cocorticoid or serotonin transporter genes that may elicit changes in both depression and the stress response system. In addition, assessment of depression appears warranted for pregnant women in regions known for high pollution.

Findings suggest pregnancy may be a critical window of sensitivity to PM2.5 exposure that escalates depression risk and induces activation of the HPA axis, evidenced in greater overall cortisol concentration. Further research is needed to identify mechanisms underlying the effects of particulate matter, especially potential methylation of glucocorticoid or serotonin transporter genes that may elicit changes in both depression and the stress response system. In addition, assessment of depression appears warranted for pregnant women in regions known for high pollution.Brand perception is a key element in achieving business success how a brand is perceived by current and potential users determines what they think and their disposition towards the brand. The users’ perception also determines whether they will perceive the sports service as offering a greater quality or value than other services, whether they will be more loyal, or whether they will recommend the service. This paper analyses the brand perception of users of a public sports service, creating a model of structural equations that analyses how credibility and trust influence a user’s congruence with the brand and the generation of positive attitudes towards the brand and how these variables influence loyalty levels and recommendations. The results indicate that the proposed model can explain the variables of trust, congruence, attitudes, loyalty and word of mouth by more than 60%. The study finds that credibility influences trust but that credibility in itself does not cause a congruence with the brand, whereas trust does. Similarly, trust does not generate attitudes towards the brand but credibility and congruence do. Congruence generates loyalty but attitudes do not, and congruence, attitudes and loyalty influence recommendation to a similar extent, with congruence having the highest influence.Workers of different generations often complain about one another as their opinions, values, attitudes, and approaches to work differ. This might lead to a reduction in labor productivity that can negatively impact the economic growth of any nation. In this paper, we used generation mix indices to analyze whether generation gap has any impact on economic growth. Using Thailand’s data between 1961 to 2019, we found that when generations were intensely mixed, economic growth did suffer.Based on a qualitative semi-structured interview, this paper argues that pedagogical positions can be negotiated and adjusted once a policy is introduced and a safe space for negotiation is created. It is a case study where we cite evidence from a Saudi university that shows the change in teachers’ assumptions and, consequently, the negotiation process they had gone through within their institution due to a sudden policy shift. The paper highlights the importance of policies and the surrounding circumstances when it comes to negotiating pedagogical beliefs. This paper challenges the long-established assumption that age and much experience make it difficult for teachers to adapt their face-to-face educational activities to online platforms. We argue that institutional policies play a crucial role in shaping and reshaping teachers’ assumptions and practices when the following conditions are met sound IT infrastructure, technological support, and continuous training.Crop productivity in most smallholder farming systems in Sub-Saharan Africa experience low use of soil amendment resources, low and erratic rainfall, frequent dry spells, and droughts. Rain-fed agriculture has a high crop yield potential if rainfall and soil nutrient input resources are utilized effectively. Thus, in 2011, we set up an on-farm experiment in Meru South (sub-humid) and Mbeere South (marginal sub-humid) sub-counties in upper Eastern Kenya to assess conservation-effective management (CEM) practices effects on maize (Zea Mays L.) yields response and soil nutrients. The CEM practices were; tied ridging (TR), mulching (MC), and minimum tillage (MT), with conventional tillage (CT) as a control. There were frequent dry spells and droughts during the experimental period. The experiment ran for four seasons, from the long rains season of 2011 (LR11), short rains seasons of 2011 (SR11), long rains season of 2012 (LR12), short rains 2012 (SR12), and long rains season of 2013 (LR13). In Meru South, TR and CEM effects on soil nutrients.The current dominating production and consumption model is based on the linear economy (LE) model, within which raw materials are extracted-processed-consumed-discarded. A circular economy (CE) constitutes a regenerative systemic approach to economic development which views waste as a valuable resource to be reprocessed back into the economy. In order to understand the circular strategy for a systemic change from an LE to a CE as a means of resolving the issue of plastic waste, this research aims to map current circular strategy trends across the system perspective contained in the literature relating to plastic CE literature. The novelty of the research lies in the mapping and review of the distribution of comprehensive circular strategies within the 9R framework across the entire system perspective (e.g. micro-meso-macro) down to its sub-levels in the literature on a plastic CE. The bibliographic mapping and systematic literature review iindicateed that the majority of the research focused on recycle (R8), on to fossil-based plastics.Genome-wide association studies (GWAS) have become beneficial in identifying genetic variants underlying susceptibility to various complex diseases and conditions, including obesity. Utilizing the Drosophila Genetic Reference Panel (DGRP), we performed a GWAS of lifespan of 193 genetically distinct lines on a high sugar diet (HSD). The DGRP analysis pipeline determined the most significant lifespan associated polymorphisms were within loci of genes involved in neural processes, behavior, development, and apoptosis, among other functions. Next, based on the relevance to obesity pathology, and the availability of transgenic RNAi lines targeting the genes we identified, whole-body in vivo knockdown of several candidate genes was performed. We utilized the GAL4-UAS binary expression system to independently validate the impacts of these loci on Drosophila lifespan during HSD. These loci were largely confirmed to affect lifespan in that HSD setting, as well as a normal diet setting. However, we also detected unexpected dietary effects of the HSD, including inconsistent diet effects on lifespan relative to a normal diet and a strong downregulation of feeding quantity.Toxoplasma gondii (T. gondii) is one of the most pervasive neurotropic pathogens causing different lesions in a wide variety of mammals as intermediate hosts, including humans. It is estimated that one-third of the world population is infected with T. gondii; however, for a long time, there has been much interest in the examination of the possible role of this parasite in the development of mental disorders, such as Alzheimer’s disease (AD). T. gondii may play a role in the progression of AD using mechanisms, such as the induction of the host’s immune responses, inflammation of the central nervous system (CNS), alteration in the levels of neurotransmitters, and activation of indoleamine-2,3-dyoxigenase. This paper presents an appraisal of the literature, reports, and studies that seek to the possible role of T. gondii in the development of AD. For achieving the purpose of the current study, a search of six English databases (PubMed, ScienceDirect, Web of Science, Scopus, ProQuest, and Google Scholar) was performed. The results support the involvement of T. gondii in the induction and development of AD. Indeed, T. gondii can be considered a risk factor for the development of AD and requires the special attention of specialists and patients. Furthermore, the results of this study may contribute to prevent or delay the progress of AD worldwide. Therefore, it is required to carry out further studies in order to better perceive the parasitic mechanisms in the progression of AD.

