Miracle-dz/UniFAR-FTUs huggingface dataset:
Image-based sexual abuse

This book investigates the causes and consequences of image-based sexual abuse in a digital era. Image-based sexual abuse refers to the taking or sharing of nude or sexual photographs or videos of another person without their consent. It includes a diversity of behaviours beyond that of “revenge porn”, such as the secret trading of nude or sexual images online; “upskirting”, “downblousing” and other “creepshots”; blackmail or “sextortion” scams; the use of artificial intelligence to construct “deepfake” pornographic videos; threats to distribute photographs or videos without consent; and the taking or sharing of sexual assault imagery. This book investigates the pervasiveness and experiences of these harms, as well as the raft of legal and non-legal measures that have been introduced to better respond to and prevent image-based sexual abuse. The book draws on groundbreaking empirical research, including surveys in three countries with over 6,000 respondents and over 100 victim-survivor and stakeholder interviews. Guided by theoretical frameworks from gender studies, sociology, criminology, law and psychology, the authors argue that image-based sexual abuse is more commonly perpetrated by men than women, and perpetration is higher among some groups, including younger men and sexual minority men. Although the motivations of perpetrators vary, a dominant theme to emerge was that of power and control. The gendered nature of the abuse means that it is best understood as a being on a “continuum of sexual violence” because victim-survivors often experience it as part of a broader pattern of gendered harassment, violence and abuse. Written in a clear and direct style, this book will appeal to students and scholars of criminology, sociology, law and psychology. Image-based sexual abuse is also an essential resource for activists, legal and policy practitioners, technology companies and victim-survivors seeking to understand the deeply complex nature of intimate-image sharing in a digital era.
Real-Time Monitoring of Grazing Cattle Using LORA-WAN Sensors to Improve Precision in Detecting Animal Welfare Implications via Daily Distance Walked Metrics

Simple Summary Global positioning system (GPS) coordinates are often used to calculate distance traveled, a useful metric for research and decision-making processes in livestock management. The study aimed to determine the accuracy of using LoRa-WAN sensors to measure the walking distances of grazing cattle in real time. The study compared the accuracy of distance computation using real-time LoRa-WAN sensed GPS alone or in combination with motion data from triaxial accelerometers. The analysis showed that the fusion of GPS and accelerometer data was more suitable for calculating walking distance in detecting animal welfare implications associated with immobility. Abstract Animal welfare monitoring relies on sensor accuracy for detecting changes in animal well-being. We compared the distance calculations based on global positioning system (GPS) data alone or combined with motion data from triaxial accelerometers. The assessment involved static trackers placed outdoors or indoors vs. trackers mounted on cows grazing on pasture. Trackers communicated motion data at 1 min intervals and GPS positions at 15 min intervals for seven days. Daily distance walked was determined using the following: (1) raw GPS data (RawDist), (2) data with erroneous GPS locations removed (CorrectedDist), or (3) data with erroneous GPS locations removed, combined with the exclusion of GPS data associated with no motion reading (CorrectedDist_Act). Distances were analyzed via one-way ANOVA to compare the effects of tracker placement (Indoor, Outdoor, or Animal). No difference was detected between the tracker placement for RawDist. The computation of CorrectedDist differed between the tracker placements. However, due to the random error of GPS measurements, CorrectedDist for Indoor static trackers differed from zero. The walking distance calculated by CorrectedDist_Act differed between the tracker placements, with distances for static trackers not differing from zero. The fusion of GPS and accelerometer data better detected animal welfare implications related to immobility in grazing cattle.
Automatic extraction and reconstruction of a 3D wireframe of an indoor scene from semantic point clouds

