Miracle-dz/UniFAR-FTUs huggingface dataset:
Health Equity Lens Embedded in the Public Health Policies of Saudi Arabia: A Qualitative Document Analysis

In the Kingdom of Saudi Arabia (KSA), no studies have been documented to analyze the equity aspects of public health policies. The aims of the study were to identify policy documents in the KSA relevant to public health and to explore whether these include an equity approach. Twenty health-related documents were identified from various ministries’ websites and analyzed through directed content analysis. The results showed that the term “equity” was neither defined nor explained in the documents and suggestions on how to tackle health inequities were lacking. None of the suggested measures communicated an explicit focus on promoting health equity or the social gradient. Several upstream, midstream, and downstream measures were suggested to improve justice and public health for the people. The study reveals that there is a need for an in-depth assessment of the policy measures across sectors and their influence on health equity to inform future health policy development and action in the KSA.
Firefighter With Co-Morbid Psychogenic Non-Epileptic Seizures and Post-Traumatic Stress Disorder Treated With Prolonged Exposure Therapy: Long-Term Follow-Up

Psychogenic non-epileptic seizures (PNES), are events that resemble epileptic seizures but lack electrophysiological or clinical evidence for epilepsy. Instead, they are psychogenic in origin. These episodes tend to occur with alterations in consciousness and bodily functions and are the result of mechanisms of conversion. Psychological trauma and post-traumatic stress disorder (PTSD) are prevalent among patients with PNES. This is a case report of a 32-year-old male who began treatment 1-year after developing PTSD followed some months later by PNES. His seizures were characterized by contorted movements of the head and neck, guttural sounds, and left sided movements or whole-body arching and were accompanied by frequent falls and injuries. They were usually brief but occurred daily. Psychotherapy had been discontinued because violent seizures often interrupted the sessions. He was treated with prolonged exposure (PE) at a PNES program and by the last session, had achieved an improvement in his seizure frequency (one every 4–6 days rather than daily episodes). This allowed him to begin therapy with a local therapist. Two years after completing treatment, the patient returned for a follow up visit. At that point, his seizure frequency, was one per month which shows he sustained and improved on this symptom. Former head drops, and grunting sounds disappeared, and he was no longer using a cane to ambulate. From an emotional standpoint (PTSD, suicidality, anxiety, quality of life), the patient had achieved and maintained a much healthier level of functioning (though no change on alexithymia, anger, depression, and trait anxiety).
Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark Target Algorithm: 2. Nonspherical Dust Model

The Dark‐target (DT) aerosol algorithm retrieves spectral Aerosol Optical Depth (AOD) and other aerosol properties from Moderate‐resolution Imaging Spectrometer (MODIS) reflectance observations. Over the ocean, the DT algorithm is known to contain scattering‐angle‐dependent biases in its retrievals of AOD, Angstrom Exponent (AE), and Fine Mode Fraction (FMF) for dust aerosols. Following a two‐step strategy to improve the DT retrieval of dust over ocean, for which the first step is to identify dusty pixels (reported in “Part 1”), in this “Part 2,” we report on construction of a new dust model lookup table (LUT) and the strategy for applying it within the existing DT algorithm. In particular, we evaluate different characterizations of dust optical properties from a variety of frameworks and databases, and compare them with the current DT retrieval assumptions. Substituting the standard operational LUT with a spheroid dust model with identified dusty pixels shows significant improvement when compared with collocated AERONET‐identified dusty pixels. Specifically, the application of the new dust model to dusty pixels reduces their AOD bias from 0.06 to 0.02 while improving the fraction of retrievals within expected error from 64% to 82%. At the same time, the overall bias in AE is reduced from 0.13 to 0.06, and the scattering‐angle‐dependent AE bias is largely eliminated. In testing on two full months of data (April and July), the new retrieval will reduce the monthly mean AOD by up to 0.1 and 0.2 in the north Atlantic and Arabian seas, respectively. The average AE and FMF are also reduced in these dust heavy regions.
The Role of Alpha Defensins in Patients with Ankylosing Spondylitis

