Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Measurement Error in the Sharp Regression Discontinuity Design

This paper develops a nonparametric analysis for the sharp regression discontinuity (RD) design in which the continuous forcing variable may contain measurement error. We show that if the observable forcing variable contains measurement error, this error causes severe identification bias for the average treatment effect given the “true” forcing variable at the discontinuity point. The bias is critical in the sense that even if there is a significant causal effect, researchers are misled to the incorrect conclusion of no causal effect. Furthermore, the measurement error leads the conditional probability of the treatment to be continuous at the threshold. To investigate the average treatment effect using the mismeasured forcing variable, we propose an approximation using the small error variance approximation (SEVA) originally developed by Chesher (1991). Based on the SEVA, the average treatment effect is approximated up to the order of the variance of the measurement error using an identified parameter when the variance is small. We also develop an estimation procedure for the parameter that approximates the average treatment effect based on local polynomial regressions and the kernel density estimation. Monte Carlo simulations reveal the severity of the identification bias caused by the measurement error and demonstrate that our approximate analysis is successful.
Inviting regulatory T cells to pregnant endometrium: friends or foes in adverse pregnancy outcomes?

Among decidual immune cells, regulatory T cells (Tregs) have been unanimously recognized as central contributors to tolerance and maintenance of healthy pregnancy. Numerical and functional downregulation of Tregs or disturbed interaction of Tregs with trophoblasts and other immune cells have been linked to early pregnancy loss such as idiopathic infertility and miscarriage and later-onset adverse pregnancy outcomes including preeclampsia. This review focuses on the mechanisms for regulating the generation, expansion, and function of Tregs, the roles of Tregs in maintaining maternal immune tolerance through crosstalk with trophoblasts and other decidual regulatory immune cells, and how Tregs may play foes to pregnancy and contribute to the programming of pregnancy-related complications. Therapeutic options for implantation failure and adverse pregnancy outcomes are now part of the emerging significance of Tregs in pregnancy tolerance and maintenance.
Extremum Seeking as a Tool for Active Damping of Active Front-End Converters

Active damping control is necessary to mitigate the resonance issues associated with the grid-connected active front-end converters equipped with LCL harmonic filters. Nonetheless, the performance and stability of active damping are highly susceptible to uncertainties due to the grid impedance variations and aging-related drift in LCL filter parameters that can lead to a mismatch between actual and modeled resonance point thereby causing deterioration in performance or even instability. This article addresses this important practical issue by proposing a novel real-time optimization-based self-tuning algorithm to adaptively change the resonant frequency of active damping control as per variations in grid and filter conditions. The approach benefits from the concept of extremum seeking as a framework to estimate actual resonant frequency. The approach is experimentally validated on a two-level three-phase converter interfaced with a dSPACE rapid control prototyping system. The results demonstrate that the proposed approach is a straightforward and effective way of obtaining the performance and stability certainty of active damped AFE systems regardless of the grids they are connected to.
Characterization of ENM Dynamic Dose-Dependent MOA in Lung with Respect to Immune Cells Infiltration

The molecular effects of exposures to engineered nanomaterials (ENMs) are still largely unknown. In classical inhalation toxicology, cell composition of bronchoalveolar lavage (BAL) is a toxicity indicator at the lung tissue level that can aid in interpreting pulmonary histological changes. Toxicogenomic approaches help characterize the mechanism of action (MOA) of ENMs by investigating the differentially expressed genes (DEG). However, dissecting which molecular mechanisms and events are directly induced by the exposure is not straightforward. It is now generally accepted that direct effects follow a monotonic dose-dependent pattern. Here, we applied an integrated modeling approach to study the MOA of four ENMs by retrieving the DEGs that also show a dynamic dose-dependent profile (dddtMOA). We further combined the information of the dddtMOA with the dose dependency of four immune cell populations derived from BAL counts. The dddtMOA analysis highlighted the specific adaptation pattern to each ENM. Furthermore, it revealed the distinct effect of the ENM physicochemical properties on the induced immune response. Finally, we report three genes dose-dependent in all the exposures and correlated with immune deregulation in the lung. The characterization of dddtMOA for ENM exposures, both for apical endpoints and molecular responses, can further promote toxicogenomic approaches in a regulatory context.
Risk Management Practices and Financial Performance: The Case of Banks in Sultanate of Oman

