Miracle-dz/UniFAR-FTUs huggingface dataset:
Distrust in government and its relationship with mental health after the Fukushima nuclear power plant accident

Background: Distrust in authorities has negative effects on mental health. Aims: In this study, we aimed to explore whether the impact of distrust in government on mental health became stronger in the area heavily affected by the 2011 Fukushima nuclear power plant accident. Methods: We examined the effects of distrust in the national government on depressive symptoms three years after the accident among community residents in Fukushima prefecture using those in the Kanto area (the area surrounding Tokyo) as a control. A questionnaire survey was administered to a random sample of 1000 residents in Fukushima prefecture and 1650 residents in the Kanto area. Distrust in the national government was assessed using a four-point single-item scale. Depressive symptoms were measured using the Patient Health Questionnaire-9. The associations of residential area (i.e. living in Fukushima prefecture or in the Kanto area) and distrust in the national government with depressive symptoms were examined, controlling for socio-demographic characteristics and disaster-related experiences using multivariate linear regression analyses. We used the interaction term of residential area and distrust in the government to explore the difference in the association between the respondents in Fukushima prefecture and those in the Kanto area. Results: Valid responses were obtained from 976 (36.8%) residents. Distrust in the government was associated with depressive symptoms and the association was stronger in Fukushima prefecture than in the Kanto area. Conclusion: The deleterious effects of distrust in the government on mental health may become more serious after a nuclear power plant accident and require careful attention during support activities in an affected area.
Toll-like receptor 2 stimulation augments esophageal epithelial barrier integrity

Background A key concept of the hygiene hypothesis is that the microbiome modulates both epithelial barrier integrity as well as host immune responses. Defective expression of tight junction complex proteins alters this homeostatic process, and plays a role in atopic disorders including eosinophilic esophagitis. We tested the hypothesis that Toll-like receptor 2 (TLR2) stimulation improves esophageal barrier function in a cell-intrinsic manner by upregulation of TJ-protein expression using an in vitro model of human epithelium. Methods Pattern recognition receptor expression was assessed in esophageal epithelial cells from patients with EoE and non-EoE control patients. Functional consequences of TLR2 stimulation were investigated using human esophageal EPC2-hTERT cells in the three-dimensional air-liquid interface culture (ALI) model to evaluate transepithelial electrical resistance (TEER) and FITC-Dextran permeability. Characterization of TLR2-stimulated ALI cultures was performed by histology, immunohistochemistry, western blotting and chromatin immunoprecipitation. Results TLR2 stimulation increased TEER (1.28 to 1.31-fold) and decreased paracellular permeability to FITC-Dextran. Notably, TLR2 stimulation-induced increases in TEER were abolished by treatment with anti-TLR2 blocking antibody. Tight junction complex proteins claudin 1 and zonula occludens 1 were increased following TLR2 stimulation, and chromatin immunoprecipitation analysis demonstrated significant increase in histone 4 acetyl binding at the CLDN1 enhancer and promoter following zymosan treatment, implying the occurrence of durable chromatin changes in the esophageal epithelium. Conclusions Our findings reveal that the TLR2 pathway may play a regulatory role as a mechanism that maintains epithelial barrier homeostasis in the esophagus.
Autoantigen presentation by splenic dendritic cells is required for RBC‐specific autoimmunity

Failure of humoral tolerance to red blood cell (RBC) antigens may lead to autoimmune hemolytic anemia (AIHA), a severe and sometimes fatal disease. Previous studies have shown that although tolerance is robust in HOD mice, autoantibodies are generated upon adoptive transfer of OTII CD4+ T cells, which are specific for an epitope contained within the HOD antigen. These data imply that antigen‐presenting cells (APCs) are presenting RBC‐derived autoantigen(s) and are capable of driving T‐cell activation. Given that multiple APCs participate in erythrophagocytosis, we used a transgenic approach to determine which cellular subsets were required for autoantigen presentation and subsequent autoreactive T‐cell activation.
Association of PPE Availability, Training, and Practices with COVID-19 Sero-Prevalence in Nurses and Paramedics in Tertiary Care Hospitals of Peshawar, Pakistan