To evaluate the association between the use of a 3D virtual App and academic performance among Peruvian medical students. In addition, factors associated with academic performance were also assessed.

We conducted an analytical cross-sectional study in students enrolled in the Musculoskeletal System course during the first semester of 2019. Students filled out a data collection form and the „Self-directed learning readiness scale” (SDLRS) questionnaire adapted by

. Linear regression models were carried out to assess the association between the appropriate use of the application and academic performance. Additionally, the factors associated with academic performance were evaluated using nested models, and β coefficients were calculated by manual forward selection.

A total of 187 medical students were included. The 61% were female and the median age was 21 [20-22] years. The average grade was 13.5 ± 2 and 21% reported an adequate use of a 3D App. No association was found between the use of the 3D App and academic performance in the adjusted model (aβ = 0.17; 95% CI -0.45 to 0.80). We found that age (aβ = -0.22; 95% CI -0.39 to -0.06), performing extracurricular activities (aβ = 0.75, 95% CI 0.25 to 1.24) and having failed an anatomy/physiology course before (aβ = -2.11 to 95% CI -2.9 to -1.8) were factors associated with academic performance.

The adequate use of a 3D application to study the anatomy of the musculoskeletal system was not significantly associated with better academic performance.

The adequate use of a 3D application to study the anatomy of the musculoskeletal system was not significantly associated with better academic performance.[This corrects the article DOI 10.1016/j.heliyon.2020.e05673.].The study seeks to identify bicycle ownership and ridership and gain insights into how demographics, perceptions and experiences of respondents influenced the status of cycling in Tamale Metropolis. Earlier studies have focused on examining the determinants of utility cycling among adults in the same metropolis, but this study assesses cycling from a broader perspective in terms of demographics, barriers, and promotional strategies. A cross-sectional survey was carried out with 500 semi-structured questionnaires through mainly a face-to-face approach. Five trained survey assistants administered the questionnaires within demarcated zones in the metropolis and tracked participants by geographic information system. Binary logistic regression, chi-squared test and descriptive statistics were employed in the analysis of the data. Out of the 439 valid questionnaires, bicycle ownership and ridership were 56% and 78% respectively. Gender and occupation were significant in owning and riding bicycles, where p less theort needs of speed and travelling with less fatigue.Assessing landform vulnerability to soil erosion is crucial for improved sustainable land use planning and management. In the Loess Plateau of the Northern Shaanxi Province of China, soil erosion has been reported as a major threat to sustainable land management and impacts on driving the socio-economic benefits that can be accrued from the landforms. Several studies especially on Erosion Potential Mapping (EPM) in the region have been conducted but the role of the fractal dimension (FD) of the terrain features has been limited. In this study, the paper assessed the role of fractal terrain features on the overall EPM. The Analytical Hierarchical Process (AHP) was adopted using 6 criteria, FD of the terrain, Land Use Land Cover, Slope, Elevation, Geomorphology and Flow Accumulation. These were developed in a Geographic Information System (GIS) framework. Eight Scales (8) were evaluated in order to select the best Scale with the lowest Consistency Ratio (CR) and the Minimum Relative Error (MRE). The results from this study shows that fractal features of terrain when integrated with the rest of the criteria produced a reliable EPM for the study area. The absence of the FD also gives unrealistic results for the EPM. The EPM with FD distribution recorded 29.4% for low erosion potential whereas EPM without FD recorded 46.7%. A larger portion of the Shaanxi province (70%) is found to be at a higher risk of erosion. Therefore, it is hoped that the findings from this research would further boost the integration of fractals into EPM in China and similar regions across the World. The study further recommends that sustainable soil management measures are put in place to reduce the erosion risk in the province to protect the natural ecological habitat.Foods frequently eaten supply both micro and macro nutrients to humans which are important in the total assessment of public health status of an individual. The analysis of these foods will provide evidence on their nutritional values, guide to appropriate choice of meal and encourage intake of varieties of food with better qualities during illness while preventing diet-associated disorders. In this study, the proximate and mineral composition of unripe, naturally ripe and the effects of ripening agents on plantain (Musa paradisiaca) commonly consumed in Nigeria were examined. The plantain fruits were analysed for proximate and mineral composition. Proximate composition analysis revealed an increase in moisture content and fat content for all the plantain ripened with ripening agents when compared with the naturally ripened plantain. Furthermore, the mineral composition of the plantain fruits was determined by means of Atomic Absorption Spectrophotometry (AAS). The result showed that plantain is a good source of minerals such as calcium (Ca), potassium (K) and iron (Fe). A relatively high level of K of 1690.55 ± 0.02; 1672.35 ± 0.03 mg kg-1 were found for both unripe and natural ripe plantain while the ripening agents had K values of 1677.45 ± 0.01; 1656.10 ± 0.02; 1589.45 ± 0.01 mg kg-1 for Ethylene glycol, Potassium Dihydrogen Phosphate, Calcium carbide respectively. Also, low level of Fe was obtained in plantain ripened with the different ripening agents.Bacterial systems have gained wide attention for depolymerization of lignocellulosic biomass, due to their high functional diversity and adaptability. To achieve the full microbial exploitation of lignocellulosic residues and the cost-effective production of bioproducts within a biorefinery, multiple metabolic pathways and enzymes of various specificities are required. In this work, highly diverse aerobic, mesophilic bacteria enriched from Keri Lake, a pristine marsh of increased biomass degradation and natural underground oil leaks, were explored for their metabolic versatility and enzymatic potential towards lignocellulosic substrates. A high number of Pseudomonas species, obtained from enrichment cultures