The main objective of this project is to define the relationship between risk management practices and bank's financial performance. This is quantitative study, where the quantitative data was collected via secondary data. Data collection from the annual reports of banks in Muscat Securities Market (MSM). The Sample size of 8 banks. In this research, data collected is analyzed using Structural Equation Modelling (SEM) with Partial Least Square PLS Software. The findings revealed that risk management is positively meaningful while avoiding risk . The findings pointed that the risk management has significant with a ROA. This result indicates that management has a significant influence on banks performance (ROA). As well as, the findings found that the risk management insignificant with a (ROE)DOI:https://doi.org/10.26905/afr.v4i2. 6312
Adherence to Gluten-Free Diet Restores Alpha Diversity in Celiac People but the Microbiome Composition Is Different to Healthy People

Celiac disease (CD) is an autoimmune disease with the destruction of small intestinal villi, which occurs in genetically predisposed individuals. At the present moment, a gluten-free diet (GFD) is the only way to restore the functionality of gut mucosa. However, there is an open debate on the effects of long-term supplementation through a GFD, because some authors report an unbalance in microbial taxa composition. Methods: For microbiome analysis, fecal specimens were collected from 46 CD individuals in GFD for at least 2 years and 30 specimens from the healthy controls (HC). Data were analyzed using an ensemble of software packages: QIIME2, Coda-lasso, Clr-lasso, Selbal, PICRUSt2, ALDEx2, dissimilarity-overlap analysis, and dysbiosis detection tests. Results: The adherence to GFD restored the alpha biodiversity of the gut microbiota in celiac people but microbial composition at beta diversity resulted as different to HC. The microbial composition of the CD subjects was decreased in a number of taxa, namely Bifidobacterium longum and several belonging to Lachnospiraceae family, whereas Bacteroides genus was found to be more abundant. Predicted metabolic pathways among the CD bacterial communities revealed an important role in tetrapyrrole biosynthesis. Conclusions: CD patients in GFD had a non-dysbiotic microbial composition for the crude alpha diversity metrics. We found significant differences in beta diversity, in certain taxon, and pathways between subjects with inactive CD in GFD and controls. Collectively, our data may suggest the development of new GFD products by modulating the gut microbiota through diet, supplements of vitamins, and the addition of specific prebiotics.
Depression and Complicated Grief, and Associated Factors, of Bereaved Family Members of Patients Who Died of Malignant Pleural Mesothelioma in Japan

Objectives: we investigated the prevalence and associated factors of depression and complicated grief (CG) among bereaved family members of malignant pleural mesothelioma (MPM) patients in Japan. Methods: Bereaved family members of MPM patients (n = 72) were surveyed. The Japanese version of the Patient Health Questionnaire-9 (PHQ-9) and the Japanese version of the Brief Grief Questionnaire (BGQ) were used to assess depression and complicated grief (CG), respectively. Socio-economic factors, anger toward asbestos, care satisfaction, achievement of good death, and quality of end-of-life care were assessed in relation to depression and CG. Results: In the family members of MPM patients, the frequencies of depression and CG were 19.4% and 15.3%, respectively. The bereaved family members who were not compensated by the asbestos-related health-damage relief system (p = 0.018) and who felt the financial impacts of the patient’s MPM on the family (p = 0.006) had a higher likelihood of depression. The bereaved family members who were not satisfied with the care given when the patient became critical (p = 0.034), who were not compensated by the asbestos-related health-damage relief system (p = 0.020), who felt the financial impact of the patient’s MPM on the family (p = 0.016), and whose deceased relative underwent surgery (p = 0.030) had a higher likelihood of CG. Conclusions: For bereaved family members of MPM patients, routine screening for depression and CG and the provision of grief care are suggested. In addition, for family members of MPM patients, financial support, including the promotion of the asbestos-related health-damage relief system, and improved care for patients who undergo surgery and when patients become critical, are recommended.
The clustering of galaxies around damped absorbers

