Tenascin C (TNC) is an element of the extracellular matrix (ECM) of various tissues, including the skin, and is involved in modulating ECM integrity and cell physiology. Although skin aging is apparently associated with changes in the ECM, little is known about the role of TNC in skin aging. Here we found that Tnc mRNA level was significantly reduced in the skin tissues of aged mice compared with young mice, consistent with reduced TNC protein expression in aged human skin. TNC-large (TNC-L; 330-kDa) and -small (TNC-S; 240-kDa) polypeptides were observed in conditional media from primary dermal fibroblasts. Both recombinant TNC polypeptides, corresponding to TNC-L and TNC-S, increased the expression of type I collagen and reduced the expression of matrix metalloproteinase-1 in fibroblasts. Treatment of fibroblasts with a recombinant TNC polypeptide, corresponding to TNC-L, induced phosphorylation of SMAD2 and SMAD3. TNC increased the level of TGF-β1 mRNA and upregulated the expression of type I collagen by activating the TGF-β signaling pathway. In addition, TNC also promoted the expression of type I collagen in fibroblasts embedded in a three-dimensional collagen matrix. Our findings suggest that TNC contributes to the integrity of ECM in young skin and to prevention of skin aging.

Multi-objective optimization (MOO) is an optimization involving minimization of several objective functions more than the conventional one objective optimization which have useful applications in Engineering. Many of the current methodologies addresses challenges and solutions to multi-objective optimization problem, which attempts to solve simultaneously several objectives with multiple constraints, subjoined to each objective. Most challenges in MOO are generally subjected to linear inequality constraints that prevent all objectives from being optimized simultaneously. This paper takes short survey and deep analysis of Random and Uniform Entry-Exit time of objectives. It then breaks down process into sub-process and then presents some new concepts by introducing methods in solving problem in MOO, which comes due to periodical objectives that do not stay for the entire duration of process lifetime unlike permanent objectives, which are optimized once for the entire process lifetime. A methodology based on partial optimization that optimizes each objective iteratively and weight convergence method that optimizes sub-group of objectives is given. Furthermore, another method is introduced which involve objective classification, ranking, estimation and prediction where objectives are classified base on their properties, and ranked using a given criteria and in addition estimated for an optimal weight point (pareto optimal point) if it certifies a coveted optimal weight point. Then finally predicted to find how much it deviates from the estimated optimal weight point. Although this paper presents concepts work only, it’s practical application are beyond the scope of this paper, however base on analysis presented, the concept is worthy of igniting further research and application.

Reduced inhibitory glycinergic neurotransmission is implicated in a number of neurological conditions such as neuropathic pain, schizophrenia, epilepsy and hyperekplexia. Restoring glycinergic signalling may be an effective method of treating these pathologies. Glycine transporters (GlyTs) control synaptic and extra-synaptic glycine concentrations and slowing the reuptake of glycine using specific GlyT inhibitors will increase glycine extracellular concentrations and increase glycine receptor (GlyR) activation. Glycinergic neurotransmission can also be improved through positive allosteric modulation (PAM) of GlyRs. Despite efforts to manipulate this synapse, no therapeutics currently target it. We propose that dual action modulators of both GlyTs and GlyRs may show greater therapeutic potential than those targeting individual proteins. To show this, we have characterized a co-expression system in Xenopus laevis oocytes consisting of GlyT1 or GlyT2 co-expressed with GlyRα1. We use two electrode voltage clamp recording techniques to measure the impact of GlyTs on GlyRs and the effects of modulators of these proteins. We show that increases in GlyT density in close proximity to GlyRs diminish receptor currents. Reductions in GlyR mediated currents are not observed when non-transportable GlyR agonists are applied or when Na+ is not available. GlyTs reduce glycine concentrations across different concentration ranges, corresponding with their ion-coupling stoichiometry, and full receptor currents can be restored when GlyTs are blocked with selective inhibitors. We show that partial inhibition of GlyT2 and modest GlyRα1 potentiation using a dual action compound, is as useful in restoring GlyR currents as a full and potent single target GlyT2 inhibitor or single target GlyRα1 PAM.

Different therapeutic strategies have been investigated to target and eliminate HIV-1-infected cells by using armed antibodies specific to viral proteins, with varying degrees of success. Herein, we propose a new strategy by combining photodynamic therapy (PDT) with HIV Env-targeted immunotherapy, and refer to it as HIV photoimmunotherapy (PIT). A human anti-gp41 antibody (7B2) was conjugated to two photosensitizers with different charges through different linking strategies; “Click” conjugation by using an azide-bearing porphyrin attached via a disulfide bridge linker with a drug-to-antibody ratio (DAR) of exactly 4, and “Lysine” conjugation by using phthalocyanine IRDye 700DX dye with average DARs of 2.1, 3.0 and 4.4. These photo-immunoconjugates (PICs) were compared via biochemical and immunological characterizations regarding the dosimetry, solubility, and cell targeting. Photo-induced cytotoxicity of the PICs were compared using assays for apoptosis, reactive oxygen species (ROS), photo-cytotoxicity, and confocal microscopy. Targeted phototoxicity seems to be primarily dependent on the binding of PS-antibody to the HIV antigen on the cell membrane, whilst being independent of the PS type. This is the first report of the application of PIT for HIV immunotherapy by killing HIV Env-expressing cells.

This study uses Landsat 8 and Digital Elevation Models (DEM) to show the dominant orientations of digital lineaments and morphotectonic features between measured trends and the tectonic evolution of the Upper Guajira, Colombia, in the northernmost region of the South American plate. Data from Landsat-8 and hillshaded images of three Digital Elevation Model (DEM) images with different resolutions (SRTM: 90m, ASTER-GDEM: 30m and Alos-Palsar: 12.5m), were used for the extraction and mapping of morpholineaments, drainage network and morphological features. Lineaments were analyzed by means of north azimuth frequency, length, density distributions, lithological distributions and geochronological periods. Tectonic control was supported by using the digitized geological map created by the Colombian Geological Service (SGC). Lineaments and faults were analyzed through the interpretation of a Riedel shear model as a result of the transtensional/transpressional tectonic arrangement of the Caribbean and South American plates. The directional trends of lineaments and faults indicate two dominant directions: NE-SW and E-W. The azimuth distribution analysis of measured structures and drainage channels show similar trends, except for some differences in the predominant directions of some drainage channels. The similarity in the orientation of lineaments, faults and drainage system highlights the degree of control exerted by underlying structures on the surface geomorphological features. Drainage channel classification illustrates the morphological and neo-tectonic complexity of the region. The extracted lineaments were divided into five geochronological groups based on the main ages of host rock formations according to the Colombian Geological Service (SGC) geological map. From the Cretaceous onward, the lineament azimuth frequency rotates from a NE-SW trend to a prominent E-W direction, which resembles the translation that Caribbean plate has been undergoing since the Cretaceous. Our results confirm that Remote Sensing techniques are reliable and useful to study the morphotectonic of an area and can be applied to zones of difficult access.

Voltage sags can cause the interruption of power supply and can negatively affect operations of customers. In this paper, the authors study the impact of battery energy storage systems (BESS) on voltage sags. A stochastic method of fault positions is used. Faults of various types are simulated and voltages are recorded. Firstly, with the BESS integrated into the network, there are higher residual voltages, fewer voltage sags and less expected critical voltage loss. Secondly, if the BESS converter power factor is reduced, recorded residual voltages are higher, voltage sags are fewer, and the number of expected critical voltage sags is lower. Finally, when three BESS converter control modes, namely constant voltage, constant power factor, and constant reactive power, were assessed, results showed similar voltage sag performances for constant power factor and constant reactive power modes. Furthermore, operating in constant voltage control outperformed the other two modes as it resulted in higher residual voltages, a lower number of voltage sags, and fewer expected critical voltage sags. The paper has demonstrated that the BESS can improve voltage sag performance. In addition, the power factor of the BESS converter and the mode of operation of the converter can influence the magnitude of the voltage sag performance improvement.

Fibrosis is a condition characterized by thickening or/and scarring of various tissues. Fibrosis may develop in almost all tissues and organs, and it may be one of the leading causes of morbidity and mortality. It provokes excessive scarring that excels the usual wound healing response to trauma in numerous organs. Currently, very little can be done to prevent tissue fibrosis, and it is almost impossible to reverse it. Therefore, fibrosis is frequently associated with premature aging. In turn, aging is associated with more frequent incidences of fibrosis. Anti-inflammatory and immunosuppressive drugs are among the few treatments that may be efficient in preventing fibrosis. Numerous publications suggest that cannabinoids and extracts of Cannabis sativa have potent anti-inflammatory and anti-fibrogenic properties. In this review, we describe the types and mechanisms of fibrosis in various tissues and discuss various strategies for prevention and dealing with tissue fibrosis. We further introduce cannabinoids and their potential for the prevention and treatment of fibrosis, and therefore for extending healthy lifespan.

Ascorbate; Pars Plana Vitrectomy; Open Angle Glaucoma; Oxidative Stress; Vitreous Me-tabolism 0. How to Use This Template

Orthologs of human glucocorticoid receptor (GR) and human mineralocorticoid receptor (MR) first appear in cartilaginous fishes. Subsequently, the MR and GR diverged to respond to different steroids: the MR to aldosterone and the GR to cortisol and corticosterone. We report that cortisol, corticosterone and aldosterone activate full-length elephant shark GR, and progesterone, which activates elephant shark MR, does not activate elephant shark GR. However, progesterone inhibits steroid binding to elephant shark GR, but not to human GR. Together, this indicates partial functional divergence of elephant shark GR from the MR. Deletion of the N-terminal domain (NTD) from elephant shark GR (truncated GR) reduced the response to corticosteroids, while truncated and full-length elephant shark MR had similar responses to corticosteroids. Swapping of NTDs of elephant shark GR and MR yielded an elephant shark MR chimera with full-length GR-like increased activation by corticosteroids and progesterone compared to full-length elephant shark MR. Elephant shark MR NTD fused to GR DBD+LBD had similar activation as full-length MR, indicating that the MR NTD lacked GR-like NTD activity. We propose that NTD activation of human GR evolved early in GR divergence from the MR.

Cisplatin-based chemotherapy has long been viewed as the first-line chemotherapy for advanced and metastatic urothelial carcinoma (UC). However, many patients with UC have been classified as “cisplatin-ineligible patient”, which requires alternative chemotherapy due to their poor responses. In fact, vast majority of those who initially responded to cisplatin-based chemotherapy eventually progressed. Understanding of UC tumor immunology provided an immunopathogenic bases for immune checkpoint inhibitors, targeting PD-1 and CTLA-4, to treat cisplatin ineligible metastatic UC and patients with platinum-refractory metastatic UC. In 2020, data from the trail further showed that PD-L1 inhibitors benefit prolonged survival and progression-free survival as maintenance therapy. Besides immune-targeting therapies, manipulation of tumor microenvironment via metabolic pathways alternation, such as inhibiting tumor glycolysis, lactate accumulation and exogenous glutamine uptake, has been investigated in the past few years. In this comprehensive review, we started by introducing traditional chemotherapy of UC, and summarized current evidences supporting the use of immune checkpoint inhibitors and highlighted ongoing clinical trials. Lastly, we reviewed the tumor metabolic characteristic and the anti-tumor treatments targeting metabolic pathways.

Solidago virgaurea L. (European goldenrod, Woundwort), Asteraceae, is a familiar medicinal plant in Europe and other parts of the world, widely used and among the most researched species from its genus. The aerial parts of European goldenrod have long been used for urinary tract conditions and as an anti-inflammatory agent in the traditional medicine of different peoples. Its main chemical constituents are flavonoids (mainly derived from quercetin and kaempferol), C6-C1 and C6-C3 compounds, terpenes (mostly from the essential oil), and a large number of saponin molecules (mainly virgaureasaponins and solidagosaponins). Published research on its potential activities is critically reviewed here: antioxidant, antiinflammatory, analgesic, spasmolitic, antihypertensive, diuretic, antibacterial, antifungal, antiparasite, cytotoxic and antitumor, antimutagenic, antiadipogenic, antidiabetic, cardioprotective, and antisenescence. The evidence concerning its potential benefits is mainly derived from non-clinical studies, some effects are rather modest, whereas others are more promising, but need more confirmation in both non-clinical models and clinical trials.

