The 100 most-cited articles in Scientific Reports, 2021

Our previous study demonstrated increased expression of Heat shock protein (Hsp) 90 in the skin of patients with systemic sclerosis (SSc). We aimed to evaluate plasma Hsp90 in SSc and characterize its association with SSc-related features. Ninety-two SSc patients and 92 age-/sex-matched healthy controls were recruited for the cross-sectional analysis. The longitudinal analysis comprised 30 patients with SSc associated interstitial lung disease (ILD) routinely treated with cyclophosphamide. Hsp90 was increased in SSc compared to healthy controls. Hsp90 correlated positively with C-reactive protein and negatively with pulmonary function tests: forced vital capacity and diffusing capacity for carbon monoxide (DLCO). In patients with diffuse cutaneous (dc) SSc, Hsp90 positively correlated with the modified Rodnan skin score. In SSc-ILD patients treated with cyclophosphamide, no differences in Hsp90 were found between baseline and after 1, 6, or 12 months of therapy. However, baseline Hsp90 predicts the 12-month change in DLCO. This study shows that Hsp90 plasma levels are increased in…

ABSTRACT COVID-19, caused by SARS-CoV-2, can involve sequelae and other medical complications that last weeks to months after initial recovery, which has come to be called Long-COVID or COVID long-haulers. This systematic review and meta-analysis aims to identify studies assessing long-term effects of COVID-19 and estimates the prevalence of each symptom, sign, or laboratory parameter of patients at a post-COVID-19 stage. LitCOVID (PubMed and Medline) and Embase were searched by two independent researchers. All articles with original data for detecting long-term COVID-19 published before 1 st of January 2021 and with a minimum of 100 patients were included. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. Heterogeneity was assessed using I 2 statistics. This systematic review followed Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) guidelines, although the study protocol was not registered. A total of 18,251 publications were…

Antimicrobial resistance (AMR) is a significant public health threat. With the rise of affordable whole genome sequencing, in silico approaches to assessing AMR gene content can be used to detect known resistance mechanisms and potentially identify novel mechanisms. To enable accurate assessment of AMR gene content, as part of a multi-agency collaboration, NCBI developed a comprehensive AMR gene database, the Bacterial Antimicrobial Resistance Reference Gene Database and the AMR gene detection tool AMRFinder. Here, we describe the expansion of the Reference Gene Database, now called the Reference Gene Catalog, to include putative acid, biocide, metal, stress resistance genes, in addition to virulence genes and species-specific point mutations. Genes and point mutations are classified by broad functions, as well as more detailed functions. As we have expanded both the functional repertoire of identified genes and functionality, NCBI released a new version of AMRFinder, known as AMRFinderPlus. This new tool allows users the option to utilize only the core set of AMR elements, or…

Cancer hallmark genes are responsible for the most essential phenotypic characteristics of malignant transformation and progression. In this study, our aim was to estimate the prognostic effect of the established cancer hallmark genes in multiple distinct cancer types. RNA-seq HTSeq counts and survival data from 26 different tumor types were acquired from the TCGA repository. DESeq was used for normalization. Correlations between gene expression and survival were computed using the Cox proportional hazards regression and by plotting Kaplan-Meier survival plots. The false discovery rate was calculated to correct for multiple hypothesis testing. Signatures based on genes involved in genome instability and invasion reached significance in most individual cancer types. Thyroid and glioblastoma were independent of hallmark genes (61 and 54 genes significant, respectively), while renal clear cell cancer and low grade gliomas harbored the most prognostic changes (403 and 419 genes significant, respectively). The eight genes with the highest significance included BRCA1 (genome instability,…

Methods to repair bone defects arising from trauma, resection, or disease, continue to be sought after. Cyclic mechanical loading is well established to influence bone (re)modelling activity, in which bone formation and resorption are correlated to micro-scale strain. Based on this, the application of mechanical stimulation across a bone defect could improve healing. However, if ignoring the mechanical integrity of defected bone, loading regimes have a high potential to either cause damage or be ineffective. This study explores real-time finite element (rtFE) methods that use three-dimensional structural analyses from micro-computed tomography images to estimate effective peak cyclic loads in a subject-specific and time-dependent manner. It demonstrates the concept in a cyclically loaded mouse caudal vertebral bone defect model. Using rtFE analysis combined with adaptive mechanical loading, mouse bone healing was significantly improved over non-loaded controls, with no incidence of vertebral fractures. Such rtFE-driven adaptive loading regimes demonstrated here could be relevant to…

Most current Alzheimer's disease (AD) and mild cognitive disorders (MCI) studies use single data modality to make predictions such as AD stages. The fusion of multiple data modalities can provide a holistic view of AD staging analysis. Thus, we use deep learning (DL) to integrally analyze imaging (magnetic resonance imaging (MRI)), genetic (single nucleotide polymorphisms (SNPs)), and clinical test data to classify patients into AD, MCI, and controls (CN). We use stacked denoising auto-encoders to extract features from clinical and genetic data, and use 3D-convolutional neural networks (CNNs) for imaging data. We also develop a novel data interpretation method to identify top-performing features learned by the deep-models with clustering and perturbation analysis. Using Alzheimer's disease neuroimaging initiative (ADNI) dataset, we demonstrate that deep models outperform shallow models, including support vector machines, decision trees, random forests, and k-nearest neighbors. In addition, we demonstrate that integrating multi-modality data outperforms single modality models in…

Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. Public attention towards NFTs has exploded in 2021, when their market has experienced record sales, but little is known about the overall structure and evolution of its market. Here, we analyse data concerning 6.1 million trades of 4.7 million NFTs between June 23, 2017 and April 27, 2021, obtained primarily from Ethereum and WAX blockchains. First, we characterize statistical properties of the market. Second, we build the network of interactions, show that traders typically specialize on NFTs associated with similar objects and form tight clusters with other traders that exchange the same kind of objects. Third, we cluster objects associated to NFTs according to their visual features and show that collections contain visually homogeneous objects. Finally, we investigate the predictability of NFT sales using simple machine learning algorithms and find that…

To provide a contemporary global prevalence of mental health issues among the general population amid the coronavirus disease-2019 (COVID-19) pandemic. We searched electronic databases, preprint databases, grey literature, and unpublished studies from January 1, 2020, to June 16, 2020 (updated on July 11, 2020), with no language restrictions. Observational studies using validated measurement tools and reporting data on mental health issues among the general population were screened to identify all relevant studies. We have included information from 32 different countries and 398,771 participants. The pooled prevalence of mental health issues amid the COVID-19 pandemic varied widely across countries and regions and was higher than previous reports before the COVID-19 outbreak began. The global prevalence estimate was 28.0% for depression; 26.9% for anxiety; 24.1% for post-traumatic stress symptoms; 36.5% for stress; 50.0% for psychological distress; and 27.6% for sleep problems. Data are limited for other aspects of mental health issues. Our findings highlight the disparities between…

Chemical state analysis in X-ray photoelectron spectroscopy (XPS) relies on assigning well-defined binding energy values to core level electrons originating from atoms in particular bonding configurations. Here, we present direct evidence for the violation of this paradigm. It is shown that the C 1s peak due to C-C/C-H bonded atoms from adventitious carbon (AdC) layers accumulating on Al and Au foils splits into two distinctly different contributions, as a result of vacuum level alignment at the AdC/foil interface. The phenomenon is observed while simultaneously recording the spectrum from two metal foils in electric contact with each other. This finding exposes fundamental problems with the reliability of reported XPS data as C 1s peak of AdC is routinely used for binding energy scale referencing. The use of adventitious carbon in XPS should thus be discontinued as it leads to nonsense results. Consequently, ISO and ASTM charge referencing guides need to be rewritten.

Brain tumor localization and segmentation from magnetic resonance imaging (MRI) are hard and important tasks for several applications in the field of medical analysis. As each brain imaging modality gives unique and key details related to each part of the tumor, many recent approaches used four modalities T1, T1c, T2, and FLAIR. Although many of them obtained a promising segmentation result on the BRATS 2018 dataset, they suffer from a complex structure that needs more time to train and test. So, in this paper, to obtain a flexible and effective brain tumor segmentation system, first, we propose a preprocessing approach to work only on a small part of the image rather than the whole part of the image. This method leads to a decrease in computing time and overcomes the overfitting problems in a Cascade Deep Learning model. In the second step, as we are dealing with a smaller part of brain images in each slice, a simple and efficient Cascade Convolutional Neural Network (C-ConvNet/C-CNN) is proposed. This C-CNN model mines both local and global features in two different routes. Also,…

In this paper we compared taxonomic results obtained by metataxonomics (16S rRNA gene sequencing) and metagenomics (whole shotgun metagenomic sequencing) to investigate their reliability for bacteria profiling, studying the chicken gut as a model system. The experimental conditions included two compartments of gastrointestinal tracts and two sampling times. We compared the relative abundance distributions obtained with the two sequencing strategies and then tested their capability to distinguish the experimental conditions. The results showed that 16S rRNA gene sequencing detects only part of the gut microbiota community revealed by shotgun sequencing. Specifically, when a sufficient number of reads is available, Shotgun sequencing has more power to identify less abundant taxa than 16S sequencing. Finally, we showed that the less abundant genera detected only by shotgun sequencing are biologically meaningful, being able to discriminate between the experimental conditions as much as the more abundant genera detected by both sequencing strategies.