where organosolv lignin served as the sole carbon and energy source, were able to assimilate a range of lignin-associated aromatic compounds. Comparatively more complex bacterial consortia, including members of Actinobacteria, Proteobacteria, Bacilli, Sphingobacteria, and Flavobacteria, were also enriched from cultures with xylan or carboxymethyl cellulose as sole carbon sources. Numerous individual isolates could target diverse structural lignocellulose polysaccharides by expressing hydrolytic activities on crystalline or amorphous cellulose and xylan. Specific isolates showed increased potential for growth in lignin hydrolysates prepared from alkali pretreated agricultural wastes. The results suggest that Keri isolates represent a pool of effective lignocellulose degraders with significant potential for industrial applications in a lignocellulose biorefinery.Frequent episodes of heat threaten sustainable agriculture in Egypt. This study is an urgent call to select tolerant genotypes of heat and discover the predicted screening phenotypic parameters. Here, twenty spring wheat genotypes were exposed to heat stress under field conditions for screening heat tolerance. Stress environments were simulated by delaying the sowing date by 53 and 58 days than the normal environments for two successive seasons. Stressed plants received the highest peak of heat during the reproductive growth stage. Eight phenotypic parameters were measured to evaluate genotype tolerance. Mean performance, reduction percentage/trait, and heat susceptibility index parameters were calculated. Additionally, the pollen grain viability during spike emergence and the germinability of producing grains were investigated. Results demonstrated (1) Highly significant differences (P less then 0.01) between genotypes, treatments and genotypes by treatments in grain yield and other traits in both studied seasons, (2) significant reduction in all studied traits compared to the non-stress environment, (3) the overall yield reduction, based on grain yield/m2, was 40.17, 41.19 % in the first and second seasons, respectively, and the most tolerant genotypes were Masr2, Sids1, Giza 171 and Line 9, (4) limited impact of heat has detected on pollen grains viability and germinability, and (5) grain yield as a selection criterion for heat stress remains the most reliable yardstick.Gold mining is one of the major problems of contamination of hydric resources in Colombia, this practice generates a high impact on water quality due to the accumulation of waste during its process. In this study water quality was evaluated in five natural stream beds corresponding to four streams with gold mining operations and one in the Cauca River, taking samples before the water inlet and after the outlet in each operation in the streams of Dios Te Dé, Tamboral, Piedra Imán, and Lorenzo affected by artisanal gold mining labor, which drain into the Salvajina Reservoir on the Cauca River in the municipality of Suárez Cauca, Colombia. Characterization of water bodies in the streams was carried out applying contamination indices of Colombia. The IDEAM protocol was used as guide to monitor the water currents. Samples were taken in 15 stations in the natural stream beds with operations and a sampling station on the Cauca River after the reservoir in these lotic ecosystems, during three periods; two from 2018 and one from 2019. The range of the contamination indices according to the environmental variables were considered. Results show that the contaminants associated with TSS, TUR, and Hg are high in the sampling stations in the output of the operations and the sampling stations of the streams with influence on the operations (T3, T4, I2, I3, D2, and D5). The water quality score according to the ICA IDEAM index varied between acceptable and regular in the different sampling stations. However the Hg concentration in sampling station C1 of the Cauca River is due to contributions from the operations in the amalgamation process. This requires strategic interventions by the communities, miners, operation owners, and control organisms as the Regional Autonomous Corporation of Cauca (CRC) and the Ministry of Environment and Sustainable Development (MADS) to minimize the negative impacts on the hydric resource and ecosystemic services associated with this resource.In an effort to improve the quality of higher education, it is necessary to find the main predictors or determinants of the quality requested. One of the indicators is alumni satisfaction. Therefore, the problems of this research are to determine the satisfaction of the Educational Management Program alumni and to examine the variables, facilities and infrastructure, professionalism of lecturers, and curriculum relevance, which determine the alumni satisfaction. This was an ex-post facto study. The research design used an ex-post facto method because this method aims to find causes that allow changes in behavior or phenomena, in this case alumni satisfaction with the teaching and learning process. The study data was obtained from the alumni of the Educational Management Program who currently work in one selected regency. A total of 36 alumni were involved as samples. The data collection instrument used by the researchers was in the form of a scale consisting of 27 items that had been proved reliable and valid. The results showed that most alumni had a high level of satisfaction, and there was 1 model that determined an alumni satisfaction of 36.10%, namely for the professionalism of lecturers.Acremonium species are prolific producers of therapeutic molecules which include the widely used beta-lactam antibiotic, cephalosporin. In light of their significant medical value, an efficient gene disruption method is required for the physiological and biochemical studies on this genus of fungi. However, the number of selection markers that can be used for gene targeting is limited, which constrain the genetic analysis of multiple functional genes. In this study, we established a uridine auxotrophy based marker recycling system which achieves scarless gene deletion, and allows the use of the same selection marker in successive transformations in a deep sea-derived fungus Acremonium sp. HDN16-126. We identified one homologue of Acremonium chrysogenum pyrG (also as a homologous gene of the yeast URA3) from HDN16-126, designated as pyrG-A1, which can be used as a selection marker on uridine free medium. We then removed pyrG-A1 from HDN16-126 genome via homologous recombination (HR) on MM medium with 5-fluoroortic acid (5-FOA), a chemical that can be converted into a toxin of 5-flurouracil by pyrG-A1 activity, thus generating the HDN16-126-△pyrG mutant strain which showed auxotrophy for