Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Modeling of Snow Avalanche Using Machine Learning Models and Geo-Environmental Factors: Comparison of Effectiveness in Two Mountain Regions

Although snow avalanches are among the most destructive natural disasters, and result in losses of life and economic damages in mountainous regions, far too little attention has been paid to the prediction of the snow avalanche hazard using advanced machine learning (ML) models. In this study, the applicability and efficiency of four ML models: support vector machine (SVM), random forest (RF), naive Bayes (NB) and generalized additive model (GAM), for snow avalanche hazard mapping, were evaluated. Fourteen geomorphometric, topographic and hydrologic factors were selected as predictor variables in the modeling. This study was conducted in the Darvan and Zarrinehroud watersheds of Iran. The goodness-of-fit and predictive performance of the models was evaluated using two statistical measures: the area under the receiver operating characteristic curve (AUROC) and the true skill statistic (TSS). Finally, an ensemble model was developed based upon the results of the individual models. Results show that, among individual models, RF was best, performing well in both the Darvan (AUROC = 0.964, TSS = 0.862) and Zarrinehroud (AUROC = 0.956, TSS = 0.881) watersheds. The accuracy of the ensemble model was slightly better than all individual models for generating the snow avalanche hazard map, as validation analyses showed an AUROC = 0.966 and a TSS = 0.865 in the Darvan watershed, and an AUROC value of 0.958 and a TSS value of 0.877 for the Zarrinehroud watershed. The results indicate that slope length, lithology and relative slope position (RSP) are the most important factors controlling snow avalanche distribution. The methodology developed in this study can improve risk-based decision making, increases the credibility and reliability of snow avalanche hazard predictions and can provide critical information for hazard managers.
Diabetic Retinopathy detection by retinal image recognizing

Many people are affected by diabetes around the world. This disease may have type 1 and 2. Diabetes brings with it several complications including diabetic retinopathy, which is a disease that if not treated correctly can lead to irreversible damage in the patient's vision. The earlier it is detected, the better the chances that the patient will not lose vision. Methods of automating manual procedures are currently in evidence and the diagnostic process for retinopathy is manual with the physician analyzing the patient's retina on the monitor. The practice of image recognition can aid this detection by recognizing Diabetic Retinopathy patterns and comparing it with the patient's retina in diagnosis. This method can also assist in the act of telemedicine, in which people without access to the exam can benefit from the diagnosis provided by the application. The application development took place through convolutional neural networks, which do digital image processing analyzing each image pixel. The use of VGG-16 as a pre-trained model to the application basis was very useful and the final model accuracy was 82%.
Gender inequality and sexual height dimorphism in Chile

Abstract Chile has experienced significant improvements in its economy; thus, a secular trend in height has been observed in its population. Gender equality has also improved hand in hand with active policies addressing the gender gap in several dimensions (work, education, health) and overall economic improvement. This study examined changes in sexual height dimorphism in four samples of Chilean male and female working-age subjects and attempted to establish associations with gender equality and welfare. Sexual height dimorphism was calculated and compared with gender equality and overall welfare indicators between 1955 and 1995. Sexual height dimorphism reduction was seen to be strongly associated with greater gender equality and some general welfare indicators, such as the infant mortality rate. Gross domestic product per capita was not associated with sexual height dimorphism, but it showed significant associations with gender equality indicators. Overall, the gender gap has been reduced in Chile, which can be observed through improvements in gender equality indicators and a reduction in height dimorphism, mainly in areas associated with women’s health. However, gender equality is still far behind in terms of female labour participation and women in political power, which require attention and further improvements.
Evaluation of PERSIANN-CDR Constructed Using GPCP V2.2 and V2.3 and A Comparison with TRMM 3B42 V7 and CPC Unified Gauge-Based Analysis in Global Scale