Executive functions demonstrate variable developmental and aging profiles, with protracted development into early adulthood and declines in older age. However, relatively few studies have specifically included middle-aged adults in investigations of age-related differences in executive functions. This study explored the age-related differences in executive function from late childhood through to old age, allowing a more informed understanding of executive functions across the lifespan. Three hundred and fifty participants aged 10 to 86 years-old completed a battery of tasks assessing the specific roles of inhibitory control, working memory, cognitive flexibility, and planning. Results highlighted continued improvement in working memory capacity across adolescence and into young adulthood, followed by declines in both working memory and inhibitory control, beginning from as early as 30-40 years old and continuing into older age. Analyses of planning abilities showed continued improvement across adolescence and into young adulthood, followed by a decline in abilities across adulthood,…

Abstract Due to urbanization and industrialization, there has been an increase in solid waste generation and has become a global concern and leakage of leachate from landfills contaminate the soil and groundwater and hence can have a severe impact on human health. The present study aimed to determine the composition of toxic metals (Cr, Mn, Cu, As) and heavy metals (Cd, Ba, Hg, Pb) in soil and water by an inductively coupled plasma optical emission spectrometer (ICP-OES). To ensure accuracy during the analysis of Cr, Mn, Cu, As, Cd, Ba, Hg, and Pb in real samples, certified reference material (CRM, SRM 2709a) of San Joaquin soil and water (SRM 1640a) were analyzed and results were presented in terms of % recovery studies. The mean concentration of all the metals in soil and water did not exceed the limit set by the European Community (EU), WHO, and US EPA except Cu where the permissible limit defined by the EU is 50–140 mg/kg in soil. The soil is uncontaminated to moderately contaminated with respect to all metals except the Cu and Pb. Among the average daily dose (ADD) of soil, ADD…

This research was set out to explore the development of arrowroot starch (AS) films using glycerol (G) as plasticizer at the ratio of 15, 30, and 45% (w/w, starch basis) using solution casting technique. The developed films were analyzed in terms of physical, structural, mechanical, thermal, environmental, and barrier properties. The incorporation of glycerol to AS film-making solution reduced the brittleness and fragility of films. An increment in glycerol concentration caused an increment in film thickness, moisture content, and solubility in water, whereas density and water absorption were reduced. The tensile strength and modulus of G-plasticized AS films were reduced significantly from 9.34 to 1.95 MPa and 620.79 to 36.08 MPa, respectively, while elongation at break was enhanced from 2.41 to 57.33%. FTIR analysis revealed that intermolecular hydrogen bonding occurred between glycerol and AS in plasticized films compared to control films. The G-plasticized films showed higher thermal stability than control films. The cross-sectional micrographs revealed that the films containing…

Living near, recreating in, and feeling psychologically connected to, the natural world are all associated with better mental health, but many exposure-related questions remain. Using data from an 18-country survey (n = 16,307) we explored associations between multiple measures of mental health (positive well-being, mental distress, depression/anxiety medication use) and: (a) exposures (residential/recreational visits) to different natural settings (green/inland-blue/coastal-blue spaces); and (b) nature connectedness, across season and country. People who lived in greener/coastal neighbourhoods reported higher positive well-being, but this association largely disappeared when recreational visits were controlled for. Frequency of recreational visits to green, inland-blue, and coastal-blue spaces in the last 4 weeks were all positively associated with positive well-being and negatively associated with mental distress. Associations with green space visits were relatively consistent across seasons and countries but associations with blue space visits showed greater heterogeneity. Nature…

This study investigates whether coupling crop modeling and machine learning (ML) improves corn yield predictions in the US Corn Belt. The main objectives are to explore whether a hybrid approach (crop modeling + ML) would result in better predictions, investigate which combinations of hybrid models provide the most accurate predictions, and determine the features from the crop modeling that are most effective to be integrated with ML for corn yield prediction. Five ML models (linear regression, LASSO, LightGBM, random forest, and XGBoost) and six ensemble models have been designed to address the research question. The results suggest that adding simulation crop model variables (APSIM) as input features to ML models can decrease yield prediction root mean squared error (RMSE) from 7 to 20%. Furthermore, we investigated partial inclusion of APSIM features in the ML prediction models and we found soil moisture related APSIM variables are most influential on the ML predictions followed by crop-related and phenology-related variables. Finally, based on feature importance measure, it has…

The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and…

Abstract The neutrophil-to-lymphocyte ratio (NLR) in peripheral blood reflects the balance between systemic inflammation and immunity and is emerging as a prognostic biomarker in many diseases, but its predictive role for mortality in the general population has not been investigated. We analyzed 1999–2014 National Health and Nutrition Examination Survey mortality-linked data, followed up until 2015. In participants aged > 30 with measurements of differential white blood cell counts, NLR was calculated and categorized into quartiles. Associations of increased NLR with overall or cause-specific mortality were assessed with Cox proportional hazard regression models, adjusted for potential confounders. Increased NLR was associated with overall mortality (hazard ratio [HR] 1.14, 95% confidence interval [CI] 1.10–1.17, per quartile NLR) and mortality due to heart disease (1.17, 1.06–1.29), chronic lower respiratory disease (1.24, 1.04–1.47), influenza/pneumonia (1.26, 1.03–1.54) and kidney disease (1.26, 1.03–1.54). NLR was associated with cancer mortality only in the first follow-up year…

Landslides are considered as one of the most devastating natural hazards in Iran, causing extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas can be used to plan for and mitigate the consequences of catastrophic landsliding events. Here, we developed a deep convolutional neural network (CNN-DNN) for mapping landslide susceptibility, and evaluated it on the Isfahan province, Iran, which has not previously been assessed on such a scale. The proposed model was trained and validated using training (80%) and testing (20%) datasets, each containing relevant data on historical landslides, field records and remote sensing images, and a range of geomorphological, geological, environmental and human activity factors as covariates. The CNN-DNN model prediction accuracy was tested using a wide range of statistics from the confusion matrix and error indices from the receiver operating characteristic (ROC) curve. The CNN-DNN model was evaluated comprehensively by comparing it to several state-of-the-art benchmark machine learning techniques including the…

Infection by the new corona virus strain SARS-CoV-2 and its related syndrome COVID-19 has been associated with more than two million deaths worldwide. Patients of higher age and with preexisting chronic health conditions are at an increased risk of fatal disease outcome. However, detailed information on causes of death and the contribution of pre-existing health conditions to death yet is missing, which can be reliably established by autopsy only. We performed full body autopsies on 26 patients that had died after SARS-CoV-2 infection and COVID-19 at the Charité University Hospital Berlin, Germany, or at associated teaching hospitals. We systematically evaluated causes of death and pre-existing health conditions. Additionally, clinical records and death certificates were evaluated. We report findings on causes of death and comorbidities of 26 decedents that had clinically presented with severe COVID-19. We found that septic shock and multi organ failure was the most common immediate cause of death, often due to suppurative pulmonary infection. Respiratory failure due to diffuse…

In recent years' synthesis of metal nanoparticle using plants has been extensively studied and recognized as a non-toxic and efficient method applicable in biomedical field. The aim of this study is to investigate the role of different parts of medical plant Carduus crispus on synthesizing silver nanoparticles and characterize the produced nanoparticle. Our study showed that silver nanoparticles (AgNP) synthesized via whole plant extract exhibited a blue shift in absorption spectra with increased optical density, which correlates to a high yield and small size. Also, the results of zeta potential, X-ray diffraction, photon cross-correlation spectroscopy analysis showed the surface charge of - 54.29 ± 4.96 mV (AgNP-S), - 42.64 ± 3.762 mV (AgNP-F), - 46.02 ± 4.17 mV (AgNP-W), the crystallite size of 36 nm (AgNP-S), 13 nm (AgNP-F), 14 nm (AgNP-W) with face-centered cubic structure and average grain sizes of 145.1 nm, 22.5 nm and 99.6 nm. Another important characteristic, such as elemental composition and constituent capping agent has been determined by energy-dispersive X-ray…

Abstract In this study, two biomass-based adsorbents were used as new precursors for optimizing synthesis conditions of a cost-effective powdered activated carbon (PAC). The PAC removed dyes from an aqueous solution using carbonization and activation by KOH, NaOH, and H 2 SO 4 . The optimum synthesis, activation temperature, time and impregnation ratio, removal rate, and uptake capacity were determined. The optimum PAC was analyzed and characterized using Fourier-transform infrared spectroscopy (FTIR), x-ray diffraction (XRD), a field emission scanning electron microscope (FESEM), Zeta potential, and Raman spectroscopy. Morphological studies showed single-layered planes with highly porous surfaces, especially PAC activated by NaOH and H 2 SO 4 . The results showed that the experimental data were well-fitted with a pseudo-second-order model. Based on Langmuir isotherm, the maximum adsorption capacity for removing methylene blue (MB) was 769.23 mg g −1 and 458.43 mg g −1 for congo red (CR). Based on the isotherm models, more than one mechanism was involved in the adsorption process,…

In the present study, we characterized the distinctive signatures of the gut microbiota (GM) from overweight/obese patients (OB), and normal-weight controls (NW), both of Sardinian origin. Fecal bacterial composition of 46 OB patients (BMI = 36.6 ± 6.0; F/M = 40/6) was analyzed and compared to that of 46 NW subjects (BMI = 21.6 ± 2.1; F/M = 41/5), matched for sex, age and smoking status, by using 16S rRNA gene sequencing on MiSeq Illumina platform. The gut microbial community of OB patients exhibited a significant decrease in the relative abundance of several Bacteroidetes taxa (i.e. Flavobacteriaceae, Porphyromonadaceae, Sphingobacteriaceae, Flavobacterium, Rikenella spp., Pedobacter spp., Parabacteroides spp., Bacteroides spp.) when compared to NW; instead, several Firmicutes taxa were significantly increased in the same subjects (Lachnospiraceae, Gemellaceae, Paenibacillaceae, Streptococcaceae, Thermicanaceae, Gemella, Mitsuokella, Streptococcus, Acidaminococcus spp., Eubacterium spp., Ruminococcus spp., Megamonas spp., Streptococcus, Thermicanus, Megasphaera spp. and Veillonella…

Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and progression detection have been intensively studied. Nevertheless, research studies often have little effect on clinical practice mainly due to the following reasons: (1) Most studies depend mainly on a single modality, especially neuroimaging; (2) diagnosis and progression detection are usually studied separately as two independent problems; and (3) current studies concentrate mainly on optimizing the performance of complex machine learning models, while disregarding their explainability. As a result, physicians struggle to interpret these models, and feel it is hard to trust them. In this paper, we carefully develop an accurate and interpretable AD diagnosis and progression detection model. This model provides physicians with accurate decisions along with a set of explanations for every decision. Specifically, the model integrates 11 modalities of 1048 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) real-world dataset: 294 cognitively normal, 254 stable mild cognitive impairment…

Abstract Drought refers to a meteorological disaster that causes insufficient soil moisture and damage to crop water balance due to long-term lack of precipitation. With the increasing shortage of water resources, drought has become one of the hot issues of global concern. The standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) can effectively reflect the changes in drought characteristics of different geomorphologies in Sichuan on time and space scales, to explore the difference in drought characteristics between different physiognomy types in Sichuan Province, We calculated the SPI and SPEI values based on the data of 44 meteorological stations in Sichuan Province from 1961 to 2019 and used Mann–Kendall trend test and multivariable linear regression method (MLR) to quantify the significance of the drought characteristic trends at different time and space scales. The results as follow: (1) The SPEI drought trend in plain and hilly regions was greater than that in plateau and mountain regions on all time scales (− 0.039 year−1 for…

Plants with medicinal properties play an increasingly important role in food and pharmaceutical industries for their functions on disease prevention and treatment. This study characterizes the phenolic composition and antioxidant activity of seven medicinal and food plants, including the leaves of Salvia officinalis L., Rosmarinus officinalis L., Olea europaea L., and Punica granatum L., as well as the leaves and young stems of Ruta graveolens L., Mentha piperita L., and Petroselinum crispum, Mill., by using colorimetric, chromatographic, and spectrophotometric assays. Results revealed that the hydro-methanolic leaf extracts of P. granatum (pomegranate) displayed the highest content of total phenols (199.26 mg gallic acid per gram of plant dry weight), ortho-diphenols (391.76 mg gallic acid per gram of plant dry weight), and tannins (99.20 mg epicatechin per gram of plant dry weight), besides a higher content of flavonoids (24 mg catechin per gram of plant dry weight). The highest antioxidant capacity measured by ABTS, DPPH, and FRAP (2.14, 2.27, and 2.33 mM Trolox per gram of plant…

Abstract Although the transition to renewable energies will intensify the global competition for land, the potential impacts driven by solar energy remain unexplored. In this work, the potential solar land requirements and related land use change emissions are computed for the EU, India, Japan and South Korea. A novel method is developed within an integrated assessment model which links socioeconomic, energy, land and climate systems. At 25–80% penetration in the electricity mix of those regions by 2050, we find that solar energy may occupy 0.5–5% of total land. The resulting land cover changes, including indirect effects, will likely cause a net release of carbon ranging from 0 to 50 gCO 2 /kWh, depending on the region, scale of expansion, solar technology efficiency and land management practices in solar parks. Hence, a coordinated planning and regulation of new solar energy infrastructures should be enforced to avoid a significant increase in their life cycle emissions through terrestrial carbon losses.

