Miracle-dz/UniFAR-FTUs huggingface dataset:
Field Experiences with Handheld Diagnostic Devices to Triage Children under Five Presenting with Severe Febrile Illness in a District Hospital in DR Congo

As part of a field study (NCT04473768) in children presenting with severe febrile illness to Kisantu hospital (DR Congo), we retrospectively compiled user experiences (not performance) with handheld diagnostic devices assisting triage: tympanic thermometer, pulse oximeter (measuring heart rate, respiratory rate and oxygen saturation), hemoglobinometer and glucometer. Guidance documents for product selection were generic and scattered. Stock rupture, market withdrawal and unaffordable prices interfered with procurement. Challenges at implementation included environmental temperature, capillary blood sampling (antisepsis, order of multiple tests, filling microcuvettes and glucose strips), calibration (environmental temperature, cold chain) and liability-oriented communication with a manufacturer. Instructions for use were readable and contained symbol keys; two devices had printed French-language instructions. Shortcomings were poor integration of figures with text and distinct procedures for the oximeter and its sensor. Usability interview revealed appreciations for quick results, visibility of the display and memory function (three devices) but also problems of capillary blood sample transfer, cleaning, too long of a time-to-results (respiratory rate) and size, fitting and disposal of thermometer probes. Pictorial error messages were preferred over alphanumeric error codes but interpretation of symbols was poor. Alarm sounds of the oximeter caused unrest in children and caretakers perceived the device as associated with poor prognosis.
Calculated Tumor-Associated Neutrophils Are Associated with the Tumor—Stroma Ratio and Predict a Poor Prognosis in Advanced Gastric Cancer

The tumor-associated neutrophils (TANs) value and tumor—stroma ratio (TSR) are promising prognostic parameters in the tumor microenvironment. We aimed to evaluate the prognostic role and relationship of TANs and TSR in gastric cancer. Our study comprised 157 patients who underwent gastrectomy for advanced gastric cancer. TANs were assessed by immunohistochemical staining (CD15 and CD66b) and were analyzed with an image analyzer. TANs have been known to have different functional subpopulations of N1 (anti-tumor) and N2 (pro-tumor). We developed “calculated TANs with pro-tumor function (cN2; CD15 minus CD66b)”. The TSR was evaluated using hematoxylin and eosin staining. High-grade CD15-positive, cN2 in the tumor center, and TSR were significantly related to poor disease-free survival (DFS). TSR and cN2 were independent prognostic factors for DFS (hazard ratio (HR) = 2.614; p = 0.001, HR = 3.976; p = 0.002) and cN2 in the tumor center showed a positive correlation with TSR (R = 0.179, p = 0.025). While CD66b stained both N1 and N2, CD15 detected most of N2. Combining both markers revealed a novel cN2, which was an independent marker of poor prognosis. The transformation from N1 to N2 predominantly occurred in the tumor center, and was associated with TSR.
Recent Advances in Surface Plasmon Resonance Sensors for Sensitive Optical Detection of Pathogens

The advancement of science and technology has led to the recent development of highly sensitive pathogen biosensing techniques. The effective treatment of pathogen infections requires sensing technologies to not only be sensitive but also render results in real-time. This review thus summarises the recent advances in optical surface plasmon resonance (SPR) sensor technology, which possesses the aforementioned advantages. Specifically, this technology allows for the detection of specific pathogens by applying nano-sized materials. This review focuses on various nanomaterials that are used to ensure the performance and high selectivity of SPR sensors. This review will undoubtedly accelerate the development of optical biosensing technology, thus allowing for real-time diagnosis and the timely delivery of appropriate treatments as well as preventing the spread of highly contagious pathogens.
Antifreeze Peptides Preparation from Tilapia Skin and Evaluation of Its Cryoprotective Effect on Lacticaseibacillus rhamnosus

