Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards automatic setup of 18 MeV electron beamline using machine learning

To improve the performance-critical stability and brightness of the electron bunch at injection into the proton-driven plasma wakefield at the AWAKE CERN experiment, automation approaches based on unsupervised machine learning (ML) were developed and deployed. Numerical optimisers were tested together with different model-free reinforcement learning (RL) agents. In order to avoid any bias, RL agents have been trained also using a completely unsupervised state encoding using auto-encoders. To aid hyper-parameter selection, a full synthetic model of the beamline was constructed using a variational auto-encoder trained to generate surrogate data from equipment settings. This paper describes the novel approaches based on deep learning and RL to aid the automatic setup of a low energy line, as the one used to deliver beam to the AWAKE facility. The results obtained with the different ML approaches, including automatic unsupervised feature extraction from images using computer vision are presented. The prospects for operational deployment and wider applicability are discussed.
Assessing Kidney Injury Induced by Mercuric Chloride in Guinea Pigs with In Vivo and In Vitro Experiments

Acute kidney injury, which is associated with high levels of morbidity and mortality, affects a significant number of individuals, and can be triggered by multiple factors, such as medications, exposure to toxic chemicals or other substances, disease, and trauma. Because the kidney is a critical organ, understanding and identifying early cellular or gene-level changes can provide a foundation for designing medical interventions. In our earlier work, we identified gene modules anchored to histopathology phenotypes associated with toxicant-induced liver and kidney injuries. Here, using in vivo and in vitro experiments, we assessed and validated these kidney injury-associated modules by analyzing gene expression data from the kidneys of male Hartley guinea pigs exposed to mercuric chloride. Using plasma creatinine levels and cell-viability assays as measures of the extent of renal dysfunction under in vivo and in vitro conditions, we performed an initial range-finding study to identify the appropriate doses and exposure times associated with mild and severe kidney injuries. We then monitored changes in kidney gene expression at the selected doses and time points post-toxicant exposure to characterize the mechanisms of kidney injury. Our injury module-based analysis revealed a dose-dependent activation of several phenotypic cellular processes associated with dilatation, necrosis, and fibrogenesis that were common across the experimental platforms and indicative of processes that initiate kidney damage. Furthermore, a comparison of activated injury modules between guinea pigs and rats indicated a strong correlation between the modules, highlighting their potential for cross-species translational studies.
The Effects of Oral Lavender Therapy on Wounding in Chimpanzees (Pan troglodytes)

Simple Summary Lavender (Lavandula angustifolia) used as a therapeutic has been shown to alleviate anxiety and stress in humans but has yet to be studied in nonhuman primates (NHPs). In this study, we administered lavender in the form of oral capsules as a possible therapy to decrease wounding in a subset of chimpanzees, with the thought that decreasing anxiety and stress may also decrease conflict and, therefore, wounding. Overall, wounding did not decrease with lavender therapy; however, the percentage of wounds requiring medical intervention did decrease with lavender therapy. Abstract Lavender administration in humans has been shown to promote calmness without the side effects often observed with benzodiazepines. Studies in both humans and rodents have found that ingestion of oral lavender capsules resulted in significantly decreased anxiety. Additionally, mice developed an anti-conflict effect and humans increased socially inclusive behaviors. Given the safety of oral lavender oil and the observed benefits, we administered daily lavender capsules to six chimpanzees who exhibited conflict-instigating behaviors in an effort to further decrease our already low levels of wounding. We compared the total number of wounds in 25 chimpanzees housed with the six lavender-treated chimpanzees in five different social groups (1) prior to administration of daily oral lavender capsules to (2) total wounds during daily oral lavender capsule treatment. We hypothesized that lavender therapy treatment would reduce overall wounding in the social groups. Surprisingly, overall wounding was higher during the lavender treatment period (p = 0.01), yet the percentage of wounds requiring treatment significantly decreased during the lavender therapy period (36% vs. 21%, p = 0.02).
A Comparison of Maximum Likelihood and Bayesian Estimation for Polychoric Correlation Using Monte Carlo Simulation