Providing reliable long-term global precipitation records at high spatial and temporal resolutions is crucial for climatological studies. Satellite-based precipitation estimations are a promising alternative to rain gauges for providing homogeneous precipitation information. Most satellite-based precipitation products suffer from short-term data records, which make them unsuitable for various climatological and hydrological applications. However, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) provides more than 35 years of precipitation records at 0.25° × 0.25° spatial and daily temporal resolutions. The PERSIANN-CDR algorithm uses monthly Global Precipitation Climatology Project (GPCP) data, which has been recently updated to version 2.3, for reducing the biases in the output of the PERSIANN model. In this study, we constructed PERSIANN-CDR using the newest version of GPCP (V2.3). We compared the PERSIANN-CDR dataset that is constructed using GPCP V2.3 (from here on referred to as PERSIANN-CDR V2.3) with the PERSIANN-CDR constructed using GPCP V2.2 (from here on PERSIANN-CDR V2.2), at monthly and daily scales for the period from 2009 to 2013. First, we discuss the changes between PERSIANN-CDR V2.3 and V2.2 over the land and ocean. Second, we evaluate the improvements in PERSIANN-CDR V2.3 with respect to the Climate Prediction Center (CPC) unified gauge-based analysis, a gauged-based reference, and Tropical Rainfall Measuring Mission (TRMM 3B42 V7), a commonly used satellite reference, at monthly and daily scales. The results show noticeable differences between PERSIANN-CDR V2.3 and V2.2 over oceans between 40° and 60° latitude in both the northern and southern hemispheres. Monthly and daily scale comparisons of the two bias-adjusted versions of PERSIANN-CDR with the above-mentioned references emphasize that PERSIANN-CDR V2.3 has improved mostly over the global land area, especially over the CONUS and Australia. The updated PERSIANN-CDR V2.3 data has replaced V2.2 data for the 2009–2013 period on CHRS data portal and NOAA National Centers for Environmental Information (NCEI) Program.
The Influence of Hydrothermal Aging on the Dynamic Friction Model of Rubber Seals

Cylinder has become an indispensable and important pneumatic actuator in the development of green production technology. The sealing performance of the cylinder directly affects its safety and reliability. Under the service environment of the cylinder, hydrothermal aging of the rubber sealing ring directly affects the dynamic friction performance of the cylinder. So, the dynamic friction model of the cylinder has been developed based on the LuGre friction model, which considers the influence of hydrothermal aging. Here, the influences of the static friction coefficient and Coulomb friction coefficient on the friction model are analyzed. Then, the aging characteristic equation of rubber is embedded in the model for revealing the influence of aging on the friction coefficient of the model. Results show that the aging temperature, aging time, and compressive stress affects the friction coefficient; the variation of the static friction coefficient is larger than that of the Coulomb friction coefficient. The improved cylinder friction model can describe the influence of the aging process on the cylinder friction characteristics, which is of great significance in the design of the cylinder’s dynamic performance.
Robust Topological Descriptors for Machine Learning Prediction of Guest Adsorption in Nanoporous Materials

In recent years, machine learning (ML) for predicting material properties has emerged as a quicker alternative to experimental and simulation-based investigations. Standard ML approaches tend to utilize specific domain knowledge when designing feature inputs. Each ML property predictor then requires a set of tailored structural features - this can commonly lead to drawbacks, due to the small number of implemented features and their lack of prediction transferability across different predictors. The latter has been empirically observed in the case of guest uptake predictors for nanoporous materials, where local and global porosity features become dominant descriptors at low and high pressures, respectively. Here, we provide a more holistic feature representation for materials structures using tools from topological data analysis and persistent homology to describe the geometry and topology of nanoporous materials at various scales. We demonstrate an application of these topology-based feature representations to predict methane uptakes for zeolite structures in the range of 1-200 bar. These predictions show a root-mean-square deviation decrease of up to 50% at low pressures and up to 100% across high pressures in comparison to a model based on commonly used local and global features. Similarly, the topology-based model shows an increase of 0.2-0.3 in R2 score in comparison to the commonly used porosity descriptors. Notably, unlike the standard porosity features, the topology-based features show accuracy across multiple different pressures. Furthermore, we show feature importance in terms of different topological features, thus elucidating information about the channel and pore sizes that correlate best to adsorption properties. Finally, we demonstrate that ML models relying on a combination of topological and commonly employed descriptors provide even better guest uptake regressors.
An Analysis of the Structural Relationships among Undergraduate Students’ Learning Motivations, Cognitive Strategies, and Academic Achievements