Primary open-angle glaucoma (POAG) is a leading cause of irreversible blindness in the world and is influenced by various sociodemographic factors. This meta-analysis aims to determine the worldwide prevalence of POAG in the adult general population for the last 20 years, and explore variation in prevalence by age, gender and geographical location. An electronic literature search was performed using the PubMed, Embase, and Web of Science databases. Population-based cross-sectional or cohort studies published in the last 20 years (2000-2020) that reported prevalence of POAG were recruited. Relevant studies meeting defined eligibility criteria were selected and reviewed systematically by meta-analysis. The prevalence of POAG was analyzed according to various risk factors. A random effect model was used for the meta-analysis. Fifty publications with a total of 198,259 subjects were included in this meta-analysis. The worldwide overall prevalence of POAG was 2.4% (95% CI 2.0 ~ 2.8%). The prevalence increases with age. Men are found to be more susceptible to POAG than women (RR 1.28, p <…

COVID-19 prevention behaviors may be seen as self-interested or prosocial. Using American samples from MTurk and Prolific (total n = 6850), we investigated which framing is more effective-and motivation is stronger-for fostering prevention behavior intentions. We evaluated messaging that emphasized personal, public, or personal and public benefits of prevention. In initial studies (conducted March 14-16, 2020), the Public treatment was more effective than the Personal treatment, and no less effective than the Personal + Public treatment. In additional studies (conducted April 17-30, 2020), all three treatments were similarly effective. Across all these studies, the perceived public threat of coronavirus was also more strongly associated with prevention intentions than the perceived personal threat. Furthermore, people who behaved prosocially in incentivized economic games years before the pandemic had greater prevention intentions. Finally, in a field experiment (conducted December 21-23, 2020), we used our three messaging strategies to motivate contact-tracing app signups (n =…

Abstract Manure application to agricultural soils is widely considered as a source of nutrients and a method of maintaining levels of soil organic carbon (SOC) to mitigate climate change. At present, it is still unclear which factors are responsible for the SOC stock dynamics. Therefore, we analyzed the relationship between SOC stock changes and site characteristics, soil properties, experiment characteristics and manure characteristics. Overall, we included 101 studies with a total of 592 treatments. On average, the application of manure on agricultural soils increased SOC stocks by 35.4%, corresponding to 10.7 Mg ha −1 . Manure applications in conventional tillage systems led to higher SOC stocks (+ 2.2 Mg ha −1 ) than applications under reduced tillage. Soil organic carbon increase upon manure application was higher in soils under non-tropical climate conditions (+ 2.7 Mg ha −1 ) compared to soils under sub-tropical climate. Larger SOC increases after manure application were achieved in intermediate and shallow topsoils (in 0–15 cm by 9.5 Mg ha −1 and in 16–20 cm by 13.6 Mg ha −1…

Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in oncology. Recently, several machine learning (ML) techniques have been adapted for this task. Although they have shown to yield results at least as good as classical methods, they are often disregarded because of their lack of transparency and little to no explainability, which are key for their adoption in clinical settings. In this paper, we used data from the Netherlands Cancer Registry of 36,658 non-metastatic breast cancer patients to compare the performance of CPH with ML techniques (Random Survival Forests, Survival Support Vector Machines, and Extreme Gradient Boosting [XGB]) in predicting survival using the [Formula: see text]-index. We demonstrated that in our dataset, ML-based models can perform at least as good as the classical CPH regression ([Formula: see text]-index [Formula: see text]), and in the case of XGB even better ([Formula: see text]-index [Formula: see text]). Furthermore, we used Shapley Additive Explanation (SHAP) values to explain the models' predictions. We concluded that…

Abstract Photoexcited lead-free perovskite CH 3 NH 3 SnI 3 based solar cell device was simulated using a solar cell capacitance simulator. It was modeled to investigate its output characteristics under AM 1.5G illumination. Simulation efforts are focused on the thickness, acceptor concentration and defect density of absorber layer on photovoltaic properties of solar cell device. In addition, the impact of various metal contact work function was also investigated. The simulation results indicate that an absorber thickness of 500 nm is appropriate for a good photovoltaic cell. Oxidation of Sn 2+ into Sn 4+ was considered and it is found that the reduction of acceptor concentration of absorber layer significantly improves the device performance. Further, optimizing the defect density (10 14 cm −3 ) of the perovskite absorber layer, encouraging results of the J sc of 40.14 mA/cm 2 , V oc of 0.93 V, FF of 75.78% and PCE of 28.39% were achieved. Finally, an anode material with a high work function is necessary to get the device's better performance. The high-power conversion efficiency…

Susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the risk of mortality among people living with human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) (PLWHA) is largely unknown. PLWHA are unique due to their altered immune system from their history of chronic HIV infection and their use of antiretroviral therapy, some of which have been used experimentally to treat coronavirus disease 2019 (COVID-19). Therefore, we conducted a systematic review and meta-analysis to assess the epidemiology of SARS-COV-2/HIV coinfection and estimate associated mortality from COVID-19 (Prospero Registration ID: CRD42020187980). PubMed, SCOPUS, OVID and Cochrane Library databases, and medRxiv preprint repositories were searched from January 1, 2020, to December 12, 2020. Data were extracted from studies reporting COVID-19 attack and mortality rates in PLWHA compared to their HIV-negative counterparts. Pooled attack and mortality risks were quantified using random-effects models. We identified 22 studies that included 20,982,498…

Abstract The potential virucidal effects of UV-C irradiation on SARS-CoV-2 were experimentally evaluated for different illumination doses and virus concentrations (1000, 5, 0.05 MOI). At a virus density comparable to that observed in SARS-CoV-2 infection, an UV-C dose of just 3.7 mJ/cm 2 was sufficient to achieve a more than 3-log inactivation without any sign of viral replication. Moreover, a complete inactivation at all viral concentrations was observed with 16.9 mJ/cm 2 . These results could explain the epidemiological trends of COVID-19 and are important for the development of novel sterilizing methods to contain SARS-CoV-2 infection.

ERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts, replacing ERA-Interim as the next generation of representative satellite-observational data on the global scale. ERA5 data have been evaluated and applied in different regions, but the performances are inconsistent. Meanwhile, there are few precise evaluations of ERA5 precipitation data over long time series have been performed in Chinese mainland. This study evaluates the temporal-spatial performance of ERA5 precipitation data from 1979 to 2018 based on gridded-ground meteorological station observational data across China. The results showed that ERA5 data could capture the annual and seasonal patterns of observed precipitation in China well, with correlation coefficient values ranging from 0.796 to 0.945, but ERA5 slightly overestimated precipitation in the summer. Nonetheless, the results also showed that the accuracy of the precipitation products was strongly correlated with topographic distribution and climatic divisions. The performance of ERA5…

All women undergo the menopause transition (MT), a neuro-endocrinological process that impacts aging trajectories of multiple organ systems including brain. The MT occurs over time and is characterized by clinically defined stages with specific neurological symptoms. Yet, little is known of how this process impacts the human brain. This multi-modality neuroimaging study indicates substantial differences in brain structure, connectivity, and energy metabolism across MT stages (pre-menopause, peri-menopause, and post-menopause). These effects involved brain regions subserving higher-order cognitive processes and were specific to menopausal endocrine aging rather than chronological aging, as determined by comparison to age-matched males. Brain biomarkers largely stabilized post-menopause, and gray matter volume (GMV) recovered in key brain regions for cognitive aging. Notably, GMV recovery and in vivo brain mitochondria ATP production correlated with preservation of cognitive performance post-menopause, suggesting adaptive compensatory processes. In parallel to the adaptive process,…

Understanding the mortality impact of COVID-19 requires not only counting the dead, but analyzing how premature the deaths are. We calculate years of life lost (YLL) across 81 countries due to COVID-19 attributable deaths, and also conduct an analysis based on estimated excess deaths. We find that over 20.5 million years of life have been lost to COVID-19 globally. As of January 6, 2021, YLL in heavily affected countries are 2-9 times the average seasonal influenza; three quarters of the YLL result from deaths in ages below 75 and almost a third from deaths below 55; and men have lost 45% more life years than women. The results confirm the large mortality impact of COVID-19 among the elderly. They also call for heightened awareness in devising policies that protect vulnerable demographics losing the largest number of life-years.

Various non-pharmaceutical interventions were adopted by countries worldwide in the fight against the COVID-19 pandemic with adverse socioeconomic side effects, which raises the question about their differential effectiveness. We estimate the average dynamic effect of each intervention on the incidence of COVID-19 and on people's whereabouts by developing a statistical model that accounts for the contemporaneous adoption of multiple interventions. Using daily data from 175 countries, we show that, even after controlling for other concurrent lockdown policies, cancelling public events, imposing restrictions on private gatherings and closing schools and workplaces had significant effects on reducing COVID-19 infections. Restrictions on internal movement and public transport had no effects because the aforementioned policies, imposed earlier on average, had already de facto reduced human mobility. International travel restrictions, although imposed early, had a short-lived effect failing to prevent the epidemic from turning into a pandemic because they were less stringent. We interpret…

Detection of plastic debris degrading into micro particles across all oceanic environments and inside of marine organisms is no longer surprising news. Microplastic contamination now appears as one of the world's environmental main concerns. To determine the levels of microplastic pollution at sea, water samples were collected across a 4000 km-trajectory in the Tropical Eastern Pacific and the Galápagos archipelago, covering an area of 453,000 square kilometres. Furthermore, 240 specimens of 16 different species of fish, squid, and shrimp, all of human consumption, were collected along the continental coast. Microplastic particles were found in 100% of the water samples and marine organisms. Microplastic particles ranging from 150 to 500 µm in size were the most predominant. This is one of the first reports simultaneously detecting and quantifying microplastic particles abundance and their impact on marine organisms of this region.

