A simulation is performed to analyze the forces that arise in a conducting DNA-like double helix in the field of a microwave electromagnetic wave under half-wave resonance conditions. The helix is comprised of twenty-and-a-half turns and has geometric parameters proportional to the size of an actual DNA molecule. The forces acting on the strands of a double helix, both in the central region and at the edges of the helix, are investigated. It has been demonstrated that the afore-mentioned forces induce a change in the shape of the helix, specifically mutual repulsion of the strands, as well as their stretching and twisting in the field of electromagnetic waves. As opposed to a pair of parallel straight conductors, there is a radial repulsion of strands in all regions of a double DNA-like helix, including the center and the edges. This unique interaction of currents in a double DNA-like helix can be attributed to its pitch angle, a characteristic that has been estab-lished through empirical evidence. Consequently, exposure to an electromagnetic wave under half-wave resonance can damage the double helix. Conversely, the impact of electromagnetic waves has the potential to introduce novel avenues for controlling the shape of the double helix. These nonlinear effects must be considered for both actual DNA molecules and double DNA-like helices that serve as components of metamaterials and metasurfaces.

A two-stage pilot plant study has been completed that evaluated the performance of a reverse osmosis (RO) membrane process for the treatment of a feedwater that consisted of a blend of nanofiltration (NF) concentrate and brackish groundwater. Membrane performance was assessed by monitoring the process operation, collecting water quality data, and documenting the blended feedwater’s impact on fouling due to a combination of, or solely caused by, plugging, scaling, microbiological, or organic means. Fluorescence and biological activity reaction tests were used to identify the types of organics and microorganisms present in the blended feedwater. Additionally, scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS) were used to analyze suspended matter that collected on the surfaces of cartridge filters used in the pilot’s pretreatment system. SEM and EDS were also used to evaluate solids collected on the surfaces of 0.45-µm silver filter pads after filtering known volumes of NF concentrate and RO feedwater blends. Water quality analyses confirmed that the blended feedwater contained little to no dissolved oxygen, and the blended feedwater was absent of a significant amount of particulate matter as defined by silt density index and turbidity measurements. However, water quality results suggested that the presence of sulfate, sulfide, iron, anaerobic bacteria, and humic acid organics likely contributed to the formation of pyrite observed on some of the membrane surfaces autopsied at the conclusion of pilot operations. It was determined that first-stage membrane productivity was impacted by the location of cartridge filter pretreatment; however, second-stage productivity was maintained with no observed flux decline during the entire pilot operation’s timeline. Study results indicated that the operation of an RO process treating a blend of NF concentrate and brackish groundwater could maintain a sustainable and productive operation that provided a practical zero-discharge process operation while the dilution of RO feedwater salinity would lower overall production costs.

Taiwan's bed and breakfast (B&B) development has been more than 25 years ago, from the first generation of retirement to the B&B industry, serving tourists from all over the world accom-modation, providing breakfast and accommodation mode to the present, after the change of employees from the second generation, more and more attention is paid to the cultivation and cultivation of business ability. With the advent of the era of AI technology networking, the ca-pabilities required for B&B operation are more focused on all aspects of service, and the good marketing ability of B&B can promote a green chimney-free tourism economy, which is also a favorite industry of various governments and the public. This study explores the basic vocational competency indicators required for running a B&B, with (1)EQ emotion management skills, (2)Financial management ability, (3)(SK) technical skills, and (4)Marketing and promotion management capabilities. Through the study method, the K-S Z test was determined by the con-sensus conclusion of expert reliability and validity p value

Although promoting healthy eating is a policy objective, the controllability of dietary habits remains uncertain. The personal dietary patterns reflect many factors, of which some are relatively controllable for individual, and others are not. In this article, assuming that some sort of information about controllability of dietary habits is contained in the observed pattern of food consumptions, we focused on dietary pattern on its own. We introduced a statistical descriptive model for data on food frequency questionnaire, estimated strength of pairwise linkage between foodstuffs, and grouped foodstuffs by applying community detection to the networks of the estimated inter-food linkages. Those linkages represent co-movement of pairs of foods consumption. Furthermore, we demonstrated an analysis on the relationship between health of mind and dietary habits considering the aspect of controllability of dietary habits. Using an observational study in Japan, we obtained the following results: 115 foodstuffs were divided into 3 groups for both of genders, but the compositions were different by gender; in the analysis of mental health, some stress response items were associated with the dependence on some of those food groupings. As the grouping of foodstuffs based on our estimation depicted the internal structure of dietary habit that a healthy eating policy should regard as constraint, it follows that we should design the policy along the line with that grouping.

This study investigates the valorization potential of yellowfin tuna tails for the production of high-value commercial products. Muscle and skins were firstly mechanically separated by using a specifically designed device. The muscle was then used as a nitrogen source for the growth of the proteolytic enzymes-producer Bacillus subtilis, whereas the skins were employed for gelatin extrac-tion. The proteases from Bacillus subtilis were partially purified and used to produce antioxidant peptides from gelatin obtained. The gelatin obtained formed a gel upon cooling, with gelling and melting temperatures at 16 ºC and 22 ºC, respectively, and Bloom Strength of ≈ 160. RSM was used to determine the optimal hydrolysis conditions to obtain the highest antioxidant activity (35.96%, measured as DPPH radical scavenging activity), which were 50°C / 6.5 IU of enzyme. The findings emphasize the importance of an integrated approach to maximize the value of tuna by-products, promoting sustainability in the frame of circular bioeconomy. Overall, these results contribute to the efficient utilization of tuna by-products, waste reduction, and enhance economic viability of the tuna industry.

Background Gingivitis can develop without mechanical cleaning within three weeks. The first clinical sign is bleeding on positive probing. The accumulation of dental biofilm generates an inflammatory gingival response. In the past decade, attention has focused mainly on the interproximal areas and the use of customsized interproximal toothbrushes.The aim of the study was to evaluate the effectiveness of individualized oral hygiene education and its role in dental prevention among patients with dental problems. Methods Before treatment, patients were clinically and radiologically examined, full mouth plaque score (FMPS), full mouth bleeding score (FMBS), and bleeding on brushing (BOB) were recorded, and matrix-metalloproteinase-8 (MMP-8) was measured by using a chair-side MMP-8 measuring system. Patients in group A had gingivitis, but no periodontal damage and patients in group B had periodontal damage. Patients in both groups A and B were identified in to four subgroups based on their toothbrushing habits and the oral health education they received. The three months after initial examination, each patient was examined three more times (2, 4 and 12 weeks later). Results It was concluded that subjects in groups A1 and B1 showed significant reduction in BOB, MMP-8, FMBS and FMPS levels after two weeks. Solo Prophylaxis (A1and B1) remained as a well-constructed protocol with hte complete resolution of interdental inflammation after two weeks. Other subgroups achieved significant reductions only after 12 weeks. Conclusions BOB and MMP-8 are valuable complements in preventive dentistry, and are able to detect potential pathological processes in interproximal spaces. The clinical relevance of BOB, in addition to FMBS, FMPS and gingival inflammation can be demonstrated to patients, which may increase compliance.

This study aimed to determine shifts in microbial populations regarding richness and diversity from the daily use of a popular over-the-counter nasal spray. In addition, the finding of nasal commensal bacterial species that overlap with the oral microbiome may prove to be potential probiotics for the “gateway microbiomes.” Nasal swab samples were obtained before and after using the most popular over-the-counter (OTC) nasal spray in 10 participants aged 18–48. All participants were healthy volunteers with no significant medical histories. The participants were randomly assigned a number by randomizing software and consisted of five men and five women. The sampling consisted of placing a nasal swab atraumatically into the nasal cavity. The samples were preserved and sent to Northwestern University Sequencing Center for whole-genome deep sequencing. After 21 days of OTC nasal spray use twice daily, the participants returned for further nasal microbiome sampling. The microbial analysis included all bacteria, archaea, viruses, molds, and yeasts via deep sequencing for species analysis. The Northwestern University Sequencing Center utilized artificial intelligence analysis to determine shifts in species and strains following nasal spray use that resulted in changes in diversity and richness.

This manuscript offers a concise overview of paper microfluidics, emphasizing its sustainable sensing applications in healthcare, environmental monitoring, and food safety. Researchers have developed innovative sensing platforms for detecting pathogens, pollutants, and contaminants by leveraging the paper’s unique properties, such as biodegradability and affordability. These portable, low-cost sensors facilitate rapid diagnostics and on-site analysis, making them invaluable tools for resource-limited settings. The review discusses fabrication techniques, principles, and applications of paper microfluidics, showcasing its potential to address pressing challenges and enhance human health and environmental sustainability.

(1) Background: The interplay between coronavirus disease 2019 (COVID-19) and laryngeal cancer represents a substantial challenge for both patients and healthcare. To garner information on recent mortality data for laryngeal cancer, including during the COVID-19 pandemic, we analyzed real-world data from the US Centers for Disease Control and Prevention (CDC). (2) Methods: We searched the CDC WONDER on-line database 2018-2022 using with the ICD-10 code for laryngeal cancer (C32; malignant neoplasm of larynx). We also performed a sub-analysis between genders, and across ten-year age groups. Data were analyzed with one-way analysis of variance (ANOVA) and Tukey post-hoc test. (3) Results: The trend of age-adjusted mortality ×100,000 did not change significantly between 2018-2022 (p=0.553). Males had higher age-adjusted mortality rates (M/F ratios between 4.6 and 5.0), but no significant variation was found in both genders (males: p=0.676; females: p=0.596). Although the mortality rate remained unchanged in people aged 35-84 years, the variation reached statistical significance in those aged 85 or older (p=0.004), displaying significant increase in 2021 compared to 2018 (p=0.006) and 2019 (p=0.039). (4) Conclusions: The impact of the COVID-19 pandemic on mortality for laryngeal cancer seemed to be relatively modest in the general US population. Nevertheless, closer attention must be paid to older people, in whom the unfavorable consequences of misdiagnosis or mistreating can be exacerbated.

For this research we are selected three indicators of wheat: yield (t/ha), producer price (USD/t) and share of the harvested area under wheat in relation to the total land area of country (%). The mentioned indicators were analyzed for the period 2006-2021 in thirty-two European countries. The purpose of the research is to determine which of the mentioned indicators achieve average annual growth/decrease rates, what is the correlation between them, how European countries are grouped with their similarities and differences. The research examines the impact of the COVID-19 pandemic on the mentioned indicators in a two time phases: Phase I, before the pandemic (2006-2019); Phase II, during the pandemic (2020-2021). The methodological approach to the research topic involved the application of descriptive statistics, as the method of principal components analysis (abbr. PCA) with graphics. A positive correlation exists only between the yield of wheat and the share of the harvested area under wheat in the total area of the land (0.291). PCA method showed that countries are grouped differently depending on the observed indicator and the analyzed time phase.

Background: The purpose of this review is to clarify the natural course of Benign Paroxysmal Torticollis (BPT) and to update the relationship of this disorder with migraine. BPT belongs to a group of “episodic syndromes that may be associated with migraine” and is diagnosed when according to diagnostic criteria of the International Classification of Headache Disorders, 3rd edition. It is present in infants and young children and it is an underdiagnosed manifestation, because it is not well recognized and in most cases with a benign evolution, but requires careful differential diagnosis. It was first described by Snyder in 1969 as a movement disorder, a cervical dystonia consequent to labyrinthic disorder.Materials and methods: The PubMed and Web of Science databases were consulted from 1968 to 2024, according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines ,2020.( PRISMA)Results: 113 articles were identified, 86 selected and 20 considered for the purpose of this review. The clinical studies were considered in relation to evolution, cognitive and motor development, to genetic and not genetic etiology, to the relationship with migraine with and without aura, vestibular migraine, hemiplegic migraine, and paroxysmal vertigo.

Duct-dependent lesions are classically divided into duct dependent pulmonary circulation which involves severe right sided obstructive lesions such as pulmonary atresia or critical stenosis, and duct dependent systemic circulation which is characterized by malformation of the left side of the heart, and whose severest spectrum is hypoplastic left heart syndrome. Dextro-transposition of the great arteries remains in gray zone between being included in some old classifications as a duct dependent pulmonary circulation lesion or a new category of duct-dependent or independent mixing lesion. We hypothesize that re-classifying duct dependent congenital defects into duct dependent perfusion and oxygenation offers a model to fit D-TGA into the same category of right sided obstructive lesions and reflects the clinical spectrum in a more comprehensive way.

Blockchain technology (BCT) has the potential for sustainable development, enhancing business efficiency, reducing costs, and strengthening data security. Despite its potential, adoption among small and medium-sized enterprises (SMEs) is low due to the need for significant changes in technology infrastructure and the challenge of interoperability. A cross-sectional survey was done with 226 Hong Kong SMEs. The PLS-SEM results highlighted favorable transformation conditions as the most critical factor for SMEs considering the adoption of BCT. These conditions address both internal and external readiness for adopting the disruptive strategy. Other contributing factors to BCT adoption include trust in BCT developers, perceived usefulness and ease of use, government support, and perceived security. The research results contributed to the literature on disruptive technology acceptance, adoption, transformation conditions, technology readiness, and SMEs’ technology adoption. Government-supported policies and initiatives can promote BCT adoption, including educational programs, case studies, and resources for readiness. Financial support and regulatory frameworks can further encourage adoption. BCT developers can demonstrate the value of their systems, effectively communicate potential ROI and cost savings, and provide user-friendly interfaces to increase SMEs’ intention to adopt BCT.

