Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of board of directors and sharia supervisory board on zakat funds at Islamic banks in indonesia

Abstract The purpose of this study was to analyze the impact of corporate governance on the distribution of zakat funds by Islamic banks in Indonesia. The study focused on two elements of governance: the characteristics of the board of directors (BOD) and the sharia supervisory board (SSB). Data were extracted from the annual reports of Islamic banks in Indonesia from 2011 to 2020 and analyzed using panel data regression in EViews. The results showed that the size and remuneration of the BOD and the size of the SSB had a significant positive effect on zakat funds, while the reputation of the SSB had no effect. This study contributes to the literature on the role of governance in improving the performance of Islamic banks by providing empirical evidence of the link between governance and increased zakat funds. While previous research has primarily focused on the role of governance in financial performance, this study highlights the importance of governance in the context of social responsibility. The practical implication of this study is that Islamic banks wishing to improve social performance, namely zakat funds, should consider designing a large BOD and large SSB structure, while also considering increasing BOD remuneration.
A Quasi-Stationary Appearance of 30 to 40 Day Period in the Cloudiness Fluctuations during the Summer Monsoon over India

By using the cloudiness data from 1966 to 1972, a quasi-stationary appearance of 30 to 40 day period was confirmed during the summer monsoon season over India, which is recently found in the data for 1973 as a predominant mode of the monsoon fluctuations (Yasunari, 1979). In the same manner as the result of Yasunari (1979), the fluctuation of this mode shows a northward movement over India-Indian Ocean area in each year. This periodicity seems to appear annually except for the severe drought years such as 1972.
The Relationships Between Meridional Position of North Pacific Sea Surface Temperature Anomalies and North American Surface Temperatures Revealed by CMIP6 Models

In this study, we obtained the first leading mode and principal component 1 (PC1) of North Pacific sea surface temperature (SST). The PC1‐related SST anomalies, located relatively north/south, are referred to as North/South PC1 events. Model outputs, observations, reanalysis datasets and sensitivity experiments show that during the North PC1 events, an enhanced Aleutian low occurs and is located relatively north, favoring anomalous southerlies over western North America. The anomalous southerlies induce a strong warming anomaly over North America via warm advection of the anomalous southerlies and temperature advection of the climatological westerlies over North America. However, the Aleutian low anomaly and corresponding southerly anomaly associated with South PC1 events shift southward, favoring weakened effects of South PC1 events on atmospheric circulations and surface temperatures over North America. The meridional position of PC1 events deserves to be considered in the studies of the PC1 and its related climate changes.
Ensemble Convolutional Neural Networks for Mode Inference in Smartphone Travel Survey

We develop ensemble convolutional neural networks (CNNs) to classify the transportation mode of trip data collected as part of a large-scale smartphone travel survey in Montreal, Canada. Our proposed ensemble library is composed of a series of CNN models with different hyper-parameter values and CNN architectures. In our final model, we combine the output of CNN models using “average voting,” “majority voting,” and “optimal weights” methods. Furthermore, we exploit the ensemble library by deploying a random forest model as a meta-learner. The ensemble method with random forest as meta-learner shows an accuracy of 91.8% which surpasses the other three ensemble combination methods, and other comparable models reported in the literature. The “majority voting” and “optimal weights” combination methods result in prediction accuracy rates around 89%, while “average voting” is able to achieve an accuracy of only 85%.
The Factors Affecting Innovative Behavior: An Employee Assessment System Based on Knowledge Creation

Organizations thrive on the innovative behavior of their personnel, but the specific factors that influence such behavior are not widely established, especially in the Thai context. An examination of the literature reveals that the knowledge management (KM) process, which has its basis in the process of knowledge creation known as the SECI process, serves to promote innovative behavior and is a key driver of competitive advantage within innovative organizations. This research study sought to determine which factors account for success in innovation, and to establish an assessment system to evaluate employee innovation. The study sample comprised 500 employees from companies operating in the technology sector. Confirmatory factor analysis (CFA) was carried out, and an eight-factor model was formulated on the basis of the available data. The eight factors in the model were determined to have a significant influence on the success of innovative behavior observed in Thai companies. The relevant factors comprised Sharing of knowledge (SK), Self-efficacy (SE), Problem solving skills (PS), Collaboration ability (CA), Culture of innovation (CI), Organizational support (OS), Culture of learning (CL), and Executive leadership (EL). Within the organizational context, the findings reveal the statistically significant contribution of Sharing of knowledge, Culture of innovation, Organizational support, and Self-efficacy in the promotion of innovative behavior. The study results may prove helpful for organizations wishing to assess the innovative capabilities of their staff, while the success factors may be implemented within organizations through the practical application of an assessment system. Also, by filling a research gap in the literature review, this work will be beneficial to academics and researchers in order to better promote innovative behavior. Doi: 10.28991/HIJ-2023-04-01-012 Full Text: PDF
Identification of host receptors for viral entry and beyond: a perspective from the spike of SARS-CoV-2