Soil property and class maps for the continent of Africa were so far only available at very generalised scales, with many countries not mapped at all. Thanks to an increasing quantity and availability of soil samples collected at field point locations by various government and/or NGO funded projects, it is now possible to produce detailed pan-African maps of soil nutrients, including micro-nutrients at fine spatial resolutions. In this paper we describe production of a 30 m resolution Soil Information System of the African continent using, to date, the most comprehensive compilation of soil samples ([Formula: see text]) and Earth Observation data. We produced predictions for soil pH, organic carbon (C) and total nitrogen (N), total carbon, effective Cation Exchange Capacity (eCEC), extractable-phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), zinc (Zn)-silt, clay and sand, stone content, bulk density and depth to bedrock, at three depths (0, 20 and 50 cm) and using 2-scale 3D Ensemble Machine Learning framework implemented in the mlr…

Microplastics are contaminants of emerging concern; they are ingested by marine biota. About a quarter of global marine fish landings is used to produce fishmeal for animal and aquaculture feed. To provide a knowledge foundation for this matrix we reviewed the existing literature for studies of microplastics in fishmeal-relevant species. 55% of studies were deemed unsuitable due to focus on large microplastics (> 1 mm), lack of, or limited contamination control and polymer testing techniques. Overall, fishmeal-relevant species exhibit 0.72 microplastics/individual, with studies generally only assessing digestive organs. We validated a density separation method for effectiveness of microplastic extraction from this medium and assessed two commercial products for microplastics. Recovery rates of a range of dosed microplastics from whitefish fishmeal samples were 71.3 ± 1.2%. Commercial samples contained 123.9 ± 16.5 microplastics per kg of fishmeal-mainly polyethylene-including 52.0 ± 14.0 microfibres-mainly rayon. Concentrations in processed fishmeal seem higher than in captured…

X-linked inhibitor of apoptosis protein (XIAP) is a member of inhibitor of apoptosis protein (IAP) family responsible for neutralizing the caspases-3, caspases-7, and caspases-9. Overexpression of the protein decreased the apoptosis process in the cell and resulting development of cancer. Different types of XIAP antagonists are generally used to repair the defective apoptosis process that can eliminate carcinoma from living bodies. The chemically synthesis compounds discovered till now as XIAP inhibitors exhibiting side effects, which is making difficulties during the treatment of chemotherapy. So, the study has design to identifying new natural compounds that are able to induce apoptosis by freeing up caspases and will be low toxic. To identify natural compound, a structure-based pharmacophore model to the protein active site cavity was generated following by virtual screening, molecular docking and molecular dynamics (MD) simulation. Initially, seven hit compounds were retrieved and based on molecular docking approach four compounds has chosen for further evaluation. To confirm…

Abstract The present study is to design an eco-friendly mode to rapidly synthesize selenium nanoparticles (SeNPs) through Ceropegia bulbosa tuber’s aqueous extracts and confirming SeNPs synthesis by UV–Vis spectroscopy, FT-IR, XRD, FE-SEM-EDS mapping, HR-TEM, DLS and zeta potential analysis. In addition, to assess the anti-cancer efficacy of the SeNPs against the cultured MDA-MB-231, as studies have shown SeNPs biosynthesis downregulates the cancer cells when compared to normal HBL100 cell lines. The study observed the IC 50 value of SeNPs against MDA-MB-231 cells was 34 µg/mL for 48 h. Furthermore, the SeNPs promotes growth inhibitory effects of certain clinical pathogens such as Bacillus subtilis and Escherichia coli . Apart, from this the SeNPs has shown larvicidal activity after 24 h exposure in Aedes albopitus mosquito’s larvae with a maximum of 250 g/mL mortality concentration. This is confirmed by the histopathology results taken at the 4th larval stage. The histopathological studies revealed intense deterioration in the hindgut, epithelial cells, mid gut and cortex region of…

Abstract Periodontal disease has been reported to be associated with diabetes mellitus. However, the direction of the association and the influence of bias are not clear. Thus, the aim of this systematic review and meta-analysis was to summarize the existing evidence on the bidirectional prospective association between periodontal disease and diabetes mellitus by accounting for the risk of bias of the original studies. The literature search was conducted on the electronic data sources PubMed and Web of Science up to February 9th, 2021. We included observational studies, which investigated the prospective association between diabetes mellitus and periodontal disease or vice versa. The risk of bias of the primary studies was evaluated by applying the Quality in Prognosis Studies (QUIPS) tool. Random effects models were used to calculate summary relative risk (SRR) with 95% CI. Subgroup analyses were applied to investigate heterogeneity and the robustness of the finding. In total, 15 studies were included . The SRR for incident diabetes mellitus was 1.26 (95% CI 1.12, 1.41; I 2 : 71%,…

Abstract Streamflow ( Q flow ) prediction is one of the essential steps for the reliable and robust water resources planning and management. It is highly vital for hydropower operation, agricultural planning, and flood control. In this study, the convolution neural network (CNN) and Long-Short-term Memory network (LSTM) are combined to make a new integrated model called CNN-LSTM to predict the hourly Q flow (short-term) at Brisbane River and Teewah Creek, Australia. The CNN layers were used to extract the features of Q flow time-series, while the LSTM networks use these features from CNN for Q flow time series prediction. The proposed CNN-LSTM model is benchmarked against the standalone model CNN, LSTM, and Deep Neural Network models and several conventional artificial intelligence (AI) models. Q flow prediction is conducted for different time intervals with the length of 1-Week, 2-Weeks, 4-Weeks, and 9-Months, respectively. With the help of different performance metrics and graphical analysis visualization, the experimental results reveal that with small residual error between the…

Fruit detection forms a vital part of the robotic harvesting platform. However, uneven environment conditions, such as branch and leaf occlusion, illumination variation, clusters of tomatoes, shading, and so on, have made fruit detection very challenging. In order to solve these problems, a modified YOLOv3 model called YOLO-Tomato models were adopted to detect tomatoes in complex environmental conditions. With the application of label what you see approach, densely architecture incorporation, spatial pyramid pooling and Mish function activation to the modified YOLOv3 model, the YOLO-Tomato models: YOLO-Tomato-A at AP 98.3% with detection time 48 ms, YOLO-Tomato-B at AP 99.3% with detection time 44 ms, and YOLO-Tomato-C at AP 99.5% with detection time 52 ms, performed better than other state-of-the-art methods.

Underground hydrogen storage (UHS) in initially brine-saturated deep porous rocks is a promising large-scale energy storage technology, due to hydrogen's high specific energy capacity and the high volumetric capacity of aquifers. Appropriate selection of a feasible and safe storage site vitally depends on understanding hydrogen transport characteristics in the subsurface. Unfortunately there exist no robust experimental analyses in the literature to properly characterise this complex process. As such, in this work, we present a systematic pore-scale modelling study to quantify the crucial reservoir-scale functions of relative permeability and capillary pressure and their dependencies on fluid and reservoir rock conditions. To conduct a conclusive study, in the absence of sufficient experimental data, a rigorous sensitivity analysis has been performed to quantify the impacts of uncertain fluid and rock properties on these upscaled functions. The parameters are varied around a base-case, which is obtained through matching to the existing experimental study. Moreover, cyclic hysteretic…

The effects of cadmium stress on the growth and physiological characteristics of Sassafras tzumu Hemsl. were studied in pot experiments. Five Cd levels were tested [CT(Control Treatment) : 0 mg/kg, Cd5: 5 mg/kg, Cd20: 20 mg/kg, Cd50: 50 mg/kg, and Cd100: 100 mg/kg]. The growth and physiological characteristics of the sassafras seedlings in each level were measured. The results showed that soil Cd had negative influences on sassafras growth and reduced the net growth of plant height and the biomass of leaf, branch and root. Significant reductions were recorded in root biomass by 18.18%(Cd5), 27.35%(Cd20), 27.57%(Cd50) and 28.95%(Cd100). The contents of hydrogen peroxide decreased first then increased while malondialdehyde showed the opposite trend with increasing cadmium concentration. Decreases were found in hydrogen peroxide contents by 10.96%(Cd5), 11.82%(Cd20) and 7.02%(Cd50); increases were found in malondialdehyde contents by 15.47%(Cd5), 16.07%(Cd20) and 7.85%(Cd50), indicating that cadmium stress had a certain effect on the peroxidation of the inner cell membranes in the…

Several comorbidities have been shown to be associated with coronavirus disease 2019 (COVID-19) related severity and mortality. However, considerable variation in the prevalence estimates of comorbidities and their effects on COVID-19 morbidity and mortality have been observed in prior studies. This systematic review and meta-analysis aimed to determine geographical, age, and gender related differences in the prevalence of comorbidities and associated severity and mortality rates among COVID-19 patients. We conducted a search using PubMed, Scopus, and EMBASE to include all COVID-19 studies published between January 1st, 2020 to July 24th, 2020 reporting comorbidities with severity or mortality. We included studies reporting the confirmed diagnosis of COVID-19 on human patients that also provided information on comorbidities or disease outcomes. We used DerSimonian and Laird random effects method for calculating estimates. Of 120 studies with 125,446 patients, the most prevalent comorbidity was hypertension (32%), obesity (25%), diabetes (18%), and cardiovascular disease (16%) while…

Dealing with a COVID-19 lockdown may have negative effects on children, but at the same time might facilitate parent-child bonding. Perceived stress may influence the direction of these effects. Using a longitudinal twin design, we investigated how perceived stress influenced lockdown induced changes in wellbeing of parents and children. A total of 106 parents and 151 children (10-13-year-olds) filled in questionnaires during lockdown and data were combined with data of previous years. We report a significant increase in parental negative feelings (anxiety, depression, hostility and interpersonal sensitivity). Longitudinal child measures showed a gradual decrease in internalizing and externalizing behavior, which seemed decelerated by the COVID-19 lockdown. Changes in parental negative feelings and children's externalizing behavior were mediated by perceived stress: higher scores prior to the lockdown were related to more stress during the lockdown, which in turn was associated with an increase in parental negative feelings and children's' externalizing behavior. Perceived stress in…

Abstract The fusion power density produced in a tokamak is proportional to its magnetic field strength to the fourth power. Second-generation high temperature superconductor (2G HTS) wires demonstrate remarkable engineering current density (averaged over the full wire), J E , at very high magnetic fields, driving progress in fusion and other applications. The key challenge for HTS wires has been to offer an acceptable combination of high and consistent superconducting performance in high magnetic fields, high volume supply, and low price. Here we report a very high and reproducible J E in practical HTS wires based on a simple YBa 2 Cu 3 O 7 (YBCO) superconductor formulation with Y 2 O 3 nanoparticles, which have been delivered in just nine months to a commercial fusion customer in the largest-volume order the HTS industry has seen to date. We demonstrate a novel YBCO superconductor formulation without the c -axis correlated nano-columnar defects that are widely believed to be prerequisite for high in-field performance. The simplicity of this new formulation allows robust and…