Hemangioblasts give rise to endothelial progenitor cells (EPCs), which also express the cell surface markers CD133 and C-kit. They may differentiate into the outgrowth endothelial cells (OECs) that control neovascularization in the developing embryo. Reduced levels of EPC in circulation have been linked to human cardiovascular disorders, according to numerous studies. Furthermore, preeclampsia and senescence have been linked to levels of EPCs produced from cord blood. Uncertainties surround how preeclampsia affects the way EPCs function. It is reasonable to speculate that preeclampsia may have an impact on the function of fetal EPCs during the in utero period; however, given the present literature's suggestion that maternal vasculopathies, including preeclampsia, damage fetal circulation. Additionally, the differentiation potential and general activity of EPCs may serve as an indicator of the health of the fetal vascular system since they promote neovascularization and repair during pregnancy. Thus, the purpose of this review is to compare, through assessment of their quantity, differentiation potency, angiogenic activity, and senescence, the angiogenic function of fetal EPCs obtained from cord blood for normal and pregnancy problems. This will shed light on the relationship between the angiogenic function of fetal EPCs and pregnancy complications, which could have an effect on the management of long-term health issues like metabolic and cardiovascular disorders in offspring with abnormal vasculature development.

Mitochondria are semiautonomous organelles, which are pivotal for the energy metabolism of eukaryotic cells. These organelles contain their own genetic system (mtDNA, mitogenome) that encodes to some structural RNAs and organellar proteins. The biogenesis and function of mitochondria is tightly regulated by nuclear-encoded protein cofactors. The mtDNAs of land plants are characteristically large, with a complex mode of gene organization and expression, in particularly at the post-transcriptional level. To become functional, the primary organellar transcripts undergo extensive maturation steps, which include endo- and exo-nucleolytic cleavage, RNA-base editing, and both ‘cis’- and ‘trans’-splicing events. These essential processing steps rely on the activities of a large set of nuclear-encoded factors. Among these, the RNA helicases serve as key players in organellar (mt-)RNA metabolism. This review summarizes the important roles played by these factors in regulating the highly dynamic processes of transcription, RNA processing, and translation within the mitochondria of land plants. We further discuss recent advancements in understanding how dysregulation of mitochondrial RNA helicases affects the organellar gene expression, respiratory functions, and hence the growth, development and physiology of land plants.

The aim of this study was utilization of ground tea waste (GT) left after brewing the black tea as a biofiller of natural rubber (NR) composites. Ionic liquids (ILs), i.e., 1-ethyl-3-methylimidazolium lactate and 1-benzyl-3-methylimidazolium chloride, often used to extract phytochemicals from tea, were applied to improve the dispersibility of GT particles in elastomeric matrix. The influence of GT loading and ILs on curing characteristics, crosslink density, mechanical properties, thermal stability and resistance of NR composites to thermo-oxidative aging was investigated. The amount of GT did not significantly affect curing characteristics and crosslink density of NR composites, but had serious impact on tensile properties. Applying 10 phr of GT improved the tensile strength by 40% compared to unfilled NR. Further increasing in GT content worsened the tensile strength due to the agglomeration of biofiller in elastomer matrix. ILs significantly improved the dispersion of GT particles in elastomer and increased the crosslink density by 20% compared to the benchmark. Owing to the poor thermal stability of pure GT, it reduced the thermal stability of vulcanizates compared to unfilled NR. Most importantly, GT-filled vulcanizates showed improved resistance to thermo-oxidative aging, since the aging factor increased by 25% compared to the unfilled vulcanizate.

Count data analysis presents unique challenges due to its discrete nature, often exhibiting excessive zeros and overdispersion. To address these complexities, count models, such as Poisson regression and Negative Binomial regression, have been developed, enabling modeling and prediction of count-based phenomena. Additionally, it’s important to notice that zero inflation, a phenomenon commonly observed in count data, requires specialized techniques for robust analysis. This article provides an overview of count data and count models, explores zero inflation, introduces Likelihood Ratio Tests, and explains how the Vuong Test can be used as a model selection criteria. Furthermore, we created a Vuong Test implementation from scratch using the Python programming language. This implementation enhances the accessibility and applicability of the Vuong Test in real-world scenarios, providing a valuable contribution to the academic community, since Python didn’t have an implementation of this statistical test.

Background: Cell proliferation and the cell cycle are fundamental to tumor development, with mitosis playing a crucial role in cell division. Understanding the complexities of the cell cycle and mitosis is critical for cancer research, especially in the context of developing therapeutic strategies. Objective: This review highlights mitotic poisons as potential anti-cancer pharmacotherapeutics, particularly their structural and functional group diversity presenting opportunity for semi-synthesis of new derivatives with multi-target mechanisms relevant for cancer pharmacotherapeutics. Also, the review explores naturally occurring mitotic poisons and inhibitors of microtubule-dependent molecular motors as promising cancer pharmacotherapeutics. Methods: A comprehensive review of literature from 2004 to 2023 was conducted, covering studies on cell proliferation, mechanism of cell cycle regulation, mitosis, cytokinesis, and anti-cancer drug development. The published literature was collected primarily from PubMed, Scopus, Medline, Web of Science Core Collections, Google Scholar and other relevant scientific databases using keywords including but not limited to mitotic poisons and cancer, sources of mitotic poisons, mechanism of mitotic poisons, targets of mitotic poisons and structural diversity of mitotic poisons. The efficacy and limitations of various mitotic poisons and their impact on different cancer types were examined. Recent advancements in targeted therapeutic interventions for various cancers were also explored. Results: The effectiveness and limitations of mitotic poisons, including Taxanes, Epothilones, Colchicine, Vinca alkaloids, Berberine, Laulimalide, and Pseudolaric acid B, were highlighted. Drugs targeting mitotic kinases such as CDKs, Aurora kinases, PLK1, and WEE1 inhibitors were reported. Inhibiting kinesin motor proteins such as Eg5 and KIF15 to interfere with spindle formation and cell division were discussed, along with specific genomic alterations in KIF genes and the discovery of KIFC1 as potential for future research and drug development. Conclusion: Targeting microtubules and mitotic kinases, along with inhibiting kinesin motor proteins, show promise for cancer pharmacotherapeutics. The combination of targeted therapies, patient stratification based on biomarkers (such as low alpha-1 acid glycoprotein and high p63 expression), and exploration of alternative natural sources of mitotic poisons and analogues can significantly advance cancer pharmacotherapy to improve patient outcomes.

This paper considers the Hermitian solutions of a new system of commutative quaternion matrix equations, we establish both necessary and sufficient conditions for the existence of solutions. Furthermore, we derive an explicit general expression when it is solvable. To illustrate our main findings, we present two numerical algorithms and examples in this paper.

ABSTRACT After locavore was chosen as “the best word of the year” in 2007, its popularity increased gradually. Today great number of locavores consciously prefer locally produced food for the benefit of themselves and their community. Undoubtedly this conscious movement has its consequences in marketing discipline. Accordingly, this paper is purposed to examine the how locavore perceptions affect loyalty towards retailers that sell locally produced food. In this context, a survey was applied to people residing in Istanbul and Kocaeli districts to measure the robustness of these effects. Furthermore, attitude towards locavore is used as a control variable to reveal to what extend locavorism affects these proposed connections. According to results, for participants with low attitude, Social Responsibility and Health Consciousness variables have significant effect on local retailer shopping loyalty. However, for participants with high attitude, all independent variables proved to have substantial effect on local retailer shopping loyalty. As the first empirical study in Turkey on the subject, this paper will provide important insight to academia and practicioners due to today’s ever-increasing consciousness in green marketing.

Environmental estrogen pollution and estrogen effects on the female reproduction system are well-recognized scientifically. Among the estrogens, 17 β-estradiol is a priority in environmental estrogen pollution, and it is also a major contributor to estrogen which regulates the female reproduction system. 17 β-estradiol is carcinogen and has a tumor promotion effect relating to breast cancer, lung cancer and others. It also affects the psychological well-being such as depression, fatigue and others. Thus, a simple method of detection of 17 β-estradiol will be important for both environmental estrogen pollution and women’s health care. This study demonstrates a simple-use, cost effective 17 β-estradiol biosensor system which can be used for both environment and women’s health care applications. The bio-recognition mechanism is based on the influence of the redox couple, K₃Fe (CN) ₆/K₄Fe (CN) ₆ by the interaction between 17 β-estradiol antigen and its α-receptor (ER- α; α-estrogen antibody). The transduction mechanism is an electrochemical analytical technique, differential pulse voltammetry (DPV). The levels of 17 β-estradiol antigen studied was between 2.25 pg/mL to 2,250 pg/mL, Phosphate buffered saline (PBS), tap water from the Cleveland regional water district, and simulate urine were used as the test media covering the potential application areas for 17 β-estradiol detection. An interference study by testosterone which has a similar chemical structure and molecular weight as those of 17 β-estradiol was carried out, and this 17 β-estradiol biosensor showed excellent specificity without any interference by similar chemicals.

Biohydrogen is a versatile energy carrier for the generation of electric energy from renewable sources. Hydrogenases can be used in enzymatic fuel cells to oxidize dihydrogen. The rate of electron transfer (ET) at the anodic side between the [NiFe]-hydrogenase enzyme distal iron-sulfur cluster and the electrode surface can be described by the Marcus equation. All parameters for the Marcus equation are accessible from DFT calculations. The distal cubane FeS-cluster has a three cysteine and one histidine coordination [Fe₄S₄](His)(Cys)₃ first ligation sphere. The reorganization energy (inner- and outer-sphere) is almost unchanged upon a histidine-to-cysteine substitution. Differences in rates of electron transfer between the wild-type enzyme and the all-cysteine mutant can be rationalized by a diminished electronic coupling between the donor and acceptor molecules in the [Fe₄S₄](Cys)₄ case. The fast and efficient electron transfer from the distal iron-sulfur cluster is realized by a fine-tuned protein environment which facilitates the flow of electrons. This study enables the design and control of electron transfer rates and pathways by protein engineering.

By using Modified simple equation method, we study the Cahn Allen equation which arises in many scientific applications such as mathematical biology, quantum mechanics and plasma physics. As a result, the existence of solitary wave solutions of the Cahn Allen equation is obtained. Exact explicit solutions interms of hyperbolic solutions of the associated Cahn Allen equation are characterized with some free parameters. Finally, the variety of structure and graphical representation make the dynamics of the equations visible and provides the mathematical foundation in mathematical biology, quantum mechanics and plasma physics.

In this study, the causal-effect between carbon dioxide emissions and forestry production and trade was investigated in Ghana by employing a data spanning from 1961 to 2014 by using the VECM and ARDL model. Evidence of the long-run equilibrium relationship in the VECM shows that, a 1% increase in veneer sheet production reduces carbon dioxide emissions by 1.47% in the long-run. There was evidence of a bidirectional causality between carbon dioxide emissions and veneer sheet production, carbon dioxide emissions and wood charcoal production, and a unidirectional causality running from carbon dioxide emissions to wood fuel production and plywood production to carbon dioxide emissions. Evidence from the long-run equilibrium relationship in the ARDL model shows that; a 1% increase in plywood production will increase carbon dioxide emissions by 0.17% in the long-run, a 1% increase in sawnwood production will increase carbon dioxide emissions by 0.17% in the long-run, a 1% increase in wood charcoal production will increase carbon dioxide emissions by 0.36% in the long-run and a 1% increase in wood fuel production will increase carbon dioxide emissions by 0.37% in the long-run.

In this study, an attempt was made to investigate the Kenya case of multivariate causality of carbon dioxide emissions by employing a time series data spanning from 1961-2011 using the ARDL method of cointegration analysis. The long-run elasticities show that, a 1% increase in financial development increases carbon dioxide emissions by 0.28%, a 1% increase in GDP per capita increases carbon dioxide emissions by 1.32% and a 1% increase in urbanization decreases carbon dioxide emissions by 1.14%. There was a unidirectional causality running from financial development, food production index, GDP per capita, industrialization and urbanization to carbon dioxide emissions. The innovation accounting shows that 20% of future shocks in carbon dioxide emissions are due to fluctuations in financial development, 9% of future shocks in financial development are due to fluctuations urbanization and 22% of future shocks in food production index are due to fluctuations in carbon dioxide emissions.

Capital structure decision plays an imperative role in firm’s performance. Recognizing the importance, there has been many studies inspected the rapport of capital structure with performance of firms and findings of those studies are inconclusive. In addition, there is relative deficiency of empirical studies examining the link of capital structure with performance of banks in Bangladesh. This paper attempted to fill this gap. Using panel data of 22 banks for the period of 2005-2014, this study empirically examined the impacts of capital structure on the performance of Bangladeshi banks assessed by return on equity, return on assets and earnings per share. Results from pooled ordinary least square analysis show that there are inverse impacts of capital structure on bank’s performance. Empirical findings of this study is of greater significance for the developing countries like Bangladesh because it will call upon concentration of the bank management and policy makers to pursue such policies to reduce reliance on debt and to accomplish optimal level capital structure. This research also contributes to empirical literatures by reconfirming (or otherwise) findings of previous studies.

Global rapidly evolving events, e.g., COVID-19, are usually followed by countermeasures and policies. As a reaction, the public tends to express their emotions on social media platforms. Therefore, predicting emotional responses to events is critical to put a plan to avoid risky behaviors. This paper proposes a machine learning-based framework to detect public emotions based on social media posts in response to specific events. It presents a precise measurement of population-level emotions which can aid governance in monitoring public response and guide it to put in place strategies such as targeted monitoring of mental health, to react to a rise in negative emotions in response to lockdowns, or information campaigns, for instance in response to elevated rates of fear in response to vaccination programs. We evaluate our framework by extracting 15,455 tweets. We annotate and categorize the emotions into 11 categories based on Plutchik’s study of emotion and extract the features using a combination of Bag of Words and Term Frequency-Inverse Document Frequency. We filter 813 COVID-19 vaccine-related tweets and use them to demonstrate our framework’s effectiveness. Numerical evaluation of emotions prediction using Random Forest and Logistic Regression shows that our framework predicts emotions with an accuracy up to 95%.

This paper addresses the lack of analytical tools for visual data analysis in IEEE Xplore, an abstract database of publications on technical problems in electronics and electrical engineering. The openness of the platform and the good fillability of a large number of bibliometric record fields make it attractive for visual data analysis. The topic of machine learning and artificial intelligence applied to power systems, which are critical issues in the energy transition process, is chosen as an example for visual data analysis. The programs and utilities used for data analysis were VOSviewer, Scimago Graphica, FP-Growth algorithm, Inkscape, and MultiDendrograms. The use of IEEE Terms field data to identify publication topics in the exported data is analyzed in the most comprehensive way. This paper can be considered a reference for professionals interested in bibliometric analysis and visualization of IEEE Xplore data.