There are potential overlapping distributions of the protozoan parasite Leishmania and the parasitic helminth Schistosoma mansoni in eastern Africa most notably in endemic regions in the Sudan and Kenya. In murine model studies, the Th₁-Th₂ model of CD4+ T helper cell differentiation is a well-established paradigm for understanding the basis of protective versus pathogenic immune responses in the concomitance state that result in enhanced pathological changes and impaired parasite resolution. In complementation to the experimental studies, the concern for presages of human leishmaniases and schistosomiasis co-infections occurring is increased by their chronicity, displacement of people between endemic areas owing to conflict, climatic changes due to human activities, the spread through irrigation, pisciculture, water conservation schemes and human mobility in pursuit of economic dynamics and resources. Based on diseases prevalence, epidemiology and analyzing the associated risk factors undercurrents, several portents of comorbidity in Kenya are pinpointed. Taking into consideration the limited local resources and diminished surveillance of the areas affected by the two neglected tropical diseases, the discourse concludes that elimination of the diseases is still a challenge. There is need for pilot studies and/or elaborate field surveillance of concomitance and development strategies to mitigate the impending defy in Kenya and beyond.

Student retention is one indicator of accountability in the implementation of educational programs. Achievement of student retention rates indicates the performance of the quality objectives of an institution or college. To get an accurate picture of the factors related to retention, we need to do modeling. The retention variable is the time response variable measured in semester units. One of the statistical analyzes that can be used to analyze response data in time is survival analysis. The selection of an accurate analytical method in modeling will produce valid conclusions and impact making policies that are right and on target. This paper presents alternative modeling of student retention in distance education using survival analysis. The method used is a literature review. This paper also briefly describes distance education, open and distance education, distance education students' characteristics, distance education student retention, and survival models for modeling student retention in distance education.

Large quantities of clothing are routinely discarded, ending up in landfills that contribute to the environmental crisis; hence, it is worthwhile investigating how to dispose of this waste in a sustainable way. This study considered environmental values and prosocial behavior from a behaviorism theory. The aim was to set up an environmental protection model for the sustainable disposal of consumer clothing. A structural equation modeling analysis of 407 undergraduate and postgraduate consumer data in Taiwan revealed that consumers’ choice to donate clothing was influenced by environmental values and prosocial behaviors. Clothing resale was influenced by the factor of prosocial behavior. However, prosocial consumers used other disposal patterns instead of resale. Clothing reuse was not influenced by either environmental values or prosocial behavior. The results indicated that environmental values and prosocial behavior did in fact influence consumers’ choices regarding clothing donation. However, prosocial consumers used other disposal patterns instead of resale. Behaviorism theory model is effective in analyzing the factors influencing sustainable clothing disposal. To face clothing waste issues, one can intensify traditional values of industriousness and thriftiness, of compassion and sympathy to others, to accelerate the promotion of the sustainable disposal of clothing.

The popularity of functional gummies has increased, which is evident from the growing line of functional gummies from almost every nutraceutical companies. Sensory evaluation serves the purpose of determining which brand of functional gummy would capture the largest market share. Texture profile analysis was used to determine the mechanical properties of functional gummies. The brands of functional gummies that came under the scope of this study were denoted as Brand A, B, C, D, E, F and G. Fourier Transform Infrared Spectroscopy was utilised to detect organic material and functional groups in the functional gummies. Texture profile analysis gave valuable insights into the gummies’ mechanical properties which are cohesiveness, springiness, hardness, gumminess, and chewiness. Amongst the gummies that were studied, Brand F gummy has the highest value of cohesiveness of 0.92. Brand A gummy has a high springiness value of 1.0. Brand B gummy possesses the highest value of hardness, gumminess and chewiness of 12 532.2 g, 7617.6 N, and 6256.8 J, respectively. Qualitative sensory evaluation reveals that Brand G gummy has the best aesthetic qualities in terms of colour and appearance. Brand B gummy tastes the best while brand A gummy claims the top spot for gumminess and chewiness. Overall, the respondents in this study preferred brand A gummy over other brands.

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential for sustenance of life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context, to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were tested and implemented for mostly cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more complex systems (for instance, multi-protein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate and the development of a new kind of kinetic analysis to study these systems is required. The current review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

Bank crisis can mostly be traced to a decrease in the value of bank assets. Banks are vulnerable to a number of risks. This happens in one or a combination of the following incidences; when loans turn bad and cease to perform (credit risk), when there are excess withdrawals over available funds (liquidity risk) and rising interest rates (interest rate risk). Bad credit management, market inefficiencies and operational risk, among a host others can trigger panic withdrawals by depositors with a sense of insecurity emanating from the fear of loss of investment. In fact, the failure of Barings Bank and Lehman Brothers Holdings Inc was attributable to varied factors spanning from non-monitoring of employee activities, management’s involvement in dubious accounting practices, unethical business practices by management, over indulging in risky and unsecured derivative trade. To guide against similar bank collapse in the near future, there should be an enhanced communication among international regulators and authorities that exercise oversight responsibilities on the security market. National bankruptcy laws should be invoked to forestall liquidity crisis so as to prevent freezing of margins and positions of solvent customers.

The intensive care units in North West London are part of one of the oldest critical carenetworks in the UK, forming a mature and established strategic alliance to shareresources, experience and knowledge for the benefit of its patients. North WestLondon saw an early surge in COVID-19 admissions, which urgently threatened thecapacity of some of its intensive care units even before the UK government announcedlockdown. The pre-existing relationships and culture within the network allowed itsmembers to unite and work rapidly to develop agile and innovative solutions, protectingany individual unit from becoming overwhelmed, and ultimately protecting its patients.Within a short 50-day period 223 patients were transferred within the network todistribute pressures. This unprecedented number of critical care transfers, combinedwith the creation of extra capacity and new pathways, allowed the region to continue tooffer timely and unrationed access to critical care for all patients who would benefitfrom admission. This extraordinary response is a testament to the power and benefitsof a regionally networked approach to critical care, and the lessons learned maybenefit other healthcare providers, managers and policy makers, especially in regionscurrently facing new outbreaks of COVID-19.

This paper presents a methodology to calculate day-ahead wind speed predictions based on historical measurements done by weather stations. The methodology was tested for three locations: Colombia, Ecuador, and Spain. The data is input into the process in two ways: 1) as a single time series containing all measurements, and 2) as twenty-four separate parallel sequences, corresponding to the values of wind speed at each of the 24 hours in the day over several months. The methodology relies on the use of three non-parametric techniques: Least-Squares Support Vector Machines, Empirical Mode Decomposition, and the Wavelet Transform. Also, the traditional and simple Auto-Regressive model is applied. The combination of the aforementioned techniques results in nine methods for performing wind prediction. Experiments using a MATLAB implementation showed that the Least-squares Support Vector Machine using data as a single time series outperformed the other combinations, obtaining the least mean square error.

(1) Background: Little is known about the baroque composer Domenico Scarlatti (1685-1757), whose life was centred behind closed doors at the royal court in Spain. There are no reports about his illnesses. From his compositions, mainly for harpsichord, an outstanding virtuosity can be read. (2) Case Presentation: In this case report, the only known oil painting of Domenico Scarlatti is presented, on which he is about 50 years old. In it one recognizes conspicuous hands with hints of watch glass nails and drumstick fingers. (3) Discussion: Whether Scarlatti had chronic hypoxia of peripheral body regions as a sign of, e.g., bronchial cancer or a severe heart disease, is not known. (4) Conclusions: The above-mentioned signs recorded in the oil painting, even if they were not interpretable at that time, are clearly represented and recorded for us and are open to diagnostic discussion from today's point of view.

In humans, coronaviruses can cause infections of the respiratory system, with damage of varying severity depending on the virus examined: ranging from mild or moderate upper respiratory tract diseases, such as the common cold, to pneumonia, severe acute respiratory syndrome, kidney failure and even death. Human coronaviruses known to date, common throughout the world, are seven. The most common - and least harmful - ones were discovered in the 1960s and cause a common cold. Others, more dangerous, were identified in the early 2000s and cause more severe respiratory tract infections. Among these the SARS-CoV, isolated in 2003 and responsible for the Severe Acute Respiratory Syndrome (the so-called SARS), which appeared in China in November 2002, the Coronavirus 2012 (2012-nCoV) cause of the Middle Eastern Respiratory Syndrome from Coronavirus (MERS), which exploded in June 2012 in Saudi Arabia, and actually SARS-CoV-2. On December 31, 2019, a new Coronavirus strain was reported in Wuhan, China, identified as a new Coronavirus beta strain ß-CoV from Group 2B, with a genetic similarity of approximately 70% to SARS-CoV, the virus responsible. of SARS. In the first half of February, the International Committee on Taxonomy of Viruses (ICTV), in charge of the designation and naming of the viruses (i.e., species, genus, family, etc.), thus definitively named the new coronavirus as SARS-CoV-2. This article highlights the main knowledge we have about the biomolecular and pathophysiologic mechanisms of SARS-CoV-2.

In the context of multiple repurposing of rural spaces, tourism represents a path for development, with the potential to revitalize these areas. The conservation and restoration of heritage, and its promotion through tourism, can become an opportunity for local development, in which a range of stakeholders fulfil different roles in the carrying out of the processes involved. The aim of the study was to analyse the process and results of channelling heritagisation through tourism in Mértola (Baixo Alentejo, Portugal). A series of interviews with the chief stakeholders in the process was conducted, from which the contexts and conceptualisations of development were determined. On the basis of secondary data (statistics), an analysis of the impacts of the process of heritagisation and the development of tourism was undertaken. The objectives of this study consisted in determining: a) the importance of the process of heritagisation in Mértola; b) the viability of the project, given the cost and lack of comprehensive conservation, in creating a unified whole; d) the performance of, and power relationships between, the various stakeholders; e) the limited participation of locals due to disaffection with the project; f) the correlation between heritage, rural tourism and local development.

Human eye is a specialized organ with complex anatomy and physiology, because it is characterized by different cell types with specific physiological functions. Given the complexity of the eye, ocular tissues are finely organized and orchestrated. In the last few years many in vitro models have been developed, in order to meet the 3Rs principle (Replacement, Reduction and Refinement) for eye toxicity testing which is necessary to ensure that the risks associated with ophthalmic products meet appropriate safety criteria and are clearly labelled. In vitro preclinical testing is now a well-established practice of significant importance for evaluating the efficacy and safety of cosmetic, pharmaceutical, and nutraceutical products. Along with in vitro testing, also computational procedures, herein described, for evaluating the pharmacological profile of potential ocular drug candidates including their toxicity, are in rapid expansion. In this review the ocular cell types and functionality are described providing an overview about the scientific challenge for the development of three-dimensional in vitro models.

For bounded unit interval, we propose a new Kumaraswamy generalized (G) family of distributions from a new generator which could be an alternate to the Kumaraswamy-G family proposed earlier by Cordeiro and de-Castro in 2011. This new generator can also be used to develop alternate G-classes such as beta-G, McDonald-G, Topp-Leone-G, Marshall-Olkin-G and Transmuted-G for bounded unit interval. Some mathematical properties of this new family are obtained and maximum likelihood method is used for estimating the family parameters. We investigate the properties of one special model called a new Kumaraswamy-Weibull (NKwW) distribution. Parameter estimation is dealt and maximum likelihood estimators are assessed through simulation study. Two real life data sets are analyzed to illustrate the importance and flexibility of this distribution. In fact, this model outperforms some generalized Weibull models such as the Kumaraswamy-Weibull, McDonald-Weibull, beta-Weibull, exponentiated-generalized Weibull, gamma-Weibull, odd log-logistic-Weibull, Marshall-Olkin-Weibull, transmuted-Weibull, exponentiated-Weibull and Weibull distributions when applied to these data sets. The bivariate extension of the family is proposed and the estimation of parameters is given. The usefulness of the bivariate NKwW model is illustrated empirically by means of a real-life data set.

Hepatitis B virus (HBV) infection remains a global public problem despite the availability of effective vaccine. In the past decades, nonalcoholic fatty liver disease (NAFLD) has surpassed HBV as the most common cause of chronic liver disease worldwide. The prevalence of concomitant chronic hepatitis B (CHB) and NAFLD, thus, reaches endemic in geographic regions where both conditions are common. Patients with CHB and NAFLD are at increased risk of liver disease progression to cirrhosis and hepatocellular carcinoma. Due to complexity of the pathogenesis, accurate diagnosis of NAFLD in CHB patients can be challenging. Liver biopsy is considered the gold standard for diagnosing and determining the disease severity, but it is an invasive procedure with potential complications. There is a growing body of literatures on the application of novel noninvasive serum biomarkers and advanced radiological modalities to diagnose and evaluate NAFLD, but most have not been adequately validated especially for patients with CHB. Currently, there is no approved therapy for NAFLD though many new agents are in different phases of development. This review provides a summary of the epidemiology, clinical features, diagnosis and management of the NAFLD and highlights the unmet needs in the areas of CHB and NAFLD coexistence.