THE CLUSTERING OF GALAXIES AROUND DAMPED ABSORBERS SEPTEMBER 2003 NICOLAS F. BOUCHE B.Sc, UNIYERSITE CATHOLIQUE DE LOUVAIN-LA-NEUVE, BELGIUM Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor James D. Lowenthal We measured the clustering of galaxies around damped absorbers, all at a redshift of approximately three. For this purpose, we used wide-field images that covered a total area of one square degree. We selected galaxies that were close to the absorbers (in a redshift slice) using bayesian photometric redshift techniques. In the redshift slice centered on the absorbers, we detected the clustering of galaxies at the 87% confidence level. Due to the small sample of absorbers, we could not conclude whether the clustering was larger or weaker than that of the galaxies with each other. As a cross-check, in three other redshift slices that were not centered on the absorbers, there was no evidence for clustering. We performed the same analysis on simulated data sets from numerical simulations. There, we found that the clustering of galaxies around the simulated absorbers is weaker than that of the galaxies with each other, by a factor of approximately two. This is consistent with damped absorbers being associated with low-luminosity
Teachers’ Attitudes towards Inclusive Education at Greek Secondary Education Schools

Advocates of inclusive education believe in the right of all learners to education and the many benefits it delivers. Teachers’ attitudes and beliefs toward inclusive education are instantly reflected in their classroom activities and practices. This research will concentrate on special and general education teachers in Greek secondary schools. It will investigate their attitudes toward inclusive education and how these attitudes alter as a consequence of variables such as age, gender, teaching experience, and inclusive education training. Quantitative, main, and correlational research was obtained between groups using a non-experimental technique. The sample was taken from 307 educators, who were almost equally divided between general and special education. The SACIE-R questionnaire was used to assess teachers’ attitudes toward inclusive education. The outcomes of the research demonstrated that attitudes toward inclusive education were impacted by the kind of special education received, as well as age and general education teaching experience. Furthermore, positive attitudes were impacted by gender, but negative sentiments and concerns were influenced by general education and special education teaching experience. Finally, the study revealed low levels of negative sentiments, medium levels of concerns, and high levels of favourable attitudes toward inclusive education.
Molecular identification of Eurycoma longifolia Jack from Sumatra, Indonesia using trnL-F region

Abstract. Yulita KS, Susilowati A, Rachmat HH, Susila, Hidayat A, Dwiyanti FG. 2022. Molecular identification of Eurycoma longifolia Jack from Sumatra, Indonesia using trnL-F region. Biodiversitas 23: 1374-1382. Eurycoma longifolia Jack (Simaroubaceae) or pasak bumi is a popular medicinal plant from Southeast Asia’s rainforests that is used as an aphrodisiac, antimicrobial, anti-malaria antidiabetic, antiulcer, and anticancer agent. However, the increasing demand for this species for medicinal industries has led to illegal export in Indonesia. This study aimed to determine the specific genetic variation and develop DNA barcode using trnL-Fregion for E. longifolia originating from Sumatra, Indonesia. Twenty-two samples of the species were collected from four locations in Sumatra. An aligned sequence of the trnL-Fwas 960 bp with an A/T rich region (A: 30.2%, T: 34.5%, C: 16.7%, and G: 18.7%). The homology search using BLASTn of the GenBank NCBI showed that the nucleotide composition of the species was similar (99.9%) to the partial trnL-Fregion of E. longifolia MH751519 and E. apiculata GU593014. Close examination of the gene structure and composition showed that the DNA sequences have five nucleotides variations that were not possessed by the reference E. longifolia, and other taxa used. The obtained variations occurred mostly in the trnL intron region, and the phylogenetic analysis showed that the correct identity of the species of the samples by their position was at a similar clade as the other accessions of E. longifolia.
The Antioxidant Cyclic 3-Hydroxymelatonin Promotes the Growth and Flowering of Arabidopsis thaliana