uridine but insensitivity to 5-FOA and enabled the use of exogenous pyrG gene as both positive and negative selection marker to achieve the scarless deletion of target DNA fragments. We further applied this marker recycling system to successfully disrupt two target genes pepL (encodes a putative 2OG-Fe (II) dioxygenase) and pepM (encodes a putative aldolase) identified from HDN16-126 genome, which are proposed to be functional genes related to 2-aminoisobutyric acid metabolism in fungi. This work is the first application of uridine auxotrophy based scarless gene deletion method in Acremonium species and shows promising potential in assisting sequential genetic analysis of filamentous fungi.A cross-sectional study of Toxoplasma gondii infection in pigs was carried out in backyard farms in three townships, within Nay Pyi Taw area from June 2014 to August 2014. Blood samples were randomly collected from 256 pigs in 129 farms. Using commercial Latex Agglutination Test kits, specific antibodies to T. gondii were analyzed. Based on LAT results, among 256 serum samples examined, 47 samples (18.4%) were found positive to T. gondii. The numbers of samples showing specific antibody titres from 47 positive pig sera were 20 at 164, 2 samples at 1128, 9 samples at 1256, 3 samples at 1512 and 13 samples at 11024. Among the hypothesized risk factors, roaming of cats around the farm was found associated to T. gondii seropositivity in pigs (OR = 3.13; 95% CI = 1.33-7.34). This study provides information on seroepidemiology study of T. gondii in backyard pigs for the first time in Myanmar. This information will be useful in developing strategies for the control of T. gondii infection in pigs.Complementary therapies are often used during in-vitro fertilization (IVF) treatment. The aim of this study was to determine how UK fertility clinic websites are advertising complementary therapy add-ons. The Human Fertilisation and Embryology Authority’s (HFEA) 'Choose a Fertility Clinic’ website was used to identify fertility clinics and their websites. Acupuncture, reflexology, nutritional advice and miscellaneous complementary therapies were examined to determine treatment provision and costs. Treatment claims for acupuncture and reflexology were analysed using an inductive coding approach, and categorized depending on whether they pertained to holistic benefits, physiological benefits or improvements to IVF treatment outcome. At least one complementary therapy was advertised by 17 of 66 (26%) websites. Acupuncture was the most commonly advertised complementary therapy (16/66 clinic websites, 24%), followed by nutritionist services (11/66, 17%), reflexology (10/66, 15%) and other miscellaneous complementary therapies (9/66, 14%). Treatment costs were found to range from less than £50 for individual appointments to hundreds of pounds for treatment packages. Treatments were not always offered in-house at the fertility clinic, but rather patients were referred to an affiliated practitioner. Analysing claims relating to the complementary therapies highlighted that there were differences in the extent to which clinics claimed that complementary therapies benefited IVF, and that information occasionally acknowledged scientific research evidence but did not always present resources in an unbiased manner. Fertility clinic websites should provide accurate information for patients for complementary therapy add-ons. HFEA should add acupuncture and reflexology to their traffic-light system with amber and red ratings, respectively.Activation of AMP activated protein kinase (AMPK) signaling has been demonstrated to extend lifespan and improve healthspan across multiple species. This suggests pharmaceutical approaches to increase AMPK hold the potential to modify the aging process and promote healthy aging. Beta-guanidinopropionic acid (GPA) is a naturally occurring metabolite structurally similar to creatine. GPA is capable of activating AMPK signaling in mammalian models via competitive inhibition of cytosolic creatine kinase. A previous report suggested that dietary GPA supplementation increased lifespan in Drosophila through its effect on AMPK signaling and regulation of autophagy. However, studies in Caenorhabditis have found no beneficial effect of this compound on worm lifespan and that GPA may actually diminish lifespan in at least one Caenorhabditis species. To confirm previous reports of increased longevity in Drosophila, we tested a wide range of GPA concentrations on lifespan and healthspan in both male and female W1118 flies. We report here that GPA does not extend lifespan in Drosophila as previously reported. Moreover, high doses of GPA are detrimental to Drosophila lifespan and stress resistance in male flies. These results suggest the lack of a robust effect of GPA on Drosophila lifespan and highlight the importance of replication studies within the field of aging.Carotenoids are powerful antioxidants capable of helping to protect the skin from the damaging effects of exposure to sun by reducing the free radicals in skin produced by exposure to ultraviolet radiation, and they may also have a physical protective effect in human skin. Since carotenoids are lipophilic molecules which can be ingested with the diet, they can accumulate in significant quantities in the skin. Several studies on humans have been conducted to evaluate the protective function of carotenoids against various diseases, but there is very limited published information available to understand the mechanism of carotenoid bioavailability in animals. The current study was conducted to investigate the skin carotenoid level (SCL) in two cattle skin sets – weaners with an unknown feeding regime and New Generation Beef (NGB) cattle with monitored feed at three different ages. Rapid analytical and sensitive Raman spectroscopy has been shown to be of interest as a powerful technique for the detection of carotenoids in cattle skin due to the strong resonance enhancement with 532 nm laser excitation. The spectral difference of both types of skin were measured and quantified using univariate and linear discriminant analysis. SCL was higher in NGB cattle than weaners and there is a perfect classification accuracy between weaners and NGB cattle skin using carotenoid markers as a basis. Further work carried out on carotenoid rich NGB cattle skin of 8, 12 and 24 months of age identified an increasing trend in SCL with age. The present work validated the ability of Raman spectroscopy to determine the skin carotenoid level in cattle by comparing it with established HPLC methods. There is an excellent correlation of R2 = 0.96 between the two methods that could serve as a model for future application for larger population studies.