Abstract Objective: Nurses and paramedics by being the frontline workers of the health-care profession need to be equipped with the relevant knowledge, skills, and protective gears against different forms of infection, including coronavirus disease 2019 (COVID-19). Although the governments and concerned stakeholders have provided personal protective equipment (PPE), training and information to protect the health-care professionals; however, until now the scientific literature has virtually not reported the impact of PPE availability, training, and practices on the COVID-19 sero-prevalence among the nurses and paramedics. This study aimed to assess the impact of PPE availability, training, and practices on COVID-19 sero-prevalence among nurses and paramedics in teaching hospitals of Peshawar, Pakistan. Methods: A cross-sectional survey was conducted with a total of 133 nurses and paramedics as subjects of the study. Results: A univariate analysis was done for 4 variables. The findings indicate that the health-care professionals (nurses and paramedics) who have received PPE on time at the start of COVID-19 emergence have fewer chances of contracting the COVID-19 infection (odds ratio = 0.96); while the odds for PPE supplies was 0.73, and the odds of hand hygiene training was 0.95. Conclusions: The study concluded that the availability of the PPE, COVID-19–related training, and compliance with World Health Organization recommended practices against COVID-19 were instrumental in protection against the infection and its spread.
Coordination of NMCP1- and NMCP2-class proteins within the plant nucleoskeleton.

Plants lack lamin proteins but contain a class of coiled-coil proteins that serve as analogs to form a laminal structure at the nuclear periphery. These Nuclear Matrix Constituent Proteins (NMCPs) play important roles in regulating nuclear morphology and are partitioned into two distinct groups. We investigated Arabidopsis NMCPs (called CRWNs) to study the inter-relationship between the three NMCP1-type paralogs (CRWN1, 2 & 3) and the lone NMCP2-type paralog, CRWN4. An examination of crwn mutants using protein immunoblots demonstrated that CRWN4 abundance depends on the presence of the NMCP1-type proteins, particularly CRWN1. The possibility that CRWN4 is co-imported into the nucleus with NLS-bearing paralogs in the NMCP1-clade was discounted based on recovery of a crwn4-2 missense allele that disrupts a predicted nuclear localization sequence (NLS) and lowers the abundance of CRWN4 in the nucleus. Further, a screen for mutations that suppress the effects of the crwn4-2 mutation, led to the discovery of a missense allele, impa-1G146E, in one of the nine importin-α genes in the Arabidopsis genome. Our results indicate that the CRWN4 carries a functional NLS that interacts with canonic nuclear import machinery. Once imported, the level of CRWN4 within the nucleus is modulated by the abundance of NMCP1 proteins.
Cultural Adaptation of Evidence-Based Lifestyle Interventions for African American Men With Prostate Cancer: A Dyadic Approach

Although a number of lifestyle interventions have been developed for cancer survivors, the extent to which they are effective for African American men with cancer is unclear. Given that African American men have the highest prostate cancer burden and the lack of proven interventions, this study developed a culturally-tailored lifestyle intervention for African American men with prostate cancer and their partners that aimed to improve healthy lifestyle behaviors (physical activity and healthy eating) and quality of life. The aim of the present study is to provide a detailed overview of the model-based process of intervention adaptation. Based on the IM Adapt approach (Highfield et al., 2015) and Typology of Adaptation (Davidson et al., 2013), the present study adapted existing, evidence-based interventions to address African American prostate cancer survivors’ and their partners’ potential unmet needs including anxiety/uncertainty about cancer progression, communication between partners, cultural sensitivity, and concordance/discordance of motivation and behaviors between partners. The intervention adaptation was a comprehensive and fluid process. To the best knowledge of the author, this is the first couple-based lifestyle intervention specifically developed for African American men with prostate cancer. The present study will be highly informative to future investigators by providing flexible and detailed information regarding lifestyle intervention adaptation for racial/ethnic minority men with prostate cancer and their partners.
Understanding Pouch Dysfunction.