Abstract Objectives Defensins are a family of antimicrobial peptides. Elevated levels of human neutrophil peptides (HNP 1–3) are seen in blood samples of patients with inflammatory bowel disease (IBD) and in many rheumatic diseases. It has been suggested that they may play a significant role in the progression and pathogenesis of these diseases. Therefore, we aimed to investigate the levels of HNP 1–3 in sera of patients with ankylosing spondylitis (AS) and its association with disease activity and other clinical features of AS. Methods A total of 36 patients, who met the Modified New York Criteria for AS, and 50 healthy controls (HCs) were included in this study. The Bath AS Disease Activity Index (BASDAI) and the Ankylosing Spondylitis Disease Activity Score (ASDAS) were used to assess disease activity. The Bath AS Radiology Index (BASRI) was used to assess radiological damage. Spinal and hip measurements were determined by the Bath AS Metrology Index (BASMI). An AS Quality of Life (ASQoL) questionnaire was administered to assess the disease-related quality of life. Serum HNP 1–3 levels were determined using the ELISA kit. Results Mean serum HNP 1–3 levels were significantly higher in patients with AS (287.01±201.307 vs. 152.09±43.75 pg/ml) compared with HCs (p=0.001). HNP 1–3 levels did not correlate with BASDAI (p=0.519), ASDAS-CRP (p=0.424), BASRI (p=0.280), BASMI (p=0.168), ASQoL (p=0.307), ESR (p=0.706) and CRP (p=0.157) values. Conclusion Elevated serum levels of HNP 1–3 may play an important role in the pathogenetic mechanisms of AS. This result may give us an opportunity to develop new treatment strategies considering the role of these peptides in the pathogenetic mechanisms of AS.
The myology of the Amazonian Manatee, Trichechus inunguis (Natterer) (Mammalia: Sirenia)

The muscles of the Amazon ian manatee are described and compared w i th those of other manatees and the dugong. Maps of muscle a t tachments and data on weights of muscles are inc luded. The manatee species d i f fe r in the forms of the m m . rectus capit is lateral is and biceps b rach i i . The mechanisms of protrusion of upperl ip bristles and opening of the nostri ls are descr ibed. The jaw apparatus is uniquely special ized, w i t h a very large temporal is muscle const i tu t ing more than hal f the adductor muscle mass, and development of a jo in t between the pterygoid process and the mandible which probably braces the mandible dur ing transverse chewing . The center of mandibular ro tat ion in transverse chewing probably lies posteromedial to the pterygoid process on the act ive side : the contra la tera l temporal is is dominant in transverse chewing . Trichechus inunguis is more specialized fo r surface-feeding and for swimming than T. ma not us. RESUMO : Os músculos do peixe-boi da Amazôn ia sâo descritos e comparados àqueles dos outros peixes-bois e do dugong . Mapas das ligações dos músculos aos ossos, e dados sobre pesos dos músculos, sâo inc luídos. Notam-se diferenças entre as espécies de peixes-bois com respeito aos músculos rectus capi t is lateral is e biceps b rach i i . Descrevem-se o mecanismo de protrusão das cerdas do lábio superior, e o mecanismo de abertura das nar inas. O aparelho mast i catór io é unicamente especial izado, com um temporal is mu i to grande, const i tu indo mais que metade do peso dos músculos adutores, e com uma art iculação entre o processo pter igoídeo e a mand íbu la . Esta provavelmente apoia a mandíbula na mast igação t ransversal . O centro de rotação da mandíbu la na mast igação transversal parece f icar posteromedial ao processo pter igoí deo no lado a t i vo ; o temporal is do outro lado fornece a maior ia da força para esta ro tação. O Trichechus inunguis é mais especializado do que o T . manatus para se a l imentar perto da superfície da água, e para nadar .
Low doses of monensin for lambs fed diets containing high level of ground flint corn