Extracellular vesicles (EVs) have been isolated from various sources, including primary and cultured cell lines and body fluids. Previous studies, including those conducted in our laboratory, have reported the stability of EVs under various storage conditions.

EVs from human whole saliva were separated via size-exclusion chromatography. To simulate the effects of gastric or intestinal fluids on the stability of EVs, pepsin or pancreatin was added to the samples. Additionally, to determine the effect of bile acids, sodium cholate was added. The samples were then subjected to western blotting, dynamic light scattering, and transmission electron microscopy analyses. In addition, the activity of dipeptidyl peptidase (DPP) IV retained in the samples was examined to monitor the stability of EVs.

Under acidic conditions, with pepsin mimicking the milieu of the stomach, the EVs remained stable. However, they partially lost their membrane integrity in the presence of pancreatin and sodium cholate, indicating thal tract.

Increasing healthcare costs need to be contained in order to maintain equality of access to care for all EU citizens. A cross-disciplinary consortium of experts was supported by the EU FP7 research programme, to produce a roadmap on cost containment, while maintaining or improving the quality of healthcare. The roadmap comprises two drivers person-centred care and health promotion; five critical enablers also need to be addressed information technology, quality measures, infrastructure, incentive systems, and contracting strategies.

In order to develop and test the roadmap, a COST Action project was initiated COST-CARES, with 28 participating countries. This paper provides an overview of evidence about the effects of each of the identified enablers. Intersections between the drivers and the enablers are identified as critical for the success of future cost containment, in tandem with maintained or improved quality in healthcare. This will require further exploration through testing.

Cost containment of future healthcare, with maintained or improved quality, needs to be addressed through a concerted approach of testing key factors. We propose a framework for test lab design based on these drivers and enablers in different European countries.

Cost containment of future healthcare, with maintained or improved quality, needs to be addressed through a concerted approach of testing key factors. We propose a framework for test lab design based on these drivers and enablers in different European countries.

Recently, there are a few moisturizers showing hydrating effects up to 24 hours after single application. Aquaporin 3 might be associated with the degree of skin hydration. We aimed to assess the effects of two brands of 24-hour moisturizers on the skin barrier function, as well as the AQP3 gene expression.

Two moisturizers were applied once daily by 20 participants age 36.15 ± 9.55 years. Upper right and left forearms were randomly assigned to application of each product, whereas the right lower forearm served as control site for application of a cream base formulation. Biophysical assessments including trans epidermal water loss (TEWL), skin hydration, pH, surface lipids, and elasticity parameters were performed before intervention, 1, 4, and 24 hours after single application, following 2 weeks daily application and 1 week after termination of use. Also 5-mm punch biopsies were performed from application sites of product B and cream base formulation in for five participants after 2 weeks of application.

A single treatment with both products led to 24-hour increase in skin moisture in comparison with the control site (

-value <.01). Daily application of both products for 14 days also led to significant improvement in skin moisture (

-value <.01), TEWL (

-value <.01), and elasticity parameters. The increase in skin hydration was associated with upregulation of AQP3 gene expression in treated area for one of the formulations (

-value=.04).

The tested 24-hour moisturizers only need to be applied once daily to improve skin barrier function and hydration and up-regulate AQP3 mRNA expression.

The tested 24-hour moisturizers only need to be applied once daily to improve skin barrier function and hydration and up-regulate AQP3 mRNA expression.

The health care and social assistance industry has one of the highest rates of non-fatal occupational injuries and illnesses, both in California and nationally. In the coming years, the health care industry will face added pressure as both the population and workforce age. The aim of this study is to identify targeted populations that may benefit from interventions to prevent future injuries, keep the workforce healthy, and decrease injury-related costs.

This retrospective study analyzed California workers’ compensation claims from 2009 to 2018 in the health care and social assistance industry.

Across the four industry sub-groups, the highest number of claims came from hospitals (n=243 605; 38.9%), followed by ambulatory care (n=187 010; 29.9%), nursing/residential care (n=133 206; 21.3%), and social assistance (n=62 211; 9.9%). Nursing/residential care settings reported the highest proportion of both lifting injuries (15.8%) and low back injuries (16.9%) as compared to the other settings. Across all settings within California, nurses had the highest proportion of injuries (22.1%), followed by aides/assistants (20.4%), services staff (13.2%), administrative staff (11.0%), and technicians (10.3%). Thirty-five of California’s counties had an increasing rate of population-adjusted claims during the study period.

This study found that while hospitals have the highest number of injuries, ambulatory care employee injuries are increasing. Employees involved in non-patient care tasks, such as those working in facility service roles, would likely benefit from additional injury prevention interventions.