This study aims to conduct a content analysis of the postgraduate theses on the education of the concept of atom in Turkey from 2000 to 2023. The study utilized the document analysis method, a qualitative research design approach. The theses were obtained by conducting a search in the "Thesis Center" of the Council of Higher Education (YÖK). "Thesis Classification Form" and "Thesis Screening Form" were used as data collection tools. Content analysis was performed on 51 theses that were conducted between 2000 and 2023 and whose full versions were accessed. It was observed that the theses were conducted in 25 different universities, using more than one data collection tool and analysis method. It was determined that most of the theses were supervised by academicians having the title of Prof.Dr. It was determined that almost all of the theses were conducted in the form of research-studies, qualitative research approach was mostly used as the research method, quasi-experimental model was mostly used as the research model, and students were generally used as the sample group. The most widely used data collection tools in the theses were interviews and achievement tests, while t-tests and content analysis were used as analysis techniques. In the selection of thesis topics, the studies in which teaching methods were tried the most were conducted. It was determined that students had difficulty in understanding the concept of atom and had misconceptions.

The author previously investigated the thermodynamic properties of the one-dimensional Potts-SOS model on the lattice of positive natural numbers N in [Akin H, Phys. Scr. 99 (2024), 055231]. In this present paper, we extend that research by determining the Gibbs measures for the same mixed-type model using partition functions constructed on a second-order semi-infinite Cayley tree. By leveraging the self-similarity of the Cayley tree, we analyze the behavior of these partition functions and identify the regions where phase transitions occur. We pinpoint these phase transition regions through a stability analysis of the dynamical system associated with the model at specific fixed points.

ObjectivesIn increasingly stressful times, many people are increasingly turning to fast food, neglecting to drink enough fluids and often forgoing regular exercise. The fast tempo of everyday life leaves little room for healthy habits, such as cooking at home, which means that a conscious and balanced diet takes a back seat.MethodsA descriptive pilot study was conducted to investigate the effects of an eight-week intervention program. This program included the daily intake of breakfast, cooking at home, adequate fluid intake and daily physical activity. The aim of the study was to evaluate the effects of these measures on the participants' body weight and general health.Results During the 56-day intervention, there was a steady trend towards weight reduction, and at the end of the intervention phase, a significant weight reduction in the test person could be observed. At the end of the intervention, the participant was still 45 years old, measured a body weight of 73.4 kg, which represents a BMI of 25.1 and is classified as slightly overweight. ConclusionThe results of the pilot study demonstrate clearly that the health mix of regular cooking at home, a daily breakfast, a daily physical activity session and sufficient fluid intake can be an effective booster for weight loss in adults. This combination has not only led to a significant reduction in body weight, but has also shown that simple, everyday measures can have a profound effect on health.

As the number of Uncrewed Aircraft Systems (UAS) operating in our National Airspace System (NAS) increases, so do UAS operations near or at an airport. The accelerating technology in Advanced Air Mobility (AAM) along with the related business opportunities will only further increase UAS operations at airports. This continued growth in new UAS technologies and applications introduces new hazards and risks to the airport environment. This proliferation of UAS highlights the importance of airports developing a robust Safety Management System (SMS) that includes specific UAS risk mitigations. To date, there is currently little empirical data regarding UAS traffic around airports. Nor is there a system to collect this data at a national level. This study attempted to gain insight into the commercial UAS operations across a broader airport population by surveying the airport manager population here in the United States. Research results found that 62% of airports are experiencing an increase in UAS operations in their surrounding airspace. This increase applies to all airspace classifications, with 67% of airports located in controlled airspace experiencing an increase in UAS operations. However, only 27% of airports have some type of UAS safety plan. Similarly, the increase in adverse UAS events near airports suggests that UAS operators may also lack robust safety plans or an understanding of the risks and regulations associated with operating near airports.

Objectives. The aim of the study is to identify relevant research topics based on pooled bibliometric data of International Journal of Hydrogen Energy publications from 2022-2024, collected from The Lens and ScienceDirect platforms. Data source. Bibliometric records of International Journal of Hydrogen Energy articles published in 2022-2024 from The Lens and ScienceDirect platforms were used. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility. Results. The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The 'Fields of Study' data of The Lens can be rationally interpreted as system keywords similar to Scopus Index Keywords. The possibility of using 'Fields of Study' data in a method similar to bibliographic coupling is shown. The practicality of using an Alluvial diagram to show the co-occurrence of the four terms was demonstrated. The study also emphasizes the advisability of joint use of VOSviewer and Scimago Graphica programs for complex visualization of bibliometric analysis results. The study identified two dominant publication topics in International Journal of Hydrogen Energy for 2022-2024, which can be described in terms of: 'Catalysis, Hydrogen, Physical_chemistry, Chemical_engineering, Nanotechnology, Electrochemistry, Organic_chemistry, Materials_science' and 'Electrical_engineering, Hydrogen_production, Renewable_energy, Environmental_science, Hydrogen_economy, Hydrogen, Engineering'.

The utilization of Artificial Intelligence (AI) in biotechnology is widespread, addressing challenges such as elucidating disease pathophysiology and novel therapeutic approaches. AI plays a critical role in tasks such as drug manufacturing, chemical analysis, RNA and DNA sequencing, and enzyme studies by automating processes and expediting data collection and analysis. AI has particularly transformed the analysis of omics data for researchers, providing tools to handle complex and multifaceted datasets effectively. Through AI, integrative analysis of multi-omics data can be conducted in efficient ways. This article discusses the application of multi-omics and AI technologies in studying various diseases related to infection (COVID-19), mutation (cancer), and senescence (alopecia) to understand their pathophysiology. The applications of AI were performed as the aspect of the diagnosis, prognosis, and treatment for each disease. We introduce AI-driven analysis of pathophysiology can overcome traditional limitations in pathology, with diverse features showing potential in defining the causes of diseases, and potentially enhancing primary omics data in the distinguish the subtype of diseases. In this context, integrated approaches using multi-omics data and AI technology could provide fresh biological insights by comprehending the molecular mechanism of diseases and is instrumental in advancing precision medicine. We anticipate that the rapidly advancing AI-based multi-omics data analysis will significantly contribute to promoting healthy longevity.

Objectives. The aim of this study was to demonstrate the ability to visualize the results of the Scilit platform's bibliometric data analysis on the topic "AI & Machine Learning" to identify publications reflecting specific issues of the topic. Data source. Bibliometric records exported from the Scilit platform on the topic "AI & Machine Learning" for the years 2021–2023 were used. For each year, 6,000 records were downloaded in CSV and RIS format. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility, GSDMM algorithm. Used services: Elicit, QuillBot, Litmaps. Results. It has been shown that bibliometric data from the open access abstract database Scilit can serve as a quality alternative to subscription-only databases. Data exported from the Scilit platform require preprocessing to make them available in a format that can be processed by programs such as VOSviewer and Scimago Graphica. The use of GSDMM and FP-growth algorithms is effective for structuring bibliometric data for further visualization. The Scimago Graphica software provides wide possibilities for building compound diagrams, in particular, for representing the network of keywords in such important coordinates for bibliometric analysis as average year of publication and average normalized citation, as well as for building an alluvial diagram of co-occurrence of more than two keywords. The possibility of using such services as elicit.com, quillbot.com and app.litmaps.com to accelerate the selection of publications on the topic under study is shown.

The anatomy of mature vertebrate hearts is marked by a looped design, which is roughly characterized by two components: (1), s-shaped (sigmoid) routing of the cardiac flow path(s), and (2,) bilaterally asymmetric (chiral) routing of the cardiac flow path(s). The looped heart design is regarded as a phylogenetically conserved feature among vertebrates and is thought to represent a significant determinant of the cardiac pumping function. It evolves during the embryonic period of development by a morphogenetic process called “cardiac looping”. During the past decades, remarkable progress has been made in the uncovering of the genetic, molecular, and biophysical factors contributing to cardiac looping. Thereby, a special focus was directed on the evolution of a bilaterally asymmetric (chiral) heart configuration, which is said to play a central role in the determination of the alignments and separations of the pulmonary and systemic flow paths in the multi-chambered hearts of tetrapods. In contrast to the recent progress made in uncovering of the biological driver of cardiac looping, our present knowledge about the functional consequences of cardiac looping is at an immature state. This article provides an overview and discussion of the currently available information about the looped design of vertebrate hearts and its functional implications.

Environmental, social, and governance (ESG) investment has become a common trend in capital markets, and many institutional investors have publicly declared their long-term ESG investment target (ESGIT). This study focuses on investors who conduct strategic asset allocation (SAA) using composite indices but establish their ESGIT outside the SAA process. A mismatch could arise between investors’ planned and actual portfolios because they must pursue their ESGIT by asset selection, which inevitably makes the constituents of their portfolios different from those of composite indices. To scrutinize the potential existence of a misalignment between their SAA and ESGIT, this study analyzes actual stock and bond indices over the past decade using traditional mean-variance optimization. The results reveal significant differences between the expected and realized performances, and the misalignment is more significant when the analysis period is divided into two sub-periods: stable and volatile. Specifically, the results indicate that the efficient frontier constructed using ESG indices significantly differs from that constructed using composite indices, and that the difference between these two efficient frontiers becomes more significant during volatile periods. Furthermore, the results show that investors cannot meet their targets if their ESGIT is established outside the SAA process.

The discovery of the quantum tunnelling effect---the transmission of particles through a high potential barrier---was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a novel deep neural network (DNN) architecture that processes information using the effect of quantum tunnelling. I demonstrate the ability of the quantum tunnelling DNN (QT-DNN) to recognise optical illusions like a human. Hardware implementation of QT-DNN is expected to result in an inexpensive and energy-efficient neuromorphic chip suitable for applications in autonomous vehicles. The optical illusions recognition tests developed in this paper should lay foundations for cognitive benchmarking tasks for AI systems of the future, benefiting the fields of sociophysics and behavioural science.

Background. Keyword co-occurrence analysis is a crucial tool for comprehending research trends, identifying relevant studies, and gaining insight into the connections between various concepts and topics. Objective. This study focuses on analyzing the co-occurrence of keywords using FP-growth algorithm and direct search methods. Materials and methods. The methodology involved extracting bibliometric data of Energies journal for 2023-2024 from MDPI publisher platform, keyword lemmatization and keyword co-occurrence estimation. Clustering and visualization were performed using Multidendrograms and Scimago Graphica software. Results. The results showed that the FP-growth algorithm can achieve a close match with the direct search results, which facilitates data preparation for clustering. In addition, finding the co-occurrence of three or more keywords significantly reduced the number of possible combinations, which allowed the identification of specific research topics. Conclusions. This study highlights the usefulness of the FP-growth algorithm in keyword analysis and provides insights into ways to refine search queries to abstract databases for the purpose of designing and writing literature and systematic reviews.

The Metaverse of Things (MoT) is an advanced technology that has the potential to revolutionise urban living in the present era. This article explores the advantages, uses, and transformative outcomes of MoT in smart cities. The covered subjects encompass sustainability, urban planning, citizen participation, infrastructure management, and various more. MoT integrates the Internet of Things (IoT) with metaverse technologies. The ultimate objective is to develop virtual environments that are highly interactive, interconnected, and immersive while maintaining a high level of fidelity to reality. The IoT utilises virtual reality (VR), augmented reality (AR), and other digital technologies to gather data, facilitate communication, and automate certain processes, thereby enhancing several elements of urban living. It is all a component of the metaverse. The IoT will bring about a profound transformation in the way cities gather and utilise data to enhance services and optimise efficiency. Cities that can efficiently distribute this data can enhance public safety, optimise energy usage, regulate traffic, and manage waste properly. MoT apps that utilise immersive technologies and the IoT can be used to generate more intelligent and captivating cityscapes. The implementation of MoT can greatly enhance the quality of life for residents of smart cities through improvements in transportation, healthcare, education, and community engagement. The study's author examined how smart cities utilise the IoT to enhance the daily experiences of their inhabitants. This study examines the technical structure, possible advantages, and difficulties of implementing MoT in urban settings, aiming to enhance the resilience, responsiveness, and adaptability of cities. The findings emphasise the importance of robust legislative frameworks, stringent security requirements, and well-developed infrastructure to facilitate the extensive use of MoT technology. These factors are crucial for establishing a highly interconnected and efficient urban environment.

This article explores the profound implications of Dr. Anthony Fauci's testimony before the U.S. House Select Subcommittee on the Coronavirus Pandemic, where he admitted that key COVID-19 policies lacked scientific backing. By analyzing the foundation of these decisions, the piece delves into the broader issues of scientific evidence, hypothesis validation, and the societal consequences of implementing unverified measures. It raises critical questions about the role of scientific rigor and accountability in policy-making, urging a reflection on our approach to scientific inquiry and decision-making in public health.

High-power lasers play an important role in modern science, industry, and medicine. A signifi-cant milestone was reached on December 5, 2022, when Inertial Confinement Nuclear Fusion (ICF) achieved scientific breakeven, releasing more energy than the input laser energy. Additionally, Extreme Ultraviolet Lithography (EUVL) has enabled the development of microchips with 3 nm process nodes, marking a leap in semiconductor technology. These examples together with the recent achievement of a 10 PW (1015 W) laser output heralds remarkable advancements in technology and science soon. Laser systems are broadly classified based on their operating re-gimes into two main categories: Continuous Wave (CW) operation, where the laser is continuously pumped and emits a steady beam of light, and the pulsed regime, in which the laser pro-duces single or multiple pulses at various repetition rates. This review will primarily focus on pulsed laser systems, exploring their various types and recent technological advancements.