Intensive crop production and extensive use of harmful synthetic chemical pesticides create numerous socio-economic problems worldwide. Therefore, sustainable solutions are needed for insect pest control, such as biological control agents. The fungal insect pathogen Beauveria bassiana has shown considerable potential as a biological control agent against a broad range of insects. The insights into virulence mechanism of B. bassiana is essential to show the robustness of its use. B. bassiana has several determinants of virulence, including the production of cuticle-degrading enzymes (CDEs), such as proteases, chitinases, and lipases. CDEs are essential in the infection process as they hydrolyze the significant components of the insect's cuticle. Moreover, B. bassiana has evolved effective antioxidant mechanisms that include enzyme families that act as ROS scavengers, e.g., superoxide dismutases, catalases, peroxidases, and thioredoxins. In B. bassiana, the number of CDEs and antioxidant enzymes characterized in recent years. The enzymatic activities are crucial for the biological control potential and significantly advanced our understanding of the infection mechanism of B. bassiana. This review focuses on the progress detailed in the studies of these enzymes and provides an overview of enzymatic activities and their contributions to virulence.

Malassezia is lipid-dependent commensal yeast of the human skin. The different culture media and skin sampling methods used to grow these fastidious yeasts are a source of heterogeneity in culture-based epidemiological study results. This study aimed to compare the performances of three methods of skin sampling, and two culture media for the detection of Malassezia yeasts by culture from the human skin. Three skin sampling methods, namely sterile gauze, dry swab and TranswabTM with transport medium, were applied on 10 healthy volunteers. Each sample was further inoculated onto either the novel FastFung medium or the reference Dixon agar for the detection of Malassezia spp. by culture. At least one colony of Malassezia spp. grew on 93/300 (31%) of the cultures, corresponding to 150 samplings. The positive culture rate was 67%, 18%, and 15% (P < 10-3), for samples collected with sterile gauze, TranswabTM, and dry swab, respectively. The positive culture rate was 62% and 38% (P < 0.003) by using the FastFung and the Dixon media, respectively. Our results showed that sterile gauze rubbing skin sampling followed by inoculation on FastFung medium should be implemented in the routine clinical laboratory procedure for Malassezia spp. cultivation.

The remarkable adsorption capacity of graphene derived materials has prompted their examination in composite materials suitable for deployment in treatment of contaminated waters. In this study, crosslinked calcium alginate – graphene oxide beads were prepared and activated by exposure to pH 4 by using 0.1M HCl. The activated beads were investigated as novel adsorbents for the removal of organic pollutants (Methylene Blue dye and the pharmaceuticals Famotidine and Diclofenac) with a range of physicochemical properties. Effects of initial pollutant concentration, temperature, pH and adsorbent dose were investigated and kinetic models were examined for fit to the data. Maximum adsorption capacities q_max obtained were 1334, 35.50 and 36.35 mg g^-1 for the uptake of Methylene blue, Famotidine and Diclofenac respectively. The equilibrium adsorption had an alignment with Langmuir isotherms while the kinetics were most accurately modelled using a pseudo- first –order and second order models according to the regression analysis. Thermodynamic parameters such as ΔG^◦, ΔH^◦ and ΔS^◦ were calculated and the adsorption process was determined to be exothermic and spontaneous.

This document describes the theoretical basis of the algorithms used to determine properties of snow and ice from the measurements of the Ocean and Land Color Instrument (OLCI) onboard Sentinel-3 satellites within the Pre-operational Sentinel-3 snow and ice products (SICE) project: http://snow.geus.dk/. The code used for the SICE retrieval and its documentation can be found at https://github.com/GEUS-SICE/pySICE. The algorithms were developed after the work from Kokhanovsky et al. (2018, 2019, 2020).

In real financial market, the delayed market feedback and the delayed effect of government macro-control are inevitable. And both the delay of market feedback and the delay of macro-control effect bring about the mathematical difficulties in studying stabilization and synchronization of the hyper-chaotic financial system. However, employing Lyapunov function method, differential mean value theorem, suitable bounded hypotheses and pulse control technology results in the globally asymptotical stabilization and synchronization criteria. It is the first paper to drive the stabilization and synchronization criteria under the assumptions of the double delays. Finally, numerical examples illuminate the effectiveness of the proposed methods.

Transparent binder is used to substitute conventional black asphalt binder and to provide light-colored pavements, whereas nano-TiO2 has the potential to promote photocatalytic and self-cleaning properties. Together, these materials provide multifunction effects and benefits when the pavement is submitted to high solar irradiation. This paper analyses the physicochemical and rheological properties of a transparent binder modified with 0.5%, 3.0%, 6.0%, and 10.0% of nano-TiO2 and compares it to the transparent base binder, and conventional and polymer modified binders (PMB) without nano-TiO2. Their penetration, softening point, dynamic viscosity, master curve, black diagram, Linear Amplitude Sweep (LAS), Multiple Stress Creep Recovery (MSCR), and Fourier-Transform Infrared Spectroscopy (FTIR) were obtained. The transparent binders (base and modified) seem to be workable considering their viscosity and exhibited values between the conventional binder and PMB regarding rutting resistance, penetration, and softening point. They showed similar behavior as the PMB, demonstrating signs of polymer-modification. The addition of TiO2 seems to reduce fatigue life, except for the 0.5% content. Nevertheless, its addition in high contents increases the rutting resistance. The TiO2 modification seems to have little effect on the chemical functional indices. The best percentage of TiO2 was 0.5%, considering fatigue and 10.0% concerning permanent deformation.

The market of ready-to-eat salads is experiencing a noticeable growth in Europe. Since they are intended to be consumed without additional treatments, these ready-to-eat products are associated with a high microbiological risk. The aim of this work was to evaluate the microbiological quality and safety of ready-to-eat salads sold in widespread supermarket chains in Lazio, Italy, at the packaging date, during shelf-life and during home-refrigeration. The study also aimed to determine the differences between low, medium, and high cost products. Salmonella spp., L. monocytogenes were chosen as safety indicators as specified by European regulations while total aerobic mesophilic bacteria and Escherichia coli were chosen as quality indicators as suggested by national guidelines. Analyses were performed following the ISO standards and in parallel, for the evaluation of total aerobic mesophilic bacteria, with an alternative colorimetric system, the Micro Biological Survey method, in order to propose a simple, affordable and accurate alternative for testing the microbiological quality of products, especially suitable for small and medium enterprises and on-site analyses. The study revealed high, unsatisfactory, total bacterial loads in all analyzed samples at the packaging date and expiring date and a very high prevalence of Salmonella spp. (67%) regardless of the selected varieties and cost-categories; L. monocytogenes was instead not recovered aligning with the results obtained in other studies.

Objective: Identify factors associated with excessive day time sleepiness (EDS) in individuals with obstructive sleep apnea (OSA), and analyze the effects that obesity and gender have on excessive daytime sleepiness in such individuals. Methods: A total of 160 people were selected for this study. All the people have completed a clinical evaluation, and whose apnea-hypopnea index (AHI) > 10 events/hour of sleep on polysomnography were included in the study from the Department of otolaryngology. Results: The Mean age was 43.87±11.34 years, mean EDS score was 14.09± 4.91, and mean AHI was 43.88±20.66 events/hour of sleep. Male presented lower mean age, higher EDS scores, and more time in apnoea, whereas females presented with higher mean age, lower EDS scores, and less time in sleep apnea. The EDS score showed best correlation with duration of apnoea (r = 0.448; p < 0.01), peripheral oxygen saturation (SpO₂; r = -0.458; p < 0.01) and AHI (r = 0.484; p < 0.01). The mean body mass index (BMI) was 27.41±3.86 kg/m². Normal, Overweight, obese, and morbidly obese were observed in 20%, 61%, 18%, and 0.6% of cases, respectively. Severity of the disease best correlated with BMI (r = 0.421; p < 0.01). Conclusions: OSA is predominant in males (M/F 5:1), and obese population. Females diagnosed with OSA have higher mean age. However, EDS scores and time spent in sleep apnoea is lower in females. Higher BMI is associated with EDS, irrespective of gender.

Reciprocal Personal/Public Protection (RPPP) featured with source control is introduced, Mask Discriminating Mouth and Nose (MDMN) is employed to serve the purpose, which includes polymer based mouth cover with optional nose cover. The new knowledge that mouth is a primary, active and dominant source of the virus has been well established, which is the base of MDMN. Source classification and related source control tools are discussed, mouth cover is recommended as the tool prioritized to use. Liquid droplets is identified as a hard issue related to mask, liquid droplets, mask fitting, comfort and facial recognition constitute real challenges of mask in addition to efficiency, All of these have been addressed with MDMN. Comparisons between MDMN and masks/face covering are taken on four aspects: efficiency and efficacy, tolerance and comfort, cost and waste, and civil rights and public interest. Mouth cover is recommended to replace the face covering and act as both a personal tool and a public utensil, mouth cover with nose cover can provide better protection than N95 etc. RPPP with MDMN, could be an alternative for lockdown, a parallel strategy to vaccine, and a collectively living way during the pandemic era. MDMN, featured with high efficiency protection, high degree comfort, easy wearing, tight-fitting, easy facial recognition & communication, reusability, cost-effective, environment friendly and scale manufacturing more readily and widely etc., is a simple and sustainable solution, which is essential for ordinary people to keep wearing it properly for protection.

The use of biodegradable materials has a growing field of application due to environmental concerns, however, scientific research on incremental forming using biomaterials is scarce. Thus, this study focuses on the single point incremental forming (SPIF) process applied to a composite sheet that combines a biodegradable thermoplastic matrix (Solanyl) reinforced with natural fibres (flax). The influence of the process parameters on the final geometry is determined, evaluating the effect of the following factors: step depth, wall angle and temperature reached during the process. Additionally, a heated aqueous medium is incorporated which facilitates the formability of the composite sheets. This method is especially useful for materials that have poor formability at room temperature. The benefits of using controlled heat include the reduction of formation forces applied to the plate, improved accuracy due to the reduction of elastic recovery, and the manipulation of the samples remarkably close to the glass transition temperatures. Through this experimental study with the variables analysed, a maximum shaping depth of 310 mm is obtained. These results confirm that the single point shaping used with bioplastic materials is possible and has positive outcomes for incremental forming.

The Strawberry Line is a linear Local Nature Reserve extending along a dismantled railway corridor in North Somerset, England. The Reserve is cherished as a recreational resource by local communities and I am very fortunate to live beside it. During the COVID-19 lockdown of spring 2020, I decided to make use of my permissible daily exercise to record the distribution of breeding birds along my particular ‘patch’ of the Strawberry Line - the Vale of Winscombe section in the Mendip Hills. In describing the Reserve’s birdlife, I hope that I can provide an added layer of interest for locals and visitors, which might help in these difficult times deliver an enhanced dose of ‘Nature’s Fix’ and perhaps also shine a light towards a greater appreciation and connection with the natural world.

Lemongrass (Cymbopogon flexuosus) is an aromatic perennial grass grown extensively for its essential oil. Lemongrass oil is chiefly a mixture of various cyclic and acyclic bioactive monoterpenes. We reviewed lemongrass oil and its biosynthesis in the present chapter along with its biochemical composition. Furthermore, we attempted to explore both the possible routes for essential oil biosynthesis in lemongrass, i.e. mevalonate and non-mevalonate pathways and how these pathways interwind with each other. Lemongrass oil has high commercial potential in medicinal, cosmetic, food and energy industries. Regarding the pharmacological properties, a wide array of biological activities has been observed in lemongrass oil such as antimicrobial, insecticidal, analgesic and anti-cancer properties as well as its efficacy as insect-repellent. The later sections were dedicated for the analysis of insecticidal property of the lemongrass oil and the mechanism working behind this phenomenon where it was observed that in addition to synergistic effects, various components of lemongrass oil can also induce specific neurotoxic and cytotoxic responses in the insects.

The COVID-19 pandemic caused by the novel coronavirus emerged in Wuhan City, Hubei province of China at the end of 2019, has radically transformed the lives of people around the world. Due to its fast spreading, it is currently considered as a worldwide health, social and economic concern. The lack of knowledge on this area has encouraged academic sphere for extensive research, which is reflected in exponentially growing scientific literature in this area. However, current state of COVID-19 research reveals only early development of knowledge, while a comprehensive and in-depth overview remains neglected. Accordingly, the main aim of this paper is to fill the aforementioned gap in the literature and provide an extensive bibliometric analysis of COVID-19 research across science and social science research landscape, using innovative and sophisticated bibliometric approaches (e.g. Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on logistic regression). The bibliometric analysis is based on the Scopus database including all relevant and latest information on COVID-19 related publications (n=16,866) in the first half of 2020. The empirical results indicate that there is still a lack of publications of COVID-19 and its implications in less-explored (non-health) sciences, especially in social sciences. Accordingly, the findings emphasize an importance of a comprehensive and in-depth approach considering different scientific disciplines in COVID-19 research. The understanding of the evolution of emerging scientific knowledge on COVID-19 is beneficial not only for scientific community but also for evidence-based policymaking in order to prevent and address the COVID-19 pandemic.