Antifreeze peptides can protect cell membranes and maintain the cell viability of probiotics under cold stress. Given this, antifreeze peptides were prepared from tilapia processing byproducts of tilapia skin by enzymolysis using the response surface methodology (RSM) method. The cryoprotective effects on Lacticaseibacillus rhamnosus ATCC7469 were investigated. Trypsin was selected as the protease for tilapia skin hydrolysis. The optimal hydrolysis conditions consisted of the amount of enzyme (2200 U/g), solid–liquid ratio (1:10, w/v), reaction temperature (49 °C), and reaction time (6.8 h), and the relative survival rate of L. rhamnosus reached 98.32%. Molecular weight (Mw) distribution and peptide sequences of the antifreeze peptides prepared from tilapia skin (APT) under the optimal conditions were analyzed. APT significantly reduced the leakage of extracellular proteins and protected β-galactosidase and lactate dehydrogenase activities of L. rhamnosus. Compared with the saline group, scanning electron microscopy (SEM) observation showed that cells had a more normal, smooth, and entire surface under the protection of APT. These findings indicate that APT can be a new cryoprotectant in preserving probiotics.
CASI-Net: A Novel and Effect Steel Surface Defect Classification Method Based on Coordinate Attention and Self-Interaction Mechanism

The surface defects of a hot-rolled strip will adversely affect the appearance and quality of industrial products. Therefore, the timely identification of hot-rolled strip surface defects is of great significance. In order to improve the efficiency and accuracy of surface defect detection, a lightweight network based on coordinate attention and self-interaction (CASI-Net), which integrates channel domain, spatial information, and a self-interaction module, is proposed to automatically identify six kinds of hot-rolled steel strip surface defects. In this paper, we use coordinate attention to embed location information into channel attention, which enables the CASI-Net to locate the region of defects more accurately, thus contributing to better recognition and classification. In addition, features are converted into aggregation features from the horizontal and vertical direction attention. Furthermore, a self-interaction module is proposed to interactively fuse the extracted feature information to improve the classification accuracy. The experimental results show that CASI-Net can achieve accurate defect classification with reduced parameters and computation.
Diversity of Powdery Mildew Mycoparasite Ampelomyces quisqualis under Natural Ecosystem and Its Molecular Characterization

The powdery mildew are the most common diseases which widely affect crops in many countries. The mildew infection appeared on leaves, petiole, buds, inflorescence and other tender tissues of crops causing 65% of the crop loss. Even though the fungicidal spray to control the disease, the residual and environmental effects are causing long term ecological imbalance in cropping system. Recently, an alternative and eco-friendly mycoparasite associated with powdery mildew pathogens was used against Erysiphe sp, Leveilulla sp, Sphaerotheca sp and Oidium sp. This study aimed to mitigated the use of the expensive and harmful fungicides to save human health and to reduce the financial costs of controlling the fungal infections of crops in the field by using a commercial biofungicide naturally associated with different species of powdery midew fungi. Our results exhibited that the isolation of the mycoparasite Ampelomyces quisqualis from the mildew pathogens was closely associated with most of the genera of powdery mildew pathogens. The natural mycoparasitization efficiency of A. quisqualis was observed and higher (81%) efficiency was recorded in Erysiphe cichoracearum followed by 76% in black gram powdery mildew caused by Erysiphe polygoni. A total of 20 mycoparasitic Ampelomyces isolates were enumerated from pycnidia of 6 different powdery mildew species that naturally infected their host plants. The pycnidial morphological variations of A.quisqualis and the largest size of pycnidia was found in the Erysiphe chichoracearum (73.54µm length × 42.15µm width) shows maximum efficiency in natural parasitization. The molecular characterization of A.quisqualis isolates based on using rDNA ITS region was carried out and sequenced. The phylogenetic analysis was performed using the Maximum likelihood technique was shown the distinct relatedness with five Ampelomyces isolates made in the present study were clustered. This is the first and detailed study on diversity of Ampelomyces and quantification of natural mycoparasitism of different genera of powdery mildew of A. quisqualis.
Devising Bone Molecular Models at the Nanoscale: From Usual Mineralized Collagen Fibrils to the First Bone Fibers Including Hydroxyapatite in the Extra-Fibrillar Volume