Many historic buildings and monuments on the Salento Peninsula (Apulia, southern Italy) were built from locally quarried Miocene calcarenites belonging to the Pietra Leccese Formation (Late Burdigalian-early Messinian). The main facies consists of a homogeneous and porous biomicrite, pale yellow in color and fine- to medium-grained, very rich in planktonic Foraminifera and massive or thick-bedded in outcrop. Additionally, there are other facies among which Piromafo stands out for its aesthetic appearance, which is enhanced by its greenish-brown or greenish-grey colors. Its physical characteristics, in terms of thermal properties mainly due to the mineral content and fabric, make it a good refractory and insulation material. Piromafo occurs in the upper part of the Pietra Leccese Fm. and is repre-sented by a fine- to medium-grained glauconitic and phosphatic biomicrite with macrofossils, es-pecially Bivalves and Gastropods. Despite its important historical use as building and ornamental material, especially in the Roman and Baroque architecture, a research gap exists in the scientific literature describing the properties of the stone and their correlation. Therefore, the aim of this paper is to present a wide range of properties useful to explain the in-situ behavior and damage susceptibility of the stone in monu-ments and buildings, but also for selecting preservation treatments and strategies. Thus, an overall assessment of the main petrophysical and mechanical properties especially for restoration/conservation purposes was performed using both standard and unconventional tech-niques. Starting from rock fabric inspection, particular attention was given to the relationship be-tween pore-size distribution and, hydraulic and thermal properties of the material. Unconfined compressive strength, flexural strength and indirect tensile strength were also estimated.

Little has been written in literature about the clinical comparison of the single use of chlorhexidine (CHX) rather than its combination with cetylpyridinium chloride (CPC). The purpose of this study was to compare the clinical effectiveness of two at-home antiseptic regimens. Healthy subjects scheduled for dental surgery were enrolled. After the surgery, patients were randomly allocated in a first group (Group A) which received a manual ultra soft toothbrush (Mentadent Professional®), an antiseptic toothpaste with 0,12% CHX and Vitamin B3 (Mentadent Professional Azione Intensiva Gengive®) and an antiseptic mouthwash with 0,12% CHX and 0,07% CPC. The second group (Group B) received solely an antiseptic mouthwash with 0,2% in conjunction with Anti Discoloration System (Curasept ADS/DNA®) and were encouraged to use their usual toothbrush and toothpaste. Patients were instructed to use the products twice a day and to rinse for 30 seconds. On day 7, patients were examined for the Early Healing Score, Visual Plaque Index of the sutures, Numerical Rating Scale and mouthwash taste. Group A showed a statistically significant levels of EHS and taste satisfaction. The regimen based on CHX associate with vitamin B3 in the toothpaste and CPC in the mouthwash resulted in superior clinical outcomes and satisfaction compared to solely CHX.

Mercury (Hg) analyses in species of fish are performed for two reasons 1) to safeguard human health, 2) to assess environmental quality, since different environmental changes may increase the Hg concentrations in fish. These analyses are important since both natural and human activities can increase these Hg concentrations, which can vary extensively, depending on the species, age and catching location. Unfortunately, humans consuming Hg contaminated fish or other marine foodstuffs cannot taste Hg contamination; this can be only detected by chemical analysis. If the aim of Hg analysis is to protect the health of marine-food consumers, researchers workers must consider the location where the fish were caught and interpret the results accordingly. Health and environmental officials must appreciate that in specific places many local people may have a daily diet almost entirely consisting of fish or other marine foods, and these individuals should not be exposed to high concentrations of Hg. Regional and national health and environmental officials should follow the guidance of international organizations when drawing their final conclusions about whether or not the products are safe to eat.

This study presents a comprehensive comparative analysis of retrofitting techniques aimed at enhancing the seismic resilience of seismically vulnerable historical buildings. Recognizing the dual objectives of structural safety and architectural preservation, this research evaluates and compares several advanced retrofitting methods, including base isolation, strengthening of masonry, steel bracing systems, Fiber-Reinforced Polymer (FRP) wrapping, and damping devices. Each technique is critically assessed based on its effectiveness in mitigating seismic risks, its compatibility with historical architectural features, and its applicability to various building types. Base isolation is highlighted for its ability to decouple buildings from ground motion, thereby significantly reducing seismic forces and protecting architectural integrity. Strengthening of masonry through the use of fiber-reinforced polymers and steel elements enhances the ductility and strength of masonry walls, making them more resilient to seismic forces. Steel bracing systems are shown to provide essential lateral support, particularly in timber-framed structures, improving overall stability and reducing deformation during earthquakes. FRP wrapping is identified as a versatile technique that strengthens structural elements without compromising aesthetic value, making it suitable for reinforcing concrete and masonry components. Damping devices, including viscous dampers and tuned mass dampers, are discussed for their ability to dissipate seismic energy and control structural vibrations, offering a minimally invasive solution that preserves historical aesthetics. The study also addresses several challenges and research gaps associated with these retrofitting techniques, such as ensuring architectural compatibility, assessing long-term material performance, optimizing cost-effectiveness, and navigating complex regulatory frameworks. By advancing knowledge in these areas, the research aims to foster interdisciplinary collaboration and innovation in the development of retrofitting solutions. Ultimately, this study contributes to the ongoing efforts to safeguard historical buildings against seismic hazards. By leveraging cutting-edge technologies and best practices in structural engineering and architectural conservation, stakeholders can develop sustainable, cost-effective, and culturally sensitive retrofitting strategies that protect valuable cultural heritage for future generations.

Salinity, resulting from climate change and excessive mineral fertilization, burdens farmers and negatively impacts soil and water ecosystems in the Northeastern Nile Delta. Organic and biological approaches are crucial for addressing these issues. This study examined the effects of individual and combined inoculations with cyanobacteria, yeast, and Arbuscular Mycorrhizal Fungi (AMF), with or without K-humate, on enhancing salinity tolerance, increasing yield, and improving crop quality of wheat and faba bean. The aim was to reduce NPK mineral fertilizer application rates to 25% of recommended doses. An economic evaluation was also conducted. In a preliminary laboratory experiment, the interactive effects of these microbiomes on the production of plant antioxidant enzymes and soil enzymes were investigated under salinity stress. Results showed that co-inoculation, especially with K-humate, yielded superior outcomes compared to individual inoculations. The laboratory experiment findings were confirmed by a field trial conducted in saline-alkaline soil in the Northeastern Nile Delta region. The study found that the integrated inoculation of cyanobacteria, yeast, and mycorrhizae with K-humate, along with 25% mineral NPK fertilization enhanced microbial activity, including AMF colonization, spore density, and total bacteria, cyanobacteria, and yeast counts in the plant rhizosphere. It also increased soil enzyme activity, improving soil fertility compared to individual or mineral control treatments. This integration resulted in wheat yields of 2.77 tons/ha and faba bean yields of 4.75 tons/ha. Crop quality improved, with higher levels of nitrogen, potassium, phosphorus, and protein in wheat grains and faba bean seeds. Microbiomes inoculation increased potassium uptake over sodium, enhancing the potassium/sodium ratio and salt stress tolerance. This approach reduces reliance on costly mineral fertilizers by up to 75%, enabling economically viable cultivation in marginal lands. These sustainable practices optimize resource utilization, maximize economic efficiency, and preserve natural resources.

Medical image segmentation is a critical step in various healthcare applications, aiding in diagnosis, treatment planning, and disease monitoring. In this study, we investigate the efficacy of a segmentation approach based on the 2D wavelet transform. Leveraging a dataset comprising 10 diverse medical images, we evaluate the performance of our segmentation method using three key metrics: accuracy, precision, and recall. Our findings demonstrate that the proposed approach enhances segmentation accuracy, offering promising results compared to existing methods. By harnessing the multi-resolution feature extraction capabilities of the 2D wavelet transform, our method achieves improved delineation of medical image structures, paving the way for more accurate and efficient healthcare interventions.

Relevance of the subject. Keyword selection is critical to finding relevant literature and requires justification for querying abstract databases and other sources to ensure accuracy and completeness. The topic of Energy Systems is of great importance due to the introduction of renewable energy sources, modern control methods, and complex energy systems during the energy transition. The aim of this study. The goal of this paper was to identify keywords that would be useful to subject matter experts when collecting literature on a particular topic, based on entries in the IEEE Terms field. Data. Bibliometric data were exported from the IEEE Xplore platform in the following order: for 2019-2023, 2000 records sorted by relevance, for 2024, 1680 records current as of April 11, 2024. Analytical methods applied and software used. VOSviewer, Scimago Graphica implementing the Clauset-Newman-Moore algorithm and agglomerative hierarchical clustering method implemented in Multidendrograms. Results. The main issues of the Energy Systems topic are presented in tabular and graphical formats. The fpgrowth utility offers flexible data preparation options, which makes it worthwhile to conduct a separate study to analyze the score of co-occurrence terms given by its algorithm.

Background: Breast cancer and other neoplasms like acute lymphocytic leukemia pose a serious threat to public health worldwide. Treatment for malignancies including acute lymphocytic leukemia and breast cancer requires enzymes that break down L-glutamine. An amidohydrolase called L-glutaminase can be an effective chemotherapeutic tool for treating various cancers. Methods: On mineral L-glutamine agar selective medium (MGA), a few bacterial isolates were examined in the current investigation to see if they produced L-glutaminase. However, the most effective positive bacterial isolates generating L-glutaminase were identified using morphological and biochemical testing. Molecular detection using the direct Southern blotting approach was also used to determine the main positive isolate that produces L-glutaminase. L-glutaminase synthesis by bacteria was evaluated for its characteristics. Using an MTT test, the anticancer activity was evaluated. Results: exclusive bacterial isolates that used L-glutamine as their sole source of metabolic nitrogen exhibited favorable growth on MGA. PH 7.4 and a temperature of 37 0C were the ideal environmental and physiological conditions for developing positive bacterial isolates. From the soil samples taken from various soil conditions in Egypt, the morphological and biochemical analyses showed that Bacillus cereus 14579 was the main positive bacterial generating L-glutaminase isolate. At a pH of 7.4 and a temperature of 37 °C, the following activators—KCL, ZnSO4, FeSO4, K2HPO4, and MgSO4—provided the high-grade circumstances for characterizing L-glutaminase synthesis. Bacillus cereus-produced L-glutaminase has shown excellent bioavailability and effectiveness as an anticancer therapy. The yield [productivity] was 5.2 U/ml during the original manufacture from MGA, but it increased to 42.96 U/ ml by bacterial recombinant DNA manufacturing. The molecular mass of L-glutaminase was roughly 37 KDa. L-glutaminase was purified, yielding final enzyme recovery of 55 1.23%, total activity 12,990± 19.76 ( U), specific activity 384.66± 8.92( U/ mg of protein), and purification fold 2± 2.99. Furthermore, the L-glutaminase activity was raised by 19%, 23%, 15%, and 9%, respectively, by the enzymatic activators Mn2+, K+, Na+, and Fe3+. It demonstrated strong DPPH scavenging activity (IC50 = 61 μg/ mL) and anticancer activity( IC50 = 40.72, 9.7, 7.39, 20.61, 51.28, and 11.55 μg/ mL, respectively) against human liver (HepG-2), colon ( HCT-116), breast ( MCF-7), lung( A-549), lymphocytic( CCL-120), and cervical( Hela) cancer cell lines. A stronger affinity for its substrate was shown by the kinetic parameters of Km and Vmax, which were 13.2 10-5 M and 119.86 μmol/ ml/ min, respectively. Conclusion: Acute lymphocytic leukemia and breast cancer are examples of auxotrophic malignancies for which L-glutamine serves as the only metabolic source, and L-glutaminase generated by Bacillus cereus was an appropriate enzyme in the therapy of these diseases.

On 17 October 1947, Niels Bohr was made a knight of the Order of the Elephant by the King of Denmark in view of his outstanding achievements and contributions to science. Bohr designed his own coat of arms that featured a pattern of Yin and Yang (Tai Chi symbol) to symbolize the wave-particle complementarity. However, Bohr’s Yin-Yang diagram (YYD) was neither drawn based on the principles of quantum mechanics, nor did it originate from the traditional Taoist YYD. Scientists still have doubts about the legitimacy of using YYD as the icon of the wave-particle complementarity, because the YYD belonging to quantum mechanics itself is unknown so far. This article reports the YYDs existing in quantum mechanics and justifies the role of YYD in the wave-particle duality by showing that any system, whether classical or quantum, has an ideal YYD as long as it satisfies Bohr’s principle of complementarity (BPC). The deviation of a deformed YYD from the ideal YYD indicates the extent to which a real system satisfies BPC. This article constructs the quantum YYD by the complex quantum trajectory of a particle tunneling via a step barrier, which displays the continuous transition between the wave behavior and the particle behavior. It appears that the YYD designed by Bohr in his coat of arms resembles the YYD generated by tunneling motion, not only in appearance but also in the governing equation.

Rubella infection is typically mild or asymptomatic except when infection occurs during pregnancy. Infection in early pregnancy can cause miscarriage, stillbirth, or congenital rubella syndrome. Only individuals that are still susceptible to rubella infection during child-bearing age are vulnerable to this burden. Rubella containing vaccine (RCV) is safe and effective, providing life-long immunity. However, average age-at-infection increases with increasing vaccination coverage, which could potentially lead to increased disease burden as well, if the absolute risk of infection during child-bearing age increases. Dynamics of rubella transmission were explored using EMOD, a software tool for building stochastic, agent-based infection models. Simulations of pre-vaccine, endemic transmission of rubella virus introduced RCV at varying levels of coverage to determine the expected future trajectories of disease burden. Introducing RCV reduces both rubella virus transmission and disease burden for a period of around 15 years. Increased disease burden is only possible more than a decade post-introduction, and only for contexts with low current burden and high transmission intensity. Low or declining rubella virus transmission intensity is concurrently associated with both greater disease burden and greater vaccine effectiveness. The risk of increasing burden through vaccination only exists for locations with persistently high infectivity, high connectivity, and high fertility. A trade-off between the risk of a small, future burden increase and a large, immediate burden decrease strongly favors RCV introduction.