In plants, melatonin is metabolized into several compounds, including the potent antioxidant cyclic 3-hydroxymelatonin (3-OHM). Melatonin 3-hydroxylase (M3H), a member of the 2-oxo-glutarate-dependent enzyme family, is responsible for 3-OHM biosynthesis. Although rice M3H has been cloned, its roles are unclear, and no homologs in other plant species have been characterized. Here, we cloned and characterized Arabidopsis thaliana M3H (AtM3H). The purified recombinant AtM3H exhibited Km and Vmax values of 100 μM and 20.7 nmol/min/mg protein, respectively. M3H was localized to the cytoplasm, and its expression peaked at night. Based on a 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay, 3-OHM exhibited 15-fold higher antioxidant activity than melatonin. An Arabidopsis M3H knockout mutant (m3h) produced less 3-OHM than the wildtype (WT), thus reducing antioxidant activity and biomass and delaying flowering. These defects were caused by reduced expression of FLOWERING LOCUS T (FT) and gibberellin-related genes, which are responsible for flowering and growth. Exogenous 3-OHM, but not exogenous melatonin, induced FT expression. The peak of M3H expression at night matched the FT expression pattern. The WT and m3h exhibited similar responses to salt stress and pathogens. Collectively, our findings indicate that 3-OHM promotes growth and flowering in Arabidopsis.
Medication Adherence of Vietnamese Outpatients with Chronic Diseases during the COVID-19 Pandemic

The purpose of this study was to determine the medication adherence of outpatients with chronic diseases and the association between both patient attitudes and preventive practices regarding COVID-19 and their medication adherence. We performed a cross-sectional study in Vietnam. Medication adherence was determined using the translated and validated Vietnamese version of the General Medication Adherence Scale (GMAS). Patient attitudes and preventive practices regarding COVID-19 were measured using the 5K message of the Vietnam Ministry of Health (facemasks, disinfection, distance, no gatherings, health declarations). The associations between patient characteristics and medication adherence were determined by multivariable regression. The study included 1852 outpatients, and 57.6% of the patients adhered to their medications. Patients who recognized the pandemic’s obstruction of medical follow-ups (OR = 1.771; 95%CI = 1.461–2.147; p < 0.001), who applied ≥2 preventive methods (OR = 1.422; 95%CI = 1.173–1.725; p = 0.001), who were employed (OR = 1.677; 95%CI = 1.251–2.248; p = 0.001), who were living in urban areas (OR = 1.336; 95%CI = 1.090–1.637; p = 0.005,) who possessed higher education levels (OR = 1.313; 95%CI = 1.059–1.629; p = 0.013), or who had ≤2 comorbidities (OR = 1.293; 95%CI = 1.044–1.600; p = 0.019) were more likely to adhere to their medications. The adherence percentage for outpatients with chronic diseases was quite low during the pandemic. Patients who did not recognize the COVID-19 pandemic’s obstruction of medical follow-ups or who had poor preventive practices were less likely to adhere to medications. Healthcare providers should pay more attention to these groups to achieve desired treatment outcomes.
Diagnosis of Human Leptospirosis: Comparison of Microscopic Agglutination Test with Recombinant LigA/B Antigen-Based In-House IgM Dot ELISA Dipstick Test and Latex Agglutination Test Using Bayesian Latent Class Model and MAT as Gold Standard

Leptospirosis is a spirochaetal infection that possesses a broad host range affecting almost all mammals. In the present study, the microscopic agglutination test (MAT) was compared with recombinant LigA/B antigen-based point-of-care diagnostics such as the in-house IgM dot ELISA dipstick test (IgM- DEDT) and the latex agglutination test (LAT) for the serodiagnosis of human leptospirosis. The comparison of the MAT with these two point–of-care diagnostics was performed using the MAT as the gold standard test and using Bayesian latent class modelling (BLCM), which considers all diagnostic tests as imperfect. The N-terminal conserved region of the LigA/B protein spanning the first to fifth big tandem repeat domains (rLigA/BCon1-5) was employed as a serodiagnostic marker in both of the bedside assays. A total of 340 serum samples collected from humans involved in high risk occupations were screened using the MAT, IgM DEDT and LAT. During the early phase of leptospirosis, BLCM analysis showed that the IgM DEDT and LAT had similar sensitivities (99.6 (96.0–100)) and (99.5 (95.2–100)), respectively, while the single acute phase MAT had the lowest sensitivity (83.3 (72.8–91.3)). Both the IgM DEDT and the LAT may be superior to the single acute phase MAT in terms of sensitivity during the early phase of infection and may be suitable for the early diagnosis of leptospirosis. However, BLCM analysis revealed that the use of both acute and convalescent samples substantially increased the sensitivity of the final MAT (98.2% (93.0–99.8%)) as a test to diagnose human leptospirosis. Both the IgM DEDT and LAT can be employed as bedside spot tests in remote locations where the MAT is not easily accessible.
Development Of Credit Scoring Model For Borrowers Using Machine Learning Techniques