The purpose of this study is to compare the maximum likelihood (ML) and Bayesian estimation methods for polychoric correlation (PCC) under diverse conditions using a Monte Carlo simulation. Two new Bayesian estimates, maximum a posteriori (MAP) and expected a posteriori (EAP), are compared to ML, the classic solution, to estimate PCC. Different types of prior distributions are used to investigate the sensitivity of a prior distribution onto the Bayesian PCC estimation. In this simulation study, it appears that the MAP would be the estimator of choice for the PCC. The performance of the MAP is not only better than the ML but also appears to overcome the limitations of the EAP (i.e., the shrinkage effect).
Scrutinizing gully erosion hotspots using hybridized deep‐learning analysis to avoid land degradation

Despite the importance of the prediction of land susceptibility to gully erosion, there is a lack of research studies adopting the deep‐learning approach. This study aimed to predict gully susceptibility hotspots using hybridized deep‐learning models and evaluate their efficiency. Field records of gully occurrences in a gully‐prone region, the Talwar watershed (6468 km2), eastern Kurdistan province, Iran, were used to generate a gully inventory dataset. A total of 14 geomorphometric, environmental, and topo‐hydrological gully drivers were selected as predictor variables. The hybridized models were developed using convolutional neural network (NNC) and metaheuristic procedures, including the gray wolf optimizer (GWO) and the imperialist competitive algorithm (ICA). The validity of the resulting outputs was investigated based on the area under the receiver operating characteristic (ROC) curve. Results revealed that the NNC‐GWO had the highest efficiency in the validation step (AUC = 97.2%), whereas the NNC‐ICA was the second‐best model (AUC = 95.1%). The standalone NNC model showed the lowest accuracy (AUC = 91.2%) in predicting gully susceptibility hotspots compared to NNC‐GWO and NNC‐ICA. Thus, both hybridized models had better predictive performance for identifying gully susceptibility in comparison with the standalone NNC model. Furthermore, according to the NNC‐GWO model, about 0.2% (1294.8 ha) and 0.05% (235.2 ha) of the study area were identified as high and very high gully susceptibility classes. In addition, the application of the standalone NNC led to an overestimation of the susceptibility degree for gully initiation. This study supports researchers efforts to increase the model's performance when working in the land degradation domain.
Prevalence of Waterpipe Smoking in Iran: A Systematic Review and Meta-analysis

Background: Considering the prevalence of waterpipe smoking (WPS) among the majority of people, it is necessary to identify the cause of this behavior. Therefore, this meta-analysis study aimed at evaluating the prevalence of waterpipe consumption in Iran based on province, education level, and gender subgroups. Materials and Methods: The search was conducted based on the PRISMA guideline. Scopus PubMed, SID, and Irandoc databases were used to retrieve papers related to the prevalence of WPS in Iran from January 1, 2005 to May 10, 2022. The keywords were "air pollution" OR "particulate matter" OR "water-pipe" OR smoking OR "Indoor air" and "Prevalence" OR "Incidence" AND "Iran". The prevalence of WPS was meta-analyzed based on province, gender, and education level subgroups in the random effects model. Results: According to the final included papers (17 articles and 48 data reports), the rank order of provinces based on the prevalence of WPS was Kerman (58.30%)>Tehran (52.38%)>Sistan and Baluchistan (42.29%)>Hormozgan (30.69%)>Yazd (24.13%)>Bushehr (19.47%)>Ardabil (19.00%)>Fars (16.37%)>Khuzestan (11.38%). The rank order of education level of participants based on the prevalence of WPS was college education (55.64%)>Student (43.47%)>University Student (17.69%). Finally, the rank order of gender of participants based on the prevalence of WPS was male (31.75%) ~ female (30.99%). Conclusion: The results demonstrated a high prevalence of WPS. It is a multi-predictor and multilevel phenomenon in several aspects. The impact of geographical location and education levels was clearly visible. There was no difference in the gender-specific gap for WPS. Regarding the substantial effects of WPS prevalence on health, regular surveillance, prevention, intervention, and control are necessary.
Community-Acquired Urinary Tract Infection Among Sexually Active Women: Risk Factors, Bacterial Profile and Their Antimicrobial Susceptibility Patterns, Arba Minch, Southern Ethiopia