Purpose of publication: - Preparation of bibliometric data exported from the Scilit platform on energy efficiency and conservation for further analysis to identify relevant research topics. - To identify potential issues in the processing of data exported from the Scilit platform. - Providing colleagues with the opportunity to use the prepared data and examples of their analysis for independent research on topical issues of energy efficiency and energy conservation using materials provided by the Scilit platform. Research Materials: Files in CSV and RIS formats exported from Scilit for the query "energy conservation OR efficiency" in Common Fields [Title, Abstract, Keyword], using filters: Content Type → Journal Article; Year→2021-2023; Subject → Industrial Engineering (29.8K), Energy and Fuel Technology (9.8K), Manufacturing Engineering (9.2K). A total of 30K records sorted by their relevance (10K for each year) were exported. Data are current as of 14-03-2024. Methods: Preprocessing of title, annotation, and keyword field texts using lemmatization dictionaries collected on GitHub, removal of keywords taken from GATE and spaCy, and "manual" editing. Using VOSviewer to analyze publication topics by clustering keywords based on their co-occurrence. Using Scimago Graphica to build bubble diagrams.Application of the GSDMM algorithm for clustering bibliometric records by title and annotation texts. Creation of a dictionary for this algorithm using the keyword field.Use of the Carrot2 demo version and the NMF algorithm for a more detailed analysis of the topics of the record clusters obtained from GSDMM. Results: are presented in the form of initial and interim tables and graphs obtained in the course of this study. The full tables are provided as references to the attached materials. Supplementary material for this preprint on figshare: Chigarev, Boris (2024). Supplementary material for preprint "Analyzing the Possibilities of Using the Scilit Platform to Identify Current Energy Efficiency and Conservation Issues". figshare. Dataset. https://doi.org/10.6084/m9.figshare.25574058.v1

Background: RSV, or respiratory syncytial virus, is a deadly condition that is present all over the world today. The infection is initially contained in the lower respiratory tract without systemic transmission. The objective of the study: Bioinformatics was used in Egypt to create an mRNA vaccine against the Respiratory syncytial virus (RSV). Methodology: In the present screening experimental study, a lipid nanoparticles vaccine of mRNA of the surface fusion protein of Respiratory syncytial virus was manufactured. The present vaccine delivery system was lipid nanoparticles with a particle size of approximately 90 nanometres, manufactured by the hot micro-emulsion method. In stages 1 and 2 of clinical trials, the immunogenicity of the current mRNA RSV vaccine was evaluated. Results: The current vaccine demonstrated 81% immunogenicity in animal testing, but only 69% in stages 1 and 2 of clinical trials. Its side effects were manageable. The results persisted for a while. In the current trial, the vaccination proved effective as a preventative measure against RSV infection. The current vaccination lacked antibody-dependent enhancement, which causes non-protective antibodies to develop. These non-neutralizing antibodies exacerbate infection by activating cytokines and complement cascade through the formation of immune complexes or enhancement of the virus entry and replication in the host cells. On the other hand, the current RSV mRNA vaccine of the surface fusion protein consequent on the production of powerful neutralizing antibodies with prolonged immunity especially to infants and elderly candidates who received the optimal dosage regimen.

The advancement of autonomous capabilities in maritime navigation has gained significant attention, with a trajectory moving from decision support systems to full autonomy. This push towards autonomy has led to extensive research focusing on collision avoidance, a critical aspect of safe navigation. Among the various possible approaches, Dynamic Programming is a promising tool for optimizing collision avoidance maneuvers. This paper presents a DP formulation for collision avoidance of autonomous vessels. We set up the problem framework, formulate it as a multi-stage decision process, define cost functions and constraints focusing on the actual requirements a marine maneuver must comply with, and propose a solution algorithm leveraging parallel computing. Additionally, we present a greedy approximation to reduce algorithm complexity. Through case studies, we demonstrate the effectiveness of the proposed approach in navigating complex scenarios, contributing to the future of autonomous maritime navigation. Through case studies, we show the efficacy of our approach in navigating complex scenarios.

Technological advances in the last decades have led to the realization of the concept of a smart environment. A significant part of this development is decentralized ledger technology and its variant, a blockchain. The blockchain database is immutable, open to all stakeholders, secure by architecture and robust. Applying a blockchain in water supply sanitary control creates opportunities for optimization, higher quality of service, cost reduction, better sanitary standards and public control. Physical, chemical, and biological water supply contamination is a great source of public health hazards. Implementation of a blockchain for water supply IoT, from the source point to the consumption point, enables effective response to changing environments, possible cross-contamination, stormwater management or disaster and emergency action. The chapter encompasses all fundamental elements and principles of water collection, distribution and consumption, with a focus on the health hazards and sanitary requirements for potable water. The chapter listed the main contaminants, methods of their registration and elimination, and requirements for drinking water in accordance with WHO, EU Drinking Water Directive and EPA standards. Blockchain technology solutions are described for smart water supply, including smart supply management, smart contracts, tokenization, smart compliance systems, and, most importantly, effective utilization of distributed ledger technologies for sanitary monitoring of water sources, water treatment, and water distribution systems.

This paper explores the relationships between marketing strategies, social media platforms, the adoption and diffusion of products and services, and organizational resilience to gain an understanding of the ability of organizations to cope with disruptive events (e.g., COVID-19). This can be achieved through effective marketing strategies and the efficient use of social media platforms. In fact, resilience thinking can help organizations maintain their operations by increasing the adoption and diffusion of their products and services through the use of effective marketing strategies. To achieve this article’s objectives, a literature review is conducted to help develop a conceptual framework that highlights a clear relationship between the previously discussed concepts. In addition, the novel nature of the relationship between marketing strategies and organizational resilience is dissected and its significance for organizations is demonstrated. In fact, the findings of this study suggest that effective marketing strategies that consider the "what," "who," and "how" dichotomies and the efficient use of social media to promote the adoption and diffusion of products and services can significantly enhance the resilience of organizations. These relationships can serve as a starting point for further studies examining and empirically analyzing marketing strategies and their positive effect on strengthening organizational resilience.

Pakistan relies mostly on fossil fuel for fulfilling its energy demand which is expensive as 11 well as not friendly for the environment. The need of the hour is to shift from fossil fuels to renew-12 able energy resources like geothermal, wind, solar etc. to cater for global warming issues. Pakistan 13 has a lot of potential geothermal sites because of several fault lines and hot springs. A sound 14 knowledge of ground temperature is essential to use geothermal energy, which is obtained by drill-15 ing boreholes and putting sensors making it an expensive procedure. Thus, to avoid huge cost for 16 drilling bore holes, particularly for ground temperature analysis, a numerical approach has been 17 considered for determining ground temperature. Furthermore, correlation charts between air and 18 ground temperatures have been developed as there were no proper studies on the ground temper-19 ature of Pakistan. Then, with the help of a boreholes drilled in National University of Sciences and 20 Technology Islamabad Pakistan, the actual ground and numerically calculated temperatures have 21 been compared which shows an error margin in the range between 0.27% for higher depths to 7.3% 22 near surface. Thus, it is shown that the proposed method is easy to implement and better than large 23 scale testing methods for the depths at which geothermal energy is extracted.

The paper presents a method to assess the effect of electrolyte additives on the energy capacity of Pb-acid batteries. The method applies to any chemically unreactive additive, including suspensions and gels. The approach is thermodynamically based and it leads to the definition of a region of admissible concentrations –the battery’s admissible range– where the battery can undergo an indefinite number of charge/discharge cycles without suffering permanent damage. An experimental procedure to determine this range is presented. The obtained results provide a way to assess the potential of electrolyte additives to improve the energy capacity of Pb-acid batteries. The same results also provide a means to determine the additive concentration that produces the maximum energy capacity increase of the battery. The paper closes with an example of application of the proposed approach to a practical case.

Determination of antibody titre of dogs vaccinated against canine distemper in Jos North and South local Government Areas of Plateau State was carried out by collection of sera of vaccinated dogs and administration of well-structured questionnaires to dog owners. The samples collected were analyzed using the immune-blot ELISA Kit to determining the antibody titre (immunoglobulin G). It indicated that dogs vaccinated against the disease mounted adequate protective immunity. The result revealed that 54 (90.0%) of the sampled dogs have protective immunity, with those given more than one dose having higher level of protective antibody. Statistically, the result showed that the antibody titre did not differ significantly in relation to immunity and sex, breed, age and location but significant difference was seen in relation to number of primary vaccination. The result also revealed that those dogs that received booster doses (secondary vaccination) had more protective antibody. The study was aimed at evaluating the antibody titre of dogs vaccinated against canine distemper in Jos, Plateau State.

This research project was funded by the Masterplan for Acceleration and Expansion of Indonesia's Economic Development (MP3EI). The objective of this study was to examine the role of indigenous people of Marind in the agricultural development of rice cultivation in Merauke. A survey was conducted in three villages in Merauke using stratified random sampling. The finding suggest that indigenous people of Marind have a crucial role in the agricultural development of rice cultivation in Papua.

The new coronavirus SARS-CoV-2 is the cause of the COVID-19 pandemic, which has created an incomparable global health problem. PLpro is a key protein involved in viral polyprotein processing and immune system evasion, making it a prime target for the development of antiviral drugs to combat COVID-19. The review begins by elucidating the functional and structural properties of SARS-CoV-2 PLpro, underscoring its significance in viral pathogenicity and replication. Employing homology modeling, a tertiary structure model of PLpro is constructed, laying the groundwork for subsequent investigations. To expedite the search for potential therapeutic candidates, the study harnesses computational methodologies. Molecular docking techniques are employed to explore binding sites for antiviral drugs within the catalytic region of PLpro. This computational approach not only aids in drug development but also provides crucial preliminary data before experimental research commences. The stability of drug-PLpro complexes is assessed through comprehensive all-atom molecular dynamics (MD) simulations, affording dynamic insights into drug-PLpro interactions. By evaluating binding energy estimates from MD simulations, stable drug-PLpro complexes with potential antiviral properties are identified. However, it is emphasized that experimental validation is imperative to confirm these computational findings, necessitating in vitro and in vivo tests to assess safety and efficacy. This pivotal stage bridges the computational realm with real-world clinical applications. The review emphasizes the imperative need for enhancements in the existing PLpro-targeting drugs currently on the market. Their actions are insufficient for clinical use and necessitate thorough characterization and improvement. The Supervised Molecular Dynamics (SuMD) simulation technique reveals critical information about drug unbinding pathways, shedding light on opportunities for refinement. In addition to optimizing existing drugs, the investigation of sub-structurally similar molecules emerges as a promising avenue for drug development. In conclusion, the review underscores the pivotal role of targeting SARS-CoV-2 PLpro in the ongoing battle against COVID-19. By integrating molecular dynamics simulations, structural modeling, and computational insights, a robust foundation is established for identifying promising antiviral drug candidates. The continual need for improvement in existing drugs and the exploration of novel compounds remain paramount in the global effort to combat COVID-19. The evolution and management of COVID-19 hinge on the symbiotic relationship between computational insights and experimental validation, illustrating the interdisciplinary synergy crucial to this endeavor.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

Coronaviruses (CoVs) have recently emerged as significant causes of respiratory disease outbreaks. The novel coronavirus pneumonia of 2019, known as COVID-19, are highly infectious and triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding virus-host interactions and molecular targets in host cell death signalling is crucial for treatment development. Small natural compounds like celastrol and curcumin, acting as proteasome inhibitors, can potentially modify NF-κB signalling for treating SARS-CoV-2 infections. Various natural constituents, including alkaloids, flavonoids, terpenoids, diarylheptanoids, and anthraquinones, inhibit viral infection, progression, and amplification of coronaviruses. Derived from medicinal herbs, these compounds possess anti-inflammatory and antiviral properties, impacting the viral life cycle, including entry, replication, assembly, and release of COVID-19 virions. This review focuses on the development of small molecules of non-covalent inhibitors targeting the Main Protease (Mpro, also called 3CLpro) enzyme of SARS-CoV-2. It highlights the design using molecular dynamics (MD) studies and computational methods for further improvements in Mpro inhibitor design. The in-silico approach, which is pivotal in this process, provides an accelerated virtual avenue for exploring and developing potential inhibitors, representing the latest advancements in drug design.

The goal of the project was to understand how topography/bathymetry is imported and used in GeoFlood with an aim towards improving efficiency and computational cost of bathymetry handling in GeoFlood.GeoFlood is a software to simulate overland flooding basing on shallow water equations.Numerical methods and programming were used for this study.The GeoFlood was ran on a given data set (Malpasset data) and it was found out that indeed topography handling during simulations has to be improved to minimise the computational time and also improve the efficiency.Through this research, we also looked at the the shallow water equations, and the numerical techniques used to solve the equations

In recent years, machine learning (ML) techniques have emerged as an efficient and effective technology within the petroleum industry. This paper focuses on the current application of ML in enhanced oil recovery (EOR) through CO2 injection, which exhibits promising economic and environmental benefits of climate-change mitigation strategy. Our comprehensive review explores the diverse use cases of ML techniques in CO2-EOR, including aspects such as minimum miscible pressure (MMP) prediction, well location optimization, oil production and recovery factor prediction, multi-objective optimization, Pressure-Volume-Temperature (PVT) properties estimation, Water Alternating Gas (WAG) analysis, and CO2-foam EOR, from 101 reviewed papers. In this comprehensive review, we catalog relative information, including the input parameters, objectives, data sources, train/test/validate information, results, evaluation, and rating score for each area based on criteria such as data quality, ML building process, and analysis of results. We also briefly summarized the benefits and limitations of ML methods in petroleum industry applications. Our detailed and extensive study could serve as an invaluable reference for employing ML techniques in the petroleum industry. Based on the review, we found that ML techniques offer great potential in solving problems in the majority of CO2-EOR areas involving prediction and regression. With the generation of massive amounts of data in the everyday oil and gas industry, machine learning techniques can provide efficient and reliable preliminary results for the industry.