ABSTRACT Accurate indoor 3D models are essential for building administration and applications in digital city construction and operation. Developing an automatic and accurate method to reconstruct an indoor model with semantics is a challenge in complex indoor environments. Our method focuses on the permanent structure based on a weak Manhattan world assumption, and we propose a pipeline to reconstruct indoor models. First, the proposed method extracts boundary primitives from semantic point clouds, such as floors, walls, ceilings, windows, and doors. The primitives of the building boundary are aligned to generate the boundaries of the indoor scene, which contains the structure of the horizontal plane and height change in the vertical direction. Then, an optimization algorithm is applied to optimize the geometric relationships among all features based on their categories after the classification process. The heights of feature points are captured and optimized according to their neighborhoods. Finally, a 3D wireframe model of the indoor scene is reconstructed based on the 3D feature information. Experiments on three different datasets demonstrate that the proposed method can be used to effectively reconstruct 3D wireframe models of indoor scenes with high accuracy.
HSMH: A Hierarchical Sequence Multi-Hop Reasoning Model With Reinforcement Learning

The incompleteness of knowledge graphs (KGs) negatively impacts the performance of KGs in downstream applications (e.g., recommendation systems and information retrieval). This phenomenon has brought an increasing rise in research related to knowledge graph reasoning. Recently, emerged reinforcement learning-based multi-hop reasoning methods can infer missing information through multi-hop reasoning according to the existing information in KGs, which has better reasoning performance and interpretability. However, these methods always use relation-entity pairs that have been pre-cropped as the action space of agents for path reasoning, which leads to two problems: 1) insufficient learning and reasoning ability of reasoning models and 2) the hard convergence of the training process of agents. To address these problems, we propose a Hierarchical Sequence Multi Hop (HSMH) reasoning framework, which consists of the interactive search reasoning model, local-global knowledge fusion mechanism, and action optimization mechanism. We use interactive search reasoning models to select relations and entities independently, thus fully mining the semantic information of relations and entities and improving the learning and reasoning ability of reasoning models. In the HSMH framework, we design the local-global knowledge fusion mechanism to acquire the local knowledge of entities and neighboring relations and the global knowledge about KG structure, which can improve the learning ability of reasoning models. Meanwhile, we design the action optimization mechanism to combine the filtered action space and the additional action space for efficient path reasoning of agents. Experimental results on benchmark datasets show that our proposed HSMH framework comprehensively outperforms the state-of-the-art multi-hop reasoning model.
Srd5a1 is Differentially Regulated and Methylated During Prepubertal Development in the Ovary and Hypothalamus

Abstract 5α-reductase-1 catalyzes production of various steroids, including neurosteroids. We reported previously that expression of its encoding gene, Srd5a1, drops in murine ovaries and hypothalamic preoptic area (POA) after early-life immune stress, seemingly contributing to delayed puberty and ovarian follicle depletion, and in the ovaries the first intron was more methylated at two CpGs. Here, we hypothesized that this CpG-containing locus comprises a methylation-sensitive transcriptional enhancer for Srd5a1. We found that ovarian Srd5a1 mRNA increased 8-fold and methylation of the same two CpGs decreased up to 75% between postnatal days 10 and 30. Estradiol (E2) levels rise during this prepubertal stage, and exposure of ovarian cells to E2 increased Srd5a1 expression. Chromatin immunoprecipitation in an ovarian cell line confirmed ESR1 binding to this differentially methylated genomic region and enrichment of the enhancer modification, H3K4me1. Targeting dCas9-DNMT3 to this locus increased CpG2 methylation 2.5-fold and abolished the Srd5a1 response to E2. In the POA, Srd5a1 mRNA levels decreased 70% between postnatal days 7 and 10 and then remained constant without correlation to CpG methylation levels. Srd5a1 mRNA levels did not respond to E2 in hypothalamic GT1-7 cells, even after dCas9-TET1 reduced CpG1 methylation by 50%. The neonatal drop in POA Srd5a1 expression occurs at a time of increasing glucocorticoids, and treatment of GT1-7 cells with dexamethasone reduced Srd5a1 mRNA levels; chromatin immunoprecipitation confirmed glucocorticoid receptor binding at the enhancer. Our findings on the tissue-specific regulation of Srd5a1 and its methylation-sensitive control by E2 in the ovaries illuminate epigenetic mechanisms underlying reproductive phenotypic variation that impact life-long health.
Numerical Modeling of Transient Flow Characteristics on the Top Surface of a Steel Slab Continuous Casting Strand Using a Large Eddy Simulation Combined with Volume of Fluid Model

