Miracle-dz/UniFAR-FTUs huggingface dataset:
Exposure to alcohol outlets and risk of suicidal behavior in a Swedish cohort of young adults

Background: Greater alcohol accessibility, for example in the form of a high density of alcohol outlets or low alcohol taxation rates, may be associated with increased risk of suicidal behavior. However, most studies have been conducted at the aggregate level, and some have not accounted for potential confounders such as socioeconomic position or neighborhood quality. Methods: In a Swedish cohort of young adults aged 18 to 25, we used logistic regressions to evaluate whether living in a neighborhood that included bars, nightclubs, and/or government alcohol outlets was associated with risk of suicide attempt (SA) or suicide death (SD) during four separate 2-year observation periods. Neighborhoods were defined using pre-established nationwide designations. We conducted combined-sex and sex-stratified analyses, and included as covariates indicators of socioeconomic position, neighborhood deprivation, and aggregate genetic liability to suicidal behavior. Results: Risk of SA was increased in some subsamples of individuals living in a neighborhood with a bar or government alcohol outlet (odds ratios [ORs] = 1.05 to 1.15). Risk of SD was also higher among certain subsamples living in a neighborhood with a government outlet (ORs = 1.47 to 1.56), but lower for those living near a bar (ORs = 0.89 to 0.91). Significant results were driven by, but not exclusive to, the male subsample. Individuals with higher aggregate genetic risk for SA were more sensitive to the effects of a neighborhood government alcohol outlet, pooled across observation periods, in analyses of the sexes combined (relative excess risk due to interaction [RERI] = 0.05; 95% confidence intervals [CI] 0.01; 0.09) and in the male subsample (RERI = 0.06; 95% CI 0.001; 0.12). Conclusions: Although effect sizes are small, living in a neighborhood with bars and/or government alcohol outlets may increase suicidal behavior among young adults. Individuals with higher genetic liability for SA are slightly more susceptible to these exposures.
Strength Characteristics of a Smooth HDPE Geomembrane/Nonwoven Geotextile Interface Based on a Novel Ring Shear Apparatus

This paper aims to investigate the interfacial strength characteristics, particularly the residual strength, of a high-density polyethylene smooth geomembrane (GMB-S)/nonwoven geotextile (NW GTX) interface using a novel ring shear apparatus under high normal stresses and two specimen conditions. A total of eight normal stresses (from 50 kPa to 2308 kPa) and two specimen conditions (dry and submerged at ambient temperature) are considered in this study. The reliability of using the novel ring shear apparatus to study the strength characteristics of the GMB-S/NW GTX interface was demonstrated by conducting a series of direct shear experiments with a maximum shear displacement of 40 mm and ring shear experiments with a shear displacement of 10 m. The peak strength, post-peak strength development, and residual strength determination method of the GMB-S/NW GTX interface are explained. Three exponential equations suitable for characterizing the relationship between the post-peak friction angle and the residual friction angle of the GMB-S/NW GTX interface are established. This relationship can be used with the relevant apparatus (i.e., an apparatus with deficiencies in executing large shear displacement) in determining the residual friction angle of the high-density polyethylene smooth geomembrane/nonwoven geotextile interface.
ON THE EXISTENCE OF p-ADIC ROOTS

In this paper, we give the condition for the existence of the q -th roots of p -adic numbers in Q p with an integer q ≥ 2 and ( p, q ) = 1. We have the conditions for the existence of the ﬁfth root and the seventh root of p -adic numbers in Q p , respectively.
Endomorphisms of C*-algebras, cross products and duality for compact groups

On definit une nouvelle sorte de produit croise d'une C*-algebre par des semigroupes d'endomorphismes avec des proprietes reliees a la symetrie de permutation et a l'existence de conjugues. Un groupe compact est alors defini intrinsequement par son action duale sur le produit croise. Cette construction donne une caracterisation des duaux de groupes compacts abstraits qui est hors d'atteinte de la theorie de dualite de Taunaka-Kein et est independante de cette theorie. Ceci resout le probleme de demontrer l'existence d'un groupe de jauge global compact en physique des particules etant seulement donnees les observables locales
Lightweight Method for On-the-fly Detection of Multivariable Atomicity Violations