This study investigates the potential of natural compounds against HIV-1 protease, a critical enzyme in the replication cycle of human immunodeficiency virus type 1 (HIV-1). HIV-1 protease is essential for cleaving large precursor proteins into smaller functional proteins necessary for viral maturation and infectivity. Protease inhibitors, specifically targeting HIV-1 protease, effectively suppress viral replication, aiding in the management of HIV infection. Using the SWISS DOCK Server, several natural compounds were investigated for their potential as inhibitors of HIV-1 protease. Docking results revealed that Amentoflavone showed excellent binding affinity with high Estimated ΔG values, suggesting its potential as an inhibitor of HIV-1 protease. Additionally, Amentoflavone exhibited similar promising results when tested against Roussarcoma virus protease. These findings indicate the potential of Amentoflavone as a natural compound against HIV and warrant further investigation into its therapeutic applications.

Before the emergence of SARS-CoV-1, MERS-CoV, and most recently SARS-CoV-2, al-ready four other coronaviruses have been circulating in the human population. The alpha coronaviruses NL63 and 229E and the beta coronaviruses OC34 and HKU1. These circulating coronaviruses all cause mild respiratory illness during the winter seasons and most people are already infected in early life. Could antibodies and/or T cells, es-pecially against the beta coronaviruses have offered some form of protection against SARS-CoV-2? Related is the question whether survivors of SARS-CoV-1 or MERS-CoV would be relatively protected against SARS-CoV-2. More importantly, would humoral and cellular immunological memory, generated during the SARS-CoV-2 pandemic, ei-ther by infection or vaccination offer protection against future coronaviruses? Or rather than protection, could antibody dependent enhancement have taken place, a mecha-nism by which circulating corona antibodies enhance the severity of COVID-19? An-other related phenomenon, the original antigen sin, would also predict that the effec-tivity of the immune response to future coronaviruses would be impaired because of reactivation of memory against irrelevant epitopes. Current available evidence indicates that latter scenarios are highly unlikely and that especially cytotoxic memory T cells directed against conserved epitopes of human coronaviruses could at least offer partial protection against future coronaviruses.

Novel drugs profoundly changed the outcomes in CLL patients and traditional prognostic/predictive factors that were delineated in the era of chemo-immunotherapy need to be validated in the contest of these new targeted therapies. Currently, the most important prognostic genetic biomarkers are immunoglobulin heavy chain variable (IGHV) mutational status, genetic aberrations including del(17p)/TP53 abnormalities and the complex karyotype. In this review we discuss the prognostic/predictive role of these genetic markers in relation to novel treatments. Moreover, we present and discuss the new score systems that were elaborated and validated in the era of new drugs. Given the deeper responses obtained with small molecules, new prognostic/predictive markers, including measurable residual disease, and validated prognostic scores could possibly be incorporated into routine prognostic scores, to better identify “very-high” CLL patients, who will need more effective treatments.

SARS-CoV-2 infection remains a global burden. Despite intensive research, the mechanism and dynamics of early viral replication are not completely understood including the kinetics of formation of genomic RNA (gRNA), sub-genomic RNA (sgRNA) and replication centers/organelles (ROs). We employed single-molecule RNA-fluorescence in situ hybridization (smRNA-FISH) to simultaneously detect viral gRNA and sgRNA, immunofluorescence to detect nsp3 protein, a marker for the formation RO, and carried out a time course analysis. We found that single molecules of gRNA are visible within the cytoplasm at 30 minutes post-infection (p.i.). Starting from 2 hr. p.i., most of the viral RNA existed in clusters/speckles, some of which were surrounded by single molecules of sgRNA. These speckles associated with nsp3 protein starting at 3 hr. p.i., indicating that these were precursors to ROs. Furthermore, RNA replication was asynchronous as cells with RNA at all stages of replication were found at any given time point. Our probes detected the SARS-COV-2 variants of concern, and BA.1 strain exhibited slower rate of replication kinetics than the WA1 strain. Our results provide insights into the kinetics of SARS-CoV-2 early post-entry events, which will facilitate identification of new therapeutic targets to early stage replication to combat COVID-19.

The synthesis and characterization of the multicomponent crystals formed by 2,2’-thiodiacetic acid (H2tda) and 2,6-diaminopurine (Hdap) or N9-(2-hydroxyethyl)adenine (9heade) are reported. The crystals are in the salt rather than cocrystal form, as witnessed by single crystal X-ray diffractometry where a structural analysis revealed their ionic nature, confirming the proton transfer from the 2,2’-thiodiacetic acid to the basic groups of the coformers. The new multicomponent crystals have molecular formulas [(H9heade+)(Htda)] (1) and [(H2dap+)2(tda2)]·2H2O (2), and were also characterized by FTIR, elemental analysis as well as thermogravimetric/differential scanning calorimetry (TG/DSC) analyses. In the crystal packing the ions interact with each other via O–H···N, O–H···O. N–H···O and N–H···N hydrogen bonds generating cyclic hydrogen bonded motifs with graph-set notation of R22(16), R22(10), R32(10), R33(10), R22(9), R32(8) and R42(8), to form different supramolecular homo- and hetero-synthons. In addition, in the crystal packing of 2, pairs of diaminopurinium ions display an strong anti-parallel ,-stacking interaction, with short inter-centroids and interplanar distances (3.39 and 3.24 Å respectively) and fairly tight angle (17.5°). These assemblies have been further analyzed energetically by using DFT calculations, MEP surface analysis and QTAIM characterization.

This study aimed to delineate the longitudinal antibody responses to the Pfizer- BioNTech COVID-19 vaccine (BNT162b2) within the Ugandan subset of the Sub-Saharan African (SSA) demographic, filling a significant gap in global datasets. We enrolled 48 participants, collecting 320 specimens over 12 months after vaccination. A validated enzyme-linked immunosorbent assay (ELISA) was used to quantify SARS-CoV-2-specific IgG, IgM, and IgA concentrations (ng/ml) and optical densities (ODs). Statistical analyses included box plots, diverging bar graphs, and the Wilcoxon test with Bonferroni correction. We showed a robust SIgG response within 14 days of the primary vaccine dose, consistent with global data. Remarkably, we observed no significant surge in S-IgG levels following the booster, contrasting trends other global populations. The S-IgM response was transient, and predominantly established thresholds, reflecting its typical early emergence and subsequent decline. S-IgA increased initially but declined six months post-vaccination, in line with the temporal dynamics of mucosal immunity. Eleven breakthrough infections occurred; however, all were asymptomatic, indicating a protective effect from the vaccination regardless of the participants' initial S-IgG serostatus. The Pfizer-BioNTech COVID-19 vaccine elicited strong S-IgG responses in the SSA demographic. However, antibody dynamics distinctly differed from global data highlight the significance of region-specific research and the necessity for customized vaccination strategies.

Smart grids are seeing an increase in renewable energy and an enormous introduction of advanced power electronics, increasing the number of disturbance sources. This requires improving the accuracy of measurement systems capable of acquiring data for use in power system monitoring applications. Rogowski Coils (RCs) and Merging Units (MUs) are being widely deployed in controlling, metering, and monitoring of digital power systems. Because the performance of digital measurement devices has a direct influence on power measurement accuracy, it is critical to perform a laboratory calibration of these measurement instruments before they are installed in any project. To determine the magnitude and phase displacement errors of the RC+MU under normal and abnormal operating conditions, this article presents a comprehensive laboratory digital calibration system constructed from precise, readily available commercial products such as a fluxgate current transducer and a National Instrument. In addition, the analysis of measurement chain is affected by sources of uncertainty is discussed. The tests yield findings that are consistent with the relevant standards.

Covid-19 is one of humanity’s biggest threat in the 21st century with WHO figures reporting 636 million cases and up to 6.6 million deaths globally. SARS-CoV-2, the virus that causes the Covid-19 disease, is characterized by high mutation which contributes to its rapid spread. While several vaccines have been produced to minimize the severity of the coronavirus and diverse treatment regimens have been approved by the US FDA under Emergency Use Authorization (EUA), SARS-CoV-2 viral mutations continue to derail the efforts of scientists as the emerging variants evade the recommended therapies. Nonetheless, diverse computational models exist that offer an opportunity to overcome the barriers involved in developing new drugs. In this review, the focus is on the use of various virtual screening techniques like molecular docking, molecular dynamics simulations, QSAR, pharmacophore modeling, and homology modeling in repurposing SARS-CoV-2 therapeutics. The results have been promising from the computer-aided drug design (CADD) studies in suggesting potential compounds for treatment of Covid-19 and helping in bringing the pandemic under control.

Healthcare workers (HCW) have been the professional category most exposed to SARS-CoV-2. The pandemic’s impact on HCW was analyzed in terms of COVID-19-related temporary disability (TD) between February 15 2020 and May 1 2021. TDs in HCW for COVID-19 infection or quarantine were described. TD quarantine/infection ratios and TDs per 100,000 affiliated HCW were compared with the cumulative incidence (CI) of COVID-19 cases notified to the National Network of Epidemiological Surveillance. TDs rates by economic activity and occupation were computed. A total of 429,127 TDs were recorded, 36,6% for infection. Three-quarters (76%) were women. The median TD quarantine/infection ratio was 2.5 (Interquartile range [IQR] 1.5-3.9). TDs rates in HCW were always above the CI except for the last two months of the fourth wave. Hospital activities accounted for 84% of TDs and showed the highest TD rate for infection (8,279/100,000). The highest TDs rates were registered among Nursing assistants, Nursing professionals and Physicians: 7,426, 6,925 and 5,508/100,000, respectively. The results demonstrate the high impact of COVID-19 on HCW in Spain and it’s inequalities. They also confirm that TDs represent a complementary source of information for epidemiological and public health surveillance and could provide an early warning of new emerging infections.

ORF7b-2 is an accessory protein of the SARS-CoV-2 virus of only 43 amino acids. It has been implicated in various functional hypotheses, some of which predict its involvement as a trans-membrane protein. In this study, ORF7b-2 has often been compared to ORF7b-1 of the SARS virus to highlight differences and similarities with a protein that should have a similar biological role. Structural analysis of ORF7b-2 and its electrostatic characteristics show a polypeptide with both ends negatively charged and a diffuse negative charge over the entire structure. Therefore, its behavior in solution is like that of a weak negative polyelectrolyte, more precisely a polyanion with a net charge of – 4 at neutral pH. Its structure was modeled with two different modeling systems, one of which was ab initio. The two best models are similar, as confirmed by the Ramachandran plot, and show a central alpha-helical structure with two disordered and mobile ends. A normal mode analysis characterized the low-frequency dynamic aspects of the protein. The analysis of the structural shows a rigid central segment with mobile and fluctuating extremities, involved in a conformational equilibrium of the helix ↔ coil type. The calculation of the dipole moment shows its vector is not aligned with the main axis of the structure with an outward tilt of 24°. Molecular dynamics simulations were also conducted and the one in water is in good agreement with the previous results. While, the simulation performed by inserting a pre-oriented dimer (OMP) into a solvated lipid showed the low tendency of the protein to solvate in the apolar environment of the membrane. ORF7b-2 also shows a widespread distribution of negative surfaces that dynamically adjust to changes in structural organization. The BioGrid platform's [Biological General Repository for Interaction Datasets] through the BioGrid COVID-19 Coronavirus Curation Project shows a very large number of experimentally proven physical interactions unique to ORF7b-2, some of them with cytoplasmic proteins. These features of ORF7b-2, evaluated together, suggest a remarkable propensity of ORF7b-2 to interact with multiple molecular partners on both an electrostatic and hydrophobic basis. All this makes it unreasonable that the only biological function of this protein should be that exerted as an intramembrane protein.

Abstract: This is a retrospective study of patients admitted to Jackson Hospital, Montgomery, Alabama with a diagnosis of COVID-19 from January 1, 2021, to February 15, 2022. The independent variable used in the models were patient sex, age, race, BMI category, daily D-dimer categories, categories of anticoagulation doses (Enoxaparin 40 mg VS. Enoxaparin 80 mg VS Enoxaparin 1mg/kg or equivalent), bleeding episodes, and vaccination status. The three different categories of anticoagulation doses were considered for the purpose of the study. Results: The study reviewed a total of one hundred (100) hospitalized patients. Intermediate-dose anticoagulation was found to be the optimal dose as only fourteen percent (14%) patients died compared to a thirty-six percent (36%) and fifty percent (57%) death rate among those treated with low-dose and high-dose anticoagulation, respectively. The multivariate linear regression model predicting patient oxygen requirements revealed D-Dimer and bleeding status to be statistically significant predictors with a p value of <0.01. For the patients who had a D-dimer value ≥ 2 µg/mL, the oxygenation requirement was predicted to be 31 L higher than those with a D-dimer <2 µg/mL (99% CI; p<0.01). When mean D-dimer and corresponding oxygen requirements were calculated per hospitalization days category, the D-dimer levels and oxygen requirements were noted to follow the same trends indicating both values tended to increase and decrease simultaneously. Conclusion: The study concludes daily D-dimer trends can predict COVID-19 patient survival or daily oxygen requirements indicating D-dimer can be the miracle molecule for COVID-19 prognosis.

Importance and need for cyber security have increased in folds since a decade. Indirectly, the country’s security depends on the country’s cyber-physical systems. Attackers are becoming more innovative, and attacks are becoming undetectable, causing huge risks to the systems. In this scenario, intelligent and evolving detection methods should be introduced to replace the basic and outworn ones. This article discusses about new-age intelligence and smart techniques dealing with artificial intelligence (AI) models. Artificial intelligence for cyber security is reviewed, and the performance of machine learning models (ML) and deep learning (DL) models are analysed.

The worldwide prevalence of type 2 diabetes (T2D) and prediabetes is rapidly increasing, particularly in children, adolescents, and young adults. Oxidative stress (OxS) has emerged as a likely initiating factor in T2D. The role of natural antioxidant products in combating T2D is best evaluated in the context of the complex physiological processes that modulate T2D-OxS such as glycemic control and exercise. The role of natural antioxidant compounds such as vitamin E in T2D must likewise be considered beyond their roles as inhibitors of OxS. In addition to antioxidant properties, vitamin E vitamers (tocopherols and tocotrienols) also exhibit distinct abilities to regulate cellular signal transduction pathways important to T2D progression. Most research on the role of vitamin E in T2D or prediabetes has been limited to tocopherols (Ts) but emerging trials with tocotrienols (T3s) show promise. Minimizing factors that induce chronic damaging OxS and maximizing natural antioxidant protective factors may provide a means of preventing or slowing T2D progression. This “optimal redox” (OptRedox) approach also provides a framework in which to discuss the potential benefits of natural antioxidant factors such as antioxidant products. Since early, effective intervention is critical, the OptRedox strategy would be optimally effective if implemented in the pediatric population.