In the current study, the transient flow characteristics on the top surface of a steel slab continuous casting strand were numerically investigated using a large eddy simulation combined with volume of fluid (LES + VOF) model. The validation of numerical simulation was verified via nail board measurement in the industrial continuous casting mold. The effects of casting speed on the top surface level profile and the instantaneous distribution of vortex were discussed. The level variation profile migrated after a period of time, moving from one side of the wide face of the mold to the other. The wave height and transient variation degree of the standing wave increased with an increase in the casting speed. The region near the SEN was more likely to promote the formation of vortices. The vortex generation became easier when the vorticity peaks were concentrated on the outer edge of the low-speed confluence area near the submerged entry nozzle. In addition, the effect of surface velocity on the instantaneous level fluctuation was analyzed. The frequency of level fluctuations was highest at 3~4 mm, and the high-frequency range of velocity fluctuation was 20~60 mm/s at 0.9 m/min casting speed for a 1500 mm × 200 mm caster section. The linear relationship between the level fluctuation and surface velocity magnitude was obtained. The present work aimed at evaluating the dynamic problem of the standing wave at the liquid powder–molten steel interface on the top surface of the mold, which is helpful in optimizing the casting parameters for regular casting practice and improving the quality of the steel slabs.
Associations among stressors, perceived stress, and psychological distress in nursing students: a mixed methods longitudinal study of a Hong Kong sample

Background Nursing students are at risk for high-stress levels and psychological distress. Limited longitudinal studies have been conducted examining factors associated with stress levels and psychological distress of nursing students in their course of study. Purpose The purpose of this study was to examine the levels of stress and corresponding stressors, particularly those predicting psychological distress, among nursing students over their 5 years of study. Methods A longitudinal design, using questionnaires and focus group interviews of a single cohort of nursing students in Hong Kong and following them over their 5 years of training. The Stressors in Nursing Students Scale-Chinese version and the Chinese version of General Health Questionnaire-12 were used to assess stress levels and psychological distress, respectively. Results Ninety-seven participants completed the questionnaires 5 times. Quantitative findings revealed that the overall stress levels of the nursing students increased over 5 years (from mean = 3.08 to 3.33), with the highest levels in the second wave (mean = 3.33). Nursing students experienced higher stress during years 2 (p = 0.006) and 4 (p = 0.037). Psychological distress was the highest in year 3 (sum score = 18.47) (p = 0.002) but declined from year 4 (p < 0.001). Thematic analysis revealed that academic performance issues, coping challenges, unfavorable learning environments, relationships were identified as the stressors. However, nursing students also used positive coping strategies to pursue success and seek support. Conclusion This study suggests that the year of study is a significant predictor of stress levels among nursing students, especially during the first and senior years due to heavy academic workload. Psychological distress was observed among nursing students, and those who worked more part-time jobs tended to report higher levels of distress. The junior year was associated with higher levels of distress related to financial and time-related stress, while academic and personal problems were more prevalent during the senior year.
Evaluating the effects of age on the long-term functional outcomes following anatomic total shoulder arthroplasty

Background In the past decade, the number of anatomic total shoulder arthroplasty (aTSA) procedures has steadily increased. Patients over 65 years of age comprise the vast majority of recipients, and outcomes have been well documented; however, patients are opting for definitive surgical treatment at younger ages.We aim to report on the effects of age on the long-term clinical outcomes following aTSA. Methods Among the patients who underwent TSA, 119 shoulders were retrospectively analyzed. Preoperative and postoperative clinical outcome data were collected. Linear regression analysis (univariate and multivariate) was conducted to evaluate the associations of clinical outcomes with age. Kaplan-Meier curves and Cox regression analyses were performed to evaluate implant survival. Results At final follow-up, patients of all ages undergoing aTSA experienced significant and sustained improvements in all primary outcome measures compared with preoperative values. Based on multivariate analysis, age at the time of surgery was a significant predictor of postoperative outcomes. Excellent implant survival was observed over the course of this study, and Cox regression survival analysis indicated age and sex to not be associated with an increased risk of implant failure. Conclusions When controlling for sex and follow-up duration, older age was associated with significantly better patient-reported outcome measures. Despite this difference, we noted no significant effects on range of motion or implant survival. Level of evidence IV.
Movement analysis for monitoring predation by large carnivores : lions in Kruger National Park