To the Editor–The article concerning pouch function written by Lee et al, and published in the Journal in February this year deserves a commentary because, like every article written about bowel function after IPAA, the authors have missed the point. The focus is on describing pouch dysfunction as if it is an inevitable consequence of having a pouch. They describe methods of measuring pouch dysfunction, and the selection of which aspects of dysfunction to report. They have compared dysfunction after IPAA with dysfunction after low anterior resection and have cited a study that compared physician perception of important symptoms post-IPAA with patient perception. The true relevance of studying pouch dysfunction is to learn how to prevent it or mitigate it, and this requires an understanding of why it happens. They have clearly not read the article published in April 2019 in this Journal that discussed pouch physiology in some detail and provided a rational explanation for the defecation pattern patients experience after IPAA. Here are the key points of this article.
Theseus: an Experiment in Operating System Structure and State Management

This paper describes an operating system (OS) called The-seus. Theseus is the result of multi-year experimentation to redesign and improve OS modularity by reducing the states one component holds for another, and to leverage a safe programming language, namely Rust, to shift as many OS re-sponsibilities as possible to the compiler. Theseus embodies two primary contributions. First, an OS structure in which many tiny components with clearly-deﬁned, runtime-persistent bounds interact without holding states for each other. Second, an intralingual approach that realizes the OS itself using language-level mechanisms such that the compiler can enforce invariants about OS semantics. Theseus’s structure, intralingual design, and state management realize live evolution and fault recovery for core OS components in ways beyond that of existing works.
Secreted protein acidic and rich in cysteine (SPARC) knockout mice have greater outflow facility

Purpose Secreted protein acidic and rich in cysteine (SPARC) is a matricellular protein that regulates intraocular pressure (IOP) by altering extracellular matrix (ECM) homeostasis within the trabecular meshwork (TM). We hypothesized that the lower IOP previously observed in SPARC -/- mice is due to a greater outflow facility. Methods Mouse outflow facility (Clive) was determined by multiple flow rate infusion, and episcleral venous pressure (Pe) was estimated by manometry. The animals were then euthanized, eliminating aqueous formation rate (Fin) and Pe. The C value was determined again (Cdead) while Fin was reduced to zero. Additional mice were euthanized for immunohistochemistry to analyze ECM components of the TM. Results The Clive and Cdead of SPARC -/- mice were 0.014 ± 0.002 μL/min/mmHg and 0.015 ± 0.002 μL/min/mmHg, respectively (p = 0.376, N/S). Compared to the Clive = 0.010 ± 0.002 μL/min/mmHg and Cdead = 0.011 ± 0.002 μL/min/mmHg in the WT mice (p = 0.548, N/S), the Clive and Cdead values for the SPARC -/- mice were higher. Pe values were estimated to be 8.0 ± 0.2 mmHg and 8.3 ± 0.7 mmHg in SPARC -/- and WT mice, respectively (p = 0.304, N/S). Uveoscleral outflow (Fu) was 0.019 ± 0.007 μL/min and 0.022 ± 0.006 μL/min for SPARC -/- and WT mice, respectively (p = 0.561, N/S). Fin was 0.114 ± 0.002 μL/min and 0.120 ± 0.016 μL/min for SPARC -/- and WT mice (p = 0.591, N/S). Immunohistochemistry demonstrated decreases of collagen types IV and VI, fibronectin, laminin, PAI-1, and tenascin-C within the TM of SPARC -/- mice (p < 0.05). Conclusions The lower IOP of SPARC -/- mice is due to greater aqueous humor outflow facility through the conventional pathway. Corresponding changes in several matricellular proteins and ECM structural components were noted in the TM of SPARC -/- mice.
The SpinalMeter biometrical assessment to improve posture diagnosis in school-age girls: a validation study

Mater ia l and methods : The measurements of the angle of trunk rotation (ATR) and SpinalMeter posture assessments were performed 8 to 10 times in a short period of time (6 s). The overall of 300 photos (SpinalMeter) and 1020 measurements (asymmetry, distance between anthropometric points as well as ATR) were obtained from 6 girls (8–15 years old). The validation study comprised of the repeatability, interclass correlation coefficient (Qw) and relative standard deviation (rSD) measurements.
Digital Fleet Management: A Scalable Cloud Framework based on Data-driven Prediction Models