Landslide risk mitigation is limited by data scarcity. This could be improved using continuous landslide detection systems. In order to investigate which image types and machine learning (ML) models are most useful for landslide detection in a Norwegian setting, we compared the performance of five different ML models, for the Jølster case study (30-July-2019), in Western Norway. These included three globally pre-trained models; i) the Continuous Change Detection and Classification (CCDC) algorithm, ii) a combined k-means clustering and Random Forest classification model, and iii) a convolutional neural network (CNN), and two locally-trained models, including; iv) Classification and Regression Trees and v) a U-net CNN model. Images used included Sentinel-1, Sentinel-2, digital elevation model (DEM) and slope. The globally-trained models performed poorly in shadowed areas, and were all outperformed by the locally-trained models. A maximum Matthew’s correlation coefficient (MCC) score of 89% was achieved with model v, using combined Sentinel-1 and -2 images as input. This is one of the first attempts to apply deep-learning to detect landslides with both Sentinel-1 and -2 images. Using Sentinel-1 images only, the locally-trained deep-learning model significantly outperformed the conventional ML model. These findings contribute towards developing a national continuous monitoring system for landslides.

The product is a centrifugal air extractor, whose objective is to extract the stale air of SARS-CoV-2 or Covid-19 (Coronavirus); designed for civil and commercial use, it works with a single-phase alternating current (AC) motor of 220 (V) and 50 (Hz), with high energy efficiency (EE). Developed under the Design Thinking methodology, by electromechanical simulation using NI Multisim 14.0 software, case design using Cfturbo 2020 R2.0 CAD software, and rapid 3D prototyping with the OverLord Pro printer; with a prototype of the conventional stator winding of a synchronous motor with a two-pole PMSM/IPM single-phase alternating current (AC) field winding and a 4000 (Gauss) ferromagnetic ceramic magnet rotor. Innovating online nº 15 of invention patent nº 381968 by Nikola Tesla, 5/1/1888.One of the objectives is to link the middle level or Technical Schools with the University system (and careers with a Technological profile) through Project B374 located in the Secretariat of Science and Technology (SCyT) of the National University of La Plata ( UNLP), whose title is: “Integrated Management of Design and Innovation. Contributions for a theoretical-conceptual and methodological review” by the Director: Mg. Federico del Giorgio Solfa. Just as links were sought with the Research and Development Laboratory of the Department of Industrial Design (LIDDI-FBA-UNLP) through its Director D.I. Pablo Ungaro and D.I. Ana Bocos. In 2021, the project participated in the INNOVAR National Contest of the Ministry of Science, Technology and Productive Innovation of the Nation (MINCYT), Argentine Republic; in the "Covid-19 Projects" category, having been selected in the catalog of innovative products, won the 1st. "Covid-19 Projects" position of the National Agency for Research and Technological Development and local innovation (R+D+i) dependent on MINCYT.The results showed, according to the analysis of the test bench, that the PMSM/IPM type synchronous motor used in the centrifugal fan, with the innovation of the reactance-inductive control in series plus the capacitor in parallel, reduces the power by 67% (Watts) and active energy consumption (kWh), performing 56% more mechanical work (Joules) on the fluid air (with a 50% reduction in carbon footprint). Which leads us to the following conclusion: it is possible to develop centrifugal fans that save electricity (kWh) without the need to resort to (1) the "Fan Affinity Law", nor (2) the use of variable speed drives (VDF) or frequency (which are devices with complex and expensive electronics). Which would bring an enormous saving of the cost of electrical energy.

Background: Both natural immunity and vaccine-induced immunity to COVID-19 may be useful to reduce the mortality/morbidity of this disease, but still a lot of controversy exists. Aims: This narrative review analyzes the literature about: a) the duration of natural immunity; b) cellular immunity; c) cross-reactivity; d) the duration of post-vaccination immune protection; e) the probability of reinfection and its clinical manifestations in the recovered patients; f) comparisons between vaccinated and unvaccinated in the possible reinfections; g) the role of hybrid immunity; h) the effectiveness of natural and vaccine-induced immunity against Omicron variant; i) comparative incidence of adverse effects after vaccination in recovered individuals vs. COVID-19-naïve subjects. Material and Methods: through multiple search engines we investigated COVID-19 literature related to the aims of the review, published since April 2020 through July 2022, including also the previous articles pertinent to the investigated topics. Results: nearly 900 studies were collected and 238 pertinent articles were included. It was highlighted that the vast majority of individuals after COVID-19 develop a natural immunity both of cell-mediated and humoral type, which is effective over time and provides protection against both reinfection and serious illness. Vaccine-induced immunity was shown to decay faster than natural immunity. In general, the severity of the symptoms of reinfection is significantly lower than in the primary infection, with a lower degree of hospitalizations (0.06%) and an extremely low mortality. Conclusions: this narrative review regarding a vast number of articles highlighted the valuable protection induced by the natural immunity after COVID-19, which seems comparable or superior to the one induced by anti-SARS-CoV-2 vaccination. Vaccination of the unvaccinated COVID-19-recovered subjects may not be indicated. Further research is needed in order to: a) measure the durability of immunity over time; b) evaluate both the impacts of Omicron-5 on vaccinated and healed subjects and of hybrid immunity.

The COVID-19 was described as a respiratory illness, however further studies recognize it as a complex heterogeneous multisystemic disorder. Global efforts have been proposed to combat COVID-19, emerging diverse therapeutic options, in which discovering new drug therapies, development of vaccines and drug repurposing have been considered the most promising approaches to fight the virus. This study aimed to repurpose known drugs for use against the COVID-19, finding better therapeutic options. Seventeen biological databases were used in this study. The genetic algorithm (GA) was performed for a set of drug target classes and COVID-19 proteins as input, whose drug candidates are obtained according to the target similarities found in the target-target similarity predictive network, resulting in a drug-target interaction network. Thus, recommended drugs correspond to the union of the drug subsets found during each GA execution. Twenty-eight drugs were indicated to be the best therapeutic targets for the virus, in special, the Cyclosporine drug was administered as adjuvant to steroid treatment for COVID-19 patients which showed positive outcomes, reducing mortality in moderate and severe cases. The drugs found have used to treat other diseases, evidencing that the COVID-19 is a multisystemic disorder and suggests that the viruses’ mechanism of action presents some comorbidity with other human diseases. Evidence shows that the drugs found in this research might act together to fight the virus in a broader fashion, however further studies including in vitro and in vivo experiments are needed to find the best combination of these drugs.

Since the detection of the first COVID-19 patient, 2 years have passed, during which more than 287,862,000 people fell ill globally, of which about 1.9% died. Implementation of SARS-CoV-2 control programs required efforts from almost all countries. An important direction in the fight against COVID-19 was the formation of herd immunity, the main tool for managing the pandemic. Study goal: to assess the seroprevalence of antibodies (Abs) to SARS-CoV-2 nucleocapsid (Nc) and receptor binding domain (RBD) in the St. Petersburg population during the COVID-19 pandemic. Materials and methods. A longitudinal cohort randomized monitoring study of Ab seroprevalence (SARS-CoV-2 Nc, RBD) was organized and conducted according to a unified methodology developed by Rospotrebnadzor with the participation of the St. Petersburg Pasteur Institute. For this purpose, a cohort of 1000 volunteers was formed who participated in all five stages of seromonitoring. The cohort was divided into 7 age groups: 1-17; 18-29; 30-39; 40-49; 50-59; 60-69; 70; and older (70+) years. Seropositivity levels (Nc, RBD) were assessed by quantitative and qualitative enzyme immunoassays. During the 2nd year of monitoring, some volunteers were vaccinated with the GamCOVIDVac (84%) or EpiVacCorona (11.6%) vaccines approved in Russia. Statistical processing was carried out using the Excel 2010 software package. Confidence intervals for shares and percentages (95% CI) were calculated using the method of A. Wald and J. Wolfowitz with adjustment (A. Agresti, B.A. Coull). The statistical significance of differences was calculated by z-test, using the appropriate online calculator (p<0.05), unless indicated. Results. There was a trend towards: an increase in Nc seropositivity in stages 1-3 of seromonitoring, with a decrease in stages 4-5 among children and adults. The share of RBD seropositive steadily increased during all 5 stages of seromonitoring. The most frequently found were low anti-RBD Abs levels (22.6-220 BAU/ml). High Ab levels were recorded statistically significantly less frequently. Asymptomatic forms were observed in 84-88% of SARS-CoV-2 seropositive volunteers. By the 5th stage of monitoring, this indicator significantly decreased to 69.8% (95% CI: 66.1-73.4). The monitoring revealed a statistically significant increase in anti-RBD Abs, alongside a statistically significant decrease in the proportion of Nc seropositive. This dynamic was especially characteristic of persons vaccinated with GamCOVIDVac. Conclusion. Prior to the use of specific vaccines, a seroprevalence of anti-Nc Abs was noted. After the introduction of the GamCOVIDVac vaccine in adults, a decrease in the level of anti-Nc Abs was noted due to an increase in the proportion of RBD seropositive persons.

This research introduces Genus-Physiognomy-Ecosystem (GPE) mapping at a prefecture level through machine learning of multi-spectral and multi-temporal satellite images at 10m spatial resolution, and later integration of prefecture wise maps into country scale for dealing with 88 GPE types to be classified from a large size of training data involved in the research effectively. This research was made possible by harnessing entire archives of Level-2A product, Bottom of Atmosphere reflectance images collected by MultiSpectral Instruments onboard a constellation of two polar-orbiting Sentinel-2 mission satellites. The satellite images were pre-processed for cloud masking and monthly median composite images consisting of 10 multi-spectral bands and 7 spectral indexes were generated. The ground truth labels were extracted from extant vegetation survey maps by implementing systematic stratified sampling approach and noisy labels were dropped out for preparing a reliable ground truth database. Graphics Processing Unit (GPU) implementation of Gradient Boosting Decision Trees (GBDT) classifier was employed for classification of 88 GPE types from 204 satellite features. The classification accuracy computed with 25% test data varied from 65-81% in terms of F1-score across 48 prefectural regions. This research produced seamless maps of 88 GPE types first time at a country scale with an average 72% F1-score. In addition, mapping of solar panels and vegetation disturbance are added.

Malignant melanoma is a lethal skin cancer containing melanoma-initiating cells (MIC), implicated in tumorigenesis, invasion, and drug resistance, and characterized by elevated expression of stem cell markers, such as CD133. We previously showed that siRNA knockdown of CD133 enhances apoptosis induced by the MEK inhibitor trametinib in melanoma cells. The current study investigates underlying mechanisms of CD133’s anti-apoptotic activity in patient-derived BAKP and POT cells, harboring difficult-to-treat NRASQ61K and NRASQ61R drivers, after CRISPR-Cas9 CD133 knockdown or Dox-inducible expression of CD133. To maintain stable expression of CD133, MACS-sorted CD133(+) positive cells were expanded by ROCK-mediated conditional reprogramming of BAKP melanoma cells (BAKR). BAKR showed increased survival via reduced apoptosis after exposure to trametinib or DTIC, compared to BAKP. CRISPR-Cas9- mediated CD133 knockdown in BAKR cells (BAKR-T3) re-sensitized the cells, while CRISPR-Cas9 knockdown of CD133 in parental BAKP and POT cells even further increased trametinib-induced apoptosis (cleaved PARP) by reducing levels of anti-apoptotic BCL-xL, p-AKT, and p-BAD, and increasing pro-apoptotic BAD and active BAX. Dox-induced CD133 overexpression had the opposite effect, and blocked trametinib-induced apoptosis in both cell lines, coincident with elevated p-AKT, p-BAD, BCL-2 and BCL-xL and decreased levels of the active form of BAX and caspases-3 and -9. The roles of CD133 in AKT and BAD phosphorylation, or in the upregulation of anti-apoptotic BCL-2 family members, was further investigated by AKT knockout with siRNA, or inhibition of BCL-2 family members with navitoclax (ABT-263). Similar to CD133 knockdown, AKT1/2 siRNA knockdown in BAKP cells also reduced p-BAD. CD133 knockdown (T3)-mediated reduction of pBAD levels was equivalent in AKT-knockdown or AKT control cells indicating that CD133 may be upstream of AKT signaling. In BAKP cells treated with trametinib and/or ABT-263, effects of ABT-263 mirrored CD133 knockdown, since levels of active BAX and cleaved-PARP in BAKP-SC (CD133-) cells increased to the same level as that exhibited by BAKP-T3 cells (CD133+). CD133 may therefore activate a survival pathway where 1) increased phosphorylation of AKT induces 2) phosphorylation and inactivation of BAD, 3) decrease in the active form of BAX, and 4) reduction in caspase-mediated PARP cleavage, indicating apoptosis suppression leading to drug resistance in melanomas. Targeting survival pathways by which CD133 may confer chemoresistance in MICs can contribute to development of more effective treatments for patients with high-risk melanoma.

A growing number of emerging SARS-CoV-2 variants is being identified worldwide, potentially impacting the effectiveness of current vaccines. We report the data obtained in several Italian regions involved in the SARS-CoV-2 variant monitoring from the beginning of the epidemic and spanning the period from October 2020 to March 2021.