Connexin 43 (Cx43) forms gap junctions that mediate the direct intercellular diffusion of ions and small molecules between adjacent cells. Cx43 displays both pro- and anti-tumorigenic properties, but the mechanisms underlying these characteristics are not fully understood. Tunneling nanotubes (TNTs) are long and thin membrane projections that connect cells, facilitating the exchange of not only small molecules, but also larger proteins, organelles, bacteria, and viruses. Typically, TNTs exhibit increased formation under conditions of cellular stress and are more prominent in cancer cells, where they are generally thought to be pro-metastatic and to provide growth and survival advantages. Cx43 has been described in TNTs, where it is thought to regulate small molecule diffusion through gap junctions. Here, we developed a high-fidelity CRISPR/Cas9 system to knockout (KO) Cx43. We found that loss of Cx43 expression was associated with significantly reduced TNT length and number in breast cancer cell lines. Notably, secreted factors present in conditioned medium stimulated TNTs more potently when derived from Cx43-expressing cells than from KO cells. Moreover, TNT formation was significantly induced by inhibition of several key cancer signaling pathways that both regulate Cx43 and are regulated by Cx43, including RhoA kinase (ROCK), protein kinase A (PKA), focal adhesion kinase (FAK), and p38. Intriguingly, drug-induced stimulation of TNTs was more potent in Cx43 KO cells than in wild-type cells. In conclusion, this work describes a novel non-canonical role for Cx43 in regulating TNTs, identifies key cancer signaling pathways that regulate TNTs in this setting, and provides mechanistic insight into a pro-tumorigenic role of Cx43 in cancer.

Nowadays, many political campaigns are using social influence (SI) in order to convince voters to support/oppose a specific candidate/party. In election control via SI problem, an attacker tries to find a set of limited influencers to start disseminating a political message in a social network of voters. A voter will change his opinion when he receives and accepts the message. In constructive case, the goal is to maximize the number of votes/winners of a target candidate/party, while in destructive case, the attacker tries to minimize them. Recent works considered the problem in different models and presented some hardness and approximation results. In this work, we consider multi-winner election control through SI on different graph structures and diffusion models, and our goal is to maximize/minimize the number of winners in our target party. We show that the problem is hard to approximate when voters' connections form a graph, and the diffusion model is the linear threshold model. We also prove the same result considering an arborescence under independent cascade model. Moreover, we present a dynamic programming algorithm for the cases that the voting system is a variation of straight-party voting, and voters form a tree.

While obesity is recognized as a key global public health issue, there has been no research to date on the perceptions of care for people with this condition held by individuals in positions of organizational power. The aim of this study was therefore to describe the perceptions and experiences of clinical leaders and managers of providing care to inpatients with obesity at a metropolitan public health service. This study applied an interpretative phenomenological analysis (IPA) approach to qualitative research, conducting interviews with 17 participants. Their perceptions of care for inpatients with obesity encompassed both their personal understanding as an individual, and their observations about the organizational, patient and carer perspectives. Three overall themes were identified: 1) The problem of inpatients with obesity, 2) Inpatients with obesity as sources of risk and 3) Personal and professional perceptions of inpatients with obesity. While clinical leaders and managers were aware of potential impact of stigma and weight bias on the care given to this cohort, elements of implicit bias, stereotyping, ‘othering’ and ambivalence were frequently present in the data. Ongoing efforts to improve care for patients with obesity must therefore include efforts to address perceptions and attitudes at all organisational levels of the workforce.

Forest plantations have a large potential for carbon sequestration, playing an important role in the global carbon cycle. However, despite the huge amount of research carried out worldwide, the absolute contribution of industrial forest plantations is still incomplete for some parts of the world. To contribute to bridge this gap, we calculated the amount of C stock in three fast growing forest species in Chile. Relevant C pools (above-ground and below-ground biomass, forest floor, and soil) were considered for this analysis. Across the industrial plantation forests of Chile, carbon accumulated in the above-ground biomass was 181–212 Mg · ha−1 for Pinus radiata, 147–180 Mg · ha−1 for Eucalyptus nitens, and 95–117 Mg · ha−1 for Eucalyptus globulus (age 20–24 years for P.radiata and 10–14 years for Eucalyptus). Our results agree with other studies showing that 30%–50% of the total C stock is stored in the soil. Total C stocks were for 343 Mg · ha−1 for P.radiata, 352 Mg · ha−1 for E.nitens, and 254 Mg · ha−1 for E. gloubulus, also at the end of a typical rotation. The carbon pool in the forest floor was found to be significantly lower (less than 4% of the total) when compared to the other pools and showed large spatial variability. We conclude that industrial forest plantations are a valuable tool to reduce atmospheric CO2 and mitigate climate change. Given the contribution of soils to total carbon stocks, special attention should be paid to forest management activities that affect the soil organic carbon pool.

Abstract The global concern about the leather industries is increasing as the leather industries grow bigger each year. These industries face a very challenging task with an increase in stringent pollution control regulation enforced by various bodies due to environmental concern and human risks. The chromium salts are the most widely used chemical for the tanning process in leather industries, about 35% of chromium used for the tanning process remain as metal and discharge to wastewater stream. The removal and recovery of this quantity of wasted chromium are necessary for environmental pollution control and economic reason. This paper sheds light on the chromium recovery and reuse system of Chromium salts in tanning wastewater by using NaOH as an effective chemical precipitation method to regenerate chromium solution, adapted chrome recovery plant, and evaluated the system technically and economically.

Streptococcus suis is a zoonotic pathogen causing serious infections in both swine and humans. Although metals are essential for life, excess amounts of metals they are toxic to bacteria. when accumulated in excess amounts. Except for zinc, Transcriptome-level data of the mechanisms for resistance to metal-induced toxicity in S. suis are available for no metals other than zinc. have not been investigated from the transcriptome level in S. suis. Herein, we explored the transcriptome-level changes of in S. suis in response to ferrous iron and cobalt toxicity by RNA sequencing. Many A lot of genes were differentially expressed in the presence of excess ferrous iron and cobalt. Most of the genes in response to cobalt toxicity showed the same expression trends as those were expressed in the same trend in response to ferrous iron toxicity. qRT-PCR analysis of the selected genes confirmed the accuracy of RNA sequencing results. Bioinformatics analysis of the differentially expressed genes indicated that ferrous iron and cobalt have similar impacts effects on the cellular processes of S. suis. Treatment with ferrous Ferrous iron treatment resulted in down-regulation of several oxidative stress tolerance-related genes involved in oxidative stress tolerance and up-regulation of the genes in an amino acid ABC transporter operon. Expression of the several genes in the arginine deiminase system was down-regulated in the presence of after ferrous iron and cobalt treatment. Collectively, our results suggested that S. suis alters the expression of a lot of multiple genes to respond to ferrous iron and cobalt toxicity.

For a considerable length of time synthetic composts are utilized to satisfy the dirt necessity of supplements and yield, however huge measure of these substance manures are hazardous for condition, advantageous microorganisms, creatures, and people also. In this way, natural inviting and savvy biofertilizers are utilized. Biofertilizer are the substances which contain microorganisms those microorganisms might be growths, microscopic organisms, and protozoa which have capacity to build ripeness of soil by Nitrogen obsession, Phosphorous solubilization, and Iron sequestration. These cycles convert insoluble type of supplements into solvent structure and make it accessible to the foundations of plant which effectively take them up and use them. There are assortment of the yields whose profitability can be expanded by applying biofertilizer, for example, rice, oat, and other grain crops. In this audit we experience the method of utilization of biofertilizers, and how the assistance the plants and in which they help.

One of the main challenges for autonomous learning in virtual environments is finding the right material that fits students’ needs and supports their learning process. Personalized recommender systems partially solve this problem by suggesting online educational resources to students based on their preferences. However, in educational environments (which need a proper characterization of both users and educational resources), most existing recommendation algorithms either fail to include all the available information or use hybrid processes that do not exploit possible relationships between users and item features. This article presents a personalized recommender system for educational resources aimed at combining user and item information into a single mathematical model based on matrix factorization. As a result, estimated latent factors can provide insight into possible interactions between users and item features, improving the quality of the information retrieval process. We validated the proposed model on a real dataset that contains the ratings assigned by students from Universidad Nacional de Colombia and Universidade Feevale to educational resources in the Colombian Federation of Learning Object Repositories (FROAC in Spanish). User characterization included learning style and educational level, whereas item characterization (obtained from the objects’ metadata), included interactivity level, aggregation level and type, and resource format. These results, compared to those obtained when not all the available information is included, show that our method can improve the recommendation process.

In recent years, the photophysical properties of crystalline metal-organic frameworks (MOFs) have become increasingly relevant for their potential application in light-emitting devices, photovoltaics, nonlinear optics and sensing. The availability of high-quality experimental data for such systems makes them ideally suited for a validation of quantum mechanical simulations, aiming at an in-depth atomistic understanding of photophysical phenomena. Here we present a computational DFT study of the absorption and emission characteristics of a Zn-based surface-anchored metal-organic framework (Zn-SURMOF-2) containing anthracenedibenzoic acid (ADB) as linker. Combining band-structure and cluster-based simulations on ADB chromophores in various conformations and aggregation states, we are able to provide a detailed explanation of the experimentally observed photophysical properties of Zn-ADB SURMOF-2: The unexpected (weak) red-shift of the absorption maxima upon incorporating ADB chromophores into SURMOF-2 can be explained by a combination of excitonic coupling effects with conformational changes of the chromophores already in their ground state. As far as the unusually large red-shift of the emission of Zn-ADB SURMOF-2 is concerned, based on our simulations, we attribute it to a modification of the exciton coupling compared to conventional H-aggregates, which results from a relative slip of the centers of neighboring chromophores upon incorporation in Zn-ADB SURMOF-2.

The reinforcement learning problem of complex action control in the Multi-player wargame is a hot research topic in recent years. In this paper , a game system based on turn-based confrontation is designed and implemented with the state-of-the-art deep reinforcement learning models. Specifically, we first design a Q-learning algorithm to achieve intelligent decision-making, which is based the DQN(Deep Q Network) to model the complex game behaviors. Then, a priori- knowledge based algorithm PK-DQN(Prior Knowledge- Deep Q Network) is introduced to improve the DQN algorithm, which accelerates the convergence speed and stability of the algorithm. The experiments demonstrate, the correctness of the PK-DQN algorithm is validated and its performance surpass the conventional DQN algorithm. Furthermore, the PK-DQN algorithm shows effectiveness in defeating the high level of rule-based opponents, which provides promising results for the exploration of the field of smart chess and intelligent game deduction.

Kluyveromyces marxianus (K. marxianus) is a newly emerging industrially relevant yeast. It is known to possess a highly efficient Non-Homologous End Joining (NHEJ) pathway that promotes random integration of non-homologous DNA fragments into its genome. The nature of the integration events was traditionally analyzed by Southern blot hybridization. However, the precise DNA sequence at the insertion sites were not fully explored. We transformed a PCR product of the Saccharomyces cerevisiae URA3 gene (ScURA3) into an uracil auxotroph K. marxianus wildtype strain and picked 24 stable Ura+ transformants for sequencing analysis. We took advantage of rapid advances in DNA sequencing technologies and developed a method using a combination of Illumina MiSeq and Oxford Nanopore sequencing. This approach enables us to uncover the Gross Chromosomal Rearrangements (GCRs) that are associated with the ScURA3 random integration. Moreover, it will shine a light on understanding DNA repair mechanisms in Eukaryotes, which could potentially provide insights for cancer research.

Methylenetetrahydrofolate reductase (MTHFR), an enzyme expressed in mammalian testes exerts direct effect on spermatogenesis; however, its protein characteristics in bovine testes remain unknown. Here, we analysed bovine testicular structure, MTHFR bioinformatics profile, mRNA, and protein expression characteristics in yellow-cattle (y-c) and yak testis using histological procedures, bioinformatics analysis, qRT-PCR, and western blot. Testes from 13 bovines, ≤ 2 years juvenile (y-c, n = 3; yak, n=3) and ≥ 3 years adult (y-c, n = 3; yak, n = 4) were collected and analysed. Anatomical characteristics of testis in y-c and yak were similar except the weight or size for which that of y-c was significantly higher or greater than yak. In y-c, an open reading frame (ORF) for 2600 nucleotides sequence, encoding 655 amino acids showed high homology with zebu cattle (99.51%) and wild yak (98.68%). Secondary and 3D protein structures were similar to that of humans with differences in number of nucleotides, amino acids, and some physico-chemical characteristics. MTHFR mRNA expression in y-c and yak were significantly higher in adult testes compared with juvenile ones. However, its protein expression was higher but not statistically significant in adult y-c and yak compared to the juvenile ones. The highlights and inferences of these and other findings are discussed.