Identification of the interaction between the host membrane receptor and viral receptor-binding domain (RBD) represents a crucial step for understanding viral pathophysiology and for developing drugs against pathogenic viruses. While all membrane receptors and carbohydrate chains could potentially be used as receptors for viruses, prioritized searches focus typically on membrane receptors that are known to have been used by the relatives of the pathogenic virus, e.g., ACE2 used as a receptor for SARS-CoV is a prioritized candidate receptor for SARS-CoV-2. An ideal receptor protein from a viral perspective is one that is highly expressed in epithelial cell surface of mammalian respiratory or digestive tracts, strongly conserved in evolution so many mammalian species can serve as potential hosts, and functionally important so that its expression cannot be readily downregulated by the host in response to the infection. Experimental confirmation of host receptors includes (1) infection studies with cell cultures/tissues/organs with or without candidate receptor expression, (2) experimental determination of protein structure of the complex between the putative viral RDB and the candidate host receptor, and (3) experiments with mutant candidate receptor or homologues of the candidate receptor in other species. Successful identification of the host receptor opens the door for mechanism-based development of candidate drugs and vaccines and facilitates the inference of what other animal species are vulnerable to the viral pathogen. I illustrate these approaches with research on identification of the receptor and co-factors for SARS-CoV-2.
Monetary policy and exchange rate anomalies in set‐identified SVARs: Revisited

Set-identified vector autoregressions typically document violations of uncovered interest rate parity ( forward discount puzzle ) and gradual appreciation-depreciation-cycles of exchange rates ( delayed overshooting puzzle ) following con-tractionary monetary policy shocks. We revisit both anomalies in a framework similar to Kim et al. (2017, JPE). We complement their identifying restrictions on how monetary policy affects the economy with restrictions on (i) how monetary policy reacts to the economy and (ii) historical monetary policy innovations. In this hybrid identification, no major forward discount premia emerge. Once we additionally impose that monetary policy propagates through domestic financial conditions, exchange rates also overshoot with less delay.
Depression and Associated Factors among People Living with Human Immunodeficiency Virus Attending Antiretroviral Therapy in Public Health Facilities, Hosanna Town, Southern Ethiopia

Background Among those infected with the human immunodeficiency virus, depression is one of the most prevalent mental health issues. Despite its high incidence, depression goes undiagnosed and untreated in the majority of HIV/AIDS patients, which has a negative impact on how well they adhere to their antiretroviral regimen. Objective To assess the magnitude of depression and associated factors among people attending antiretroviral therapy in public health facilities of Hosanna town, Hadiya Zone, Southern Ethiopia, 2019. Methods Institution-based cross-sectional study was conducted at public health facilities of Hosanna town from June 6 to July 6, 2019, among people living with HIV/AIDS aged 18 years and older who were on ART. A systematic sampling technique was used to select 392 participants. Data were collected using a pretested and standardized structured interviewer-administered questionnaire. Variables having a p value less than 0.2 in bivariate analysis were entered into the multiple logistic regression model. Odds ratio with 95% CI was computed, and variables with p value < 0.05 were considered as statistically significantly associated with depression. Result The prevalence of depression among HIV patients was 37.8%. Being female (AOR = 2.15, 95% CI (1.21, 3.84)), not disclosing their HIV status (AOR = 2.77, 95% CI (1.57, 4.89)), rural dwellers (AOR = 2.69, 95% CI (1.58, 4.57)), poor ART adherence (AOR = 1.89, 95% CI (1.10, 3.24)), having HIV-perceived stigma (AOR = 1.71, 95% CI (1.01, 2.88)), and poor social support (AOR = 1.85, 95% CI (1.11, 3.09)) were significantly associated with depression. Conclusion The magnitude of depression was high among PLWHIVs. Being female, rural dwellers, not disclosing HIV status, poor ART adherence, HIV-perceived stigma, and poor social support were significantly associated with depression. Enhancing adherence, counseling, and linking those patients who had poor social support to the concerned relatives for care and support is recommended. Providing health education both at the facility level and at the community level may reduce stigma and subsequently depression. Encouraging disclosing HIV status may help to prevent depression.
Input‐to‐state exponents and related ISS for delayed discrete‐time systems with application to impulsive effects

