Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between Demographic Characteristics of Committee Members and Corporate Social Responsibility Commitment : Evidence from Thailand

This study aims to consider the role of women serving in the executive committee of the company and determine how it related to corporate social and environmental responsibilities (CSR and ESR). The data was collected from the 344 companies listed on the Stock Exchange of Thailand (SET) between 2013 and 2014. Especially, the CSR and ESR data was collected from the annual report and used to measure activities related to environmental and social responsibilities of companies listed on the SET. This study employed panel analysis regression to analyze the relationship between dependent and independent variables. The results indicated that the role of women who served in the executive committees of companies listed on SET had a positive impact on the social and environmental responsibilities of companies listed on the SET. The Granger causality test showed that the proportion of women holding positions on the board of directors had a statistically significant relationship with CSR and ESR, which is a unidirectional relationship. Moreover, the size of the company and the return to total assets also have a positive significant relationship with the CSR and ESR
WORKING PAPER SERIES FETAL SHOCK OR SELECTION ? THE 1918 INFLUENZA PANDEMIC AND HUMAN CAPITAL DEVELOPMENT

Almond (2006) argues that in utero exposure to the 1918 influenza pandemic lowered socioeconomic status in adulthood, whereas Brown and Thomas (2016) find that the effect disappears after controlling for parental characteristics of the 1919 birth cohort. We link microdata from the 1920 and 1930 censuses to WWII enlistment records and city-level influenza data. The result is a data set with much more precisely measured influenza exposure and parental characteristics. Results indicate that in the absence of the pandemic, the 1919 birth cohort would have been more likely to graduate from high school and would have obtained more years of schooling. The impact on high school graduation is largely unaffected by including parental controls and city-specific time trends. Adding household fixed effects (and thus exploiting variation among brothers) yields similar but somewhat larger results. Brian Beach Department of Economics College of William and Mary P.O. Box 8795 Williamsburg, VA 23187 and NBER bbbeach@wm.edu Joseph P. Ferrie Department of Economics Northwestern University 2001 Sheridan Road Evanston, IL 60208-2600 and NBER ferrie@northwestern.edu Martin H. Saavedra Department of Economics Oberlin College Oberlin, OH 44074 Martin.Saavedra@oberlin.edu
Effects of Implementing Multiple Components in a School-Wide Antibullying Program: A Randomized Controlled Trial in Elementary Schools.

This study investigates the effectiveness of the PRIMA antibullying program for elementary education using a cluster-randomized trial with two experimental conditions (with and without student lessons) and a control group. Students of 31 schools participated in the study (N = 3,135; Mage = 10 years). Multilevel regression analyses demonstrated positive effects of the program on peer-reported victimization and reinforcing behavior. Implementing multiple program components was related to stronger program effects. The results provide partial experimental evidence for the beneficial effects of combining student lessons and teacher training in antibullying programs. Future experimental research is needed to investigate other approaches that reduce not only peer-reported victimization, but also self-perceived bullying and victimization.
Sign Language Gloss Translation using Deep Learning Models

Converting sign language to a form of natural language is one of the recent areas of the machine learning domain. Many research efforts have focused on categorizing sign language into gesture or facial recognition. However, these efforts ignore the linguistic structure and the context of natural sentences. Traditional translation methods have low translation quality, poor scalability of their underlying models, and are timeconsuming. The contribution of this paper is twofold. First, it proposes a deep learning approach for bidirectional translation using GRU and LSTM. In each of the proposed models, Bahdanau and Luong’s attention mechanisms are used. Second, the paper experiments proposed models on two sign languages corpora: namely, ASLG-PC12 and Phoenix-2014T. The experiment conducted on 16 models reveals that the proposed model outperforms the other previous work on the same corpus. The results on the ASLG-12 corpus, when translating from text to gloss, reveal that the GRU model with Bahdanau attention gives the best result with ROUGE (Recall-Oriented Understudy for Gisting Evaluation) score 94.37% and BLEU (Bilingual Evaluation Understudy)-4 score 83.98%. When translating from gloss to text, the results also show that the GRU model with Bahdanau attention achieves the best result with ROUGE score 87.31% and BLEU-4 66.59%. On Phoenix-2014T corpus, the results of text to gloss translation show that the GRU model with Bahdanau attention gives the best result in ROUGE with a score of 42.96%, while the GRU model with Luong attention gives the best result in BLEU-4 with 10.53%. When translating from gloss to text, the results report that the GRU model with Luong attention achieves the best result in ROUGE with a score of 45.69% and BLEU-4 with a score of 19.56%. Keywords—Sequence to sequence model; neural machine translation; sign language; deep learning; LSTM; GRU
A novel harmonic elimination pulse-width modulation technique for static converter and drives