As symbionts of fungi and algae, lichens produce a variety of secondary products which pharmacological activities. This study aimed to investigate the anti-inflammatory activities of Heterodermia hypoleuca and its main compound, atraric acid. The results confirmed that atraric acid could regulating induced pro-inflammatory cytokine, nitric oxide, induced nitric oxide synthase and cyclooxygenase-2 expression by lipopolysaccharide (LPS)-stimulated RAW264.7 cells. Means while, atraric acid down-regulated expression of phosphorylated IκB, ERK and nuclear factor kappa B (NFκB) signaling pathway to exhibit anti-inflammatory effects in LPS-stimulated RAW264.7 cells. Based on these results, the anti-inflammatory effect of atraric acid during LPS-induced endotoxin shock in a mouse model was confirmed. In the atraric acid treated-group, cytokine production was decreased in the peritoneum and serum, and each organ damaged by LPS-stimulation was recovered. These results show that atraric acid has an anti-inflammatory effect and its molecular mechanism may be involved in the inactivation of the ERK/NFκB signaling pathway, demonstrating its value as a potential therapeutic for inflammatory diseases.

Despite the considerable focus on job characteristics and individual differences in job crafting research, the influence of social factors on job crafting has not been well-acknowledged. This meta-analysis estimates the associations between social factors and job crafting, and how social factors contribute to employee outcomes through their job crafting. Based on a sample of 51 empirical studies that included 54 independent effect sizes (N = 17,863), we found that social factors of positive leadership styles (e.g., empowering and transformational) and coworker support were positively related to employee job crafting. Further, our study showed that employee job crafting positively mediate the relationships between social factors and work outcomes (e.g., job performance and well-being). Our study contributes to job crafting literature by integrating social factors into the job crafting model and demonstrating that the social context of work (in particular organizational-insiders) play a crucial role in shaping employees’ job crafting behavior. We also emphasize the critical role that job crafting plays in transmitting valuable social resources into improved work outcomes. Building on our results, we provide future direction for job crafting research and discuss how our results can imply practice in terms of job crafting training.

The implementation of teaching interventions in learning needs has received considerable attention, as the provision of the same educational conditions to all students, is pedagogically ineffective. In contrast, more effectively considered the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that support automatic modeling study and adjust the teaching content on educational needs and students' skills. Effective utilization of these educational approaches can be enhanced with Artificial Intelligence (AI) technologies in order to the substantive content of the web acquires structure and the published information is perceived by the search engines. This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is a novel hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a hybrid method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.

Multi-wire saw machining (MWSM) used for slicing hard-brittle materials in semiconductor, is an important material removal process that uses free abrasives. Cutting model of single-wire saw machining (SWSM) is the basis of MWSM, and the material removal mechanism of SWSM can better understand than MWSM. Mathematical model (includes brittle fracture and plastic deformation) is presented in this paper for SWSM ceramic with abrasives. This paper determines the effect of various machining parameters on the removal of hard-brittle materials. For brittle fracture of SWSM ceramics, the minimum of the strain energy density is used as a fracture criterion. The material removed of SWSM ceramics due to plastic deformation is calculated using the equations of motion. Actual wire-sawing experiments are conducted to verify the results from the developed mathematical model. Theoretical results agree with experimental data and practical experience. The developed mathematical model shows that brittle fracture plays a major concern role in material removed of SWSM ceramics. Wire speed and working load have positively correlated with material removed of SWSM ceramics. The coefficient of friction is low, a lateral crack, which propagates almost parallel to the working surface, leads to more brittle fracture and material removed is increased on SWSM ceramics.

COVID-19 emerged in Wuhan and is later declared as a pandemic by World Health Organization. Different-aged people have varying gender-wise immunity control properties that necessitates understanding COVID-19 impact on age and gender which does not exist, currently. In this paper, COVID-19 surveillance variables are extensively studied along with hospitalization, tests-performed, and recovery data. Dataset is curated from three sources; however, age and gender data belong to Belgium, particularly. Visualizations, frequencies, Pearson’s and polyserial correlation, student’s t-test, and Cramer’s V are used for enhanced analysis. Results show higher mortality rate in males and need of more ventilators to combat severe symptoms.

Inhibition of acetylcholinesterase (AChE) enzyme is a known procedure to treat severe Alzheimer's disease through increasing the acetylcholine level in the brain and thus slowing down the progression of Alzheimer's symptoms. The approved medications are only considered as palliative and addressed some reported deficiencies. Therefore, the demand for safe and effective compounds is substantially increasing. A newly series of coumaryl 1,3-selenazoles derivatives was synthesized in four steps. Then, their antioxidant activities were evaluated using DPPH, ABTS cation radical scavenging assay and cupric reducing antioxidant capacities (CUPRAC). The anticholinesterase activities were evaluated using the Ellman method. Then, the docking studies were carried out to explain the possible correlation between in vitro anticholinesterase activity results and the ligand-receptor interactions. Ten new coumaryl 1,3-selenazoles (5a-5d series and 6a-6f series) derivatives were successfully synthesized. The DPPH radical scavenging assay showed that all tested compounds have IC50 value &gt; 200 μM, for ABTS cation radical scavenging assay the IC50 value &gt; 1000 μM and for CUPRAC assay the IC50 value &gt; 200 μM. Compound 5c was found to be the most active compound against AChE and BChE in its series with IC50 value for AChE is 99.76 μM and IC50 for BChE is 140.28 μM while 6b exhibited the most potent inhibition in its series with IC50 value for AChE is 56.01 μM and IC50 for BChE is 121.34 μM. Besides, the docking studies showed that compound 5c and 6b formed π-π stacking interaction with aromatic residues at the active site of AChE and BChE, which is responsible for inhibiting the enzymes. This shows that the synthesized compounds contain skeletal structures that can interact and inhibit within the enzymes active site.

The article is devoted to biological models using recurrence sequences, which are connected with the harmonic progression 1, 1/2, …, 1/n, and some cooperative properties of genomes. The harmonic progression is itself one of the recurrence sequences based on the harmonic mean. This progression appears in the hyperbolic rules of oligomer cooperative organization in eukaryotic and prokaryotic genomes. This allows thinking that the harmonic progression is also related to inherited physiological systems, which must be structurally consistent with the genetic coding system for their transmission to descendants and survival in evolution. The harmonic progression is one of historically known mathematical series, whose features were studied by Pythagoras, Leibniz, Newton, Euler, Fourier, Dirichlet, Riemann. It is widely used in many known algorithms and is closely related to some other important mathematical objects, for example, the function of the natural logarithm and harmonic numbers. Accordingly, the article describes the possibilities of using these interrelated mathematical objects to model biological structures, including logarithmic spirals and some other. Modeling inherited spiral configurations seems to be a particularly urgent task, since they are extremely common at all levels of organization of living bodies and, according to Goethe, are lines of life. The principle of a recurrence similarity, that is a special similarity of parts and transformations presented in recurrence sequences of numbers and matrix operators (the scale similarity and scale transformations are only particular cases of such similarity), is considered as one of the key principles of structural organization of living bodies.

A label-free four-step procedure to identify amino acids (AAs) is described. In Step 1 molecules of AA, a tRNA, the related tRNA synthetase (AARS), and ATP are confined in a cavity to enable charging of tRNA. In Step 2 the tRNA, charged or uncharged, is separated from the other reactants (ATP, AARS, and possibly AMP and free AAs). In Step 3 the separated tRNA is subjected to non-enzymatic deacylation to dissociate the AA if tRNA is charged. In Step 4 the products are transferred to an electrolytic cell with a nanopore, where a current blockade occurs if and only if there is a dissociated AA. If a blockade is observed AA is immediately known, identification is unambiguous because of tRNA superspecificity. The exact blockade size need not be known (for any AA) in Step 4 so there is no need to distinguish among different AAs. This is unlike other nanopore-based methods, which are crucially dependent on precise blockade level measurements. The procedure is done in parallel with N (20 ≤ N ≤ 61) copies of AA, N reservoir-cavities, and N pairs of e-cells each with a different tRNA, related AARS, and ATP. At least one of the tRNAs gets charged. Assuming no charging errors, if N₁ tRNAs get charged in Step 1 and at least one of N₂ (≤ N₁) charged tRNAs is deacylated in Step 3, then with N₁N₂ tRNA molecules entering Step 1 AA can be identified with probability 1.

The novel coronavirus named by WHO and Coronavirus Study Group (CSG) as SARS-COV-2 is the etiological agent of the newly emerged Coronavirus disease (COVID-19). COVID-19 has become a pandemic threat as the WHO declared it a public health emergency of international concern. Early and precise detection of the virus is important for effective diagnosis and treatment. Various testing kits and assays, including real-time reverse Transcriptase PCR, thermal screening guns, ELISA-based immunoassays, and Point-of-Care (POC), have been implemented or are being explored to detect the virus and/or characterise cellular and antibody responses to the infection. However, these approaches have inherent limitations such as non-specificity, high cost, characterize by long turnaround times for test results, and can be labour intensive. Aptamers, which are single-stranded oligonucleotides, generated artificially by SELEX (Evolution of Ligands by Exponential Enrichment) may offer the capacity to generate high affinity bioprobes for monitoring relevant SARS-COV 2 and COVID-19 biomarkers. This article discusses the prospects of implementing aptasensing technologies for rapid point-of-care detection of SARS-COV-2.

The goal of this paper is to explore the relationship between the specific non-performing loan ratio (NPL ratio) and the corresponding impact on the bank’s profitability and lending behavior. It also seeks to investigate the macroeconomic impacts of economies with excessively high NPL ratios as well as the efficacy and impact of alleviation measures used by banks and governments around the world to help facilitate a decrease in high NPL ratios. The possible implications and effects of the COVID-19 pandemic on NPL ratios is also addressed in this paper. It is found that when excessively high NPL ratios go unaddressed, the economy tends to suffer. On the other hand, this study shows that when measures are taken to reduce or eliminate the high NPL ratios, economic performance improves, and the reduction has a clear positive impact on the economy.

Chronic obstructive pulmonary disease (COPD) is associated with high morbidity and mortality globally. Studies show that airway mucus hypersecretion strongly compromises lung function, leading to frequent hospitalization and mortality, highlighting an urgent need for effective COPD treatments. MUC5AC is known to contribute to severe muco-obstructive lung diseases, worsening COPD pathogenesis. Various pathways are implicated in the aberrant MUC5AC production and secretion MUC5AC. These include signaling pathways associated with mucus-secreting cell differentiation [ nuclear factor-κB (NF-кB)and IL-13-STAT6- SAM pointed domain containing E26 transformation-specific transcription factor (SPDEF), as well as epithelial sodium channel (ENaC) and cystic fibrosis transmembrane conductance regulator (CFTR)], and signaling pathways related to mucus transport and excretion-ciliary beat frequency (CBF). Various inhibitors of mucus hypersecretion are in clinical use but have had limited benefits against COPD. Thus, novel therapies targeting airway mucus hypersecretion should be developed for effective management of muco-obstructive lung disease. Here, we systematically review the mechanisms and pathogenesis of airway mucus hypersecretion, with emphasis on multi-target and multi-link intervention strategies for the elucidation of novel inhibitors of airway mucus hypersecretion.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an RNA virus, is responsible for coronavirus disease 2019 (COVID-19) pandemic of 2020. Experimental evidence suggests that microRNA can mediate an intracellular defence mechanism against some RNA viruses. The purpose of this study was to identify microRNA with predicted binding sites in the SARS-CoV-2 genome, compare these to their microRNA expression profiles in lung epithelial tissue and make inference towards possible roles for microRNA in mitigating coronavirus infection. We hypothesize that high expression of specific coronavirus-targeting microRNA in lung epithelia may protect against infection and viral propagation, conversely low expression may confer susceptibility to infection. We have identified 128 human microRNA with potential to target the SARS-CoV-2 genome, most of which have very low expression in lung epithelia. Six of these 128 microRNA are differentially expressed upon in vitro infection of SARS-CoV-2. Twenty-eight and 23 microRNA also target the SARS-CoV and MERS-CoV, respectively. In addition, 48 and 32 microRNA are commonly identified in two other studies. Further research into identifying bona fide coronavirus targeting microRNA will be useful in understanding the importance of microRNA as cellular defence mechanism against pathogenic coronavirus infections.

