hazards that are overlooked and one of them is scrap tires. Without a good management, scrap tires treatment can threaten not only our environment, but the public health as well. For instant, run-off from scrap tire fires can contaminate groundwater and surface water, and scrap tire sites are an ideal habitat for the breeding of insects carrying disease. In this paper we present an experimental approach on understanding and managing the environmental hazards of co-products resulted during energy recovery processes applied on scrap tyres. As tyre combustion faces serious problems related to harmful emissions, pyrolysis appears as a process that allows the management of toxic compounds. The experimental data were used to highlight the influence of textile and metal tyre compounds and provided worthy and substantive information on the issues to conduct and manage the thermochemical process in order to maximize the interest product yield. Thus, for the reactions occurs during pyrolysis and combustion of tyres organic matters the main intensive degradation thermal ranges have been established. The work was carried out by coupling thermogravimetric analysis (TGA) of tyre samples with bench scale reactor in order to identify the relationships between thermochemical behaviour and products distribution. TGA results afford the study of the kinetics parameters while the laboratory facilities allow the comprehension of tyres behaviours in real conditions. The processing temperature was limited at 700 degrees C and the measures focused on the mass balance determination and gaseous products analysis. It was found that the three obtained products have a good energetic potential: the solid (20-32 MJ/kg), the liquid (41-43 MJ/kg) and the gas (32-36 MJ/m3). Nevertheless, the liquid need to be upgrading in order to be used as Diesel-like fuel and gases should be treated to remove sulphur compounds. With this purpose some catalysts, known for their ability to increase gaseous fraction have been studied in TGA and an important shift of degradation peaks was identified and discussed.

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In this paper, the evolution in thermochemical behaviours of hospital plastic wastes and changes in chemical composition and characteristics of pyrolysis liquid products have been investigated by using different fixed bed reactor scales. The main objective is to identify the critical technical parameters enabling thermochemical process adaptation in function of raw materials chemical structure, with the aim of maximising the yield of condensable fraction and optimising its energetic properties related to internal combustion engines. It is a step-by-step procedure using three reactor capacity levels, which allows various aspects approach of thermochemical process development from the evaluation of global reaction kinetic parameters to the measurement of physicochemical properties of the final pyrolysis products. In order to reduce the gas and solid fractions with corresponding increasing of condensable products, the transposition of thermal and kinetic information provided by thermogravimetric analysis (TGA) to larger reactors is used to control of process parameters. In this experimental work the mass of samples increases from 0.05 g in the thermogravimetric analyser to 600 g in the bench scale reactor. Gas-chromatography techniques have been used to identify the chemical composition of gases (GC/TCD) and liquids (GC/FID-MS). It was established that changing the reactor scale does not result in significant differences in pyrolysis product distribution, neither in gas composition. On the other hand, the aspect and the quality of condensable fraction display a high variability. Also, the energy contained in the final valuable pyrolysis product was compared with the energy demand during the thermochemical transformation in order to evaluate the energy efficiency of the process. (C) 2015 Elsevier Ltd. All rights reserved.

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Purpose - The purpose of this paper is to develop and empirically test a new framework that shows how different signals of movie quality along with key control variables affect consumers' post-consumption evaluations, critics' reviews (CR), and movie box office revenues. Design/methodology/approach - The data set consists of a sample of 332 movies released between 2000 and 2008. Regression was used to test the study hypotheses. Findings - The results suggest that the three signals of movie quality exhibit different effects on three movie performance measures. Of the three cues, the peripheral quality signal is positive related to movie box, moviegoers' evaluations (ME), and CR. Furthermore, star performance quality is positive related to both ME and CR. Surprisingly, overall quality signal does not display any influence on movie performances. Research limitations/implications - The primary limitation is the use of cross-sectional study design and future research should apply for time-series technique to test the relationships between movie quality signals and movie performances. Practical implications - The findings suggest that consumers and critics evaluate movie qualities based on various movie quality signals. Furthermore, the characteristics of movies also have mixed impacts on movie performances. Movie studios may take these findings into account to produce better movies. Originality/value - This study proposes and empirically tests the impacts of three groups of movie signals peripheral quality signal, star performance quality signal, and overall quality signal on motion picture performance. This study contributes to service quality literature and signal theory by categorizing different Academy Awards into three groups of quality signals and by empirically testing the proposed relationships.