Background Globally, urinary tract infections (UTIs) are a common health issue among women. Investigating risk factors associated with culture-proven UTIs and the antimicrobial resistance profile of uropathogens would provide insight into planning prevention and control measures. Objective To identify the risk factors associated with UTIs among sexually active women and determine antimicrobial susceptibility patterns of uropathogenic bacterial isolates. Methods A case-control study was conducted from February to June 2021, involving 296 women (62 case group and 234 control group in a ratio of 4:1). Cases were defined as culture-confirmed UTIs, and controls were non-UTIs. A semi-structured questionnaire was used to collect demographic, clinical, and behavioral data. The antimicrobial susceptibility test was done by the Kirby-Bauer disc diffusion method. The data were analyzed using SPSS version 25. Bivariable and multivariable logistic regressions were used to identify risk factors, and the strength of association was measured by adjusted odds ratios and a 95% confidence interval used at P-values < 0.05. Results The results revealed that recent coitus and frequency of coitus more than three times per week (P=0.001) were independent predictors of UTIs. Swabbing from back to front, a history of UTI and a delay in voiding were also independent predictors (P < 0.05). On the other hand, a daily water intake of 1 to 2 litres reduced the risk of UTI (P= 0.001). The predominant uropathogenic isolate was Escherichia coli (35.48%). Over 60% of isolates were resistant to cotrimoxazole, penicillin, cephalosporin, and fluoroquinolones. The most effective antibiotics included piperacillin-tazobactam, aminoglycosides, carbapenem, and nitrofurantoin. 85% and 50% of isolates were MDR and ESBL producers, respectively. Conclusion The finding indicates the importance of public intervention targeting the identified risk factors and the resistance phenotype to reduce the burden of UTIs with antimicrobial resistance in the study area.
Optical Character of Barium Titanate Based Thin Films around the Phase Transition

The 0.5BaZr0. 2Ti0.8O3-0.5Ba0. 7Ca0.3TiO3 (BCZT50) thin films have been prepared on platinized silicon substrates by spin coating and turned out to be ferroelectrics at room temperature. The spectroscopic ellipsometry parameters are accurately simulated by a three-layer model with a Tauc-Lorentz oscillator formula. The calculated temperature-dependent refractive index is intensively investigated. It shows organized variation and a refractive peak explicitly, indicating a significant reference in ferroelectric optics device fabrication.
ANALYSIS OF EFFECTS OF INSURGENCY ON COWPEA PRODUCTION IN POTISKUM LOCAL GOVERNMENT AREA OF YOBE STATE, NIGERIA

This study analysed the effects of insurgency on cowpea production in Potiskum local government area of Yobe State, Nigeria. A sample of 120 cowpea farmers were randomly interviewed using structured questionnaire. Data were analyzed using descriptive and inferential statistics. The results show that 35% of the respondents fell within the age bracket of 28-33 years; males constituted 55% and 42% had primary education. The findings further showed that 77.50% of the farmers perceived the effect of insurgency on their livelihood. Majority 70.80% of the respondent perceived increase in poverty and job loses. The result shows that majority (52.5%) of the respondents affected by the conflicts, children (21.7%), women (13.3%) and adult men (8.3%), lost their houses (32.50%), lost their livestock (29.20%), and 16.70% and 13.30% lost their crops and sustained body injury, respectively. Majority (67.50%) of the respondents proffered all the methods in resolving the insurgency, military action (16.70%), negotiation (6.70%), 5.0% and 4.20% suggested state of emergency and amnesty, respectively. Furthermore, regression analysis reveals that 74% variation of the effects of the insurgency on cowpea output was accounted by the independent variables in the model. However, educational level, sex and income were significant at p< 0.001, while household size, farm size and distance from farm to homestead were significant at p< 0.05. Chi-square analysis reveals that the variables included in the model such as sex, educational level, age, income and distance from farmlands to homestead were significant at p< 0.05, with the exception of farm size, marital status and farming experience. The study concluded that insurgency do exist in the study area and the effects include loss of lives, crops, and destruction of infrastructures, such as schools, telecommunication mast, mosques, churches, markets and houses. The study recommended that education and employment opportunities be provided to the youths in the study area.
Analisis Faktor Adopsi E-Wallet Gopay, OVO, dan DANA dengan Model UTAUT2 pada Masyarakat Jawa Barat