This study found that while hospitals have the highest number of injuries, ambulatory care employee injuries are increasing. Employees involved in non-patient care tasks, such as those working in facility service roles, would likely benefit from additional injury prevention interventions.There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.Long-term peritoneal dialysis (PD) is accompanied by low-grade intraperitoneal inflammation and may eventually lead to peritoneal membrane injury with a high solute transport rate and ultrafiltration failure. Osteopontin (OPN) is highly expressed through the stimulation of pro-inflammatory cytokines in many cell types. This study aimed to investigate the potential of OPN as a new indicator of peritoneal deterioration. One hundred nine continuous ambulatory PD patients were analyzed. The levels of OPN and IL-6 in peritoneal effluents or serum were analyzed by ELISA kits. The mean effluent OPN concentration was 2.39 ± 1.87 ng/mL. The OPN levels in drained dialysate were correlated with D/P Cr (p less then 0.0001, R = 0.54) and D/D0 glucose (p less then 0.0001, R = 0.39). Logistic regression analysis showed that the OPN levels in peritoneal effluents were an independent predictive factor for the increased peritoneal solute transport rate (PSTR) obtained by the peritoneal equilibration test (p less then 0.001). The area under the receiver operating characteristic curve of OPN was 0.84 (95% CI 0.75-0.92) in predicting the increased PSTR with a sensitivity of 86% and a specificity of 67%. The joint utilization of effluent OPN with age, effluent IL-6, and serum albumin further increased the specificity (81%). Thus, OPN may be a useful indicator of peritoneal deterioration in patients with PD.Query optimization is the process of identifying the best Query Execution Plan (QEP). The query optimizer produces a close to optimal QEP for the given queries based on the minimum resource usage. The problem is that for a given query, there are plenty of different equivalent execution plans, each with a corresponding execution cost. To produce an effective query plan thus requires examining a large number of alternative plans. Access plan recommendation is an alternative technique to database query optimization, which reuses the previously-generated QEPs to execute new queries. In this technique, the query optimizer uses clustering methods to identify groups of similar queries. However, clustering such large datasets is challenging for traditional clustering algorithms due to huge processing time. Numerous cloud-based platforms have been introduced that offer low-cost solutions for the processing of distributed queries such as Hadoop, Hive, Pig, etc. This paper has applied and tested a model for clustering variant sizes of large query datasets parallelly using MapReduce. The results demonstrate the effectiveness of the parallel implementation of query workloads clustering to achieve good scalability.In reinforcement learning (RL), dealing with non-stationarity is a challenging issue. However, some domains such as traffic optimization are inherently non-stationary. Causes for and effects of this are manifold. In particular, when dealing with traffic signal controls, addressing non-stationarity is key since traffic conditions change over time and as a function of traffic control decisions taken in other parts of a network. In this paper we analyze the effects that different sources of non-stationarity have in a network of traffic signals, in which each signal is modeled as a learning agent. More precisely, we study both the effects of changing the context in which an agent learns (e.g., a change in flow rates experienced by it), as well as the effects of reducing agent observability of the true environment state. Partial observability may cause distinct states (in which distinct actions are optimal) to be seen as the same by the traffic signal agents. This, in turn, may lead to sub-optimal performance. We show that the lack of suitable sensors to provide a representative observation of the real state seems to affect the performance more drastically than the changes to the underlying traffic patterns.The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due to its practical implications in manufacturing systems and emerging new variants, in order to model and optimize more complex situations that reflect the current needs of the industry better. This work presents a new metaheuristic algorithm called the global-local neighborhood search algorithm (GLNSA), in which the neighborhood concepts of a cellular automaton are used, so that a set of leading solutions called smart-cells generates and shares information that helps to optimize instances of the FJSP. The GLNSA algorithm is accompanied by a tabu search that implements a simplified version of the Nopt1 neighborhood defined in Mastrolilli & Gambardella (2000) to complement the optimization task. The experiments carried out show a satisfactory performance of the proposed algorithm, compared with other results published in recent algorithms, using four benchmark sets and 101 test problems.