The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: ‘model organisms’ chosen for their phylogenetic/aetiological similarities; multivariable statistical models to estimate the strength/direction of (potentially causal) relationships between variables (through ‘causal inference’), and the (past/future) value of unmeasured variables (through ‘classification/prediction’); and a range of modelling techniques to predict beyond the available data (through ‘extrapolation’), compare different hypothetical scenarios (through ‘simulation’), and estimate key features of dynamic processes (through ‘projection’). Each of these models: address different questions using different techniques; involve assumptions that require careful assessment; and are vulnerable to generic and specific biases that can undermine the validity and interpretation of their findings. It is therefore necessary that the models used: can actually address the questions posed; and have been competently applied. In this regard, it is important to stress that extrapolation, simulation and projection cannot offer accurate predictions of future events when the underlying mechanisms (and the contexts involved) are poorly understood and subject to change. Given the importance of understanding such mechanisms/contexts, and the limited opportunity for experimentation during outbreaks of novel diseases, the use of multivariable statistical models to estimate the strength/direction of potentially causal relationships between two variables (and the biases incurred through their misapplication/misinterpretation) warrant particular attention. Such models must be carefully designed to address: ‘selection-collider bias’, ‘unadjusted confounding bias’ and ‘inferential mediator adjustment bias’ – all of which can introduce effects capable of enhancing, masking or reversing the estimated (true) causal relationship between the two variables examined. Selection-collider bias occurs when these two variables independently cause a third (the ‘collider’), and when this collider determines/reflects the basis for selection in the analysis. It is likely to affect all incompletely representative samples, although its effects will be most pronounced wherever selection is constrained (e.g. analyses focusing on infected/hospitalised individuals). Unadjusted confounding bias disrupts the estimated (true) causal relationship between two variables when: these share one (or more) common cause(s); and when the effects of these causes have not been adjusted for in the analyses (e.g. whenever confounders are unknown/unmeasured). Inferentially similar biases can occur when: one (or more) variable(s) (or ‘mediators’) fall on the causal path between the two variables examined (i.e. when such mediators are caused by one of the variables and are causes of the other); and when these mediators are adjusted for in the analysis. Such adjustment is commonplace when: mediators are mistaken for confounders; prediction models are mistakenly repurposed for causal inference; or mediator adjustment is used to estimate direct and indirect causal relationships (in a mistaken attempt at ‘mediation analysis’). These three biases are central to ongoing and unresolved epistemological tensions within epidemiology. All have substantive implications for our understanding of COVID-19, and the future application of artificial intelligence to ‘data-driven’ modelling of similar phenomena. Nonetheless, competently applied and carefully interpreted, multivariable statistical models may yet provide sufficient insight into mechanisms and contexts to permit more accurate projections of future disease outbreaks.

Background: Twitter is a major tool for communication in emergencies such as natural disasters. This online social network allows the user to produce content, and it is not designed exclusively for news releases, as opposed to other service providers. Aim: The aim of this study is to investigate Twitter uses in natural disasters and pandemics. Methods: The included studies reported the role of Twitter in natural disasters. The studies that report in settings other than the natural disasters (such as man-made disasters) and other social media were excluded. Electronic databases for a comprehensive literature search including MEDLINE, Web of Science, CINAHL, PsycINFO, Cochrane Register of Controlled Trials (CENTRAL) and EMBASE were used to identify the records that match the mentioned inclusion criteria published till May 2020. The study characteristics were extracted from the qualified studies including year of publication, findings, and geographical location of the study conduct. A narrative synthesis for this literature review was used. Results: The search identified 822 articles of which 780 articles were removed, 256 were not available, 311 papers were not relevant, 16 were duplicated articles, and 197 were non-related to the emergencies. 45 articles met the selection criteria and were included in the review. eleven themes were found in the narrative synthesis including early warning, disseminating information and misinformation, advocacy, personal gains, assessment, various roles of organizations, public mood, geographical analysis, charity, using influencers, and trust. Conclusions: It is recommended that influential individuals be identified in each country and community before disasters occur so that the necessary information can be disseminated in response to disasters. Preventing the spread of misinformation is one of the most important issues in times of disaster, especially pandemics. Disseminating accurate, transparent, and prompt information from relief organizations and governments can help. Also, analyzing Twitter data can be a good source for understanding the mental state of the community, estimating the number of injured people, estimating the points affected by natural disasters, and modeling the prevalence of epidemics. Therefore, various groups such as politicians, the government, non-governmental organizations, aid workers, and the health system can use this information to plan and implement interventions.

Proteins possess complex three-dimensional structures, and these structures are stable only within specific ranges of temperature which mostly correspond to the temperature ranges of the host organisms. However, few exceptional proteins, called heat-stable proteins, are stable at temperatures that are substantially higher than those tolerated by the host organisms themselves. Most of the heat-stable proteins possess heat stability to perform their functions at high temperatures, but some of them are intrinsically heat-stable due to their structure. Heat-stable proteins are usually divided into three or four groups depending upon the intricacies of their structures and thermal behaviors. Their peculiar property, i.e. heat-stability, makes them very valuable in applications such as polymerase chain reaction, industrial processes requiring high temperature, and protein engineering. Heat-stability also makes it feasible to purify such proteins, from the rest of the heat-labile proteins, using a simple heat-treatment method. Moreover, heat treatment can be used as a combined cell-lysis and protein purification step which, as compared to conventional methods, can result in a higher yield of heat-stable proteins. Furthermore, some special heat-stable proteins, i.e. intrinsically disordered proteins (which include the proteins involved in important neurodegenerative diseases), need heat-treatment step, in some cases, as the only way for their successful purification and study. Hence, this paper provides a first-ever comprehensive review of all major aspects of heat-stable proteins, i.e., their structure, evolution, classification, significance, and heat-treatment mediated purification.

Background: Social Anxiety Disorder (SAD) is among the most common anxiety disorders worldwide with data largely emerging from the Euro-American and Pacific Rim populations. In contrast, there is a dearth of studies among the populations of Arabian Gulf countries including Oman. This study has two interrelated aims: (i) to explore the prevalence of SAD among Omani adults, and (ii) to tease out the links between sociodemographic factors and SAD in Oman. Methods: A cross-sectional study via an online survey was conducted among 1019 adult Omani nationals residing in Oman. The presence of SAD was assessed using the Arabic version of the Liebowitz Social Anxiety Scale (LSAS). Result: Nearly half the participants (45.9%, n=468) endorsed themselves as having features of SAD as defined by LSAS. In the multivariate logistic analysis, participants below 40 years of age were 1.6 times (OR=1.568, p=0.026) more likely to have SAD than those who were 40 and older. Women were 1.3 times (OR=1.348, p=0.038) more likely to endorse SAD than men. Participants who had secondary or undergraduate education were respectively 1.5 times (OR=1.45, p=0.014) and 2.5 times (OR=2.509, p<.001) to have SAD than who were postgraduates. Conclusion: The present data suggest that 45.9% of the participants reached the cut-off for case-ness in LSAS, which is high compared to reports from other populations. As online survey respondents tend to belong to similar demographics, the current results need not be representative of the Omani adult population, which calls for studies that adopt more inclusive survey methods.

In order to design efficient and sustainable office spaces and to automate lighting, heating and air circulation in these facilities, solving the challenge of occupancy prediction is crucial. In office spaces where large areas need to be observed, multiple sensors must be used for full coverage. In these cases, it is normally important to keep the costs low, but also to make sure that the privacy of the people who use such environments are preserved. Low-cost and low-resolution heat (thermal) sensors can be very useful to build solutions that address these concerns. However, they are extremely sensitive to noise artifacts which might be caused by heat prints of the people who left the space or by other objects which are either using electricity or exposed to sunlight. There are some earlier solutions for occupancy prediction that employ low-resolution heat sensors, however, they have not addressed nor compensate for such heat artifacts. Therefore, in this paper, we present a low-cost and low-energy consuming smart space implementation to predict the number of people in the environment based on whether their activity is static or dynamic in time. We use a low-resolution (8×8) and non-intrusive heat sensor to collect data from an actual meeting room. We propose two novel workflows to predict the occupancy; one based on computer vision and one based on machine learning. Besides comparing the advantages and disadvantages of these different workflows, we use several state-of-the-art explainability methods in order to provide a detailed analysis of the algorithm parameters and how the image properties influence the resulting performance. Furthermore, we analyze noise resources which affect the heat sensor data. We hope that our analysis brings light into understanding how to handle very low-resolution heat images in these environments. The presented workflows could be used in various domains and applications other than smart offices, where occupancy prediction is essential, e.g., for elderly care.

With the outbreak of the COVID-19 disease, the research community is producing unprecedented efforts dedicated to better understand and mitigate the affects of the pandemic. In this context, we review the data integration efforts required for accessing and searching genome sequences and metadata of SARS-CoV2, the virus responsible for the COVID-19 disease, which have been deposited into the most important repositories of viral sequences. Organizations that were already present in the virus domain are now dedicating special interest to the emergence of COVID-19 pandemics, by emphasizing specific SARS-CoV2 data and services. At the same time, novel organizations and resources were born in this critical period to serve specifically the purposes of COVID-19 mitigation, while setting the research ground for contrasting possible future pandemics. Accessibility and integration of viral sequence data, possibly in conjunction with the human host genotype and clinical data, are paramount to better understand the COVID-19 disease and mitigate its effects.

This paper presents the results of the experimental research and numerical analysis of three reinforced concrete deep beams with openings, designed by the Strut-and-Tie method according to the EN 1992-1-1 recommendations. All tested specimens were made in full size, with the same geometric characteristics and quality of the materials. The specimens, constructed as simply supported beams, were loaded with two concentrated forces and were tested for bending until failure. Each specimen was reinforced with different reinforcement layout determined by parameter variation within the Strut-and-Tie method. Based on the results of experimental research, it was concluded that the behavior of loaded members was in agreement with the proposed forms of the Strut-and-Tie models that were used for their design.

Achieving neuroprotection in ischemic stroke patients has been a multi-decade medical challenge. Numerous clinical trials were discontinued in futility and many were terminated in response to deleterious treatment effects. Recently however, several positive reports have generated the much-needed excitement surrounding stroke therapy. In this review, we describe the clinical studies that significantly expanded the time window of eligibility for patients to receive mechanical endovascular thrombectomy. We summarize the results available thus far for nerinetide, which can be considered the most promising neuroprotective agent yet for stroke treatment. Lastly, we reflect upon aspects of these successful trials in our own studies targeting the Kv2.1-mediated cell death pathway in neurons for neuroprotection. We propose that recent changes in the clinical landscape must be adapted by preclinical research in order to continue progressing toward the development of efficacious neuroprotective therapies for ischemic stroke.

Metal additive manufacturing (AM) has gained much attentions in recent years due to its advantages including geometric freedom and design complexity, appropriate to a wide range of potential industrial applications. However, conventional metal AM methods have high-cost barriers due to the initial cost of the capital equipment, support and maintenance, etc. This study presents a unique low-cost metal material extrusion (MME) technology. The filaments used have polylactic acid (PLA) as the matrix and metal powders (copper, bronze, stainless steel, high carbon iron, and aluminum) as reinforcements. Using the proposed fabrication technology, test specimens were built by extruding polymer/metal composite filaments, which were then sintered in an open-air furnace to produce solid metallic parts. In this research, the mechanical and thermal properties of the built parts are examined using tensile tests, thermogravimetric-, thermomechanical- and microstructural analysis.

This study empirically investigates the complex interplay between the severity of the coronavirus pandemic, mobility changes in retail and recreation, transit stations, workplaces, and residential areas, and lockdown measures in 88 countries of the word. To conduct the study, data on mobility patterns, socioeconomic and demographic characteristics of people, lockdown measures, and coronavirus pandemic were collected from multiple sources (e.g., Google, UNDP, UN, BBC, Oxford University, Worldometer). A Structural Equation Modeling (SEM) technique is used to investigate the direct and indirect effects of independent variables on dependent variables considering the intervening effects of mediators. Results show that lockdown measures have significant effects to encourage people to maintain social distancing. However, pandemic severity and socioeconomic and institutional factors have limited effects to sustain social distancing practice. The results also explain that socioeconomic and institutional factors of urbanity and modernity have significant effects on pandemic severity. Countries with a higher number of elderly people, employment in the service sector, and higher globalization trend are the worst victims of the coronavirus pandemic (e.g., USA, UK, Italy, and Spain). Social distancing measures are reasonably effective at tempering the severity of the pandemic.

The purpose of this study was to better understand the interactive impact of two soil-borne pathogens, Phytophthora cactorum (as the primary pathogen) and Armillaria gallica (as secondary), on two-year-old seedlings of silver birch (Betula pendula) subjected to stress caused by mechanical defoliation simulating primary insect feeding. One year after treatments, the chlorophyll fluorescence measurement and gas chromatography coupled with mass spectrometry (GC-MS) were used to analyze the photosynthetic activity in leaves, the volatile organic compounds (VOCs) emitted by birch leaves and chemical compounds from roots. Only the infection of roots by P. cactorum increased photosynthetic rates in the leaves, which may suggest its cryptic development in contrast to fungi. The birch leaves in seedlings exposed to 50% defoliation, inoculation with P. cactorum and A. gallica emitted more aromatic carbonyls and alcohols, as well as half as much aliphatic esters, compared to untreated controls. In infected birch roots, the production of phenols, triterpenes and fatty alcohols increased, but fatty acids decreased. This was the first experimental confirmation of the pathogenicity of P. cactorum on silver birch seedlings in Poland. The most severe damage to roots took place only in the case of two-way or three-way interactions. Higher levels of aromatic carbonyls and alcohols in leaves, as well as phenolic compounds in roots of stressed birches (compared to control) suggest an activation of plant systemic acquired resistance (SAR).