A novel harmonic elimination PWM (HEPWM) technique for drives and static power converters is presented. The technique can be implemented on-line in real-time using a simple software algorithm, without resorting to any traditional off-line numerical techniques nor extensive lookup tables (LUTs). It is shown that the developed HEPWM technique can be implemented by calculating switching angles using simple algebraic equations and selecting switching states. In comparison with the previous reports which require the calculation of the switching angles in the first sextant, only the switching angles in the first half sextant are required. Simulation and experimental results are presented to confirm and demonstrate the features of the technique.
Rapid Coating of Aqueous Pearls with Carbon Nanotubes via In Situ Polymerization of Dopamine

Millimeter-scale calcium alginate aqueous core capsules (mm-CaSA-Caps) are suitable for embedding of temperature and chemical sensitive substances because of its excellent biocompatibility and biodegradability. In this study, mm-CaSA-Caps were coated with multiwalled carbon nanotubes (MWNTs) via in situ self-polymerization of dopamine (DA) under mild conditions. During the modification process, mm-CaSA-Caps transferred quickly from colorless and transparent capsules to dark and opaque “pearls” in 15min. *e obtained MWNTs-polydopamine(PDA-) modified mm-CaSA-Caps (mm-MWNTs-PDA@CaSA-Caps) retained the spherical appearance of mm-CaSA-Caps with uniform coating of MWNTs-PDA. Obviously, the MWNTs were easily coated on the mm-PDA@CaSA-Caps due to the strong adhesive property of PDA. As the MWNTs content increased, the stacking density of MWNTs on surface of the mm-MWNTs-PDA@CaSA-Caps raised. *e water loss ratio of mm-MWNTs-PDA@CaSACaps was enhanced ascribed to increasing the path length of water by raising stacking density of MWNTs. *is study provided a new path for enhancement of the barrier property of hydrogel capsules.
COVID-19 testing, timeliness and positivity from ICMR’s laboratory surveillance network in India: Profile of 176 million individuals tested and 188 million tests, March 2020 to January 2021

Background The Indian Council of Medical Research set up a pan-national laboratory network to diagnose and monitor Coronavirus disease 2019 (COVID-19). Based on these data, we describe the epidemiology of the pandemic at national and sub-national levels and the performance of the laboratory network. Methods We included surveillance data for individuals tested and the number of tests from March 2020 to January 2021. We calculated the incidence of COVID-19 by age, gender and state and tests per 100,000 population, the proportion of symptomatic individuals among those tested, the proportion of repeat tests and test positivity. We computed median (Interquartile range—IQR) days needed for selected surveillance activities to describe timeliness. Results The analysis included 176 million individuals and 188 million tests. The overall incidence of COVID-19 was 0.8%, and 12,584 persons per 100,000 population were tested. 6.1% of individuals tested returned a positive result. Ten of the 37 Indian States and Union Territories accounted for about 75.6% of the total cases. Daily testing scaled up from 40,000 initially to nearly one million in March 2021. The median duration between symptom onset and sample collection was two (IQR = 0,3) days, median duration between both sample collection and testing and between testing and data entry were less than or equal to one day. Missing or invalid entries ranged from 0.01% for age to 0.7% for test outcome. Conclusion The laboratory network set-up by ICMR was scaled up massively over a short period, which enabled testing a large section of the population. Although all states and territories were affected, most cases were concentrated in a few large states. Timeliness between the various surveillance activities was acceptable, indicating good responsiveness of the surveillance system.
H9N2 virus-derived M1 protein promotes H5N6 virus release in mammalian cells: Mechanism of avian influenza virus inter-species infection in humans

H5N6 highly pathogenic avian influenza virus (HPAIV) clade 2.3. 4.4 not only exhibits unprecedented intercontinental spread in poultry, but can also cause serious infection in humans, posing a public health threat. Phylogenetic analyses show that 40% (8/20) of H5N6 viruses that infected humans carried H9N2 virus-derived internal genes. However, the precise contribution of H9N2 virus-derived internal genes to H5N6 virus infection in humans is unclear. Here, we report on the functional contribution of the H9N2 virus-derived matrix protein 1 (M1) to enhanced H5N6 virus replication capacity in mammalian cells. Unlike H5N1 virus-derived M1 protein, H9N2 virus-derived M1 protein showed high binding affinity for H5N6 hemagglutinin (HA) protein and increased viral progeny particle release in different mammalian cell lines. Human host factor, G protein subunit beta 1 (GNB1), exhibited strong binding to H9N2 virus-derived M1 protein to facilitate M1 transport to budding sites at the cell membrane. GNB1 knockdown inhibited the interaction between H9N2 virus-derived M1 and HA protein, and reduced influenza virus-like particles (VLPs) release. Our findings indicate that H9N2 virus-derived M1 protein promotes avian H5N6 influenza virus release from mammalian, in particular human cells, which could be a major viral factor for H5N6 virus cross-species infection.
Spatial parameters associated with the risk of banana bunchy top disease in smallholder systems