The purpose of this study was to examine the relationships among undergraduate students’ learning motivations, cognitive strategies, and academic achievement. For this study, the Motivated Strategies for Learning Questionnaire(MSLQ) was conducted with 338 participants from A University to measure the level of motivation and cognitive strategies. As a result, first, structural equation models, which indicate learning motivations influence on academic achievement, were fit for the purpose. Second, direct effects of learning motivations on academic achievement were not statistically significant. Third, learning motivations had an indirect impact on academic achievement by mediating cognitive strategies. Overall, even with no direct effect of learning motivation on academic achievement, students who had high levels of learning motivation used more cognitive strategies. Also, the more cognitive strategies students used the higher were their levels of academic achievement.
Effect of N‐palmitoylethanolamine‐oxazoline on comorbid neuropsychiatric disturbance associated with inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic disorder characterized by inflammation of the gastrointestinal (GI) tract, and it is associated with different neurological disorders. Recent evidence has demonstrated that the gut‐brain‐axis has a central function in the perpetuation of IBS, and for this reason, it can be considered a possible therapeutic target. N‐Palmitoylethanolamine‐oxazoline (PEA‐OXA) possesses anti‐inflammatory and potent neuroprotective effects. Although recent studies have explained the neuroprotective properties of PEA‐OXA, nothing is known about its effects on the gut‐brain axis during colitis. The aim of this study is to explore the mechanism and the effect of PEA‐OXA on the gut‐brain axis in rats subjected to experimental colitis induced by oral administration of dextran sulfate sodium (DSS). Daily oral administration of PEA‐OXA (10 mg/kg daily o.s.) was able to decrease the body weight loss, macroscopic damage, colon length, histological alteration, and inflammation after DSS induction. Additionally, PEA‐OXA administration enhanced neurotrophic growth factor release and decreased the astroglial and microglial activation induced by DSS. Moreover, PEA‐OXA restored intestinal permeability and tight junctions (TJs) as well as reduced apoptosis in the colon and brain. In our work, we demonstrated, for the first time, the action of PEA‐OXA on the gut‐brain axis in a model of DSS‐induced colitis and its implication on the “secondary” effects associated with colonic disturbance.
Learning a Latent Space of Style-Aware Symbolic Music Representations by Adversarial Autoencoders

We address the challenging open problem of learning an effective latent space for symbolic music data in generative music modeling. We focus on leveraging adversarial regularization as a flexible and natural mean to imbue variational autoencoders with context information concerning music genre and style. Through the paper, we show how Gaussian mixtures taking into account music metadata information can be used as an effective prior for the autoencoder latent space, introducing the first Music Adversarial Autoencoder (MusAE). The empirical analysis on a large scale benchmark shows that our model has a higher reconstruction accuracy than state-of-the-art models based on standard variational autoencoders. It is also able to create realistic interpolations between two musical sequences, smoothly changing the dynamics of the different tracks. Experiments show that the model can organise its latent space accordingly to low-level properties of the musical pieces, as well as to embed into the latent variables the high-level genre information injected from the prior distribution to increase its overall performance. This allows us to perform changes to the generated pieces in a principled way.
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Toxoplasma gondii Recombinant antigen AMA1: Diagnostic Utility of Protein Fragments for the Detection of IgG and IgM Antibodies