At the molecular scale, bone is mainly constituted of type-I collagen, hydroxyapatite, and water. Different fractions of these constituents compose different composite materials that exhibit different mechanical properties at the nanoscale, where the bone is characterized as a fiber, i.e., a bundle of mineralized collagen fibrils surrounded by water and hydroxyapatite in the extra-fibrillar volume. The literature presents only models that resemble mineralized collagen fibrils, including hydroxyapatite in the intra-fibrillar volume only, and lacks a detailed prescription on how to devise such models. Here, we present all-atom bone molecular models at the nanoscale, which, differently from previous bone models, include hydroxyapatite both in the intra-fibrillar volume and in the extra-fibrillar volume, resembling fibers in bones. Our main goal is to provide a detailed prescription on how to devise such models with different fractions of the constituents, and for that reason, we have made step-by-step scripts and files for reproducing these models available. To validate the models, we assessed their elastic properties by performing molecular dynamics simulations that resemble tensile tests, and compared the computed values against the literature (both experimental and computational results). Our results corroborate previous findings, as Young’s Modulus values increase with higher fractions of hydroxyapatite, revealing all-atom bone models that include hydroxyapatite in both the intra-fibrillar volume and in the extra-fibrillar volume as a path towards realistic bone modeling at the nanoscale.
Reinforcement Learning for Collaborative Robots Pick-and-Place Applications: A Case Study

The number of applications in which industrial robots share their working environment with people is increasing. Robots appropriate for such applications are equipped with safety systems according to ISO/TS 15066:2016 and are often referred to as collaborative robots (cobots). Due to the nature of human-robot collaboration, the working environment of cobots is subjected to unforeseeable modifications caused by people. Vision systems are often used to increase the adaptability of cobots, but they usually require knowledge of the objects to be manipulated. The application of machine learning techniques can increase the flexibility by enabling the control system of a cobot to continuously learn and adapt to unexpected changes in the working environment. In this paper we address this issue by investigating the use of Reinforcement Learning (RL) to control a cobot to perform pick-and-place tasks. We present the implementation of a control system that can adapt to changes in position and enables a cobot to grasp objects which were not part of the training. Our proposed system uses deep Q-learning to process color and depth images and generates an ϵ-greedy policy to define robot actions. The Q-values are estimated using Convolution Neural Networks (CNNs) based on pre-trained models for feature extraction. To reduce training time, we implement a simulation environment to first train the RL agent, then we apply the resulting system on a real cobot. System performance is compared when using the pre-trained CNN models ResNext, DenseNet, MobileNet, and MNASNet. Simulation and experimental results validate the proposed approach and show that our system reaches a grasping success rate of 89.9% when manipulating a never-seen object operating with the pre-trained CNN model MobileNet.
Development of a Soft Robotics Module for Active Control of Sitting Comfort

Sitting comfort is an important factor for passengers in selecting cars, airlines, etc. This paper proposes a soft robotic module that can be integrated into the seat cushion to provide better comfort experiences to passengers. Building on rapid manufacturing technologies and a data-driven approach, the module can be controlled to sense the applied force and the displacement of the top surface and actuate according to four designed modes. A total of 2 modules were prototyped and integrated into a seat cushion, and 16 subjects were invited to test the module’s effectiveness. Experiments proved the principle by showing significant differences regarding (dis)comfort. It was concluded that the proposed soft robotics module could provide passengers with better comfort experiences by adjusting the pressure distribution of the seat as well as introducing a variation of postures relevant for prolonged sitting.
Art Making Promotes Mental Health: A Solution for Schools That Time Forgot

This article presents art as a tool for promoting mental health in schools by examining the effects of art making in a sample of 104 school-based mental health professionals. It unites findings from unrelated disciplines to derive and test a new conceptual framework proposing that active engagement in a visual-tactile process over time mediates a shift to healthy mental states and that regular engagement in such process builds mental health capacity. Four hypotheses are tested through psychometrics with statistically significant findings for all (p < .05). Through this study, we advance Flow Theory in identifying a new causal mechanism for accessing Flow; and we make a novel, interdisciplinary contribution to the field of mental health in providing psychometric evidence that making visual art promotes mental health.
Effect of Copper on Expression of Functional Genes and Proteins Associated with Bradyrhizobium diazoefficiens Denitrification