Two experiments were proposed to evaluate the addition of monensin for lambs fed diets containing a high level of mature ground flint corn. The experimental diets were as follows: no inclusion of monensin (M0) and inclusion of 8 (M8), 16 (M16) and 24 mg kg–1 of monensin (M24). In experiment 1, eight cannulated wethers were divided into a double 4 × 4 Latin square experimental design to evaluate nutrient digestibility, plasma parameters and rumen fermentation. The experiment lasted 112 days, divided into four periods of 28 days each. In experiment 2, ninety-two lambs were used in a randomized block design to evaluate the performance over 56 days. In experiment 1, doses of monensin had no effect on nutrient intake (p ≥ 0.07) and digestibility (p ≥ 0.09). There was a quadratic effect for acetate molar proportion (p = 0.01), acetate to propionate ratio (p = 0.04) and rumen pH (p < 0.01). However, there was no effect on the molar proportion of propionate and butyrate. The monensin decreased linearly the total SCFA concentration (p < 0.01). The inclusion of monensin increased glucose (p < 0.01) and decreased lactate concentration in plasma (p = 0.05). In experiment 2, monensin decreased dry matter intake (p = 0.04). However, there was a quadratic effect for average daily gain (p = 0.03) and feed efficiency (p < 0.01), with the greatest values observed for the M8 diet. Thus, the inclusion of 8 mg kg–1 of dry matter diet (DM) improves ruminal fermentation and plasma parameters, resulting in greater growth performance in lambs.
Direct inference of base-pairing probabilities with neural networks improves RNA secondary structure prediction with pseudoknots

Motivation Existing approaches for predicting RNA secondary structures depend on howto decompose a secondary structure into substructures, so-called the architecture, to define their parameter space. However, the architecture has not been sufficiently investigated especially for pseudoknotted secondary structures. Results In this paper, we propose a novel algorithm to directly infer base-pairing probabilities with neural networks that does not depend on the architecture of RNA secondary structures, followed by performing the maximum expected accuracy (MEA) based decoding algorithms; Nussinov-style decoding for pseudoknot-free structures, and IPknot-style decoding for pseudoknotted structures. To train the neural networks connected to each base-pair, we adopt a max-margin framework, called structured support vector machines (SSVM), as the output layer. Our benchmarks for predicting RNA secondary structures with and without pseudoknots show that our algorithm achieves the best prediction accuracy compared with existing methods. Availability The source code is available at https://github.com/keio-bioinformatics/neuralfold/. Contact satoken@bio.keio. ac.jp
Pedestrian Re-ID Based on Improved Triplet Loss

Person re-identification technology is an important foundation for security, pedestrian tracking and other fields, and is the key to building a safe and smart city. In recent years, a large number of researchers have trained pedestrian re-identification networks through triplet loss, especially the triplet loss with batch hard mining (BHTri loss) has greatly improved person re-identification networks on accuracy. However, triplet loss with batch hard mining for an anchor sample only select the hardest positive sample and the hardest negative sample to calculate the loss, ignoring the influence of other samples on network parameters. In response to the above issues, this paper proposes a variant of triplet loss with batch hard mining, which is called adaptive weight triplet loss with batch hard mining. After the training dataset extracts features from the backbone network, in the phase of calculating loss, it takes the average of the sum of the distances between an anchor sample and all corresponding positive samples as a threshold, and both positive samples with an anchor point distance greater than the threshold and negative samples smaller than the threshold are retained, then based on The distance of the anchor sample is given the corresponding sample weight for calculating the loss. Compared with BHTri, mAP have improved 1.79%, 2.04%, and 1.25% respectively on the Market1501, DukeMTMC-reID and CUHK03 datasets, indicating that the proposed algorithm is effective.
Status Politics and the Political Influences of Concealed Handgun License Demand in Texas

ABSTRACT Do political dynamics inform concealed handguns demand better than crime levels? In this study we argue and find support for the idea that handgun demand is a product of status politics, displays of political symbolism in response to real or perceived threats to those supporting gun rights and conservative values. We also compare this argument with previous explanations of handgun demand such as crime rates and racial demographics. We find locations supporting conservative political views do have greater rates of CHL applications during moments when status politics were most likely while less support is found for criminal justice predictors.
Species assemblages and community structure of deep-sea demersal ichthyofauna of the South-eastern Arabian Sea (SEAS)