In the last decades droughts, deforestation and wildfires have become recurring phenomena that have affected both human activities and natural ecosystems in Amazonia. The time an ecosystem requires to recover from carbon losses is a crucial metric to evaluate disturbance impacts on forests. However, the factors influencing and controlling the recovery time and its spatiotemporal patterns at the regional scale are still poorly understood. In this study, we combined forest growth model, remote sensing and field plots, to map Amazonia-wide (300-ha resolution) impact and recovery time of aboveground biomass (AGB) after drought, fire and a combination of logging and fire. Our simulated results indicate that AGB decreases by 4%, 19% and 46% in forests disturbed by drought, fire and logging + fire, respectively, with an average AGB recovery time of 27 years for drought, 44 years for burned and 63 years for logged + burned areas and with maximum values reaching 184 years in areas of high fire intensity. Our findings provide two major insights in the spatial and temporal patterns of drought and wildfire in the Amazon: 1) the recovery time of the forests takes longer in the southeastern part of the basin, and, 2) as droughts and wildfires become more frequent – since the intervals between the disturbances is getting shorter than forest regeneration – potentially causing a long-lasting damage in these fragile ecosystems and a permanent degradation.

The study’s objective was to evaluate the influence of thinning on the quality and regularity of yield of 'Regina' cherries grown on a dwarf Gisela 5 rootstock. The experiments were conducted in the years 2009-2012 in Western Poland. Trees were thinned using a chemical agent, ammonium thiosulphate (ATS) at doses of 20g ATS × L-1, 30g ATS × L-1 and 40g ATS × L-1, and by hand, and the results of chemical and hand thinning were compared with those obtained for unthinned trees. The course of weather conditions in winter and during flowering had a significant impact on yield. Chemical thinning is known to be an effective method to regulate fruiting of pome trees, but it can also be successful if applied to cherry trees, as reflected by the alternate bearing index, which was the lowest after applying ATS at a dose of 40g. ATS treatment improved fruit quality in full crop years. Thinning resulted in, among other things, larger and darker fruit and higher content of total soluble solids and titratable acidity. Treatment with 40g ATS × L-1 significantly stimulated the vegetative growth of trees.

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

Several coatings configurations of combined aluminizing and diffusion layered aluminide on 316 steel were produced and characterized. These coatings, typically employed as thermal barrier coating (TBC), can also be effective as vibration reduction elements at intermediate and high temperatures. This preliminary work has been focused on the microstructural design and processing effects of the coatings. The damping of the produced specimens was measured up to 450°C and compared with that of the steel substrate. The most performing coatings contain an Al-Si layer and exhibit a steep damping increase above 200 °C, reasonably due to dislocation movements by plastic straining of soft alloy layer and to the interface sliding between layers with different elastic moduli.

Manual interpretation of these huge amounts of image volumes are susceptible to inter-reader variability and human error. Thus, accurate automated CAD scheme is highly desirable in clinical pathological diagnosis. In this research, plethora of machine learning paradigms (e.g. feature extraction, dimensionality reduction and supervised classification methods) were explored, evaluated, compared and analyzed to identify the optimal pathway for brain MR images (normal vs neoplastic) binary classification task. External validation dataset was used to test the generalizability of the optimal predictive models implemented. Relevant and informative features were selected to construct cross-validated decision tree and eventually simple rule set was built based on the decision tree. The experimental results show that almost all pattern recognition paradigms achieve high accuracy with careful selection of number of attributes. LDA+ELM with 55 features are the optimal pipelines which achieve perfect classification when training and test data are of same source; and achieving (accuracy=97.5%, AUC=0.989, sensitivity=95% and specificity=100%) under balanced test dataset; (accuracy=99.5%, AUC=0.988, sensitivity=95% and specificity=100%). Cross-validated decision tree model also shows comparable performance: accuracy=98.8%, AUC=99.1%, sensitivity=99.6% and specificity=98.2%. Three highly relevant and robust attributes are visualized and selected for construction of decision tree models and finally a rule sets are read directly off the decision tree. This rule sets can potentially serve as fast and accurate classification algorithm.

Construction of Pontoons is based on multiple elements, dimensions and weight. The study has addressed about how the industry of the floating reinforcement concrete precast (pontoons) installs in the factory with the combinations of utility, electricity services, and Internet service. The pontoon bridges are successfully installed in the road for transport or sea for shops. The installation process for pontoons is successfully attempted in a balanced situation above surface of the sea to the resistant of floating precast (pontoons) to any ambient effects such as weather conditions, the movement of the waves or any others effects. The findings elaborate that it is not just a military solution. Pontoon installation can significantly serve for civil purposes.

In the past two decades, acoustic metamaterials have garnered much attention owing to their unique functional characteristics, which is difficult to be found in naturally available materials. The acoustic metamaterials have demonstrated to exhibit excellent acoustical characteristics that paved a new pathway for researchers to develop effective solutions for a wide variety of multifunctional applications such as low-frequency sound attenuation, sound wave manipulation, energy harvesting, acoustic focusing, acoustic cloaking, biomedical acoustics, and topological acoustics. This review provides an update on the acoustic metamaterials' recent progress for simultaneous sound attenuation and air ventilation performances. Several variants of acoustic metamaterials, such as locally resonant structures, space-coiling, holey and labyrinthine metamaterials, and Fano resonant materials, are discussed briefly. Finally, the current challenges and future outlook in this emerging field is discussed as well.

One of the most reliable methods of authentication used today is biometric matching. This authentication process, which is done by using biometrics information such as fingerprint, iris, face, etc. is used in many application areas. Authentication at border gates is one of these areas. However, some restrictions have been introduced to storing and using such data, especially with the General Data Protection Regulation (GDPR). The main goal of this work is to find the practical implementation of fully homomorphic encryption-based biometric matching in border controls. In this paper, we propose a biometric authentication system based on hash expansion and fully homomorphic encryption features, considering these restrictions. One of the most significant drawbacks of the homomorphic encryption method is the long execution time. We solved this problem by executing the matching algorithm in parallel manner. The proposed scheme is implemented as proof-of-concept in the SMILE, and its advantages in privacy preservation has been demonstrated.

A Mild traumatic brain injury (mTBI) or concussion has become a public health problem in the United State. Sports and recreational activities are major sources of concussions; with the most incidents connected to American football. Recently, many companies and research institutions have started studying concussions and introduced some means of protection and some alarming systems of strong jolts. The major detection and protection system currently available on the market is the electronic helmet (e-helmet) composed of measurement devices to record head impact acceleration. The most commonly used devices in e-helmets are accelerometers to measure linear acceleration and gyroscopes for rotational/angular acceleration. Using smart textiles for concussion detection is currently uncommon and limited due to the lack of literature studying their voltage related errors. Actually, there are few works that characterize some voltage-force related errors for such type of sensors but for small impact forces and under bench testing while the behavior of those sensors was not described for higher ranges of applied forces and in field situations. This paper previews some common techniques used in e-helmets for concussion detection and highlights electronic textiles and smart fabric sensors that could be very useful for these applications. It discusses and validates the general behavior of such type of sensors under high impact forces and on field testing instead of bench testing, and also it characterizes the effect of increasing the thickness of the sensing element layer on the sensor. A custom-made pressure sensor was created of some available fabrics to be embedded within the padding of a football helmet to quantify the impacting force to the head. The sensor is mainly composed a Semi Conductive Polymer Composite SCPC layer with modifiable thickness that was modified three times with 0.2, 0.4, and 1.6mm to characterize the general behavior of the sensor due to a high amount of impacts and correlated with the thickness. A pendulum system was built to test the pressure sensors, while a special camera and an open-source video analysis software, Tracker was used to track the pendulum bob. The speed and the acceleration of the pendulum bob were measured, then the impact force was calculated and a voltage-force response was obtained. The results showed that no meaningful improvement occurs by small increase in the thickness but better sensor behavior could be obtained by significant increment to observe any difference. Despite that at a very high impacts, the suggested sensor with Velostat layers is not giving the real voltage readings that reflect the actual applied forces but it gives a helpful information that illustrate the distribution of the force through identification the place of the highest and lowest voltage readings regardless of the exact values of those readings. However, the proposed smart textile pressure sensor could be applicable in future e-helmet designs with additional research-based improvements especially on the structure of the sensing element layer to be able to withstand such high impacts which in turns improves the overall sensor performance and accurately measures pressure in concussion-inducing ranges.

The AtomDB project provides models of X-ray and EUV emitting astrophysical spectra for optically thin, hot plasma. We present the new software package, PyAtomDB, which now underpins the entire project, providing access to the underlying database, collisional radiative model calculations, and spectrum generation for a range of models. PyAtomDB is easily extensible allowing users to build new tools and models for use in analysis packages such as XSPEC. We present two of these, the kappa and ACX models for non-Maxwellian and Charge-Exchange plasmas respectively. In addition, PyAtomDB allows full open access to the apec code which underlies all of the AtomDB spectra and has enabled development of a module for estimating the sensitivity of emission lines and diagnostic line ratios to uncertainties in the underlying atomic data. We present these publicly available tools and results for several X-ray diagnostics of Fe L-shell ions and He-like ions as examples.

The Coronavirus Disease 2019 (COVID-19) pandemic has resulted in a significant surge of critically ill patients and an unprecedented demand on intensive care services. The rapidly evolving understanding of pathogenesis, limited disease specific evidence and demand-resource imbalances have posed significant challenges for intensive care clinicians. COVID-19 is a complex multisystem inflammatory vasculopathy with a significant mortality implication for those admitted to intensive care. Institutional strategic preparation and meticulous intensive care support are essential to maximising outcomes during the pandemic. The significant mortality variation observed between institutions and internationally, despite a single aetiology and uniform presentation, highlights the potential influence of management strategies on outcome. Given that optimal organ support and adjunctive therapies for COVID-19 have not yet been well defined by trial-based outcomes, strategies are predicated on existing literature and experiential learning. This review outlines the relevant pathophysiology and management strategies for critically ill patients with COVID-19, and shares some of the collective learning accumulated in a high volume Severe Respiratory Failure centre in London.

Energy use is of crucial importance for the global challenge of climate change but also an essential part of daily life. Hence, research on energy needs to be robust and valid. Other scientific disciplines have experienced a reproducibility crisis, that is, existing findings could not be reproduced in new studies, and energy research might be impacted as well. In this paper, we suggest the ‘TReQ’ approach to improve the research practices in the energy field and arrive at greater Transparency, Reproducibility, and Quality. We acknowledge the specific challenges of energy research and suggest a highly adaptable suite of tools that can be applied to research approaches across this multi-disciplinary and fast-changing field. In particular, we introduce preregistration of studies, making data and code publicly available, using preprints, and employing reporting guidelines to heighten the standard of research practices within the energy field. We argue that through wider adoption of these tools, we will be able to have greater trust in the findings of research used to inform evidence-based policy and practice in the energy field.

Alzheimer’s disease is one of the neurodegenerative diseases, characterized by the accumulation of abnormal protein deposits, which disrupt the signal transduction in neurons and other glia cells. The pathological protein Tau and amyloid-β contributes to the disrupted microglial signaling pathways, actin cytoskeleton, and cellular receptor expression. The important secondary messenger lipids i.e., phosphatidylinositols are largely affected by protein deposits of amyloid-beta in Alzheimer’s disease. Phosphatidylinositols are the product of different phosphatidylinositol kinases and the state of phosphorylation at D3, D4, and D5 positions of inositol ring. PI 3, 4, 5-P3 involves in phagocytic cup formation and relates actin remodeling whereas PI 4, 5-P2-mediates the process of phagosomes formation and further fusion with early endosome. The necessary activation of actin-binding proteins such as Rac, WAVE complex, and ARP2/3 complex for the actin polymerization in the process of phagocytosis, migration is regulated and maintained by PI 3, 4, 5-P3 and PI 4, 5-P2. Dietary fatty acids depending on their ratio and types of intake influence secondary lipid messenger along with the cellular content of phaphatidylcholine and phosphatidylethanolamine. The deposited Aβ deposits and extracellular Tau seed disrupt levels of phosphatidylinositol and actin cytoskeletal changes that hamper microglia signaling pathways in AD. We hypothesize that being a lipid species intracellular levels of phosphatidylinositol would be regulated by dietary fatty acids. We keen to understand different types of phosphatidylinositol species levels in signaling events such as phagocytosis and actin remodeling owing to the exposure of various types of dietary fatty acids.