13 Introduction . 14 Methods and Materials . 16 Study area . 16 GPS collars and cluster investigation . 16 Statistical Methods . 18 Results . 22 Discussion . 25 Management implications . 29 Tables . 30 Figures . 31 Chapter 3: Feasibility of using proximity tags to locate female lion (Panthera leo) kills . 35 Abstract . 36 Introduction . 37 Materials and methods . 39 Results . 41 Discussion . 42. 36 Introduction . 37 Materials and methods . 39 Results . 41 Discussion . 42 2 Figures . 47 Chapter 4: Combining GPS locations and scat analysis to estimate the diet of a large carnivore . 50 Abstract . 5
HLA-G 14 bp Ins/Del (rs66554220) Variant Is Not Associated with Breast Cancer in Women from Western Mexico

HLA-G is a physiology and pathologic immunomodulator detrimentally related to cancer. Its gene is heavily transcriptionally and post-transcriptionally regulated by variants located in regulator regions like 3′UTR, being the most studied Ins/Del of 14-bp (rs66554220), which is known to influence the effects of endogen cell factors; nevertheless, the reports are discrepant and controversial. Herein, the relationship of the 14-bp Ins/Del variant (rs66554220) with breast cancer (BC) and its clinical characteristics were analyzed in 182 women with non-familial BC and 221 disease-free women as a reference group. Both groups from western Mexico and sex–age-matched (sm-RG). The rs66554220 variant was amplified by SSP-PCR and the fragments were visualized in polyacrylamide gel electrophoresis. The variant rs66554220 was not associated with BC in our population. However, we suggest the Ins allele as a possible risk factor for developing BC at clinical stage IV (OR = 3.05, 95% CI = 1.16–7.96, p = 0.01); nevertheless, given the small stratified sample size (n = 11, statistical power = 41%), this is inconclusive. In conclusion, the 14-bp Ins/Del (rs66554220) variant of HLA-G is not associated with BC in the Mexican population, but might be related to advanced breast tumors. Further studies are required.
Characterization of Botanical Parts of Erythrina crista-galli Using Pyrolysis-Gas Chromatography/Mass Spectrometry and Multivariate Analysis

Erythrina crista-galli is commonly used in folk medicines for its pharmacological properties which are associated with the bioactive compounds. Profiling botanical parts of E. crista-galli is an exciting topic and essential to uncover the similarity and clustering based on their chemical content. The botanical parts of E. crista-galli, including bark, flowers, leaves, roots, and twigs, were subjected to pyrolysis-gas chromatography/mass spectrometry. The samples were pyrolyzed using a multi-shot pyrolyzer. The relative abundance of the pyrolysate was subjected to multivariate analysis, i.e., principal component analysis (PCA) and hierarchical cluster analysis (HCA). The scree plot for PC.1, PC. 2, and PC. 3 accounted for 36.5%, 27.2%, and 20.3%, respectively. Together, the first three PCs explain 84% of the total variance. The PCA allows characterizing the roots of E. crista-galli by the highest relative abundance of lignin G, followed by the twigs, bark, and leaves, while the flowers had the least relative abundance of lignin G. The HCA allows to cluster the botanical parts of E. crista-galli into three different clusters based on their chemical component similarity, i.e., flowers-leaves, twigs, and roots-bark. In conclusion, Py-GC/MS analysis can be used in conjunction with multivariate data analysis to characterize the botanical parts of E. crista-galli.
Open-Source Wearable Sensors for Behavioral Analysis of Sheep Undergoing Heat Stress