Testing to detect on-the-fly concurrency errors, such as atomicity violations caused by multiple shared variables, in a multi-threaded program is challenging because of the need to consider various factors, including correlations between variables and access event interleaving. An improved method for detecting atomicity violations during program execution is presented in this study. This method applies a straightforward approach to recognize a substantial number of related variables that make up atomicity as a single group and as one variable. This enhanced method was implemented, similarly to a test tool, and experimental comparisons were performed using a set of synthetic programs that modeled the execution of the seven representative multivariable atomicity violations. The results showed that compared with the original run of the test programs and a state-of-the-art detection method, the execution time increased by 1.07 and 1.05, respectively. This result included the accuracy of detecting all the multivariable atomicity violations undetected by the prior method.
MLP-UNet: Glomerulus Segmentation

Glomerulus segmentation in kidney tissue segments is a crucial nephropathology process used to diagnose renal diseases effectively. This study proposes a novel and robust application of MLP (Multi-Layer Perceptron) based architectures for the segmentation of glomeruli in PAS (Periodic AcidSchiff) stained whole renal images for effective diagnosis of renal diseases. For the segmentation challenge, the proposed unique solution uses MLP-UNet (Multi-Layer Perceptron U-Net), a novel design that evades using conventional convolution and self-attention mechanisms. Additionally, the study compares various approaches, including U-Net, and for the first time, trains the TransUNet model on the kidney WSI (Whole Slide Image) dataset. Dice Score and Dice Loss were used for training these models as the metric and loss function. Results showed that MLP-based architectures provide comparable results (89.96%) to pre-trained architectures like TransUNet (90.58%) with effectively 20% lesser parameters and no pre-training, and also produce superior Dice scores across the 5-fold cross-validation training and learn more quickly than conventional U-Net architectures.
The Zero Error Capacity of a Noisy Channel

The zero error capacity C 0 of a noisy channel is defined to be the least upper bound of rates at which it is possible to transmit information with zero probability of error. Various properties of C 0 are studied; upper and lower bounds and methods of evaluation of C 0 are given. Inequalities are obtained for the C 0 relating to the ? >sum ? > and ? >product ? > of two given channels. The analogous problem of zero error capacity C 0F for a channel with a feedback link is considered. It is shown that while the ordinary capacity of a memoryless channel with feedback is equal to that of the same channel without feedback, the zero error capacity may be greater. A solution is given to the problem of evaluating C 0F .
“Big Data Assimilation” Revolutionizing Severe Weather Prediction

AbstractSudden local severe weather is a threat, and we explore what the highest-end supercomputing and sensing technologies can do to address this challenge. Here we show that using the Japanese flagship “K” supercomputer, we can synergistically integrate “big simulations” of 100 parallel simulations of a convective weather system at 100-m grid spacing and “big data” from the next-generation phased array weather radar that produces a high-resolution 3-dimensional rain distribution every 30 s—two orders of magnitude more data than the currently used parabolic-antenna radar. This “big data assimilation” system refreshes 30-min forecasts every 30 s, 120 times more rapidly than the typical hourly updated systems operated at the world’s weather prediction centers. A real high-impact weather case study shows encouraging results of the 30-s-update big data assimilation system.
An Analysis of Deep Ocean Sound Attenuation at Very Low Frequencies

The attenuation coefficient of low‐frequency, deep ocean acoustic waves is computed for various assumptions regarding the depth profile and the frequency dependence of the scatterers. The calculations are made for a realistic velocity profile by means of a perturbation technique proposed by Guthrie [Ph. D. dissertation, The University of Auckland (1975)]. It is shown that excellent agreement with experimental data is obtained when the attenuation function is independent of frequency and decreases exponentially with depth with a characteristic depth of 200 to 500 m. A surface value of 0.11 dB/km gives good agreement with the data. At frequencies below 50 Hz the attenuation in the water column is comparable to the attenuation in the sediments for the lowest order normal modes.
A model and experimental study of evaporation from bare-soil surfaces