A scalable Digital Fleet Management system can be leveraged by most organizations with high-volume high-value assets. In such scenarios, predictive analytics for tool health becomes central, as it enables decision-making in terms of planning, maintenance, end-of-life replacement, tool selection, etc. End-to-end solutions, spanning all the way from gathering live tool data to the visual representation of tool health, are certainly of major interest. Long-term fleet management can be accomplished through a consistent evaluation of the fleet performance profile. Predictive analysis can anticipate maintenance needs and resultant downtimes, and in turn it helps improve scheduling of procurement and distribution of the fleet. This paper focuses on managing a fleet of thousands of downhole tools based on tool health condition and other variables – a very common use case in Oil & Gas Services. An end-to-end automated scalable cloud framework is described in detail. This framework integrates failure prediction models for each single asset in the fleet of tools. Based on historical tool data, the models generate tool risk indices (one index per asset) which correlate to the probability of tool failure during near-future field jobs. These risk indices can be used for optimal asset-to-job mapping. They also help in de-risking field operations by identifying tools for overhaul or retirement. The proposed method integrates the tasks of: fetching data from 200,000+ tools, performing feature engineering, modeling via Machine Learning (ML) , and visualizing into a cloud pipeline. Framework scalability becomes a key requirement as fleet size increases or decreases over time to match market demands. The framework also allows for the addition of new ML models to the platform by citizen data scientists, who are not cloud experts. Finally, it is shown who this framework provides systematic steps for sustenance of such large cloud platform.
FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression

Despite their great success in various ﬁelds, modern convolutional neural networks (CNNs) require huge amount of computation in inference due to their deeper network structure, which prevents them from being used in resource-limited devices such as mobile phones and embedded sensors. Recently, ﬁlter pruning had been introduced as a promising model compression method to reduce computation cost and storage overhead. However, existing ﬁlter pruning approaches are mainly model-based, which rely on empirical model to evaluate the importance of ﬁlters and set parameters manually to guide model compression. In this paper, we observe that CNNs commonly consist of large amount of inactive ﬁlters, and introduce Filter Inactive RatE (FIRE), a novel metric to evaluate the importance of ﬁlters in a neural network. Based on FIRE, we develop a learning based ﬁlter pruning strategy called FIREPruning for fast model compression. It adopts a regression model to predict the FIRE value and uses a three stage pipeline (FIRE prediction, pruning, and ﬁne-tuning) to compress the neural network eﬃciently. Extensive experiments based on widely-used CNN models and well-known datasets show that FIREPruning reduces overall computation cost up to 86.9% without sacriﬁcing too much accuracy, which signiﬁcantly outperforms the state-of-the-art model compression methods.
Avian remains from the Early Bronze Age settlement near Dyadovo village (vicinity of the town of Nova Zagora, Stara Zagora Region, SE Bulgaria)

BOEV Z. 2006. Avian remains from the Early Bronze Age settlement near Dyadovo village (vicinity of the town of Nova Zagora, Stara Zagora Region, SE Bulgaria). – Historia naturalis bulgarica, 17: 133-135. Abstract. Nineteen bird bone remains (MNI=7), dated ca. 5000 B.P. of Coturnix coturnix, Gallus gallus domestica and Otis tarda have been identified. This is the second site in Bulgaria proving the existence of poultry-breeding in the Eneolithic-Early-Bronze-Age period. It is also the tenth archaeological site of the Great Bustard in the country.
Gesture Sample Classification Algorithm Construction of Gaussian Mixture Model Extract Head Feature Set Classificatio n Result

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common mental-health disorders, affecting around 5%-10% of school-age children. This paper details about various methodologies for detecting and diagnosing the ADHD disease in patients using different soft computing and deep learning techniques. The limitations of advantages of each ADHD method were discussed in detail with its corresponding simulation results. The feature extraction method and its training with classification procedure for each conventional ADHD method were illustrated in detail.
Abating Biomechanical Risks: A Comparative Review of Ergonomic Assessment Tools