In recent days, study of topological Weyl semimetals have become an active branch of physics and materials science because they led to realization of the Weyl fermions and exhibited protected Fermi arc surface states. Therefore, topological Weyl semimetals TaX (X = P, As) are important electronic systems to investigate both from the point of view of fundamental physics and potential applications. In this work, we have studied the structural, elastic, mechanical, electronic, bonding, acoustic, thermal and optical properties of TaX (X = P, As) in detail via first-principles method using the density functional theory. A comprehensive study of elastic constants and moduli shows that both TaP and TaAs possesses low to medium level of elastic anisotropy (depending on the measure), reasonably good machinability, mixed bonding characteristics with ionic and covalent contributions, brittle nature and relatively high Vickers hardness with a low Debye temperature and melting temperature. The minimum thermal conductivities and anisotropies of TaX (X = P, As) are calculated. Bond population…

The COVID-19 pandemic and its social and economic consequences have had adverse impacts on physical and mental health worldwide and exposed all segments of the population to protracted uncertainty and daily disruptions. The CoRonavIruS health and Impact Survey (CRISIS) was developed for use as an easy to implement and robust questionnaire covering key domains relevant to mental distress and resilience during the pandemic. In the current work, we demonstrate the feasibility, psychometric structure and construct validity of this survey. We then show that pre-existing mood states, perceived COVID risk, and lifestyle changes are strongly associated with negative mood states during the pandemic in population samples of adults and in parents reporting on their children in the US and UK. Ongoing studies using CRISIS include international studies of COVID-related ill health conducted during different phases of the pandemic and follow-up studies of cohorts characterized before the COVID pandemic.

Artificial intelligence technology has advanced rapidly in recent years and has the potential to improve healthcare outcomes. However, technology uptake will be largely driven by clinicians, and there is a paucity of data regarding the attitude that clinicians have to this new technology. In June-August 2019 we conducted an online survey of fellows and trainees of three specialty colleges (ophthalmology, radiology/radiation oncology, dermatology) in Australia and New Zealand on artificial intelligence. There were 632 complete responses (n = 305, 230, and 97, respectively), equating to a response rate of 20.4%, 5.1%, and 13.2% for the above colleges, respectively. The majority (n = 449, 71.0%) believed artificial intelligence would improve their field of medicine, and that medical workforce needs would be impacted by the technology within the next decade (n = 542, 85.8%). Improved disease screening and streamlining of monotonous tasks were identified as key benefits of artificial intelligence. The divestment of healthcare to technology companies and medical liability implications…

Traditionally, topographic surveying in earth sciences requires high financial investments, elaborate logistics, complicated training of staff and extensive data processing. Recently, off-the-shelf drones with optical sensors already reduced the costs for obtaining a high-resolution dataset of an Earth surface considerably. Nevertheless, costs and complexity associated with topographic surveying are still high. In 2020, Apple Inc. released the iPad Pro 2020 and the iPhone 12 Pro with novel build-in LiDAR sensors. Here we investigate the basic technical capabilities of the LiDAR sensors and we test the application at a coastal cliff in Denmark. The results are compared to state-of-the-art Structure from Motion Multi-View Stereo (SfM MVS) point clouds. The LiDAR sensors create accurate high-resolution models of small objects with a side length > 10 cm with an absolute accuracy of ± 1 cm. 3D models with the dimensions of up to 130 × 15 × 10 m of a coastal cliff with an absolute accuracy of ± 10 cm are compiled. Overall, the versatility in handling outweighs the range limitations,…

Recently, a new two-dimensional allotrope of carbon (biphenylene) was experimentally synthesized. Using first-principles calculations, we systematically investigated the structural, mechanical, electronic, and HER properties of biphenylene. A large cohesive energy, absence of imaginary phonon frequencies, and an ultrahigh melting point up to 4500 K demonstrate its high stability. Biphenylene exhibits a maximum Young's modulus of 259.7 N/m, manifesting its robust mechanical performance. Furthermore, biphenylene was found to be metallic with a n-type Dirac cone, and it exhibited improved HER performance over that of graphene. Our findings suggest that biphenylene is a promising material with potential applications in many important fields, such as chemical catalysis.

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the social, financial and political entities around the world. Without an existing effective medical therapy, vaccines are urgently needed to avoid the spread of this disease. In this study, we propose an in silico deep learning approach for prediction and design of a multi-epitope vaccine (DeepVacPred). By combining the in silico immunoinformatics and deep neural network strategies, the DeepVacPred computational framework directly predicts 26 potential vaccine subunits from the available SARS-CoV-2 spike protein sequence. We further use in silico methods to investigate the linear B-cell epitopes, Cytotoxic T Lymphocytes (CTL) epitopes, Helper T Lymphocytes (HTL) epitopes in the 26 subunit candidates and identify the best 11 of them to construct a multi-epitope vaccine for SARS-CoV-2 virus. The human population coverage, antigenicity, allergenicity, toxicity, physicochemical properties and secondary structure of the designed vaccine are…

Abstract This investigation is carried out to understand the effects of water absorption on the mechanical properties of hybrid phenol formaldehyde (PF) composite fabricated with Areca Fine Fibres (AFFs) and Calotropis Gigantea Fibre (CGF). Hybrid CGF/AFF/PF composites were manufactured using the hand layup technique at varying weight percentages of fibre reinforcement (25, 35 and 45%). Hybrid composite having 35 wt.% showed better mechanical properties (tensile strength ca. 59 MPa, flexural strength ca. 73 MPa and impact strength 1.43 kJ/m 2 ) under wet and dry conditions as compared to the other hybrid composites. In general, the inclusion of the fibres enhanced the mechanical properties of neat PF. Increase in the fibre content increased the water absorption, however, after 120 h of immersion, all the composites attained an equilibrium state.

Abstract Ascorbic acid is among the most abundant antioxidants in the lung, where it likely plays a key role in the mechanism by which particulate air pollution initiates a biological response. Because ascorbic acid is a highly redox active species, it engages in a far more complex web of reactions than a typical organic molecule, reacting with oxidants such as the hydroxyl radical as well as redox-active transition metals such as iron and copper. The literature provides a solid outline for this chemistry, but there are large disagreements about mechanisms, stoichiometries and reaction rates, particularly for the transition metal reactions. Here we synthesize the literature, develop a chemical kinetics model, and use seven sets of laboratory measurements to constrain mechanisms for the iron and copper reactions and derive key rate constants. We find that micromolar concentrations of iron(III) and copper(II) are more important sinks for ascorbic acid (both AH2and AH−) than reactive oxygen species. The iron and copper reactions are catalytic rather than redox reactions, and have unit…

Abstract The age of precision medicine demands powerful computational techniques to handle high-dimensional patient data. We present MultiSurv, a multimodal deep learning method for long-term pan-cancer survival prediction. MultiSurv uses dedicated submodels to establish feature representations of clinical, imaging, and different high-dimensional omics data modalities. A data fusion layer aggregates the multimodal representations, and a prediction submodel generates conditional survival probabilities for follow-up time intervals spanning several decades. MultiSurv is the first non-linear and non-proportional survival prediction method that leverages multimodal data. In addition, MultiSurv can handle missing data, including single values and complete data modalities. MultiSurv was applied to data from 33 different cancer types and yields accurate pan-cancer patient survival curves. A quantitative comparison with previous methods showed that Multisurv achieves the best results according to different time-dependent metrics. We also generated visualizations of the learned multimodal…

Abstract Gold nanoparticles (AuNPs) are highlighted due to their low toxicity, compatibility with the human body, high surface area to volume ratio, and surfaces that can be easily modified with ligands. Biosynthesis of AuNPs using plant extract is considered a simple, low-cost, and eco-friendly approach. Brazilian Red Propolis (BRP), a product of bees, exhibits anti-inflammatory, anti-tumor, antioxidant, and antimicrobial activities. Here, we described the biosynthesis of AuNPs using BRP extract (AuNPextract) and its fractions (AuNPhexane, AuNPdichloromethane, AuNPethyl acetate) and evaluated their structural properties and their potential against microorganisms and cancer cells. AuNPs showed a surface plasmon resonance (SPR) band at 535 nm. The sizes and morphologies were influenced by the BRP sample used in the reaction. FTIR and TGA revealed the involvement of bioactive compounds from BRP extract or its fractions in the synthesis and stabilization of AuNPs. AuNPdichloromethaneand AuNPhexaneexhibited antimicrobial activities against all strains tested, showing their efficacy as…

Non-melanoma skin cancers (NMSCs) are the most common malignancies diagnosed in Caucasian populations. Basal cell carcinoma (BCC) is the most frequent skin cancer, followed by squamous cell carcinoma (SCC). Unfortunately, most European cancer registries do not record individual types of NMSC. To evaluate the incidence of primary BCCs and SCCs regarding age, sex, tumour site and tumour subtype to determine trends in epidemiology of both cancers. Retrospective analysis of BCCs and SCCs diagnosed and treated across seven sites in Poland from 1999 to 2019. We recorded 13,913 NMSCs occurring in 10,083 patients. BCC represented 85.2% of all cases. SCC patients were older than BCC patients (77.1 ± 11.3 years vs. 70.1 ± 12.3 years, p < 0.01). The nodular subtype was the most common subtype of BCC, followed by the superficial and infiltrative subtypes. The superficial BCC subtype was more common on photoprotected areas (p < 0.01), whereas the nodular BCC subtype occurred on the face (p < 0.01). The high-risk SCC subtypes were more common on face compared to low-risk SCC subtypes (p < 0.01).…

The identification and mapping of trees via remotely sensed data for application in forest management is an active area of research. Previously proposed methods using airborne and hyperspectral sensors can identify tree species with high accuracy but are costly and are thus unsuitable for small-scale forest managers. In this work, we constructed a machine vision system for tree identification and mapping using Red-Green-Blue (RGB) image taken by an unmanned aerial vehicle (UAV) and a convolutional neural network (CNN). In this system, we first calculated the slope from the three-dimensional model obtained by the UAV, and segmented the UAV RGB photograph of the forest into several tree crown objects automatically using colour and three-dimensional information and the slope model, and lastly applied object-based CNN classification for each crown image. This system succeeded in classifying seven tree classes, including several tree species with more than 90% accuracy. The guided gradient-weighted class activation mapping (Guided Grad-CAM) showed that the CNN classified trees according…