Financial organizations such as banks have experienced an increase in demand for loans from borrowers over the years. These organizations are highly interested in knowing whether a borrower can pay back if granted the loan requested. Granting loans to defaulters can cripple the business, hence, these financial organizations are compelled to evaluate credit worthiness of clients using the vast volume of historical data related to financial position of borrowers. Like other prediction models, credit scoring is a technique used in predicting the probability that a loan applicant, existing borrower, or counterparty will default. Machine learning technique has ability to solve these challenges faced by credit analyst by automating the processing and extraction of knowledge from data. This research focuses on the development of a credit scoring model using Rough Set Theory (RST) and Multi-Layer Perceptron (MLP) Neural Network. RST was used for feature selection while ANN trained with backpropagation was used for classification. This research used two credit scoring datasets; Australian and German credit dataset. Data pre-processing and machine learning were performed using the Anaconda software. This research compares the result obtained from the RST and MLP with Decision Tree, Logistic Regression, Random Forest, Support Vector Machine, Nayes Bayes, K-Nearest Neighbour and ANN using standard evaluation metric to ascertain its performance on the two datasets and conclude the major findings. This research contributes a credit scoring model with improved performance while saving the computational costs.
Organizational Characteristics Affecting Ratee Perceptions of the Appraisal Process and Ratee Intentions to Change (Performance Appraisals).

To evaluate an expanded version of Ilgen, Fisher, and Taylor's (1979) model of feedback effectiveness, measures of organizational characteristics, ratee perceptions of the appraisal process, and ratee intentions to change were collected from paying and receiving tellers (n=l63) in three banking institutions. Regression analysis indicated that four organizational characteristics: a) openness surrounding the appraisal process, b) frequency of evaluation, c) participation in the performance feedback session, and d) quality of the rater-ratee relationship were significantly related to ratee satisfaction with the appraisal process which, in turn, influenced a) ratee intentions to turnover and b) ratee intentions to file a formal grievance. Overall, the results partially support Ilgen et al.'s model, emphasize the importance of ratee satisfaction with the appraisal process in performance appraisal implementation, and demonstrate the need to include variables such as organizational characteristics, ratee perceptions of the appraisal process, and ratee intentions to change in models of performance appraisal effectiveness.
Role of Psychological Contracts in Enhancing Employee Creativity Through Knowledge Sharing: Do Boundary Conditions of Organization’s Socialization and Work-Related Curiosity Matter?

COVID-19 has had a huge impact on workers and workplaces across the world while putting regular work practices into disarray. Apart from the obvious effects of COVID-19, the pandemic is anticipated to have a variety of social–psychological, health-related, and economic implications for individuals at work. Despite extensive research on psychological contracts and knowledge sharing, these domains of pedagogic endeavor have received relatively little attention in the context of employee creativity subjected to the boundary conditions of the organization’s socialization and work-related curiosity. This study investigates, empirically, the role of psychological contracts in escalating employee creativity through knowledge sharing by considering the moderating role of an organization’s socialization and work-related curiosity. The response received from 372 employees of the manufacturing sector has been investigated and analyzed through Smart PLS software. The results have revealed that knowledge sharing is mediating the relationship between psychological contract and employee creative performance, whereas the moderators significantly moderate the relationships between psychological contract and knowledge sharing and between knowledge sharing and employee creative performance accordingly. It has also been depicted that the moderating impact shown by both moderators is significantly high.