The Banana Bunchy Top Disease (BBTD), caused by the Banana Bunchy Top Virus (BBTV) is the most important and devastating in many tropical countries. BBTD epidemiology has been little studied, mixed landscape smallholder systems. The relative risks associated with this disease vary between geographical areas and landscapes. This work analyzed the management and vegetation conditions in smallholder gardens to assess the factors linked to landscape-level BBTV transmission and management. Mapping was done in this study area which is in a BBTD-endemic region, involving farmers actively managing the disease, but with household-level decision making. A spatial scanning statistic was used to detect and identify spatial groups at the 5% significance threshold, and a Poisson regression model was used to explore propagation vectors and the effect of surrounding vegetation and crop diversity. Spatial groups with high relative risk were identified in three communities, Dangbo, Houéyogbé, and Adjarra. Significant associations emerged between the BBTD prevalence and some crop diversity, seed systems, and BBTD management linked factors. The identified factors form important candidate management options for the detailed assessment of landscape-scale BBTD management in smallholder communities.
Risk Factors and Outcomes of Early Hospital Readmission in Canadian Kidney Transplant Recipients: A Population-Based Multi-Center Cohort Study

Background: Early hospital readmissions (EHRs) occur commonly in kidney transplant recipients. Conflicting evidence exists regarding risk factors and outcomes of EHRs. Objective: To determine risk factors and outcomes associated with EHRs (ie, hospitalization within 30 days of discharge from transplant hospitalization) in kidney transplant recipients. Design: Population-based cohort study using linked, administrative health care databases. Setting: Ontario, Canada. Patients: We included 5437 kidney transplant recipients from 2002 to 2015. Measurements: Risk factors and outcomes associated with EHRs. We assessed donor, recipient, and transplant risk factors. We also assessed the following outcomes: total graft failure, death-censored graft failure, death with a functioning graft, mortality, and late hospital readmission. Methods: We used multivariable logistic regression to examine the association of each risk factor and the odds of EHR. To examine the relationship between EHR status (yes vs no [reference]) and the outcomes associated with EHR (eg, total graft failure), we used a multivariable Cox proportional hazards model. Results: In all, 1128 kidney transplant recipients (20.7%) experienced an EHR. We found the following risk factors were associated with an increased risk of EHR: older recipient age, lower income quintile, several comorbidities, longer hospitalization for initial kidney transplant, and older donor age. After adjusting for clinical characteristics, compared to recipients without an EHR, recipients with an EHR had an increased risk of total graft failure (adjusted hazard ratio [aHR]: 1.46, 95% CI: 1.29, 1.65), death-censored graft failure (aHR: 1.62, 95% CI: 1.36, 1.94), death with graft function (aHR: 1.34, 95% CI: 1.13, 1.59), mortality (aHR: 1.41, 95% CI: 1.22, 1.63), and late hospital readmission in the first 0.5 years of follow-up (eg, 0 to <0.25 years: aHR: 2.11, 95% CI: 1.85, 2.40). Limitations: We were not able to identify which readmissions could have been preventable and there is a potential for residual confounding. Conclusions: Results can be used to identify kidney transplant recipients at risk of EHR and emphasize the need for interventions to reduce the risk of EHRs. Trial registration: This is not applicable as this is a population-based cohort study and not a clinical trial.
The Superior Parietal Lobule of Macaque Monkey: Relative Influence of Gaze and Static Arm Position during Reaching

Abstract The superior parietal lobule (SPL) integrates somatosensory, motor, and visual signals to dynamically control arm movements. During reaching, visual and gaze signals are used to guide the hand to the desired target location, while proprioceptive signals allow to correct arm trajectory, and keep the limb in the final position at the end of the movement. Three SPL areas are particularly involved in this process: V6A, PEc, PE. Here, we evaluated the influence of eye and arm position on single neuron activity of these areas during the holding period at the end of arm reaching movements, when the arm is motionless and gaze and hand positions are aligned. Two male macaques (Macaca fascicularis) performed a foveal reaching task while single unit activity was recorded from areas V6A, PEc, and PE. We found that at the end of reaching movements the neurons of all these areas were modulated by both eye position and static position of the arm. V6A and PEc showed a prevalent combination of gaze and proprioceptive input, while PE seemed to encode these signals more independently. Our results demonstrate that all these SPL areas combine gaze and proprioceptive input to provide an accurate monitoring of arm movements.
Approaches for Implementing Healthy Food Interventions in Settings With Limited Resources: A Case Study of Sodium Reduction Interventions in Emergency Food Programs Addressing Food Insecurity