The novel coronavirus outbreak began in late December 2019 and rapidly spread worldwide, critically impacting public health systems. A number of already approved and marketed drugs are being tested for repurposing, including Favipiravir. We aim to investigate the efficacy and safety of Favipiravir in treatment of COVID-19 patients through a systematic review and meta-analysis. This systematic review and meta-analysis were reported in accordance with the PRISMA statement. We registered the protocol in the PROSPERO (CRD42020180032). All clinical trials which addressed the safety and efficacy of Favipiravir in comparison to other control groups for treatment of patients with confirmed infection with SARS-CoV2 were included. We searched electronic databases including LitCovid/PubMed, Scopus, Web of Sciences, Cochrane, and Scientific Information Database up to 31 December 2020. We assessed the risk of bias of the included studies using Cochrane Collaboration criteria. All analyses were performed using the Comprehensive Meta-Analysis software version 2, and the risk ratio index was…

Abstract Using publicly-available average monthly groundwater level data in 478 sub-basins and 30 basins in Iran, we quantify country-wide groundwater depletion in Iran. Natural and anthropogenic elements affecting the dynamics of groundwater storage are taken into account and quantified during the period of 2002–2015. We estimate that the total groundwater depletion in Iran to be ~ 74 km 3 during this period with highly localized and variable rates of change at basin and sub-basin scales. The impact of depletion in Iran’s groundwater reserves is already manifested by extreme overdrafts in ~ 77% of Iran’s land area, a growing soil salinity across the entire country, and increasing frequency and extent of land subsidence in Iran’s planes. While meteorological/hydrological droughts act as triggers and intensify the rate of depletion in country-wide groundwater storage, basin-scale groundwater depletions in Iran are mainly caused by extensive human water withdrawals. We warn that continuation of unsustainable groundwater management in Iran can lead to potentially irreversible impacts…

Abstract Total phosphorus (TP) loss from planting was one of the resources causing agricultural non-point source pollution. It is significant to clarify the factors influencing TP loss, as well as explore the relationship between TP loss from planting and surface water eutrophication for making recommendations on the reduction of environmental pollution. In this study, the minimum and maximum of average TP loss was appeared in Qinghai and Shandong province with the TP loss of 7.7 × 102 t and 7.5 × 103 t from 2012 to 2014, respectively. The results of structural equation model (SEM) indicating that the effect of anthropogenic drivers on TP loss was more important than natural conditions due to the higher path coefficient of anthropogenic drivers (0.814) than that of natural conditions (0.130). For anthropogenic drivers, the path coefficients of usage of fertilizer and pesticides, which was often excessively applied in China, were 0.921 and 0.909, respectively causing they the two dominant factors affecting TP loss. Annual precipitation and relative humidity, which were belongs to…

Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissue sampling for pathologist review is the most reliable method for histology classification, however, recent advances in deep learning for medical image analysis allude to the utility of radiologic data in further describing disease characteristics and for risk stratification. In this study, we propose a radiomics approach to predicting non-small cell lung cancer (NSCLC) tumor histology from non-invasive standard-of-care computed tomography (CT) data. We trained and validated convolutional neural networks (CNNs) on a dataset comprising 311 early-stage NSCLC patients receiving surgical treatment at Massachusetts General Hospital (MGH), with a focus on the two most common histological types: adenocarcinoma (ADC) and Squamous Cell Carcinoma (SCC). The CNNs were able to predict tumor histology with an AUC of 0.71(p = 0.018). We also found that using machine learning classifiers such as k-nearest neighbors (kNN) and support vector machine (SVM) on CNN-derived quantitative radiomics features…

COVID-19 took a heavy toll on older adults. In Belgium, by the end of August, 93% of deaths due to COVID-19 were aged 65 or older. Similar trends were observed in other countries. As a consequence, older adults were identified as a group at risk, and strict governmental restrictions were imposed on them. This has caused concerns about their mental health. Using an online survey, this study established the impact of the COVID-19 pandemic on adults aged 65 years or older, and which factors moderate this impact. Participants reported a significant decrease in activity level, sleep quality and wellbeing during the COVID-19 pandemic. Depression was strongly related to reported declines in activity level, sleep quality, wellbeing and cognitive functioning. Our study shows that the COVID-19 pandemic had a severe impact on the mental health of older adults. This implies that this group at risk requires attention of governments and healthcare.

Microplastic (MP) is a pervasive pollutant in nature that is colonised by diverse groups of microbes, including potentially pathogenic species. Fungi have been largely neglected in this context, despite their affinity for plastics and their impact as pathogens. To unravel the role of MP as a carrier of fungal pathogens in terrestrial ecosystems and the immediate human environment, epiplastic mycobiomes from municipal plastic waste from Kenya were deciphered using ITS metabarcoding as well as a comprehensive meta-analysis, and visualised via scanning electron as well as confocal laser scanning microscopy. Metagenomic and microscopic findings provided complementary evidence that the terrestrial plastisphere is a suitable ecological niche for a variety of fungal organisms, including important animal and plant pathogens, which formed the plastisphere core mycobiome. We show that MPs serve as selective artificial microhabitats that not only attract distinct fungal communities, but also accumulate certain opportunistic human pathogens, such as cryptococcal and Phoma-like species.…

Abstract Antimicrobial resistance seriously threatened human health, and new antimicrobial agents are desperately needed. As one of the largest classes of plant secondary metabolite, flavonoids can be widely found in various parts of the plant, and their antibacterial activities have been increasingly paid attention to. Based on the physicochemical parameters and antibacterial activities of sixty-six flavonoids reported, two regression equations between their ACD⁄LogP or LogD7.40 and their minimum inhibitory concentrations (MICs) to gram-positive bacteria were established with the correlation coefficients above 0.93, and then were verified by another sixty-eight flavonoids reported. From these two equations, the MICs of most flavonoids against gram-positive bacteria could be roughly calculated from their ACD⁄LogP or LogD7.40, and their minimum values were respectively predicted as approximately 1.7 or 3.0 μM, more likely fall into the range from 0.9 to 3.4 μM, or from 1.5 to 6.0 μM, respectively. Simultaneously, both tendentiously concave regression curves indicated that the…

Abstract We systematically reviewed observational and clinical trials (baseline) studies examining differences in gait parameters between Parkinson’s disease (PD) in on-medication state and healthy control. Four electronic databases were searched (November-2018 and updated in October-2020). Independent researchers identified studies that evaluated gait parameters measured quantitatively during self-selected walking speed. Risk of bias was assessed using an instrument proposed by Downs and Black (1998). Pooled effects were reported as standardized mean differences and 95% confidence intervals using a random-effects model. A total of 72 studies involving 3027 participants (1510 with PD and 1517 health control) met the inclusion criteria. The self-selected walking speed, stride length, swing time and hip excursion were reduced in people with PD compared with healthy control. Additionally, PD subjects presented higher cadence and double support time. Although with a smaller difference for treadmill, walking speed is reduced both on treadmill (.13 m s −1 ) and on overground (.17 m s −1 )…

The rapid development of mega-constellations risks multiple tragedies of the commons, including tragedies to ground-based astronomy, Earth orbit, and Earth's upper atmosphere. Moreover, the connections between the Earth and space environments are inadequately taken into account by the adoption of a consumer electronic model applied to space assets. For example, we point out that satellite re-entries from the Starlink mega-constellation alone could deposit more aluminum into Earth's upper atmosphere than what is done through meteoroids; they could thus become the dominant source of high-altitude alumina. Using simple models, we also show that untracked debris will lead to potentially dangerous on-orbit collisions on a regular basis due to the large number of satellites within mega-constellation orbital shells. The total cross-section of satellites in these constellations also greatly increases the risk of impacts due to meteoroids. De facto orbit occupation by single actors, inadequate regulatory frameworks, and the possibility of free-riding exacerbate these risks. International…

Some of the longest and most comprehensive marine ecosystem monitoring programs were established in the Gulf of Alaska following the environmental disaster of the Exxon Valdez oil spill over 30 years ago. These monitoring programs have been successful in assessing recovery from oil spill impacts, and their continuation decades later has now provided an unparalleled assessment of ecosystem responses to another newly emerging global threat, marine heatwaves. The 2014-2016 northeast Pacific marine heatwave (PMH) in the Gulf of Alaska was the longest lasting heatwave globally over the past decade, with some cooling, but also continued warm conditions through 2019. Our analysis of 187 time series from primary production to commercial fisheries and nearshore intertidal to offshore oceanic domains demonstrate abrupt changes across trophic levels, with many responses persisting up to at least 5 years after the onset of the heatwave. Furthermore, our suite of metrics showed novel community-level groupings relative to at least a decade prior to the heatwave. Given anticipated increases in…

Reproductive ageing in females is defined by a progressive decline in follicle number and oocyte quality. This is a natural process that leads to the loss of fertility and ovarian function, cycle irregularity and eventually menopause or reproductive senescence. The factors that underlie the natural depletion of follicles throughout reproductive life are poorly characterised. It has been proposed that inflammatory processes and fibrosis might contribute to ovarian ageing. To further investigate this possibility, we evaluated key markers of inflammation and immune cell populations in the ovaries of 2, 6, 12 and 18-month-old C57BL/6 female mice. We report that the decrease in follicle numbers over the reproductive lifespan was associated with an increase in the intra-ovarian percentage of CD4 + T cells, B cells and macrophages. Serum concentration and intra-ovarian mRNA levels of several pro-inflammatory cytokines, including IL-1α/β, TNF-α, IL-6, and inflammasome genes ASC and NLRP3, were significantly increased with age. Fibrosis levels, as determined by picrosirius red staining for…

Skin aging has been defined to encompass both intrinsic and extrinsic aging, with extrinsic aging effected by environmental influences and overlaying the effects of chronological aging. The risk factors of skin aging have been studied previously, using methods of quantifying skin aging. However, these studies have yet to be reviewed. To better understand skin aging risk factors and collate the available data, we aimed to conduct a systematic review and meta-analysis. We conducted our systematic review in compliance with Preferred Reporting Item for Systematic Review and Meta-Analyses (PRISMA) guidelines. Embase, PubMed and Web of Science databases were searched in October 2020 using specific search strategies. Where odds ratios were reported, meta-analyses were conducted using the random effects model. Otherwise, significant factors were reported in this review. We identified seven notable risk factors for various skin aging phenotypes: age, gender, ethnicity, air pollution, nutrition, smoking, sun exposure. This review's results will guide future works, such as those aiming to…

Abstract Two classical criteria, by Pugh and Pettifor, have been widely used by metallurgists to predict whether a material will be brittle or ductile. A phenomenological correlation by Pugh between metal brittleness and its shear modulus to bulk modulus ratio was established more than 60 years ago. Nearly four decades later Pettifor conducted a quantum mechanical analysis of bond hybridization in a series of intermetallics and derived a separate ductility criterion based on the difference between two single-crystal elastic constants, C12–C44. In this paper, we discover the link between these two criteria and show that they are identical for materials with cubic crystal structures.