This paper aims to investigate the input‐to‐state exponents (IS‐e) and the related input‐to‐state stability (ISS) for delayed discrete‐time systems (DDSs). By using the method of variation of parameters and introducing notions of uniform and weak uniform M‐matrix, the estimates for 3 kinds of IS‐e are derived for time‐varying DDSs. The exponential ISS conditions with parts suitable for infinite delays are thus established, by which the difference from the time‐invariant case is shown. The exponential stability of a time‐varying DDS with zero external input cannot guarantee its ISS. Moreover, based on the IS‐e estimates for DDSs, the exponential ISS under events criteria for DDSs with impulsive effects are obtained. The results are then applied in 1 example to test synchronization in the sense of ISS for a delayed discrete‐time network, where the impulsive control is designed to stabilize such an asynchronous network to the synchronization.
Influence of the Absolute Pressure of the Extraction System on the Yield and Composition of Corymbia citriodora (Hook.) K.D.Hill and L.A.S.Johnson Leaf Essential Oil Extracted by Steam Distillation

This study aimed to evaluate the extraction of Corymbia citriodora (Hook.) K.D. Hill and L.A. S.Johnson essential oil by steam distillation under reduced pressure. Yield and composition of the essential oils obtained at different system pressures were analyzed. System pressure had a significant influence on essential oil yield, resulting in a reduction of 78.6% when the pressure was reduced from 690 Torr to 240 Torr. There were also changes in essential oil composition, with an increase in citronellol content (oxygenated monoterpene). However, the major compound (citronellal) remained at a high content in all tests. Regarding the extracted mass of the major compounds (citronellal, citronellol), there was a significant reduction for all when the system pressure was reduced. Although the reduction in the pressure of the system caused a reduction in oil yield, it was possible to carry out the steps of extraction and purification of the major compound simultaneously. Reduced pressure extraction may decrease process time, increasing its efficiency and reducing costs in the extraction of essential oils.
Wind Profile and Power Performance Measurements Using a Nine-beam Nacelle Lidar

Light detection and ranging (lidar) is a remote sensing method that can measure the average wind speed of larger volumes compared with conventional wind sensors like cup anemometers. Two-beam nacelle lidar is the most representative remote sensor for wind inflow measurement. The remote sensors and conventional wind sensors cannot measure the wind profile it influences the power generation output. Wind data were measured for a 300-kW wind turbine using both a nacelle anemometer installed in it and a nine-beam nacelle lidar, and then compared. The authors were able to obtain a wind profile by using a nine-beam nacelle lidar, which can irradiate the laser in nine directions and observe the inside of the target volume at a higher resolution than the two-beam version. Unlike nacelle lidars released in the past, the recent nine-beam version allowed also wind profile observations. Since the power output of the turbine was influenced by the wind profile, its relationship with the rotor equivalent wind speed (REWS) was clarified.
Digital Twin for Math Education: A Study on the Utilization of Games and Gamification for University Mathematics Education

Gamification has emerged as a promising strategy for engaging students and enhancing learning outcomes across various disciplines, including education. It involves incorporating game-like elements into non-game contexts to motivate and engage users. Extensive research has demonstrated the positive impact of gamification on student engagement, motivation, and learning outcomes in diverse subjects, including mathematics. Nevertheless, there is a paucity of research on the effectiveness of gamification in mathematics education. To bridge this gap, we investigated the effects of gamification in college mathematics education, with a specific emphasis on students from liberal arts backgrounds who may lack foundational mathematical knowledge. In this work, we designed and implemented a gamified mathematics course tailored for liberal arts students in a Korean university. Leveraging digital twin technology for game and gamification, we created an immersive learning environment that allows students to visualize mathematical concepts through games, pair gamification factors on physical and virtual worlds, and engage in interactive problem-solving activities. The effectiveness of this gamified course in improving students’ engagement, motivation, and learning outcomes was thoroughly evaluated. Digital twin technology, in conjunction with gamification, holds immense potential to revolutionize the way mathematics is taught and learned, making it more accessible, interactive, and engaging for students from diverse educational backgrounds.
Immunomodulatory effect of a proprietary polyherbal formulation on healthy participants: A single- blind, randomized, placebo- controlled, exploratory clinical study