Abstract A model is constructed for estimating evaporation from bare-soil surfaces. In the model, the evaporation is parameterized with the soil-water content for the upper 2 cm of the soil (Kondo et al.), and the heat and water transport within the soil layer below 2 cm is explicitly described by the heat conduction and moisture diffusion equations. Experiments on evaporation from loam packed in pans are also carried out. The present model well simulates the observed evaporation and vertical profiles of soil temperature and water content. Long time simulations of evaporation by the present model an compared with the force-restore method and the bucket model for a drying period of over several months. The decrease in evaporation rate for the bucket model is comparatively small. However, the evaporation by the present model and the force-restore method decreases rapidly several days after the beginning of the drying period. Differences between the evaporation by the present model and that by the force-rest.
The Influence of Product Quality, Promotion, and Store Atmosphere on Revisit Intention

The purpose of this study was to determine the effect of quality products, promotion, and store atmosphere on revisit intentions. This type of research is explanatory research. The population used in this study was 100 respondents, the sample was taken as a whole because it amounts to 100. The type of research data used was quantitative data and the data source in the study was primary data. Research data collection through questionnaires. The method of data analysis in this research is scale range, and multiple linear regression analysis. The calculation of the range of the quality product scale shows high results, the promotion scale shows high results, the store atmosphere scale shows high results and the revisit intentions show high results. The results showed that quality products, promotion, store atmosphere have a significant direct effect on revisit intention. Meanwhile, the store atmosphere variable has the most dominant influence on revisit intention.
Conceptualizing the Role of Social Entrepreneurial Orientation in the Triple Bottom Line in the Social Enterprise Context: Developing Country Perspective

Social entrepreneurship is becoming widely recognized as essential to developing economies and societies. However, we find that the lack of a clear and cohesive conceptualization for understanding the distinctive context and reliable role of social entrepreneurship is a challenging aspect. Furthermore, the research is lacking in developing country perspectives. Accordingly, this study argues that a social entrepreneurship conceptual model needs to be developed from a developing country perspective to advance the literature on the social entrepreneurship notion. Specifically, this study followed a qualitative research approach and conducted in-person semi-structured interviews with 24 Sri Lankan social enterprises by adopting the maximum variation sampling technique. The data were analyzed using thematic analysis. Consequently, our model explicates how social entrepreneurial orientation leads to the triple bottom line through dynamic capability and social innovation. The proposed model anticipates that social entrepreneurial orientation alone cannot achieve the triple bottom line in social entrepreneurship. Thus, based on existing research evidence, we believe that the following constructs—social entrepreneurial orientation, dynamic capabilities, social innovations, and the triple bottom line—can be integrated to provide a solid conceptual model for social entrepreneurial ventures in developing countries.
Existence of thresholds in proton flares and application to solar energetic particle alerts

This article discusses our statistical investigations into the occurrence of proton events for solar energetic particle (SEP) alerts in space weather forecasts. We analyzed X‐ray flux and proton intensity data obtained with the GOES satellite in the 23rd solar cycle. We found that the total soft X‐ray flux (1–8Å) of almost all flares related to proton events exceeded a threshold value, which was ∼20 ergs cm−2. This means that there is a threshold in flare duration in regard to peak X‐ray flux and this is ∼30 min for an M1.0 flare and/or 3 min for an X1.0 flare. We also confirmed this threshold with data in the 22nd solar cycle. These results will provide some of the most important criteria for SEP alerts and solar proton event forecasts in the future.
Roles of Hormones in Elevated pH-Mediated Mitigation of Copper Toxicity in Citrus sinensis Revealed by Targeted Metabolome