Heat stress (HS) negatively affects animal productivity and welfare. The usage of wearable sensors to detect behavioral changes in ruminants undergoing HS has not been well studied. This study aimed to investigate changes in sheep’s behavior using a wearable sensor and explore how ambient temperature influenced the algorithm’s capacity to classify behaviors. Six sheep (Suffolk, Dorset, or Suffolk × Dorset) were assigned to 1 of 2 groups in a cross-over experimental design. Groups were assigned to one of two rooms where they were housed for 20d prior to switching rooms. The thermal environment within the rooms was altered five times per period. In the first room, the temperature began at a thermoneutral level and gradually increased before decreasing. Simultaneously, in the second room, the temperature began at hot temperatures and gradually decreased before increasing again. Physiological responses (respiratory rate, heart rate, and rectal temperature) were analyzed using a linear mixed-effects model. A random forest algorithm was developed to classify lying, standing, eating, and ruminating (while lying and standing). Thermal stress shifted daily animal behavior budgets, increasing total time spent standing in hot conditions (p = 0.036). Although models had a similar capacity to classify behaviors within a temperature range, their accuracy decreased when applied outside that range. Although wearable sensors may help classify behavioral shifts indicative of thermal stress, algorithms must be robustly derived across environments.
The Hematological and Biochemical Effects from Pesticide Exposure on Thai Vegetable Farmers

Pesticide-related health concerns are a global public health issue. Few studies in Thailand have explored the hematological and biochemical effects of occupational pesticide exposure. The goal of this study was to investigate the effects of pesticides on the hematology, hepatic, and renal function of Thai vegetable farmers. A cross-sectional study was carried out in Chiang Mai, northern Thailand. A total of 124 apparently healthy vegetable farmers were interviewed about their lifetime exposure to agricultural pesticides. Blood samples were collected via venipuncture to be tested for complete blood count (CBC), liver function, and kidney function. Approximately 46% of the farmers were pesticide users who reported a history of pesticide use for their crops, while 54% were non-pesticide users. In the male farmers, the activities of aspartate aminotransferase (AST), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were significantly higher in the pesticide users compared to the non-pesticide users, while the estimated glomerular filtration rate (eGFR), hematocrit (HCT), and red blood cells (RBC) were significantly lower (p < 0.05). In the females, the pesticide users had significantly higher levels of alanine aminotransferase (ALT), alkaline phosphatase (ALP), and MCHC than the non-pesticide users (p < 0.05). Pesticide use among Thai vegetable farmers may cause hematological alterations and increase the risk of hepatic and renal dysfunction. Some hematological and biochemical parameters may be used for monitoring to protect them from the adverse health effects of occupational exposure to pesticides.
Whole-genome phylogeography of the intertidal snail Littorina saxatilis

Understanding the factors that have shaped the current distributions and diversity of species is a central and longstanding aim of evolutionary biology. The recent inclusion of genomic data into phylogeographic studies has dramatically improved our understanding in organisms where evolutionary relationships have been challenging to infer. We used whole-genome sequences to study the phylogeography of the intertidal snail Littorina saxatilis, which has successfully colonized and diversified across a broad range of coastal environments in the northern hemisphere amid repeated cycles of glaciation. Building on past studies based on short DNA sequences, we used genome-wide data to provide a clearer picture of the relationships among samples spanning most of the species natural range. Our results confirm the trans-Atlantic colonization of North America from Europe, and have allowed us to identify rough locations of glacial refugia and to infer likely routes of colonization within Europe. We also investigated the signals in different datasets to account for the effects of genomic architecture and non-neutral evolution, which provides new insights about diversification of four ecotypes of L. saxatilis (the crab, wave, barnacle and brackish ecotypes) at different spatial scales. Overall, we provide a much clearer picture of the biogeography of L. saxatilis, providing a foundation for more detailed phylogenomic and demographic studies.