Plants have an important place in the life of all living things. Today, there is a risk of extinction for many plant species due to climate change and its environmental impact. Therefore, researchers have conducted various studies with the aim of protecting the diversity of the planet’s plant life. Generally, research in this area is aimed at determining plant species and diseases, with works predominantly based on plant images. Advances in deep learning techniques have provided very successful results in this field, and have become widely used in research studies to identify plant species.

In this paper, a Multi-Division Convolutional Neural Network (MD-CNN)-based plant recognition system was developed in order to address an agricultural problem related to the classification of plant species. In the proposed system, we divide plant images into equal nxn-sized pieces, and then deep features are extracted for each piece using a Convolutional Neural Network (CNN). For each part of the obtained deep featuresage, Flower17, Flower102, and LeafSnap datasets achieved results of 99.77%, 99.93%, 97.87%, 98.03%, and 94.38%, respectively.In the last decade, deep learning has been applied in a wide range of problems with tremendous success. This success mainly comes from large data availability, increased computational power, and theoretical improvements in the training phase. As the dataset grows, the real world is better represented, making it possible to develop a model that can generalize. However, creating a labeled dataset is expensive, time-consuming, and sometimes not likely in some domains if not challenging. Therefore, researchers proposed data augmentation methods to increase dataset size and variety by creating variations of the existing data. For image data, variations can be obtained by applying color or spatial transformations, only one or a combination. Such color transformations perform some linear or nonlinear operations in the entire image or in the patches to create variations of the original image. The current color-based augmentation methods are usually based on image processing methods that apply color transformations such as equalizing, solarizing, and posterizing. Nevertheless, these color-based data augmentation methods do not guarantee to create plausible variations of the image. This paper proposes a novel distribution-preserving data augmentation method that creates plausible image variations by shifting pixel colors to another point in the image color distribution. We achieved this by defining a regularized density decreasing direction to create paths from the original pixels’ color to the distribution tails. The proposed method provides superior performance compared to existing data augmentation methods which is shown using a transfer learning scenario on the UC Merced Land-use, Intel Image Classification, and Oxford-IIIT Pet datasets for classification and segmentation tasks.As the necessity of wireless charging to support the popularization of electric vehicles (EVs) emerges, the development of a wireless power transfer (WPT) system for EV wireless charging is rapidly progressing. The WPT system requires alignment between the transmitter coils installed on the parking lot floor and the receiver coils in the vehicle. To automatically align the two sets of coils, the WPT system needs a localization technology that can precisely estimate the vehicle’s pose in real time. This paper proposes a novel short-range precise localization method based on ultrawideband (UWB) modules for application to WPT systems. The UWB module is widely used as a localization sensor because it has a high accuracy while using low power. In this paper, the minimum number of UWB modules consisting of two UWB anchors and two UWB tags that can determine the vehicle’s pose is derived through mathematical analysis. The proposed localization algorithm determines the vehicle’s initial pose by globally optimizing the collected UWB distance measurements and estimates the vehicle’s pose by fusing the vehicle’s wheel odometry data and the UWB distance measurements. To verify the performance of the proposed UWB-based localization method, we perform various simulations and real vehicle-based experiments.