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Given that the reliability of a very large-scaled system is inversely related to the number of computing elements, fault tolerance has become a major concern in high performance computing including the most recent deployments with graphic processing units (GPUs). Many fault tolerance strategies, such as the checkpoint/restart mechanism, have been studied to mitigate failures within such systems. However, fault tolerance mechanisms generate additional costs and these may cause a significant performance drop if it is not used carefully. This paper presents a novel fault tolerance scheduling model that explores the interplay between the GPGPU application performance and the reliability of a large GPU system. This work focuses on the checkpoint scheduling model that aims to minimize fault tolerance costs. Additionally, a GPU performance analysis is conducted. Furthermore, the effect of a checkpoint/restart mechanism on the application performance is thoroughly studied and discussed.

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The ideas expressed in this work pertain to biochemical modeling. We explore our technique, the Nondeterministic Waiting Time algorithm, for modeling molecular signaling cascades. The algorithm is presented with pseudocode along with an explanation of its implementation. We discuss several important extensions including: (i) a heap with special maintenance functions for sorting reaction waiting times, (ii) a nondeterminstic component for handling reaction competition, and (iii) a memory enhancement allowing slower reactions to compete with faster reactions. Several example systems are provided for comparisons between modeling with systems of ordinary differential equations, the Gillespie Algorithm, and our Nondeterministic Waiting Time Algorithm. Our algorithm has a unique ability to exhibit behavior similar to the solutions to systems of ordinary differential equations for certain models and parameter choices, but it also has the nondeterministic component which yields results similar stochastic methods (e.g., the Gillespie Algorithm). There are several extensions for the current work discussed at the end of the chapter.

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The paper refers to a bioactive matrix in membrane shape, with a thickness of 0.5 - 1.0 mm, and consisting of gelatine, chitosan, and α-chymotrypsin, with or without addition of glutaraldehyde as a cross-linking agent. The bioproduct is a biomaterial with biomedical applications as biocompatible membrane with anti-inflammatory action due to coupling of the proteolytic enzyme. Bioproducts have complex implications in the treatment of traumatized tissue, accelerating the pus cleansing of infected wound, blood clots and other cellular debris, secretions liquefaction and cleansing of necrotic tissue, and also stimulating tissue regeneration and a faster healing of open infected wounds. In order to establish the influence of cross- linking process and membrane’s thickness on mechanical properties, ultrastructural studies were carried out on obtained biomaterials by electron microscopy analysis. To demonstrate the biological qualities of new enzymatic biomaterials, the membrane’s biological effect was analyzed in a cell culture model (mouse fibroblasts NCTC). © 2014 Vasile Goldis University Press.

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A high-performance computing (HPC) system, which is composed of a large number of components, is prone to failure. To maximize HPC system utilization, one should understand the failure behavior and the reliability of the system. Studies in the literature show that the time to failure of a node is best described by a Weibull distribution. In this study, we consider, without loss of generality, the Weibull as the distribution of time to failure and develop a reliability model for a system of k nodes where nodes can fail simultaneously. From this model, we develop expressions for the probability of failure of the system at any time t, for the failure rate, and for the mean time to failure. Also, we validate the model by using failure data from the Blue Gene/L logs obtained from the Lawrence Livermore National Laboratory. Results show that if failures of the components (nodes) in the system possess a degree of dependency, the system becomes less reliable, which means that the failure rate increases and the mean time to failure decreases. Also, an increase in the number of nodes decreases the reliability of the system.