Analysis of the Gopay, OVO, and DANA E-Wallet Adoption Factors with the UTAUT2 Model in the West Java. Fintech is changing the banking industry, reshaping business, and changing the way consumers manage and use money. This study's purpose is to examine the factors that affect the adoption of e-wallet, a product of fintech in West Java using the UTAUT 2 model. This study used data collection techniques in the form of surveys by distributing online and manual questionnaires. The respondents of this research are 400 users from Gopay, OVO, or DANA, domiciled in West Java, and ranging in age from 18-40 years. This study used the PLS-SEM model. The results showed that there were three accepted hypotheses. Only the Habit variable (H7a) has a positive significant effect on the Behavioral Intention, while the other variables have no significant effect. Also, it was found that the variables of Facilitating Conditions (H4b) and Behavioral Intention (H8) had a significant positive effect on Use Behavior. In addition, only the Gender variable moderates the independent variable with the dependent variable. ABSTRAKAnalisis Faktor Adopsi E-wallet Gopay, OVO, dan DANA dengan Model UTAUT2 pada Masyarakat Jawa Barat. Fintech telah mengubah industri perbankan, membentuk kembali bisnis, dan mengubah cara konsumen mengatur dan menggunakan uang mereka. Tujuan dari penelitian ini yaitu untuk meneliti faktor-faktor yang mempengaruhi adopsi e-wallet yang merupakan produk dari fintech pada masyarakat Jawa Barat menggunakan model UTAUT 2. Penelitian ini menggunakan teknik pengambilan data berupa survei dengan menyebarkan kuesioner secara online dan manual. Responden penelitian ini merupakan 400 pengguna dari Gopay, OVO, atau DANA, berdomisili di Jawa Barat, dan berusia 18-40 tahun. Penelitian ini akan menggunakan model PLS-SEM. Hasil penelitian menunjukkan bahwa terdapat tiga hipotesis yang diterima. Hanya variabel Kebiasaan (H7a) yang berpengaruh signifikan positif dengan niat menggunakan, sedangkan variabel lainnya tidak berpengaruh signifikan. Kemudian ditemukan bahwa variabel Kondisi Pendukung (H4b) dan Niat Menggunakan (H8) berpengaruh signifikan positif dengan perilaku menggunakan. Kemudian, hanya variabel jenis kelamin yang memoderasi variabel independen dengan variabel dependen.
Iron overload induces islet β cell ferroptosis by activating ASK1/P-P38/CHOP signaling pathway

Background Recent studies have shown that the accumulation of free iron and lipid peroxides will trigger a new form of cell death—ferroptosis. This form of cell death is associated with a variety of diseases, including type 2 diabetes. We hypothesize that iron overload may play a role in driving glucose metabolism abnormalities by inducing endoplasmic reticulum stress that mediates ferroptosis in islet β cells. In this study, we tested this conjecture from in vivo and in vitro experiments. Methods We established a mouse iron overload model by intraperitoneal injection of iron dextrose (50 mg/kg) and an iron overload cell model by treating MIN6 cells with ferric ammonium citrate (640 μmol/L, 48 h) in vitro. The iron deposition in pancreatic tissue was observed by Prussian blue staining, and the pathological changes in pancreatic tissues by HE staining and the protein expression level by pancreatic immunohistochemistry. In the cellular experiments, we detected the cell viability by CCK8 and observed the cellular ultrastructure by transmission electron microscopy. We also used MDA and ROS kits to detect the level of oxidative stress and lipid peroxidation in cells. Western blotting was performed to detect the expression levels of target proteins. Results Iron overload induces MIN6 cell dysfunction, leading to increased fasting blood glucose, impaired glucose tolerance, and significantly decreased insulin sensitivity in mice. This process may be related to the ferroptosis of islet β cells and the activation of ASK1/P-P38/CHOP signaling pathway.
Increased Rates of Hospitalized Children with Type 1 and Type 2 Diabetes Mellitus in Central Brooklyn during the COVID-19 Pandemic