Consumer electronics or daily use home appliances are the basic necessity of every household. With the adoption of IoT in consumer electronics, this industry is set to rise exponentially. In recent times, the demand for consumer electronics rises amidst the pandemic due to a paradigm shift from in-office culture to work from home. Despite intelligent IoT devices, smart home configuration, and appliances at our disposal, the rudimentary client-server architecture fails to provide facilities like full access control of data and devices, transparency, secured communication, and synchronization between multiple devices, etc. to the users.

To overcome these limitations, Blockchain technology has been adopted in recent years, however, it has its own set of limitations in its widespread implementation. Hence, we propose a methodology using the IOTA platform, a distributed ledger technology (DLT) for secured communication between consumer electronics devices and appliances.

The implementation provides access control, interoperability, data storage, and management with an exploratory insight towards a decentralized micro-payment use-case between Electric cars and charging stations.

The implementation provides access control, interoperability, data storage, and management with an exploratory insight towards a decentralized micro-payment use-case between Electric cars and charging stations.

Until now, there are still a limited number of resources available to predict and diagnose COVID-19 disease. The design of novel drug-drug interaction for COVID-19 patients is an open area of research. Also, the development of the COVID-19 rapid testing kits is still a challenging task.

This review focuses on two prime challenges caused by urgent needs to effectively address the challenges of the COVID-19 pandemic, i.e., the development of COVID-19 classification tools and drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models.

In this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease. This study provides recommendations for future research and facilitates knowledge collection and formation on the application of the AI techniques for dealing with the COVID-19 epidemic and its consequences.

The AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients.

The AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients.In this paper, a novel feature selection method called Robust Proportional Overlapping Score (RPOS), for microarray gene expression datasets has been proposed, by utilizing the robust measure of dispersion, i.e., Median Absolute Deviation (MAD). This method robustly identifies the most discriminative genes by considering the overlapping scores of the gene expression values for binary class problems. Genes with a high degree of overlap between classes are discarded and the ones that discriminate between the classes are selected. The results of the proposed method are compared with five state-of-the-art gene selection methods based on classification error, Brier score, and sensitivity, by considering eleven gene expression datasets. Classification of observations for different sets of selected genes by the proposed method is carried out by three different classifiers, i.e., random forest, k-nearest neighbors (k-NN), and support vector machine (SVM). Box-plots and stability scores of the results are also shown in this paper. The results reveal that in most of the cases the proposed method outperforms the other methods.

While there is no cure for Alzheimer’s disease (AD), early diagnosis and accurate prognosis of AD may enable or encourage lifestyle changes, neurocognitive enrichment, and interventions to slow the rate of cognitive decline. The goal of our study was to develop and evaluate a novel deep learning algorithm to predict mild cognitive impairment (MCI) to AD conversion at three years after diagnosis using longitudinal and whole-brain 3D MRI.

This retrospective study consisted of 320 normal cognition (NC), 554 MCI, and 237 AD patients. Longitudinal data include T1-weighted 3D MRI obtained at initial presentation with diagnosis of MCI and at 12-month follow up. Whole-brain 3D MRI volumes were used without a priori segmentation of regional structural volumes or cortical thicknesses. MRIs of the AD and NC cohort were used to train a deep learning classification model to obtain weights to be applied via transfer learning for prediction of MCI patient conversion to AD at three years post-diagnosis. Two (zero-shot anneural network model using longitudinal and whole-brain 3D MRIs without extracting regional brain volumes or cortical thicknesses to predict future MCI to AD conversion at 3 years after diagnosis. This approach could lead to early prediction of patients who are likely to progress to AD and thus may lead to better management of the disease.

This is the first convolutional neural network model using longitudinal and whole-brain 3D MRIs without extracting regional brain volumes or cortical thicknesses to predict future MCI to AD conversion at 3 years after diagnosis. This approach could lead to early prediction of patients who are likely to progress to AD and thus may lead to better management of the disease.