Background: A malfunction of the innate immune response in COVID-19 is associated with eosinopenia particularly in more severe cases. This study tested the hypothesis that this eosinopenia is COVID-19 specific and is associated with systemic activation of eosinophils.. Methods: Blood of 15 healthy controls and 75 adult patients with suspected COVID-19 at the ER were included before PCR testing and analyzed by point-of-care automated flow cytometry (CD10, CD11b, CD16 and CD62L) in the absence or presence of a formyl peptide (fNLF). 45 SARS-CoV-2 PCR positive patients were grouped based on disease severity. PCR negative patients with proven bacterial (n=20) or other viral (n=10) infections were used as disease controls. Eosinophils were identified with the use of the FlowSom algorithm. Results: Low blood eosinophil numbers (<100 cells/microL; p<0.005) were found both in patients with COVID-19 and with other infectious diseases albeit less pronounced. Two discrete eosinophil populations were identified in healthy controls both before and after activation with fNLF based on the expression of CD11b. Before activation, the CD11bbright population consisted of 5.4% (CI95% = 3.8, 13.4) of total eosinophils. After activation, this population of CD11bbright cells comprised nearly half the population (42.21%, CI95% = 35.9, 54.1). Eosinophils in COVID-19 had a similar percentage of CD11bbright cells before activation (7.6%, CI95% = 4.5, 13.6), but were clearly refractory to activation with fNLF as a much lower percentage of cells end up in the CD11bbright fraction after activation (23.7%, CI95% = 18.5, 27.6; p<0.001). Conclusion: Low eosinophil numbers in COVID-19 are associated with refractoriness in responsiveness to fNLF, which is likely caused by migration of fully functional cells to the tissue. Such homing might be beneficial as eosinophils have been implicated in viral killing.

Many individuals are wearing face masks improperly at ‘half mask’ and potentially breathing out microbes that can contaminate the air as well as anything below the nose. This note provides the first report that bacteria and fungi breathed out during nasal air exhalation are able to be cultured after landing on blood agar plates. The CFU’s are higher after both 10 breaths and extremely significant for 20 breaths compared to the control plates exposed to the air. Implications of this finding are that going ‘nose commando’ may be able to continue the spread of respiratory diseases such as COVID-19.

As reported by us and others previously (1, 2), the D614G mutation appeared in the spike glycoprotein (SPG) of the SARS-CoV-2 (the pathogen behind COVID-19) at the early stages of the pandemic and then G614 containing variant of SARS-CoV-2 became the predominant strain in most human populations across the world. However, one of the most recent reports from India (3) stated the incidence of G614 to be only 26% in the Indian population. This report is contradictory to the information available through the GenBank (4) SARS-CoV-2 sequence deposits made by various laboratories from India. The above stated report currently circulating in the Indian media is likely to create a public perception that the Indian strain is less contagious and such a notion could be harmful to people’s welfare. In view of this concern we have re-evaluated, updated and recalculated the incidence of the G614 variant in the Indian population by analyzing 395 Indian SARS-CoV-2 genomic sequences available in the GenBank as of June 26, 2020. In our analysis we have categorized the samples by the month in which the samples were collected. We have used an alignment-free software tool named Compare (5, 6), and the Basic Local Alignment Search Tool (BLAST) (7) in the present analysis. We finally inspected each of the 395 sequences physically for the presence of aspartic acid (D) or glycine (G) at the 614^th position of the spike glycoprotein. We analyzed an Australian cohort in parallel for comparison. We have found that the prevalence of G614 variant in the Indian samples for the month of June 2020 is 90.6%. The trends are similar with the Australian samples.

The severity and outcome of coronavirus disease 2019 (COVID-19) largely depends on a patient’s age. Over 80% of hospitalizations are of those over 65 years of age with a 23-fold greater risk of death. In the clinic, COVID-19 patients most commonly present with fever, cough and dyspnea. Particularly in those over 65, it can progress to pneumonia, lung consolidation, cytokine release syndrome, endotheliitis, coagulopathy, multiple organ failure and death. Comorbidities such as cardiovascular disease, diabetes, obesity and hypertension increase the chances of fatal disease, but they alone do not explain the variability in COVID-19 symptoms. Here, we present the molecular differences between the young, middle-aged and elderly that may determine whether COVID-19 is a mild or life-threatening illness. We also discuss several biological age clocks that could be used in conjunction with genetic tests to identify both the mechanisms of the disease and individuals most at risk. Finally, based on these mechanisms, we discuss treatments that could increase survival in the elderly, not simply by inhibiting the virus, but by restoring patients’ ability to clear the infection.

The current COVID-19 pandemic is one of the most devastating events in recent history. The virus causes relatively minor damage to young, healthy populations, imposing life-threatening danger to the elderly and people with diseases of chronic inflammation. Therefore, if we could reduce the risk for vulnerable populations, it would make the COVID-19 pandemic more similar to other typical outbreaks. Children don’t suffer from COVID-19 as much as their grandparents and have a much higher melatonin level. Bats are nocturnal animals possessing high levels of melatonin, which may contribute to their high anti-viral resistance. Viruses induce an explosion of inflammatory cytokines and reactive oxygen species, and melatonin is the best natural antioxidant that is lost with age. The programmed cell death coronaviruses cause, which can result in significant lung damage, is also inhibited by melatonin. Coronavirus causes inflammation in the lungs which requires inflammasome activity. Melatonin blocks these inflammasomes. General immunity is impaired by anxiety and sleep deprivation. Melatonin improves sleep habits, reduces anxiety and stimulates immunity. Fibrosis may be the most dangerous complication after COVID-19. Melatonin is known to prevent fibrosis. Mechanical ventilation may be necessary but yet imposes risks due to oxidative stress, which can be reduced by melatonin. Thus, by using the safe over-the-counter drug melatonin, we may be immediately able to prevent the development of severe disease symptoms in coronavirus patients, reduce the severity of their symptoms, and/or reduce the immuno-pathology of coronavirus infection on patients’ health after the active phase of the infection is over.

The current global pandemic of coronavirus disease 2019 (COVID-19) caused by the coronavirus SARS-CoV-2 has already had a major adverse impact on the world due to the exponentially increasing deaths due to the disease and the extreme actions taken by the world community to prevent its spread. It is important to explore novel methods of reducing the illnesses and fatality rates of the coronavirus-infected patients. Since the weakness of the immune system is one of the major contributing factors for the illnesses caused by such viruses, and since inflammation is a major contributing factor for the mortality of COVID-19 patients, interventions that boost the immune system and/or are anti-inflammatory may reduce the COVID-19 incidence and the mortality due to the disease. A large variety of interventions are known to improve the immune response and/or reduce inflammation. However, all the interventions would not be applicable or acceptable to everyone and so the interventions would need to be individualized based on individual circumstances and preferences. This approach, known as “Individualized Interventions to Improve the Immune Response”, or the I⁴R approach, should be studied in pilot clinical trials urgently, in order to potentially reduce the harm caused by the current coronavirus pandemic.

Since mid-December of 2019, coronavirus disease 2019 (COVID-19) has been spreading from Wuhan, China. As of February 21, total 75,773 confirmed cases worldwide have spread to more than two dozen countries. Transmission of COVID-19 can occur early in the course of infection since SARS-CoV-2 viral loads in asymptomatic patients are similar to that in the symptomatic patients. Therefore, more sensitive diagnostic methods are needed to detect early phase of the infection to prevent secondary or tertiary spreads. Here, we compare the RT-PCR confirmatory test results using two different SARS-CoV-2 viral RNAs from two Korean COVID-19 confirmed cases.RT-PCR method targeting the RdRP gene, which was recommended by WHO guideline, was less sensitive than targeting N genes (as per CDC guideline). Because many countries follow the WHO guideline, our findings may contribute to the early diagnosis of COVID-19.

The current spreading novel coronavirus SARS-CoV-2 is highly infectious and pathogenic and has attracted global attention. Recent studies have found that SARS-CoV-2 and SARS-CoV share around 80% of homology and use the same cell entry receptor, ACE2. These inspired us to study other receptors of SARS-CoV, which may be used for SARS-CoV-2 binding as well. In this study, we screened the gene expression of three receptors (ACE2, DC-SIGN and L-SIGN) in four datasets of normal lung tissue from lung adenocarcinoma patients and two single-cell RNA sequencing datasets from normal lung and bronchial epithelial cells separately. No significant difference in gene expression of these three receptors were found between gender groups (male vs female). We found higher gene expression of DC-SIGN in elder with age>60 and higher gene expression of L-SIGN in Caucasian than Asian. Similar to ACE2, we observed significantly higher DC-SIGN gene expression in the lungs of smokers, especially former smokers. However, smokers upregulate ACE2 and DC-SIGN gene expression in different cell types. In the whole lung, ACE2 is actively expressed in remodeled Alveolar Type II cells of former smokers, while DC-SIGN is largely expressed in monocytes of former smokers and dendritic cells of current smokers. In bronchial epithelium, no obvious gene expression of DC-SIGN and L-SIGN was observed while ACE2 was found to be actively expressed in goblet cells of current smokers and club cells of non-smokers. In conclusion, our findings may indicate that smokers, especially former smokers, and people over 60 have higher risk and are more susceptible to SARS-CoV-2 infection. Also, this study provides hints on possible SARS-CoV-2 pathogenicity mechanisms in lung infection.

Purpose: Acute kidney injury (AKI) is a severe symptom of the 2019 novel coronavirus disease (COVID-19), especially for patients in a critical condition.This study explored the potential mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on AKI at the single-cell level. Methods: 15 normal human kidney samples were collected and analyzed using single-cell RNA sequencing (scRNA-seq). Subsequently, we analyzed the components and proportions of kidney cells expressing the host cellular receptor ACE2 and the key protease TMPRSSs family, and analyzed the expression differences in Occidental and Asian populations. Results: We drafted the currently available world's largest human kidney cell atlas with 42,589 cells and identified 19 clusters through unsupervised hierarchical clustering analysis. ACE2 and TMPRSSs genes were significantly co-expressed in podocytes and proximal convoluted tubules as potential host cells targeted by SARS-CoV-2. Comparative analysis showed that ACE2 expression in kidney cells was no less than that in the lung, esophagus, small intestine and colon, suggesting that the kidney may be an important target organ for SARS-CoV-2. In addition, given the high expression of ACE2 and kidney disease-related genes in Occidental donors relative to Asian donors, Occidental populations with SARS-CoV-2 infection might be a higher risk of of kidney injury.

Selection is a fundamental part of the plant breeding process, enabling the identification and development of varieties with desirable traits. Thanks to advances in genetics and biotechnology, the selection process has become more precise and efficient, resulting in faster breeding progress and better adaptation of crops to environmental challenges. Genetic parameters related to gene additivity and epistasis play a key role and can influence decisions on the suitability of breeding material. In this study, 188 rapeseed doubled haploid lines were assessed in field conditions for resistance to Leptosphaeria spp. Through next-generation sequencing, a total of 133,764 molecular markers (96,121 SilicoDArT and 37,643 SNP) were obtained. The similarity of the DH lines at the phenotypic and genetic levels was calculated. The results indicate that the similarity at the phenotypic level was markedly different than the similarity at the genetic level. Genetic parameters related to additive gene action effects and epistasis (double and triple) were calculated using two methods: based on phenotypic observations only and using molecular marker observations. All evaluated genetic parameters (additive, additive-additive and additive-additive-additive) were statistically significant for both estimation methods. The parameters associated with the interaction (double and triple) had opposite signs depending on the estimation method.

Histological evidence of active prosthetic valve endocarditis (PVE) in cardiac valve tissue is widely regarded as a criterion established by Duke to confirm the presence of this condition, although the histological characteristics of mechanical prosthetic valve endocarditis have not yet been definitively established. The primary objective of this study was to determine the histologic differences in mechanical PVE in individuals with either early- or late-onset PVE, with the aim of distinguishing the unique aspects of this rare condition. Histological analysis of mechanical cardiac valve tissue was conducted in 27 patients who underwent surgical valve removal, comprising individuals with early onset and late-onset PVE. The findings were compared between the two groups. Histopathologically, PVE in individuals with mechanical heart valves is typically associated with the formation of vegetation and considerable neutrophil-rich infiltrates. In cases of early onset PVE, the affected valve tissue displays intense inflammation predominantly consisting of lymphocytes. In contrast, valve tissue samples from patients with late-onset PVE exhibit extensive fibrosis and inflammation, comprising macrophages, which are specialized immune cells and calcifications.

Sinonasal carcinomas are aggressive neoplasms that present a high morbidity and mortality rate with unfavorable prognosis. This group of tumors exhibits morphological and genetic diversity. Genetic and epigenetic alterations in these neoplasms are currently targets for diagnosis and treatment. The most common type of cancer originated in the sinonasal tract are sinonasal squa-mous cell carcinomas (SNSCC), which presents different histological patterns and variable his-tological aggressiveness. A significant number of alterations have been reported in sinonasal tu-mors, including deficiencies in the SwItch/Sucrose non-fermentable (SWI/SNF) chromatin remod-eling complex. In the sinonasal tract, deficiencies of the subunits SMARCB1/INI1, SMAR-CA4/BRG1 and SMARCA2 have been noted in carcinomas, adenocarcinomas, and soft tissue tu-mors with distinctive high-grade morphology and fatal prognosis. Objective: To identify the status of the SWI/SNF complex using immunohistochemistry in sinonasal squamous cell carci-nomas and its association with morphology and survival. Methods: A total of 1582 SNSCC cases were analyzed, selecting those with high-grade malignancy morphology, which were then evalu-ated immunohistochemically for SMARCB1 and SMARCA4 proteins. Their expression was compared with the biological behavior and survival of the patients. Results: Among the SNSCC, 47% corresponded to the non-keratinizing squamous cell carcinoma (NKSCC) type with high-grade characteristics, 40% were keratinizing squamous cell carcinomas (KSCC), 9% were SMARCB1-deficient carcinomas, and 4% were SMARCA4-deficient carcinomas. Mosaic expres-sion for SMARCB1 (NKSCC 33%, KSCC 21.9%) and SMARCA4 (NKSCC 14.6%, KSCC 12.2%) was identified, showing an impact on tumor size and progression. Conclusions: We identified that the mosaic expression of INI1 in NKSCC exhibited a worse prognosis compared to intact carcinomas and was similar to SMARCB1-deficent carcinoma.