Following reports of increased new-onset diabetes and worse severity of DKA for children with diabetes following SARS-CoV-2 infection, we studied hospitalization rates for children with type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in our center during the citywide shutdown. Methods. We conducted a retrospective chart review of children admitted to our two hospitals from January 1, 2018, to December 31, 2020. We included ICD-10 codes for diabetic ketoacidosis (DKA), hyperglycemic hyperosmolar syndrome (HHS), and hyperglycemia only. Results. We included 132 patients with 214 hospitalizations: 157 T1DM, 41 T2DM, and 16 others (14 steroid induced, 2 MODY). Overall admissions rates for patients with all types of diabetes were 3.08% in 2018 to 3.54% in 2019 (p = 0.0120) and 4.73% in 2020 (p = 0.0772). Although there was no increase of T1DM admissions across all 3 years, T2DM admission rates increased from 0.29% to 1.47% (p = 0.0056). Newly diagnosed T1DM rates increased from 0.34% in 2018 to 1.28% (p = 0.002) in 2020, and new-onset T2DM rates also increased from 0.14% in 2018 to 0.9% in 2020 (p = 0.0012). Rates of new-onset diabetes presenting with DKA increased from 0.24% in 2018 to 0.96% in 2020 (p = 0.0014). HHS increased from 0.1% in 2018 to 0.45% in 2020 (p = 0.044). The severity of DKA in newly diagnosed was unaffected (p = 0.1582). Only 3 patients tested positive for SARS-CoV-2 infection by PCR. Conclusion. Our urban medical center is located in Central Brooklyn and serves a majority who are Black. This is the first study investigating pediatric diabetes cases admitted to Brooklyn during the first wave of the pandemic. Despite the overall pediatric admissions declining in 2020 due to the citywide shutdown, overall hospitalization rates in children with T2DM and in new-onset T1DM and T2DM increased, which is not directly associated with active SARS-CoV-2 infection. More studies are needed to elucidate the reason for this observed increase in hospitalization rates.
Applied Compressive Strain Governs Hyaline-like Cartilage versus Fibrocartilage-like ECM Produced within Hydrogel Constructs

The goal of cartilage tissue engineering (CTE) is to regenerate new hyaline cartilage in joints and treat osteoarthritis (OA) using cell-impregnated hydrogel constructs. However, the production of an extracellular matrix (ECM) made of fibrocartilage is a potential outcome within hydrogel constructs when in vivo. Unfortunately, this fibrocartilage ECM has inferior biological and mechanical properties when compared to native hyaline cartilage. It was hypothesized that compressive forces stimulate fibrocartilage development by increasing production of collagen type 1 (Col1), an ECM protein found in fibrocartilage. To test the hypothesis, 3-dimensional (3D)-bioprinted hydrogel constructs were fabricated from alginate hydrogel impregnated with ATDC5 cells (a chondrogenic cell line). A bioreactor was used to simulate different in vivo joint movements by varying the magnitude of compressive strains and compare them with a control group that was not loaded. Chondrogenic differentiation of the cells in loaded and unloaded conditions was confirmed by deposition of cartilage specific molecules including glycosaminoglycans (GAGs) and collagen type 2 (Col2). By performing biochemical assays, the production of GAGs and total collagen was also confirmed, and their contents were quantitated in unloaded and loaded conditions. Furthermore, Col1 vs. Col2 depositions were assessed at different compressive strains, and hyaline-like cartilage vs. fibrocartilage-like ECM production was analyzed to investigate how applied compressive strain affects the type of cartilage formed. These assessments showed that fibrocartilage-like ECM production tended to reduce with increasing compressive strain, though its production peaked at a higher compressive strain. According to these results, the magnitude of applied compressive strain governs the production of hyaline-like cartilage vs. fibrocartilage-like ECM and a high compressive strain stimulates fibrocartilage-like ECM formation rather than hyaline cartilage, which needs to be addressed by CTE approaches.