Nitrous oxide (N2O) is a powerful greenhouse gas that contributes to climate change. Denitrification is one of the largest sources of N2O in soils. The soybean endosymbiont Bradyrhizobium diazoefficiens is a model for rhizobial denitrification studies since, in addition to fixing N2, it has the ability to grow anaerobically under free-living conditions by reducing nitrate from the medium through the complete denitrification pathway. This bacterium contains a periplasmic nitrate reductase (Nap), a copper (Cu)-containing nitrite reductase (NirK), a c-type nitric oxide reductase (cNor), and a Cu-dependent nitrous oxide reductase (Nos) encoded by the napEDABC, nirK, norCBQD and nosRZDFYLX genes, respectively. In this work, an integrated study of the role of Cu in B. diazoefficiens denitrification has been performed. A notable reduction in nirK, nor, and nos gene expression observed under Cu limitation was correlated with a significant decrease in NirK, NorC and NosZ protein levels and activities. Meanwhile, nap expression was not affected by Cu, but a remarkable depletion in Nap activity was found, presumably due to an inhibitory effect of nitrite accumulated under Cu-limiting conditions. Interestingly, a post-transcriptional regulation by increasing Nap and NirK activities, as well as NorC and NosZ protein levels, was observed in response to high Cu. Our results demonstrate, for the first time, the role of Cu in transcriptional and post-transcriptional control of B. diazoefficiens denitrification. Thus, this study will contribute by proposing useful strategies for reducing N2O emissions from agricultural soils.
Accessibility to Digital Mental Health Services among the General Public throughout COVID-19: Trajectories, Influencing Factors and Association with Long-Term Mental Health Symptoms

Digital mental health services (DMHSs) have great potential for mitigating the mental health burden related to COVID-19, but public accessibility (ease of acquiring services when needed) to DMHSs during the pandemic is largely unknown. Accessibility to DMHSs was tracked longitudinally among a nationwide sample of 18,804 adults in China from before to one year after COVID-19 outbreak. Unconditional and conditional latent growth curve models and latent growth mixture models were fitted to explore the overall growth trend, influencing factors, and latent trajectory classes of accessibility to DMHSs throughout COVID-19. Generalized estimating equation models and generalized linear mixed models were employed to explore the association between accessibility to DMHSs and long-term mental health symptoms. We found that people generally reported increased difficulty in accessing DMHSs from before to one year after COVID-19 outbreak. Males, youngsters, individuals with low socioeconomic status, and individuals greatly affected by COVID-19 reported greater difficulty in accessing DMHSs. Four DMHS accessibility trajectory classes were identified: “lowest–great increase” (6.3%), “moderate low–slight increase” (44.4%), “moderate high–slight decrease” (18.1%) and “highest–great decrease” (31.2%). Trajectory classes reporting greater difficulty in accessing DMHSs were at higher risk for long-term mental symptoms. In conclusion, an overall increase in difficulty in accessing DMHSs is observed throughout COVID-19, and heterogeneity exists in DMHS accessibility trajectories. Our results suggest that easy access to DMHSs should be consistently facilitated. Moreover, access gaps should be reduced across demographic groups, and target populations for service allocation should alter as the pandemic evolves.
Electronarcosis protocols in broiler chickens for the halal market