Purpose This study describes how recipients of the Centers for Disease Control and Prevention funded Sodium Reduction in Communities Program (SRCP) worked with emergency food programs to improve access to healthy food to address chronic conditions. Design SRCP recipients partnered with emergency food programs to implement sodium reduction strategies including nutrition standards, procurement practices, environmental strategies, and behavioral economics approaches. Setting SRCP recipients and emergency food programs in Washington County and Benton County, Arkansas and King County, Washington. Subjects SRCP recipient staff, emergency food program staff, and key stakeholders. Measures We conducted semi-structured interviews with key stakeholders and systematic review of program documents. Analysis Data were analyzed using effects matrices for each recipient. Matrices were organized using select implementation science constructs and compared in a cross-case analysis. Results Despite limited resources, emergency food programs can implement sodium reduction interventions which may provide greater access to healthy foods and lead to reductions in health disparities. Emergency food programs successfully implemented sodium reduction interventions by building on the external and internal settings; selecting strategies that align with existing processes; implementing change incrementally and engaging staff, volunteers, and clients; and sustaining changes. Conclusion Findings contribute to understanding the ways in which emergency food programs and other organizations with limited resources have implemented public health nutrition interventions addressing food insecurity and improving access to healthy foods. These strategies may be transferable to other settings with limited resources.
A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets

Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and progress has been limited by challenges related to the lack of labeled datasets adequate for training and testing. Large quantities of known and as yet unidentified broadband signal types mingle in marine recordings, with variability introduced by acoustic propagation, source depths and orientations, and interacting signals. Manual classification of these datasets is unmanageable without an in-depth knowledge of the acoustic context of each recording location. A signal classification pipeline is presented which combines unsupervised and supervised learning phases with opportunities for expert oversight to label signals of interest. The method is illustrated with a case study using unsupervised clustering to identify five toothed whale echolocation click types and two anthropogenic signal categories. These categories are used to train a deep network to classify detected signals in either averaged time bins or as individual detections, in two independent datasets. Bin-level classification achieved higher overall precision (>99%) than click-level classification. However, click-level classification had the advantage of providing a label for every signal, and achieved higher overall recall, with overall precision from 92 to 94%. The results suggest that unsupervised learning is a viable solution for efficiently generating the large, representative training sets needed for applications of deep learning in passive acoustics.
Cholesteatoma Is Associated With Pediatric Progressive Sensorineural Hearing Loss

Objectives: This study identified an association between cholesteatoma and progressive sensorineural hearing loss using a large pediatric longitudinal audiologic dataset. Cholesteatoma is a potential sequela of chronic otitis media with effusion, a commonly observed auditory pathology that can contribute to hearing loss in children. The purpose of this report is to (i) describe the process of identifying the association between cholesteatoma and progressive sensorineural hearing loss in a large pediatric dataset and (ii) describe the audiologic data acquired over time in patients identified with cholesteatoma-associated progressive sensorineural hearing loss. Design: Records of patients included in the Audiologic and Genetics Database (n = 175,215 patients) were examined using specified criteria defining progressive hearing loss. A linear regression model examined the log frequency of all diagnostic codes in the electronic health record assigned to patients for a progressive hearing loss cohort compared with a stable hearing loss group. Based on findings from the linear regression analysis, longitudinal audiometric air (AC) and bone conduction (BC) thresholds were extracted for groups of subjects with cholesteatoma-associated progressive (n = 58 subjects) and stable (n = 55 subjects) hearing loss to further analyze changes in hearing over time. Results: The linear regression analyses identified that diagnostic codes for cholesteatoma were associated with progressive sensorineural hearing loss in children. The longitudinal audiometric data demonstrated within-subject changes in masked BC sensitivity consistent with progressive sensorineural hearing loss in children diagnosed with cholesteatoma. Additional analyses showed that mastoidectomy surgeries did not appear to contribute to the observed progressive hearing loss and that a high number of cholesteatoma patients with progressive hearing loss had normal-hearing thresholds at their first test. Conclusions: The statistical analyses demonstrated an association between cholesteatoma and pediatric progressive sensorineural hearing loss. These findings inform clinical management by suggesting that children with cholesteatoma diagnoses may be at increased risk for progressive sensorineural hearing loss and should receive continued monitoring even after a normal masked BC baseline has been established.