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Simulated annealing (SA) is a heuristic technique popular in forest planning, providing solutions close to optimality in reduced computation time. The present study challenges the common approach used to establish the parameters of SA that mimic physical processes by proving that slow cooling or large initial temperatures do not necessarily lead to optimal solutions. The study has two objectives: (1) to identify the parameters (i.e., initial temperature and annealing rate) that could supply close to optimal results with reduced experimentation time and (2) to assess the impact of parameters determining SA performances. Using three forest inventory data sets from British Columbia, we investigated the influence of initial temperature, annealing rate, and numbers of runs on forest planning solutions using a replicated completely randomized design organized as a factorial experiment within a repeated-measures framework. The optimal solution seems to be little influenced by the number of runs; our findings indicate that the combination of initial temperature and rate of annealing is critical in obtaining superior results. Furthermore, the selection of the SA parameters seems to be dependent on the harvest age, which indicates that the parameters should be selected considering whether or not a stand is harvested more than once during the planning period.

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An improved biointerface was developed, dynamic layer-by-layer self-assembly surface (d-LbL), and utilized as a biologically-active substrate for platelet adhesion and aggregation. Possible clinical applications for this research include improved anti-coagulation surfaces. This work demonstrated the functionality of d-LbL biointerfaces in the presence of platelet-rich-plasma (PRP) with the addition of 20 mu M adenosine diphosphate (ADP), a thrombus activator. The surface morphology of the experimental control, plain PRP, was compared to PRP containing additional ADP (PRP + ADP) and resulted in an expected increase of platelet adhesions along the fibrinogen d-LbL substrate. The d-LbL process was used to coat glass slides with fibrinogen, Poly (sodium 4-styrene-sulfonate), and Poly (diallydimethlyammonium chloride). Slides were exposed to PRP under flow and static conditions with and without 20 mu M of ADP. Fluorescence microscopy (FM), phase contrast microscopy (PCM), atomic force microscopy (AFM), and field emission-scanning electron microscopy (FE-SEM) were used to evaluate platelet adhesions under the influence of varied shear conditions. PCM images illustrated differences between the standard LbL and d-LbL substrates. FM images provided percent surface coverage values. For high-shear conditions, percent surface coverage values increased when using ADP whereas plain PRP exposure displayed no significant increase. AFM scans also displayed higher mean peak height values and unique surface characteristics for PRP + ADP as opposed to plain PRP. FE-SEM images revealed platelet adhesions along the biointerface and unique characteristics of the d-LbL surface. In conclusion, PRP + ADP was more effective at increasing platelet aggregation, especially under high shear conditions, providing further validation of the improved biointerface.

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With virtualization technology, Cloud computing utilizes resources more efficiently. A physical server can deploy many virtual machines and operating systems. However, with the increase in software and hardware components, more failures are likely to occur in the system. Hence, one should understand failure behavior in the Cloud environment in order to better utilize the cloud resources. In this work, we propose a reliability model and estimate the mean time to failure and failure rate based on a system of k nodes and s virtual machines under four scenarios. Results show that if the failure of the hardware and/or the software in the system exhibits a degree of dependency, the system becomes less reliable, which means that the failure rate of the system increases and the mean time to failure decreases. Additionally, an increase in the number of nodes decreases the reliability of the system. © 2013 Springer-Verlag.

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The cultivation of medicinal and aromatic plants has a long tradition in the Calarasi - Silistra region. In this area, 81 species of medicinal and aromatic plants - from the cultivated and spontaneous flora - were identified as a result of a study we performed. Of those, 16 species were experimentally cultivated in two pilot cultures, one in Calarasi County and one in Silistra District, and were analyzed from the point of view of the active principles they contain. The following compound categories were identified during the study: aminoacids, proteins, alkaloids, saponins, tannins, triterpenoids, glycosides, polysaccharides, vitamins A and E. The results of the study allowed the identification of species with a high content of active principles and led to recommendations for local cultivators of medicinal plants. A database was also created, containing information about the most common medicinal plants found in the area and their active principles content (www.medplanet.dbioro.eu).

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In this paper we consider sequential SNP systems where the sequentiality of the system is induced by the max-spike: the neuron with the maximum number of spikes out of the neurons that can spike at one step will fire. This corresponds to a global view of the whole network that makes the system sequential. We continue the study in the direction of max-spike and show that systems with 132 neurons are universal. This improves a recent result in the area. © 2012 Springer-Verlag.