Studies of species assemblages and community structure are of vital importance in the deep-sea realm. Data for the present study were collected during the research expedition of FORV ‘Sagar Sampada’ in the latitude 8.02°N and 11.58°N, longitude 74.16°E and 78.35°E. High Speed Demersal Trawl – Crustacean Version (HSDT-CV) was used for the operations at a depth of 200 and 1000 m. The total catch came to 2148.35 kg from 10 stations. An analysis of the catch composition was made. Total catch was dominated by Priacanthus hamrur (27.66%) followed by Neoepinnula orientalis (15.57%), Psenopsis cyanea (10.05%), Glyptophidium oceanium (3.55%), Lamprogrammus niger (3.17%), Narcine timlei (3.08%), Lamprogrammus sp. (2.6%), Pterigotrygla hemisticta (2.17%). About 76 species recorded from 22 orders were identified. The diversity indices, Cluster analysis, k-dominance plot were analysed using PRIMER v6 software. The diversity indices including Margalef richness index (d), Shanon index (log e2), Pielou's evenness index (J′) and Simpson diversity index (1 − λ) were calculated. Diversity indices were compared with the previous studies in the same area, and this can be a reference point for future studies.
Situational awareness extraction: a comprehensive review of social media data classification during natural hazards

ABSTRACT Social media (e.g., Twitter and Facebook) can be regarded as vital sources of information during disasters to improve situational awareness (SA) and disaster management since they play a significant role in the rapid spread of information in the event of a disaster. Due to the volume of data is far beyond the capabilities of manual examination, existing works utilize natural language processing methods based on keywords, or classification models relying on features derived from text and other metadata (e.g., user profiles) to extract social media data contributing to SA and automatically categorize them into the relevant classes (e.g., damage and donation). However, the design of the classification schema and the associated information extraction methods are far less than straightforward and highly depend on: (1) the event type, (2) the study or analysis purpose, and (3) the social media platform used. To this end, this paper reviews the literature for extracting social media data and provides an overview of classification schemas that have been used to assess SA in events involving natural hazards from five different analytical perspectives (content, temporal, user, sentiment, and spatiotemporal) by discussing the prevalent topic categories, disaster event types, purpose of studies, and platforms utilized from each schema. Finally, this paper summarizes classification methods, and platforms that are most commonly used for each disaster event type, and outlines a research agenda with recommendations for future innovations.
Biological traits explain bryophyte species distributions and responses to forest fragmentation and climatic variation

Forest ecosystems have been subjected to intensive exploitation, and on top of these land use‐driven habitat alterations, there is an ongoing and rapid climate change. Understanding why environmental responses differ across species and how differences are mediated by species’ traits is crucial for predicting the complex effects of global change on forest biodiversity. We used (1) single‐species distribution models and (2) multispecies predictive fourth‐corner models of varying complexity to identify critical response traits of dead wood inhabiting bryophytes and to quantify species’ relationships with climatic and forest landscape variation. We hypothesized that reproductive and life‐history traits would be mainly linked with forest connectivity, whereas morphological traits would mostly relate to (micro‐)climatic variation. The inferred trait–environment relationships based on the different fourth‐corner models were consistent. Unexpectedly, reproduction modes were more closely linked to climatic and habitat factors than to forest connectivity. Sexual reproduction was positively related to high temperatures and broadleaf trees, but negatively to high amounts of precipitation. The opposite was true for species which predominantly, or additionally, reproduce asexually. Bryophyte life‐forms were related to both habitat and climatic conditions. The positive relationship of shoot length with both high temperatures and high amounts of precipitation suggested that competitive exclusion is important in determining trailing edges of dead wood inhabiting bryophytes. Synthesis. Differences in physiological tolerances obviously play a much greater role in shaping the distributional pattern of bryophyte species with different reproductive systems than previously thought. Evidence suggests that current geographic ranges were primarily determined by physiological tolerances and competitive abilities. Species’ relationships with forest connectivity were complex and determined by the combination of reproductive traits with other critical species’ properties. Given the different species’ relationships with climatic gradients, and the varying species’ dispersal and competitive capacities, we expect clear changes in metacommunity composition following climate change and an overall decrease in the diversity of dead wood inhabiting bryophytes in Sweden.
Peripheral elaboration model: The impact of incidental news exposure on political participation