The effects of copper (Cu)–pH interactions on the levels of hormones and related metabolites (HRMs) in Citrus sinensis leaves and roots were investigated. Our findings indicated that increased pH mitigated Cu toxicity-induced alterations of HRMs, and Cu toxicity increased low-pH-induced alterations of HRMs. Increased pH-mediated decreases in ABA, jasmonates, gibberellins, and cytokinins, increases in (±)strigol and 1-aminocyclopropanecarboxylic acid, and efficient maintenance of salicylates and auxins homeostasis in 300 μM Cu-treated roots (RCu300); as well as efficient maintenance of hormone homeostasis in 300 μM Cu-treated leaves (LCu300) might contribute to improved leaf and root growth. The upregulation of auxins (IAA), cytokinins, gibberellins, ABA, and salicylates in pH 3.0 + 300 μM Cu-treated leaves (P3CL) vs. pH 3.0 + 0.5 μM Cu-treated leaves (P3L) and pH 3.0 + 300 μM Cu-treated roots (P3CR) vs. pH 3.0 + 0.5 μM Cu-treated roots (P3R) might be an adaptive response to Cu toxicity, so as to cope with the increased need for reactive oxygen species and Cu detoxification in LCu300 and RCu300. Increased accumulation of stress-related hormones (jasmonates and ABA) in P3CL vs. P3L and P3CR vs. P3R might reduce photosynthesis and accumulation of dry matter, and trigger leaf and root senescence, thereby inhibiting their growth.
C- reactive protein levels in women with prelabour rupture of membrane and women with normal labour

Background: There is a very little information known about CRP in term pregnancies. It is a marker that is easily tested and is inexpensive. Although CRP has been used very effectively in diagnosing infection in the neonate, its clinical use and values have not been studied in term pregnancies. The level of CRP that is truly normal or clinically innocuous is not known. Objectives: This is a cross-sectional study to compare the CRP levels in antenatal women with PROM and women with normal labor and assess its utility to predict sepsis. Methods: This is a prospective study done over a period of one year and approved by the insititutional ethical committee (IRB. Min. No 11102[OBSERVE] dated 10.01.2018). Sample for CRP was collected from 112 antenatal women with prelabor rupture of membranes within 12 hours of admission (Group A) and from 112 antenatal women in spontaneous labor without rupture of membrane (Group B). CRP samples are processed by nephelometry method. Results: The median CRP value in Group A is 9.15 and Group B is 7.26, with no statistical difference. Chorioamnionitis, neonatal sepsis, and endometritis were similar in both the groups. Conclusion: CRP cannot be used as predictor for chorioamnionitis, endometritis, and neonatal sepsis. There was no significant difference in CRP levels between the two groups.
Geometry of the Schrödinger equation and stochastic mass transportation

The Schrodinger equation is deduced from a geometric principle. Lagrange, Hamilton-Jacobi, and Hamilton formalisms are defined almost analogously to the deterministic case, which can be identified as geometric optic. The form of these formalisms is identical to the deterministic formalisms. Furthermore, it will be shown how the deterministic case is “superficial” to the stochastic one if Planck’s constant is very small. An elementary proof of Heisenberg’s uncertainty relation finishes the paper.
A CNN-OSELM Multi-Layer Fusion Network With Attention Mechanism for Fish Disease Recognition in Aquaculture