Ergonomic assessment tools are crucial for evaluation of biomechanical risk factors at workplaces to understand the contributing factors and reduce the prevalence of musculoskeletal disorders (MSDs) which have negative implications on employees’ health and productivity. This review examines a range of methods and ergonomic assessment tools. It shows ergonomic assessment tools, particularly postural analysis to comprise self-reports from workers, observation methods, direct measurement method and advanced techniques for assessment of postural change in executing highly dynamic activities. These tools have been designed for different work activities consisting typically of manual handing, repetitive tasks and static loading. Some of the tools target at specific body parts while others at multiple body parts. The tools have the strengths particularly in the assessment of recurring tasks in standing or sitting postures involving specific or multiple body parts. However, the tools also have obvious limitations in terms of not considering vibration, contact stress and trauma to other body parts for tools assessing specific body parts, and undifferentiated weight of different ergonomic risks for whole-body tools. These strengths and shortcomings prompt a user to consider the job nature and tasks to be assessed prior to selecting the tools. This review advocates an integrated approach in ergonomic assessment using a combination of general and specific methods with direct measurements if permissible. It contributes to the accurate selection of the postural analysis tools through systematically presenting their features and limitations besides highlighting improvement of methods and approaches in ergonomic assessment. Review Article Tang; JERR, 17(3): 41-51, 2020; Article no.JERR. 62146 42
Review of Laser Raman Spectroscopy for Surgical Breast Cancer Detection: Stochastic Backpropagation Neural Networks

Laser Raman spectroscopy (LRS) is a highly specific biomolecular technique which has been shown to have the ability to distinguish malignant and normal breast tissue. This paper discusses significant advancements in the use of LRS in surgical breast cancer diagnosis, with an emphasis on statistical and machine learning strategies employed for precise, transparent and real-time analysis of Raman spectra. When combined with a variety of “machine learning” techniques LRS has been increasingly employed in oncogenic diagnostics. This paper proposes that the majority of these algorithms fail to provide the two most critical pieces of information required by the practicing surgeon: a probability that the classification of a tissue is correct, and, more importantly, the expected error in that probability. Stochastic backpropagation artificial neural networks inherently provide both pieces of information for each and every tissue site examined by LRS. If the networks are trained using both human experts and an unsupervised classification algorithm as gold standards, rapid progress can be made understanding what additional contextual data is needed to improve network classification performance. Our patients expect us to not simply have an opinion about their tumor, but to know how certain we are that we are correct. Stochastic networks can provide that information.
Hypericum ascyron L. extract reduces particulate matter‐induced airway inflammation in mice

The consequences of increased industrialization increased the risk of asthma and breathing difficulties due to increased particulate matter in the air. We aim to investigate the therapeutic properties of Hypericum ascyron L. extract (HAE) in airway inflammation and unravel its mechanism of action. We conducted nitric oxide and cell viability assay, real‐time PCR and western blot analyses along with in vitro studies. in vivo studies include a model of coal fly ash and diesel exhaust particle (CFD)‐induced airway inflammation in mice. HAE reduced coal fly ash (CFA)‐induced nitric oxide secretion without exhibiting cytotoxicity in MH‐S cells. HAE also reduced the mRNA expression of pro‐inflammatory cytokines and reduced the expression of proteins in the NFκB and MAPK pathways. In a mice model of CFD‐induced airway inflammation, HAE effectively reduced neutrophil infiltration in bronchoalveolar lavage fluid (BALF) and increased the amount of T cells in the BALF, lungs, and blood while reducing all other immune cell subtypes to reduce airway inflammatory response. CXCL‐1, IL‐17, MIP‐2, and TNF‐α expression in the BALF were also reduced. HAE effectively reduced MIP‐2 and TNF‐α mRNA expression in the lung tissue of mice. In a nutshell, HAE is effective in preventing airway inflammation induced by CFA in MH‐S cells, as well as inflammation induced by CFD in mice.