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The Strategy for the Danube region, presently developed by the Danube countries under the guidance of the European Commission, focuses on 4 pillars (connectivity, protecting the environment, building prosperity and strengthening the Danube region).Within the strategy frame the major aims are to implement an integrative policy in the region and to enhance cross-border cooperation as a way to achieve the EU overarching goal of sustainability (COM 400, 2009). Reaching the peak at the beginning of 2000, since in June 2011 the European Commission adopted the mentioned Strategy for the Danube region, the Danube river and its related issues were a matter of concern in the last centuries. The present notes are addressing the objective of creating a new structure able to support the regional efforts in the Danube Strategy implementation.

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The Strategy for the Danube region, presently developed by the Danube countries under the guidance of the European Commission, focuses on 4 pillars (connectivity, protecting the environment, building prosperity and strengthening the Danube region). Within the strategy frame the major aims are to implement an integrative policy in the region and to enhance cross-border cooperation as a way to achieve the EU overarching goal of sustainabiliry (COM 400, 2009). Reaching the peak at the beginning of 2000, since in June 2011 the European Commission adopted the mentioned Strategy for the Danube region, the Danube river and its related issues were a matter of concern in the last centuries. The present notes are addressing the objective of creating a new structure able to support the regional efforts in the Danube Strategy implementation.

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A systematic use of the Monte Carlo method appeared since the early days of electronic computing and since then it is more present in different scientific research fields. Therefore, many techniques were developed based on this method and one of them is called sequential importance sampling. This technique is an adaptation of the Monte Carlo method that can be used to better extract samples form the domain using an importance weight function.

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The paper is a survey of the recent model of P systems with proteins on membranes introduced by Paun and Popa in 2006. This model can be viewed as an extension of the highly successful paper of (Paun and Paun 2002) describing P systems based on symport/antiport. The previous model represented an important change of direction from strings to objects in the area of P systems. The main drawback of the model from 2002 was the massive parallelism that is not seen in real life. The 2006 model was a step in controlling the parallelism the same way it is done in nature in symporters and antiporters: these processes take place through protein channels embedded at the level of the membrane which can only be used by a molecule at a time, thus yielding a sequentiality with respect to the number of such proteins embedded in the membrane.

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P systems with proteins on membranes are inspired closely by switching protein channels. This model of membrane computing using membrane division has been previously shown to solve an NP-complete problem in polynomial time. In this paper we characterize the class of problems solvable by these P systems in polynomial time and we show that it equals PSPACE. Therefore, these P systems are computationally equivalent (up to a polynomial time reduction) to the alternating Turing machine or the PRAM computer. The proof technique we employ reveals also some interesting trade-offs between certain P system properties, as antiport rules, membrane labeling by polarization or the presence of proteins. © 2010 Springer-Verlag.

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We show that the absolute worst case time complexity for Hopcroft's minimization algorithm applied to unary languages is reached only for deterministic automata or cover automata following the structure of the de Bruijn words. A previous paper by Berstel and Carton gave the example of de Bruijn words as a language that requires O(n log n) steps in the case of deterministic automata by carefully choosing the splitting sets and processing these sets in a FIFO mode for the list of the splitting sets in the algorithm. We refine the previous result by showing that the Berstel/Carton example is actually the absolute worst case time complexity in the case of unary languages for deterministic automata. We show that the same result is valid also for the case of cover automata and an algorithm based on the Hopcroft's method used for minimization of cover automata. We also show that a LIFO implementation for the splitting list will not achieve the same absolute worst time complexity for the case of unary languages both in the case of regular deterministic finite automata or in the case of the deterministic finite cover automata as defined by S. Yu. Published by Elsevier B.V.

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We consider the absolute worst case time complexity for Hopcroft's minimization algorithm applied to unary languages (or a modification of this algorithm for cover automata minimization). We show that in this setting the worst case is reached only for deterministic automata or cover automata following the structure of the de Bruijn words. We refine a previous result by showing that the Berstel/Carton example reported before is actually the absolute worst case time complexity in the case of unary languages for deterministic automata. We show that the same result is valid also when considering the setting of cover automata and an algorithm based on the Hopcroft's method used for minimization of cover automata. We also show that a LIFO implementation for the splitting list is desirable for the case of unary languages in the setting of deterministic finite automata.