Deep convolutional neural networks, assisted by architectural design strategies, make extensive use of data augmentation techniques and layers with a high number of feature maps to embed object transformations. That is highly inefficient and for large datasets implies a massive redundancy of features detectors. Even though capsules networks are still in their infancy, they constitute a promising solution to extend current convolutional networks and endow artificial visual perception with a process to encode more efficiently all feature affine transformations. Indeed, a properly working capsule network should theoretically achieve higher results with a considerably lower number of parameters count due to intrinsic capability to generalize to novel viewpoints. Nevertheless, little attention has been given to this relevant aspect. In this paper, we investigate the efficiency of capsule networks and, pushing their capacity to the limits with an extreme architecture with barely 160 K parameters, we prove that the proposed architecture is still able to achieve state-of-the-art results on…

Histopathology tissue analysis is considered the gold standard in cancer diagnosis and prognosis. Whole-slide imaging (WSI), i.e., the scanning and digitization of entire histology slides, are now being adopted across the world in pathology labs. Trained histopathologists can provide an accurate diagnosis of biopsy specimens based on WSI data. Given the dimensionality of WSIs and the increase in the number of potential cancer cases, analyzing these images is a time-consuming process. Automated segmentation of tumorous tissue helps in elevating the precision, speed, and reproducibility of research. In the recent past, deep learning-based techniques have provided state-of-the-art results in a wide variety of image analysis tasks, including the analysis of digitized slides. However, deep learning-based solutions pose many technical challenges, including the large size of WSI data, heterogeneity in images, and complexity of features. In this study, we propose a generalized deep learning-based framework for histopathology tissue analysis to address these challenges. Our framework is, in…

Abstract University administrators and mental health clinicians have raised concerns about depression and anxiety among Ph.D. students, yet no study has systematically synthesized the available evidence in this area. After searching the literature for studies reporting on depression, anxiety, and/or suicidal ideation among Ph.D. students, we included 32 articles. Among 16 studies reporting the prevalence of clinically significant symptoms of depression across 23,469 Ph.D. students, the pooled estimate of the proportion of students with depression was 0.24 (95% confidence interval [CI], 0.18–0.31; I 2 = 98.75%). In a meta-analysis of the nine studies reporting the prevalence of clinically significant symptoms of anxiety across 15,626 students, the estimated proportion of students with anxiety was 0.17 (95% CI, 0.12–0.23; I 2 = 98.05%). We conclude that depression and anxiety are highly prevalent among Ph.D. students. Data limitations precluded our ability to obtain a pooled estimate of suicidal ideation prevalence. Programs that systematically monitor and promote the mental health of…

Covid-19 pandemics has fostered a pervasive use of facemasks all around the world. While they help in preventing infection, there are concerns related to the possible impact of facemasks on social communication. The present study investigates how emotion recognition, trust attribution and re-identification of faces differ when faces are seen without mask, with a standard medical facemask, and with a transparent facemask restoring visual access to the mouth region. Our results show that, in contrast to standard medical facemasks, transparent masks significantly spare the capability to recognize emotional expressions. Moreover, transparent masks spare the capability to infer trustworthiness from faces with respect to standard medical facemasks which, in turn, dampen the perceived untrustworthiness of faces. Remarkably, while transparent masks (unlike standard masks) do not impair emotion recognition and trust attribution, they seemingly do impair the subsequent re-identification of the same, unmasked, face (like standard masks). Taken together, this evidence supports a dissociation…

The use of pathogen-resistant cultivars is expected to increase yield and decrease fungicide use in agriculture. However, in potato breeding, increased resistance obtained via resistance genes (R-genes) is hampered because R-gene(s) are often specific for a pathogen race and can be quickly overcome by the evolution of the pathogen. In parallel, susceptibility genes (S-genes) are important for pathogenesis, and loss of S-gene function confers increased resistance in several plants, such as rice, wheat, citrus and tomatoes. In this article, we present the mutation and screening of seven putative S-genes in potatoes, including two DMR6 potato homologues. Using a CRISPR/Cas9 system, which conferred co-expression of two guide RNAs, tetra-allelic deletion mutants were generated and resistance against late blight was assayed in the plants. Functional knockouts of StDND1, StCHL1, and DMG400000582 (StDMR6-1) generated potatoes with increased resistance against late blight. Plants mutated in StDND1 showed pleiotropic effects, whereas StDMR6-1 and StCHL1 mutated plants did not exhibit any…

In this report, the utilization of mixed methanol-ethanol system for the production of biodiesel from waste cooking oil (WCO) using enhanced eggshell-derived calcium oxide (CaO) nano-catalyst was investigated. CaO nano-catalyst was produced by calcination of eggshell powder at 900 °C and followed by hydration-dehydration treatment to improve its catalytic activity. The particle size, morphology, and elemental composition of a catalyst were characterized by using XRD, SEM, and EDX techniques, respectively. After hydration-dehydration the shape of a catalyst was changed from a rod-like to honeycomb-like porous microstructure. Likewise, average particle size was reduced from 21.30 to 13.53 nm, as a result, its surface area increases. The main factors affecting the biodiesel yield were investigated, accordingly, an optimal biodiesel yield of 94% was obtained at 1:12 oil to methanol molar ratio, 2.5 wt% catalyst loading, 60 °C, and 120-min reaction time. A biodiesel yield of 88% was obtained using 6:6 equimolar ratio of methanol to ethanol, the yield even increased to 91% by increasing…

ABSTRACT Background Patients with coronavirus disease 19 ( COVID-19 ) are at high risk for thrombotic arterial and venous occlusions. At the same time, bleeding complications have been observed in some patients. Better understanding the balance between coagulation and fibrinolysis will help inform optimal approaches to thrombosis prophylaxis and potential utility of fibrinolytic-targeted therapies. Methods 118 hospitalized COVID-19 patients and 30 healthy controls were included in the study. We measured plasma antigen levels of tissue-type plasminogen activator ( tPA ) and plasminogen activator inhibitor-1 ( PAI-1 ) and performed spontaneous clot lysis assays. Findings We found markedly elevated levels of tPA and PAI-1 among patients hospitalized with COVID-19. Both factors demonstrated a strong correlation with neutrophil counts and markers of neutrophil activation. High levels of tPA and PAI-1 were associated with worse respiratory status. High levels of tPA, in particular, were also strongly correlated with mortality and with a significant enhancement in spontaneous ex vivo clot…

Microplastics (MPs) have gained a high degree of public interest since they are associated with the global release of plastics into the environment. Various studies have confirmed the presence of MPs throughout the food chain. However, information on the ingestion of MPs via the consumption of many commonly consumed foods like dairy products are scarce due to the lack of studies investigating the "contamination" of this food group by MPs. This lack of occurrence data is mainly due to the absence of robust analytical methods capable of reliably quantifying MPs with size < 20 µm in foods. In this work, a new methodology was developed to accurately determine and characterize MPs in milk-based products using micro-Raman (μRaman) technology, entailing combined enzymatic and chemical digestion steps. This is the first time that the presence of relatively low amounts of small-sized MP (≥ 5 µm) have been reported in raw milk collected at farm just after the milking machine and in some processed commercial liquid and powdered cow's milk products.

New Coronavirus Disease 2019 (COVID-19) vaccines are available to prevent the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. We compared the efficacy of new COVID-19 vaccines to prevent symptomatic and severe disease in the adult population and to prevent symptomatic COVID-19 among the elderly. Leading medical databases were searched until August 30, 2021. Published phase 3 randomized controlled trials (RCTs) evaluated efficacy of the vaccine to prevent symptomatic and sever COVID-19 in adults were included. Two reviewers independently evaluated the literature search results and independently extracted summary data. The risk of bias was evaluated using the Cochrane Risk of Bias Assessment Tool. We performed a network meta-analysis (NMA) according to PRISMA-NMA 2015 to pool indirect comparisons between different vaccines regarding their relative efficacy. The primary outcomes were the efficacy of the vaccine against symptomatic COVID-19 in adults (PROSPERO registration number: CRD42021235364). Above 200,000 adult participants from eight phase 3 RCTs…

Abstract Drought is one of the major environmental stresses that negatively affect the maize ( Zea mays L.) growth and production throughout the world. Foliar applications of plant growth regulators, micronutrients or osmoprotectants for stimulating drought-tolerance in plants have been intensively reported. A controlled pot experiment was conducted to study the relative efficacy of salicylic acid (SA), zinc (Zn), and glycine betaine (GB) foliar applications on morphology, chlorophyll contents, relative water content (RWC), gas-exchange attributes, activities of antioxidant enzymes, accumulations of reactive oxygen species (ROS) and osmolytes, and yield attributes of maize plants exposed to two soil water conditions (85% field capacity: well-watered, 50% field capacity: drought stress) during critical growth stages. Drought stress significantly reduced the morphological parameters, yield and its components, RWC, chlorophyll contents, and gas-exchange parameters except for intercellular CO 2 concentration, compared with well water conditions. However, the foliar applications…

Generalized anxiety disorder (GAD) and major depressive disorder (MDD) are highly prevalent and impairing problems, but frequently go undetected, leading to substantial treatment delays. Electronic health records (EHRs) collect a great deal of biometric markers and patient characteristics that could foster the detection of GAD and MDD in primary care settings. We approached the problem of predicting MDD and GAD using a novel machine learning pipeline to re-analyze data from an observational study. The pipeline constitutes an ensemble of algorithmically distinct machine learning methods, including deep learning. A sample of 4,184 undergraduate students completed the study, undergoing a general health screening and completing a psychiatric assessment for MDD and GAD. After explicitly excluding all psychiatric information, 59 biomedical and demographic features from the general health survey in addition to a set of engineered features were used for model training. We assessed the model's performance on a held-out test set and found an AUC of 0.73 (sensitivity: 0.66, specificity: 0.7)…

Studies estimate that gender-diverse persons represent 0.1 to 2% of populations investigated, but no such assessment was performed in Latin America. In a representative sample of Brazil's adult population (n = 6000), we investigated participants' sociodemographic characteristics and possible associations between these and current gender identity, categorized as cisgender, transgender or non-binary gender. We also investigated transgender individuals' distress associated with gender-related body characteristics. As main results, we found that transgender individuals represented 0.69% (CI95% = 0.48-0.90) of the sample, whereas non-binary persons were 1.19% (CI95% = 0.92-1.47). These percentages were not different among Brazil's 5 geographic regions. Preliminary analyses showed that transgender individuals were on average younger (32.8 ± 14.2 years, CI95% = 28.5-37.1), compared to cisgender (42.2 ± 15.9, CI95% = 42.5-42.8) and non-binary (42.1 ± 16.5 years, CI95% = 38.3-46.5) groups. Non-binary persons are less likely to be in a relationship compared to cisgender individuals (OR =…