ABSTRACT This study places the “cognitive elaboration model” on news gathering and political behavior within the dual-processing “elaboration likelihood model” to derive hypotheses about the effects of incidental news exposure and tests them using two-wave panel data. Results indicate incidental news exposure predicts online participation but not offline participation – underlining the importance of differentiating between political behaviors in the two environments. The key finding, however, is that news elaboration mediates the positive relationship between incidental exposure and political participation, which is theorized as taking place through the peripheral route of elaboration – as opposed to intentional exposure, which engages the central route.
Safely Reopening K-12 Schools During the COVID-19 Pandemic

Early school closures were a consistent, nationwide response to the COVID-19 pandemic in mid-March due to the role that children play in spreading influenza. This left us with limited understanding of COVID-19 transmission in children until several states reopened schools for the 2020-2021 school year. While early school closures were likely beneficial in protecting children in the initial stages of the pandemic in the U.S., long-term closures pose significant cumulative effects in children who rely on schools for instruction and additional social services, and for parents who need to balance work and childcare obligations. Reopening schools safely is a high priority for many interested stakeholders.Proposed in-person school reopening plans include traditional, 100% school capacity, five days per week instruction, hybrid scenarios with reduced in-person instruction and virtual learning, and various reduced school capacity schedules with non-pharmaceutical interventions in place. To assess the potential impacts of different reopening plans, we created a modified SIR-type transmission model that captures multiple known pathways of COVID-19 transmission in a 100,000-person community.Our results show that plans that utilize consecutive days in school and divide students into separated smaller cohorts who attend school together, as well as plans that emphasize distance learning, are better able to suppress disease spread and reduce risk from an introduced infective into the community. Plans with more consecutive school days are protective for both the schoolchildren and surrounding community by acting to separate the larger intermixing population into smaller intermixing subpopulations. The “Five-Day Switch” plan, which separates students into two cohorts, each of whom attend in-person learning for five consecutive days followed by five days of distance learning, best captures these protective attributes. All modeled plans assumed initially disease-free communities and that children’s interactions with the community are greatly reduced during instructional days, both for in-person and distance learning.
Homogeneous region regularized multilayer non-negative matrix factorization for hyperspectral unmixing

Abstract. Hyperspectral unmixing is one of the most important procedures for remote sensing image processing. The multilayer non-negative matrix factorization (MLNMF)-based method has been widely used for hyperspectral unmixing due to its good performance for highly mixed data with multiple-decomposition structure. However, few works consider the spatial information in the image, which may enhance the performance. In order to solve this issue, we propose a homogeneous region regularized multilayer non-negative matrix factorization (HR-MLNMF) method for hyperspectral unmixing. In HR-MLNMF, the spatial information, depicted by the homogeneous region, is applied to regularize MLNMF, which could enhance the smoothness of each homogeneous spatial field to achieve better performance. Experiments on both synthetic and real datasets have validated the effectiveness of our method and shown that it has outperformed several state-of-the-art approaches of hyperspectral unmixing.
6 Computational Modeling of Long-Distance Space Exploration A Guide to Predictive and Prescriptive Approaches to the Dynamics of Team Composition

Introduction . 108 Computational Modeling and Space Teams . 111 Motivating ABMs for Space Team Composition . 113 Developing an Agent-based Model for Crew Composition Effects . 115 Model Construction . 116 Defining Model Scope . 116 Theory, Prior Empirical Research, and Meta-Analysis . 117 An Integrated Model of Team Composition . 117 Model Calibration . 119 Model Validation . 121 Model Application . 123 Virtual Experiments . 123 Translating Science to Practice . 123