Toxoplasma gondii is an important zoonotic protozoan that infects a wide variety of vertebrates as intermediate hosts. For this reason, the diagnosis of this disease is very important and requires continuous improvement. One possibility is to use recombinant antigens in serological tests. Apical membrane antigen 1 (AMA1), a protein located in specific secretory organelles (micronemes) of T. gondii, is very interesting in regard to its potential diagnostic utility. In the present study, we attempted to identify a fragment of the AMA1 protein with a high sensitivity and specificity for the serological diagnosis of human toxoplasmosis. The full-length AMA1 and two different fragments (AMA1N and AMA1C) were produced using an Escherichia coli expression system. After purification by metal affinity chromatography, recombinant proteins were tested for their utility as antigens in enzyme-linked immunosorbent assays (ELISAs) for the detection of IgG and IgM anti-T. gondii antibodies in human and mouse immune sera. Our data demonstrate that the full-length AMA1 recombinant antigen (corresponding to amino acid residues 67–569 of the native protein) has a better diagnostic potential than its N- or C-terminal fragments. This recombinant protein strongly interacts with specific anti-T. gondii IgG (99.4%) and IgM (80.0%) antibodies, and may be used for developing new tools for diagnostics of toxoplasmosis.
Short chain fatty acids and methylamines produced by gut microbiota as mediators and markers in the circulatory system

Ample evidence suggests that gut microbiota-derived products affect the circulatory system functions. For instance, short chain fatty acids, that are the products of dietary fiber bacterial fermentation, have been found to dilate blood vessels and lower blood pressure. Trimethylamine, a gut bacteria metabolite of carnitine and choline, has recently emerged as a potentially toxic molecule for the circulatory system. To enter the bloodstream, microbiota products cross the gut–blood barrier, a multilayer system of the intestinal wall. Notably, experimental and clinical studies show that cardiovascular diseases may compromise function of the gut–blood barrier and increase gut-to-blood penetration of microbiota-derived molecules. Hence, the bacteria products and the gut–blood barrier may be potential diagnostic and therapeutic targets in cardiovascular diseases. In this paper, we review research on the cardiovascular effects of microbiota-produced short chain fatty acids and methylamines. Impact statement Despite a progress in the diagnosis and treatment of cardiovascular diseases, there are still significant gaps in understanding complex mechanisms underlying cardiovascular pathology. Increasing evidence suggests that gut microbiota products such as short chain fatty acids or methylamines may affect the circulatory system in health and disease. Hence, the microbiota-derived molecules are potential diagnostic and therapeutic targets in cardiovascular diseases. Therapeutic options may include administration of selected bacterial strains (probiotics) producing desired metabolites or administration of direct gut microbiota products.
Survey on Health Condition and Dietary Custom in the Residents of High and Medium Prevalence of Gastric Cancer in Fujian,China

[Objective] To study the differences in health condition and dietary custom between the residents of high (Changle City)and medium (Tongan District)prevalence of gastric cancer in Fujian,and explore the possible factors related to gastric cancer. [Methods] By random sampling method,the residents living in Changle or Tongan for more than five years were interviewed with a questionnaire. [Results] The rates of the residents with the history of chronic atrophic gastritis and gastrointestinal ulcer or with the family history and the symptoms of gastrointestinal diseases in Changle were higher than those in Tongan District.Changle residents consumed fish sauce,pickle vegetable,hot food and old grain more frequently than those in Tongan.However,Tongan residents consumed fresh vegetable and tea more frequently than those in Changle. [Conclusion] The results suggest that the significant differences in health condition and dietary custom remain in the two areas.It is necessary to carry out health education for the prevention of gastric cancer.
Hippocampal growth hormone modulates relational memory and the dendritic spine density in CA1