Abstract This study considered the parameters of the halal market to evaluate different protocols for broiler electronarcosis regarding time to return of consciousness, bleeding efficiency, and carcass and meat quality at a broiler slaughterhouse. One hundred and eighty-four 43-day-old male broilers of the Cobb® strain were used. The experimental design used was completely randomized with 46 broilers for each protocol. The protocols used 80 V and 600 Hz, 50 V and 1000 Hz, 60 V and 1000 Hz, and 70 V and 1000 Hz. Time to return of consciousness, bleeding efficiency, bruising, presence of broken bones in pectoral muscle, and meat quality were evaluated. Birds subjected to stunning by the 50 V and 1000 Hz protocol showed the shortest time to return of consciousness after electronarcosis, and high incidence of breast hemorrhage. Birds subjected to the 60 V and 1000 Hz protocol had a higher percentage of broken bones in the pectoralis minor. The 50 V and 1000 Hz electronarcosis protocol fits better to the halal market due to the shorter time to return of consciousness and improved bleeding efficiency. This study suggests new proposals for stunning protocols to serve the halal market. Résumé Cette étude a considéré les paramètres du marché halal afin d’évaluer différents protocoles d’électronarcose (ou étourdissement électrique) des poulets à griller en ce qui a trait au temps de retour à la conscience, l’efficacité de la saignée, et la qualité de la carcasse et de la viande dans un abattoir de poulets à griller. Cent quatre-vingt-quatre poulets à griller mâles âgés de 43 jours de race Cobb® ont été utilisés. Le design expérimental utilisé était complètement aléatoire avec 46 poulets à griller pour chaque protocole. Les protocoles utilisés : 80 V et 600 Hz; 50 V et 1000 Hz; 60 V et 1000 Hz; 70 V et 1000 Hz. Le temps pour le retour à la conscience, l’efficacité de la saignée, les contusions, la présence de fractures aux os dans le muscle pectoral, et la qualité de viande ont été évalués. Les poulets ayant subi le protocole 50 V/1000 Hz ont montré la plus courte durée du retour à la conscience après l’électronarcose, et la plus grande incidence d’hémorragie de la poitrine. Les poulets ayant subi le protocole 60 V et 1000 Hz avaient un plus grand pourcentage de fractures d’os dans le Pectoralis minor. Le protocole d’électronarcose 50 V et 1000 Hz convient mieux au marché halal puisqu’il a la plus courte durée du retour à la conscience, et la meilleure efficacité de la saignée. Cette étude suggère de nouvelles propositions en matière de protocoles d’étourdissement pour servir le marché halal. [Traduit par la Rédaction]
Public School Funding, School Quality, and Adult Crime

This paper asks whether improving the quality of public schools can be an effective long-run crime-prevention strategy in the U.S. Specifically, we examine the effect of school quality improvements early in children’s lives on the likelihood that they are arrested as adults. We exploit quasi-experimental variation in school quality due to increases in public school funding, leveraging two natural experiments in Michigan and a novel administrative dataset linking the universe of Michigan public school students to adult criminal justice records. The first research design exploits variation in operating expenditures due to Michigan’s 1994 school finance reform, Proposal A. The second design exploits variation in capital spending by leveraging close school district capital bond elections in a regression discontinuity framework. In both cases, we find that students exposed to additional funding during elementary school were substantially less likely to be arrested in adulthood. We show that the social benefits of improving school quality (via increases in funding) are greater than the costs, even when considering only the crime-reducing benefits. ∗We received valuable feedback from Peter Arcidiacono, Patrick Bayer, Eric Brunner, George Bulman, Eric Chyn, Eric Edmonds, Ezra Goldstein, Max Gross, Nathan Hendren, Kirabo Jackson, Brian Jacob, Max Kapustin, Julien Lafortune, Juan Carlos Suárez Serrato, and seminar and conference participants at Brown University, Cornell University, Dartmouth College, University of Connecticut, University of Michigan, Williams College, the American Economic Association, the Triangle Economists in Applied Microeconomics seminar, the National Tax Association, the Triangle Economics of Education Workshop, the Online Economics of Crime Seminar organized by Jennifer Doleac, and the Policy Impacts Annual Conference. We appreciate Joseph Ryan, Brian Jacob, and the Child and Adolescent Data Lab for their generosity in sharing data, Jonathan Hartman and Kyle Kwaiser for their help with record linkage, and Jasmina Camo-Biogradlija, Andrea Plevek, and Nicole Wagner Lam for coordinating data access. The project received approval from the University of Michigan’s Institutional Review Board: HUM00195369. This research used data structured and maintained by the MERI-Michigan Education Data Center (MEDC). MEDC data are modified for analysis purposes using rules governed by MEDC and are not identical to those data collected and maintained by the Michigan Department of Education (MDE) and/or Michigan’s Center for Educational Performance and Information (CEPI). This research was funded with help from training grants R305B170015 and R305B150012 from the U.S. Department of Education’s Institute of Education Sciences, and the Early Career Scholars Grant at Policy Impacts. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not reflect the views of any other entity. †Duke University and NBER. Email: jason.baron@duke.edu. ‡Amherst College. Email: jhyman@amherst.edu. §University of Michigan. Email: vasqbn@umich.edu.