The market of ready-to-eat salads is experiencing a noticeable growth in Europe. The commercial success of these products is linked to the growing demand for fresh, healthy and nutritionally valuable products that can be consumed without preparation time and are perceived as safe and very high-quality products. Since they are intended to be consumed without additional treatments, these ready-to-eat products are associated with a high microbiological risk. The aim of this work was to evaluate the microbiological quality and safety of ready-to-eat salads sold in widespread supermarket chains in Lazio, Italy, at the packaging date, during shelf-life and during home-refrigeration. The study also aimed to determine the differences between low, medium and high cost products. Salmonella spp., L. monocytogenes were chosen as safety indicators as specified by European regulations while total aerobic mesophilic bacteria and Escherichia coli were chosen as quality indicators as suggested by national guidelines. Analyses were performed following the ISO standards and in parallel, for the evaluation of total aerobic mesophilic bacteria, with an alternative colorimetric system, the MBS method, in order to propose a simple, affordable and accurate alternative for testing the microbiological quality of products, especially suitable for small and medium enterprises and on-site analyses.

The unfolded band structure and optical properties of Cu-doped KCl crystals were computed by first principles within the framework of density functional theory, implemented in the ABINIT electronic structure package utilizing pseudopotential approximation and a plane-wave basis set. From a theoretical point of view, Cu substitution into pristine KCl crystals requires calculation by the supercell (SC) method. This procedure shrinks the Brillouin zone, resulting in a folded band structure that is difficult to interpret. To solve this problem and gain insight into the effect of copper ions (Cu+) on electronic properties, the band structure of SC KCl:Cu was unfolded to make a direct comparison with the band structure of the primitive cell (PC) of pristine KCl. To understand the effect of Cu substitution on optical absorption, we calculated the imaginary part of the dielectric function of KCl:Cu through a sum-over-states formalism and broke it down into different band contributions by partially making an iterated cumulative sum (ICS) of selected valence and conduction bands. Consequently, we identified those interband transitions that give rise to the absorption peaks due to the Cu+ ion. These transitions involve valence and conduction bands formed by the Cu-3d and Cu-4s electronic states

Background: The antimalarial drug chloroquine and antimicrobial drug azithromycin have received significant attention during the current COVID-19 pandemic. Both drugs can alter cardiac electrophysiology and have been associated with drug-induced arrhythmias. Meanwhile, sympathetic activation is commonly observed during systemic inflammation and oxidative stress (e.g., in SARS-CoV-2 infection), and may influence the electrophysiological effects of chloroquine and azithromycin. Here, we investigated the effect of beta-adrenergic stimulation on proarrhythmic properties of chloroquine and azithromycin using a detailed in silico model of ventricular electrophysiology. Methods: Concentration-dependent chloroquine and azithromycin-induced alterations in ion-channel function were incorporated into the Heijman canine ventricular cardiomyocyte model. Single and combined drug effects on action-potential (AP) properties were analyzed using a population of 592 models accommodating inter-individual variability. Sympathetic stimulation was simulated by an increase in pacing rate and experimentally validated isoproterenol-induced changes in ion-channel function. Results: At 1 Hz pacing, therapeutic doses of chloroquine and azithromycin (5 and 20 µM, respectively) individually prolonged AP duration (APD) by 33% and 13%. Their combination produced synergistic APD prolongation (+161%) with incidence of proarrhythmic early afterdepolarizations in 53.5% of models. Increasing the pacing frequency to 2 Hz shortened APD and together with 1 µM isoproterenol corrected the drug-induced APD prolongation. No afterdepolarizations occurred following increased rate and simulated application of 0.1-1 µM isoproterenol. Conclusion: Sympathetic stimulation limits chloroquine- and azithromycin-induced proarrhythmia by reducing their APD-prolonging effect, suggesting the importance of heart rate and autonomic status monitoring in particular conditions (e.g., COVID-19).

Bacterial infections occur when wound healing fails to reach the final stage of healing, usually hindered by the presence of different pathogens. Different topical antimicrobial agents are used to inhibit bacterial growth due to antibiotic failure in reaching the infected site accompanied very often by an increased drug resistance and other side effects. In this review, we focus on antimicrobial peptides (AMPs), especially those with a high potential of efficacy against multidrug-resistant and biofilm-forming bacteria and fungi present in wound infections. Currently, different AMPs undergo preclinical and clinical phase to combat infection-related diseases. AMP dendrimers (AMPDs) have been mentioned as potent microbial agents. Various AMP delivery strategies, such as polymers, scaffolds, films and wound dressings, organic and inorganic nanoparticles, to combat infection and modulate the healing rate have been discussed as well. New technologies such as CRISPR-Cas are taken into consideration as potential future tools for AMP delivery in skin therapy.

The etiopathogenesis of autism spectrum disorder (ASD) remains largely unclear. Among other biological hypotheses, researchers have evidenced an imbalance in the endocannabinoid (eCB) system, which regulates some functions typically impaired in ASD, such as emotional responses and social interaction. Also, cannabidiol (CBD), the non-intoxicating component of Cannabis sativa, has been recently approved for treatment-resistant epilepsy. Seizures represent frequent medical comorbidities of ASD and could be responsible for the onset or worsening of behavioral problems. Thus, it has been hypothesized that cannabinoids could be useful in improving some ASD symptoms. Our systematic review was conducted according to the PRISMA guidelines and aimed to summarize the literature regarding the use of cannabinoids in ASD. After searching in Web of Knowledge^TM, PsycINFO, and Embase, we included ten studies (eight papers and two abstracts). Four ongoing trials were retrieved in ClinicalTrials.gov. Findings are promising, as cannabinoids appeared to improve problem behaviors, sleep, hyperactivity, and communication deficits, with limited cardiac and metabolic side effects. Interestingly, they generally allowed to reduce the number of prescribed medications and decreased the frequency of seizures in epileptic patients. Mechanisms of action could be linked to the excitatory/inhibitory imbalance found in people with ASD. However, further trials need to be implemented with better characterization and homogenization of samples, and well-defined outcomes.

The COVID-19 pandemic plagues the whole world, bringing numerous challenges which need to be addressed. One of them is the privacy of patient data. There are several problems related to data privacy in IoT environments, the use of applications, devices, and functionalities in hospital processes. Therefore, we have compared works from the literature and developed a taxonomy consisting of the requirements necessary to control patient privacy data in a hospital setting in the current pandemic. Based on the studies, an application was modeled and implemented. According to the tests and comparisons drawn between the variables, the application yielded satisfactory results.

The quantified residence time distribution (RTD) provides a numerical characterization of mixing in the continue casting tundish, thus allowing the engineer to better understand the metallurgical performance of the reactor. This paper describes a computational fluid dynamic (CFD) modelling study for analyzing the flow pattern and the residence time distribution in a five-strand tundish. Two passive scalar transport equations are applied to separately calculate the E-curve and F-curve in the tundish. The numerical modelling results are compared to the water modelling results for the validation of the mathematical model. The volume fraction of different flow regions (plug, mixed and dead) and the intermixing time during the ladle changeover are calculated to study the effects of the flow control device (FCD) on the tundish performance. The result shows that a combination of the U-baffle with deflector holes and the turbulence inhibitor has three major effects on the flow characteristics in the tundish: i) reduce the extent of the dead volume; ii) evenly distribute the liquid streams to each strand and iii) shorten the intermixing time during the ladle changeover operation.

The 'big data revolution' has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the challenges, limitations and risks associated with it. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define ‘successful reuse’ as the use of previously published data to enable novel scientific findings and use selected examples of such reuse from different disciplines to illustrate the enormous potential of the practice, while acknowledging their respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of the practice as a norm has the potential to benefit all stakeholders in the life sciences.

The use of wind energy has been developing fast over the last years. The global cumulative wind power capacity increased by 10.5% in 2019, most of which comes from onshore wind farms. One of the consequences of this continuous increase is the use of land for onshore wind farms. There are already cases worldwide where lack of well-established plans and strategies have caused delays in projects. The need for efficiently using land for wind farms will be mandatory in the short term. In this work, we present a numerical analysis to evaluate wind farm land-use. By defining the ratio between mechanical output power over an area as a parameter called land-use ratio, this work focused on comparing several cases of aligned and staggered layouts. Mechanical output power was estimated using a validated code based on Blade Element Momentum code, and the wake velocities and wake interaction effects were estimated using a validated wind turbine CFD model. In terms of output power, staggered designs are more efficient than aligned designs. However, the results showed that even though staggered designs produced higher output power, aligned farms with tight lateral spacing could be as efficient as staggered ones in terms of land-use but using fewer turbines. In summary, tightly aligned designs should be a tendency in the future towards efficient use of land in wind farms.

The novel COVID-19 pandemic prompted an unprecedented Institutional reaction to aggregate existing capacity from silos of research laboratories to establish a multidisciplinary research laboratory for COVID19 testing. In less than two weeks, resources were mobilized from the community to strengthen public health response and epidemic control. Such strengthening of institutional research capacity to support public health response contributes to a natural knowledge transfer, facilitates collaboration, and generates new frontiers for knowledge production that should ultimately lead to professional development and retention of skilled human resources. This report describes the pre-established mechanisms and involvement of the authors that made it possible to set-up a multidisciplinary laboratory in a remarkably short period of time. We also discuss the opportunities and sustainability of multidisciplinary laboratory research post-COVID19. Existing institutional capacity can be repurposed to establish multidisciplinary research laboratories to support the strengthening of basic and clinical translational research capacity in resource limited settings and impact on public health and scientific knowledge for socioeconomic development.

Kim-Kim [12] introduced the new type of degenerate Bernoulli numbers and polynomials arising from the degenerate logarithm function. In this paper, we introduce a new type of degenerate poly-Euler polynomials and numbers, are called degenerate poly-Euler polynomials and numbers, by using the degenerate polylogarithm function and derive several properties on the degenerate poly-Euler polynomials and numbers. In the last section, we also consider the degenerate unipoly-Euler polynomials attached to an arithmetic function, by using the degenerate polylogarithm function and investigate some identities of those polynomials. In particular, we give some new explicit expressions and identities of degenerate unipoly polynomials related to special numbers and polynomials.

In this study we investigate the formation of dynamical energy cascades in higher order KdV-type equations. In the beginning we recall what is known about the dynamic cascades for the classical KdV (quadratic) and mKdV (cubic) equations. Then, we investigate further the mKdV case by considering a richer set of initial perturbations in order to check the validity and persistence of various facts previously established for the narrow-banded perturbations. Afterwards we focus on higher order nonlinearities (quartic and quintic) which are found to be quite different in many respects from the mKdV equation. Throughout this study we consider both the direct and double energy cascades. It was found that the dynamic cascade is always formed, but its formation is not necessarily accompanied by the nonlinear stage of the modulational instability. Direct cascade structure remains invariant regardless the size of the spectral domain. In contrast, the double cascade shape can depend on the size of the spectral domain, even if the total number of cascading modes remains invariant. Results obtained in this study can be potentially applied to plasmas, free surface and internal wave hydrodynamics.

Design criteria for coastal defenses exposed to wave overtopping are usually assessed by mean overtopping discharges and maximum individual overtopping volumes. However, it is often difficult to give clear and precise limits of tolerable overtopping for all kind of layouts. A few studies analyzed the relationship between wave overtopping flows and hazard levels for people on sea dikes, confirming that one single value of admissible mean discharge or individual overtopping volume is not a sufficient indicator of the hazard, but detailed characterization of flow velocities and depths is required. This work presents the results of an experimental campaign aiming at characterizing the flow characteristics associated to maximum individual overtopping volumes for an urbanized stretch of a town along the Catalan coast, where a walking and bike path and a railway run along the coastline are exposed to significant overtopping events every stormy season. The work compares different safety criteria for pedestrian. Results prove that safety of pedestrian on a sea dike can be still guaranteed even for overtopping volumes larger than 1000 l/m. Pedestrian hazard is rather proved to be linked to the combination of overtopping flow velocity and flow depth.

Among the best-known capillarity phenomena is a capillary rise, the understanding of which is essential in fluidics. Some capillary flows rise monotonically whereas others oscillate, but until now no criteria have been formulated for this scenario. In this paper, the Levine's capillary rise modelling is computed numerically, then the critical radius of the capillary tube is formulated by using the dimensional method and data fitting for identification of exponent index. The phase space diagram of capillary velocity versus height is obtained for the first time and shows that the phase transition from oscillating to monotonic rising happens when the phase trajectory decreases exponentially to somewhere other than the "attractor." Two general Maple codes of the problem are provided as an essential part of this paper.