Can the use of psychedelic drugs induce lasting changes in metaphysical beliefs? While it is popularly believed that they can, this question has never been formally tested. Here we exploited a large sample derived from prospective online surveying to determine whether and how beliefs concerning the nature of reality, consciousness, and free-will, change after psychedelic use. Results revealed significant shifts away from 'physicalist' or 'materialist' views, and towards panpsychism and fatalism, post use. With the exception of fatalism, these changes endured for at least 6 months, and were positively correlated with the extent of past psychedelic-use and improved mental-health outcomes. Path modelling suggested that the belief-shifts were moderated by impressionability at baseline and mediated by perceived emotional synchrony with others during the psychedelic experience. The observed belief-shifts post-psychedelic-use were consolidated by data from an independent controlled clinical trial. Together, these findings imply that psychedelic-use may causally influence metaphysical…

Remote monitoring devices, which can be worn or implanted, have enabled a more effective healthcare for patients with periodic heart arrhythmia due to their ability to constantly monitor heart activity. However, these devices record considerable amounts of electrocardiogram (ECG) data that needs to be interpreted by physicians. Therefore, there is a growing need to develop reliable methods for automatic ECG interpretation to assist the physicians. Here, we use deep convolutional neural networks (CNN) to classify raw ECG recordings. However, training CNNs for ECG classification often requires a large number of annotated samples, which are expensive to acquire. In this work, we tackle this problem by using transfer learning. First, we pretrain CNNs on the largest public data set of continuous raw ECG signals. Next, we finetune the networks on a small data set for classification of Atrial Fibrillation, which is the most common heart arrhythmia. We show that pretraining improves the performance of CNNs on the target task by up to [Formula: see text], effectively reducing the number of…

Due to the increasing demand for eco-friendly, cost-effective and safe technologies, biosynthetic metal nanoparticles have attracted worldwide attention. In this study, silver nanoparticles (AgNPs) were extracellularly biosynthesized using the culture supernatants of Aspergillus sydowii. During synthesis, color change was preliminarily judge of the generation of AgNPs, and the UV absorption peak at 420 nm further confirms the production of AgNPs. Transmission electron microscopy and X-ray diffraction were also used to identify the AgNPs. The results shows that AgNPs has crystalline cubic feature and is a polydisperse spherical particle with size between 1 and 24 nm. Three main synthesis factors (temperature, pH and substrate concentration) were optimized, the best synthesis conditions were as follows 50 °C, 8.0 and 1.5 mM. In the biological application of AgNPs, it shows effective antifungal activity against many clinical pathogenic fungi and antiproliferative activity to HeLa cells and MCF-7 cells in vitro. Our research finds a new path to biosynthesis of AgNPs in an eco-friendly…

Abstract An increased nitrate (NO 3 − ) concentration in groundwater has been a rising issue on a global scale in recent years. Different consumption mechanisms clearly illustrate the adverse effects on human health. The goal of this present study is to assess the natural and anthropogenic NO 3 − concentrations in groundwater in a semi arid area of Rajasthan and its related risks to human health in the different groups of ages such as children, males, and females. We have found that most of the samples (n = 90) were influenced by anthropogenic activities. The background level of NO 3 − had been estimated as 7.2 mg/L using a probabilistic approach. About 93% of nitrate samples exceeded the background limit, while 28% of the samples were beyond the permissible limit of 45 mg/L as per the BIS limits. The results show that the oral exposure of nitrate was very high as compare to dermal contact. With regard to the non-carcinogenic health risk, the total Hazard Index (HI Total ) values of groundwater nitrate were an average of 0.895 for males, 1.058 for females, and 1.214 for children.…

Abstract High quality silver (Ag) decorated CeO 2 nanoparticles were prepared by a facile one-step chemical method. The samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), High resolution transmission electron microscopy (HR-TEM), fourier transform infrared spectrometer (FT-IR), electron paramagnetic resonance (EPR), X-ray photoelectron spectroscopy (XPS), UV–Visible absorption (UV–Vis), photoluminescence (PL) and thermogravimetric analysis. The decoration of Ag on CeO 2 surface was confirmed by XRD, EPR and HR-TEM analysis. Harmful textile pollutant Rose Bengal dye was degraded under sunlight using the novel Ag decorated CeO 2 catalyst. It was found that great enhancement of the degradation efficiency for Ag/CeO 2 compared to pure CeO 2 , it can be ascribed mainly due to decrease in its band gap and charge carrier recombination rate. The Ag/CeO 2 sample exhibited an efficient photocatalytic characteristic for degrading RB under visible light irradiation with a high degradation rate of 96% after 3 h. With the help of various characterizations,…

Abstract The highly successful PBE functional and the modified Becke–Johnson exchange potential were used to calculate the structural, electronic, and optical properties of the vacancy-ordered double perovskites A 2 BX 6 (A = Rb, Cs; B = Sn, Pd, Pt; X = Cl, Br, and I) using the density functional theory, a first principles approach. The convex hull approach was used to check the thermodynamic stability of the compounds. The calculated parameters (lattice constants, band gap, and bond lengths) are in tune with the available experimental and theoretical results. The compounds, Rb 2 PdBr 6 and Cs 2 PtI 6 , exhibit band gaps within the optimal range of 0.9–1.6 eV, required for the single-junction photovoltaic applications. The photovoltaic efficiency of the studied materials was assessed using the spectroscopic-limited-maximum-efficiency (SLME) metric as well as the optical properties. The ideal band gap, high dielectric constants, and optimum light absorption of these perovskites make them suitable for high performance single and multi-junction perovskite solar cells.

Abstract Environmentally friendly copper oxide nanoparticles (CuO NPs) were prepared with a green synthesis route without using hazardous chemicals. Hence, the extracts of mint leaves and orange peels were utilized as reducing agents to synthesize CuO NPs-1 and CuO NPs-2, respectively. The synthesized CuO NPs nanoparticles were characterized using scanning electron microscopy (SEM), Energy Dispersive X-ray Analysis (EDX), BET surface area, Ultraviolet–Visible spectroscopy (UV–Vis), and Fourier Transform Infrared Spectroscopy (FT-IR). Various parameters of batch experiments were considered for the removal of Pb(II), Ni(II), and Cd(II) using the CuO NPs such as nanosorbent dose, contact time, pH, and initial metal concentration. The maximum uptake capacity (q m ) of both CuO NPs-1 and CuO NPs-2 followed the order of Pb(II) > Ni(II) > Cd(II). The optimum q m of CuO NPs were 88.80, 54.90, and 15.60 mg g −1 for Pb(II), Ni(II), and Cd(II), respectively and occurred at sorbent dose of 0.33 g L −1 and pH of 6. Furthermore, isotherm and kinetic models were applied to fit the experimental…

Drug discovery for a protein target is a very laborious, long and costly process. Machine learning approaches and, in particular, deep generative networks can substantially reduce development time and costs. However, the majority of methods imply prior knowledge of protein binders, their physicochemical characteristics or the three-dimensional structure of the protein. The method proposed in this work generates novel molecules with predicted ability to bind a target protein by relying on its amino acid sequence only. We consider target-specific de novo drug design as a translational problem between the amino acid "language" and simplified molecular input line entry system representation of the molecule. To tackle this problem, we apply Transformer neural network architecture, a state-of-the-art approach in sequence transduction tasks. Transformer is based on a self-attention technique, which allows the capture of long-range dependencies between items in sequence. The model generates realistic diverse compounds with structural novelty. The computed physicochemical properties and…

With the development of artificial intelligence, big data classification technology provides the advantageous help for the medicine auxiliary diagnosis research. While due to the different conditions in the different sample collection, the medical big data is often imbalanced. The class-imbalance problem has been reported as a serious obstacle to the classification performance of many standard learning algorithms. SMOTE algorithm could be used to generate sample points randomly to improve imbalance rate, but its application is affected by the marginalization generation and blindness of parameter selection. Focusing on this problem, an improved SMOTE algorithm based on Normal distribution is proposed in this paper, so that the new sample points are distributed closer to the center of the minority sample with a higher probability to avoid the marginalization of the expanded data. Experiments show that the classification effect is better when use proposed algorithm to expand the imbalanced dataset of Pima, WDBC, WPBC, Ionosphere and Breast-cancer-wisconsin than the original SMOTE…

Tailoring heat treatments for Laser Powder Bed Fusion (LPBF) processed materials is critical to ensure superior and repeatable material properties for high-end applications. This tailoring requires in-depth understanding of the LPBF-processed material. Therefore, the current study aims at unravelling the threefold interrelationship between the process (LPBF and heat treatment), the microstructure at different scales (macro-, meso-, micro-, and nano-scale), and the macroscopic material properties of AlSi10Mg. A similar solidification trajectory applies at different length scales when comparing the solidification of AlSi10Mg, ranging from mould-casting to rapid solidification (LPBF). The similarity in solidification trajectories triggers the reason why the Brody-Flemings cellular microsegregation solidification model could predict the cellular morphology of the LPBF as-printed microstructure. Where rapid solidification occurs at a much finer scale, the LPBF microstructure exhibits a significant grain refinement and a high degree of silicon (Si) supersaturation. This study has…

Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of Mycobacterium tuberculosis (Mtb). Bacillus Calmette-Guérin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine. In the current study, we select the very conserved, experimentally confirmed Mtb antigens, including Rv2608, Rv2684, Rv3804c (Ag85A), and Rv0125 (Mtb32A) to design a novel multi-epitope subunit vaccine. By using the Immune Epitopes Database (IEDB), we predicted different B-cell and T-cell epitopes. An adjuvant (Griselimycin) was also added to vaccine construct to improve its immunogenicity. Bioinformatics tools were used to predict, refined, and validate the 3D structure and then docked with toll-like-receptor (TLR-3) using different servers. The constructed vaccine was used for further processing based on allergenicity, antigenicity, solubility,…

The student population has been highly vulnerable to the risk of mental health deterioration during the coronavirus disease (COVID-19) pandemic. This study aimed to reveal the prevalence and predictors of mental health among students in Poland, Slovenia, Czechia, Ukraine, Russia, Germany, Turkey, Israel, and Colombia in a socioeconomic context during the COVID-19 pandemic. The study was conducted among 2349 students (69% women) from May-July 2020. Data were collected by means of the Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-8), Perceived Stress Scale (PSS-10), Gender Inequality Index (GII), Standard & Poor's Global Ratings, the Oxford COVID-19 Government Response Tracker (OxCGRT), and a sociodemographic survey. Descriptive statistics and Bayesian multilevel skew-normal regression analyses were conducted. The prevalence of high stress, depression, and generalized anxiety symptoms in the total sample was 61.30%, 40.3%, and 30%, respectively. The multilevel Bayesian model showed that female sex was a credible predictor of PSS-10, GAD-7, and PHQ-8 scores.…