Growth hormone (GH) deficiency is associated with cognitive decline which occur both in normal aging and in endocrine disorders. Several brain areas express receptors for GH although their functional role is unclear. To determine how GH affects the capacity for learning and memory by specific actions in one of the key areas, the hippocampus, we injected recombinant adeno-associated viruses (rAAVs) in male rats to express green fluorescent protein (GFP) combined with either GH, antagonizing GH (aGH), or no hormone, in the dorsal CA1. We found that aGH disrupted memory in the Morris water maze task, and that aGH treated animals needed more training to relearn a novel goal location. In a one-trial spontaneous location recognition test, the GH treated rats had better memory performance for object locations than the two other groups. Histological examinations revealed that GH increased the dendritic spine density on apical dendrites of CA1, while aGH reduced the spine density. GH increased the relative amount of immature spines, while aGH decreased the same amount. Our results imply that GH is a neuromodulator with strong influence over hippocampal plasticity and relational memory by mechanisms involving modulation of dendritic spines. The findings are significant to the increasing aging population and GH deficiency patients.
The inhibition of apoptosis through myocardial postconditioning by affecting Fas/FasIg signaling through miR139‐3p and miR181a‐1

Ischemic postconditioning (PostC) is considered to be one of the strongest mechanisms limiting the extent of myocardial infarction, and reducing ischemia‐reperfusion (I/R) injury. I/R‐induced myocardial injury results in apoptosis, autophagy, and necrosis. The aim of the present study was to investigate the roles of the necrotic gene cytochrome b‐245 beta chain (Cybb); Cybb‐related microRNA miR139‐3p; the autophagy gene Beclin‐1 (Becn1); proapoptotic genes Fas, Faslg and growth arrest and DNA‐damage‐inducible 45 alpha (Gadd45a); and apoptosis‐related microRNA miR181a‐1 levels on I/R injury, as well as, the potential protective effects of PostC through this gene and microRNAs.
Major Adverse Cardiovascular Events Associated With Postoperative Atrial Fibrillation After Noncardiac Surgery

Supplemental Digital Content is available in the text. Background: Postoperative atrial fibrillation (POAF) is a frequent occurrence after noncardiac surgery. It remains unclear whether POAF is associated with an increased risk of major adverse events. We aimed to elucidate the risk of stroke, myocardial infarction, and death associated with POAF following noncardiac surgery by a meta-analysis of randomized controlled studies and observational studies. Methods: We searched electronic databases from inception up to August 1, 2019 for all studies that reported stroke or myocardial infarction in adult patients who developed POAF following noncardiac surgery. We used random-effects models to summarize the studies. Results: The final analyses included 28 studies enrolling 2 612 816 patients. At 1-month (10 studies), POAF was associated with an ≈3-fold increase in the risk of stroke (weighted mean 2.1% versus 0.7%; odds ratio [OR], 2.82 [95% CI, 2.15–3.70]; P<0.001). POAF was associated with ≈4-fold increase in the long-term risk of stroke with (weighted mean, 2.0% versus 0.6%; OR, 4.12 [95% CI, 3.32–5.11]; P≤0.001) in 8 studies with ≥12-month follow-up. There was a significant overall increase in the risk of stroke and myocardial infarction associated with POAF (weighted mean, 2.5% versus 0.9%; OR, 3.44 [95% CI, 2.38–4.98]; P<0.001) and (weighted mean, 12.6% versus 2.7%; OR, 4.02 [95% CI, 3.08–5.24]; P<0.001), respectively. Furthermore, POAF was associated with a 3-fold increase in all-cause mortality at 30 days (weighted mean, 15.0% versus 5.4%; OR, 3.36 [95% CI, 2.13–5.31]; P<0.001). Conclusions: POAF was associated with markedly higher risk of stroke, myocardial infarction, and all-cause mortality following noncardiac surgery. Future studies are needed to evaluate the impact of optimal cardiovascular pharmacotherapies to prevent POAF and to decrease the risk of major adverse events in these high-risk patients.
FOC7-2SALIVA CYTOKINE CONCENTRATIONS THE DAY AFTER HEAVY ALCOHOL CONSUMPTION IN DRINKERS SUFFERING FROM A HANGOVER VERSUS THOSE WHO CLAIM TO BE HANGOVER RESISTANT

Aim. As it has been suggested that the immune system plays a role in the pathogenesis of the alcohol hangover, the purpose of this naturalistic study (amount, day and place of drinking were the subjects own choice) was to investigate cytokines concentrations in saliva after an evening of alcohol consumption. Drinkers …