Context: Clinical study for immunity. Aims: The present study aimed to assess the effect of proprietary polyherbal formulation (PPHF), labelled as Kofol immunity tablets (KIT) on innate and adaptive immune responses in healthy individuals, on the backdrop of COVID-19 pandemic. Settings and Design: Single-blind, randomized, placebo-controlled, exploratory study in institutional setting. Materials and Methods: Post Ethics Committee permission, screened healthy individuals of either sex aged 18–35 years were randomized to PPHF/Placebo for 2 months. Major assessment variables included peak expiratory flow rate (PEFR), questionnaire-based immune status, perceived stress, and quality of life (QOL) with immune-specific cell counts (CD4+, CD8+), cytokines (interferon gamma [IFN-γ], tumor necrosis factor-alpha [TNF-α], interleukin 10 [IL-10]), and oxidative stress in red blood cells (RBCs) (malondialdehyde (MDA), glutathione peroxidase [GPx]), done at day 60. Statistical Analysis Used: Mean ± standard deviation and paired/unpaired t-test for parametric data analysis while median (range) and Wilcoxon Rank sum test/Mann–Whitney test for nonparametric data analysis, were done. Categorical data was analyzed using Chi-square test. GraphPad InStat software, version 9 was used with p < 0.05, as the level of statistical significance. Results: Of 52 recruited, 28 individuals completed the study. PPHF significantly increased PEFR, improved immune status along with QOL compared to baseline. It also decreased perceived stress from moderate and severe grade to mild. Serum IFN-γ levels remained almost constant post-PPHF treatment. PPHF significantly decreased MDA and increased GPx in RBCs. Significant decrease and increase in TNF-α and IL-10, respectively, were seen in PPHF group. The safety parameters post-PPHF treatment remained within normal reference ranges. Conclusions: PPHF is an efficacious and safe formulation with immunomodulatory potential.
Quantifying the role of land–atmosphere feedbacks in mediating near‐surface temperature persistence

Weather persistence from month to month is an important source of predictability on the intraseasonal time‐scale. Persistence in the lower troposphere is thought to be mainly due to dynamical feedbacks between the atmosphere and physical variables at or below the surface. Many recent improvements of dynamical seasonal forecasting models have been due to better initialisations and representations of the lower boundary. While many physical mechanisms that mediate persistence are well‐understood, they have not previously been considered simultaneously in a causal framework. Here we use linear methods that are widely used in the field of causal inference in statistics to identify mediators between persistent near‐surface temperature anomalies from one month to the next. The variables considered are soil temperature and soil moisture at four levels, and snow depth. In Northern Europe, the high persistence of temperature in summer is shown to be mediated mainly by soil temperature anomalies. The high persistence in winter is mediated by snow depth and soil moisture in addition to soil temperature. The annual cycles of persistence are also investigated for the mid‐ and high latitudes of the Northern Hemisphere, confirming the important role of soil temperature in summer. Snow depth is an important mediator when, and where, its interannual variability is large: in winter at midlatitudes and in spring and autumn at high latitudes. The novel contribution of this study is the introduction of a linear causal methodology and a holistic approach that allows quantification and comparison of the different roles of soil variables and snow depth in mediating near‐surface temperature persistence.
Choice of Polymer, but Not Mesh Structure Variation, Reduces the Risk of Bacterial Infection with Staphylococcus aureus In Vivo

Background: Synthetic mesh material is of great importance for surgical incisional hernia repair. The physical and biochemical characteristics of the mesh influence mechanical stability and the foreign body tissue reaction. The influence on bacterial infections, however, remains ill-defined. The aim of the present study was to evaluate the influence of a modified mesh structure with variation in filament linking on the occurrence of bacterial infection that is indicated by the occurrence of CD68+, CD4+, and CD8+ cells in two different materials. Methods: A total of 56 male Sprague Dawley rats received a surgical mesh implant in a subcutaneous abdominal position. The mesh of two different polymers (polypropylene (PP) and polyvinylidenfluoride (PVDF)) and two different structures (standard structure and bold structure with higher filament linking) were compared. During the implantation, the meshes were infected with Staphylococcus (S.) aureus. After 7 and 21 days, meshes were explanted, and the early and late tissue responses to infection were histologically evaluated. Results: Overall, the inflammatory tissue response was higher at 7 days when compared to 21 days. At 7 days, PP meshes of the standard structure (PP-S) showed the strongest inflammatory tissue response in comparison to all the other groups. At 21 days, no statistically significant difference between different meshes was detected. CD8+ cytotoxic T cells showed a significant difference at 21 days but not at 7 days. PP meshes of both structures showed a higher infiltration of CD8+ T cells than PVDF meshes. CD4+ T helper cells differed at 7 days but not at 21 days, and PVDF meshes in a bold structure showed the highest CD4+ T cell count. The number of CD68+ macrophages was also significantly higher in PP meshes in a standard structure when compared to PVDF meshes at 21 days. Conclusion: The inflammatory tissue response to S. aureus infection appears to be highest during the early period after mesh implantation. PP meshes showed a higher inflammatory response than PVDF meshes. The mesh material appears to be more important for the risk of infection than the variation in filament linking.
Deep demosaicking for multispectral filter arrays.

We propose a novel demosaicking method for multispectral filter arrays based on a deep convolutional neural network. The proposed method first interpolates mosaicked multispectral images utilizing a bilinear approach, then applies a residual network to initial demosaicked images. The residual network consists of various three-dimensional convolutional layers and a rectified linear unit for describing the features of a multispectral data cube. Experimental results reveal that the proposed method outperforms conventional demosaicking methods.