The increasing global population has escalated the demand for fish products. This calls for a stable supply which can only be met through improved aquaculture practices. The automatic recognition of fish diseases from diseased underwater images is one of such practices that aims to control disease, improve fish production and optimize profits. However, due to lack of public fish disease dataset, there has been limited research towards fish disease recognition. Moreover, due to low quality of underwater images and complex underwater environments, traditional hand-designed feature extraction methods or convolutional neural networks (CNNs)-based classifiers cannot adequately recognize fish diseases in real underwater scenes. Therefore, this paper proposes a novel hybrid approach based on multilayer fusion, attention mechanism and online sequential extreme learning machine (OSELM) to recognize fish diseases in aquaculture. We further compare the classification performance of the proposed model with baseline, attention-based, ConvNeXt and Swin transformer models. Feature extraction is enhanced by integrating same level features and focusing on salient features for fish disease recognition. The characteristic information of fish disease is refined by using strongly discriminative features of the infected fish regions and weakening regions of low interest using convolutional block attention module (CBAM). The module is added to the multilayer fusion network to sequentially infer attention maps along the channel and spatial dimensions for every intermediate feature map. Fish disease recognition is then done using OSELM for faster learning and improved classification performance. The models are trained, validated and tested on a custom dataset with image samples collected from various internet sources. The proposed method achieves 94.28% of accuracy, precision of 92.67%, recall of 92.17% and 92.42% of F1- score on dataset with background elimination. The proposed method can be used for fish disease identification in complex underwater environments in aquaculture.
Few-Shot Classification of Screen Defects With Class-Agnostic Mask and Context-Based Classifier

In the real mobile screen production line, the yield of normal products is relatively high, so some defects are difficult to collect. Besides, samples of emerging defects are difficult to collect in large numbers in a short time. To address the few-shot problem caused by these, we propose a few-shot classification method to simultaneously recognize both the known defects with adequate training data and novel defects with scarce labeled training samples. First, we design a feature extractor with the class-agnostic mask. This module applies normal images to weaken irrelevant background information, thus extracting defect-highlighted features. Then, to avoid drowning limited important features in noise, the class prototype generator (CPG) is introduced to produce more representative class prototypes. Finally, a context-based classifier (CBC), which applies global context information, is proposed. This module can make better classification decisions among all classes. Experiments demonstrate that our method significantly outperforms other few-shot methods on the mobile screen defect dataset. The proposed method achieves 89.19% accuracy, 96.96% accuracy, and 97.55% accuracy in the one-shot, five-shot, and ten-shot test scenarios, respectively. The code is available at https://github.com/CFZ1/FSL_Cls_Screen.
Validation of the Auralization Technique : Comparative Speech-Intelligibility Tests in Real and Virtual Classrooms

Speech-intelligibility tests with human subjects give more realistic results than do the measurement or the prediction of objective metrics. However, human testing in real environments has a number of limitations. Auralization offers a solution to the limitations, having unlimited capability to reproduce realistic listening environments. The work presented here aimed to validate the auralization technique for speech-intelligibility testing, in comparison with live listening tests in real classrooms. Results for two real and virtual classrooms were compared. Acoustical parameters were measured in the real classrooms and speech-intelligibility tests performed. The Modified Rhyme Test and speech-babble noise were generated by loudspeakers. Speech-intelligibility tests were performed at three positions with normal-hearing subjects. The classrooms and the speech-intelligibility test conditions were modeled using the CATT-Acoustics prediction and auralization system. Predicted and measured room-acoustical parameters were compared. Speech-intelligibility tests were performed in the virtual classrooms with the same subjects, and the results in the real and virtual classrooms were compared. Auralized speech-intelligibility tests were found to be reliable if the classroom was not very absorptive or noisy.
Accretion onto Pre-Main-Sequence Stars

Accretion through circumstellar disks plays an important role in star formation and in establishing the properties of the regions in which planets form and migrate. The mechanisms by which protostellar and protoplanetary disks accrete onto low-mass stars are not clear; angular momentum transport by magnetic fields is thought to be involved, but the low-ionization conditions in major regions of protoplanetary disks lead to a variety of complex nonideal magnetohydrodynamic effects whose implications are not fully understood. Accretion in pre-main-sequence stars of masses ≲1M⊙ (and in at least some 2–3-M⊙ systems) is generally funneled by the stellar magnetic field, which disrupts the disk at scales typically of order a few stellar radii. Matter moving at near free-fall velocities shocks at the stellar surface; the resulting accretion luminosities from the dissipation of kinetic energy indicate that mass addition during the T Tauri phase over the typical disk lifetime ∼3 Myr is modest in terms of stellar evo.