Miracle-dz/UniFAR-FTUs huggingface dataset:
‘I don’t know how we can stop ragging’: a qualitative study on the perceptions of staff and work-affiliated individuals at a Sri Lankan University, on the phenomena of ragging

ABSTRACT Ragging in Sri Lanka is a longstanding initiation ritual, similar to hazing and bullying. The severe harassment of new students by seniors has led to adverse consequences including depression, university dropouts and suicide. Although, a significant problem, research on ragging is scarce. This research aimed to explore how staff and work-affiliated individuals at Jaffna University resonate around the phenomenon of ragging. Seven focus group discussions and eleven semi-structured interviews were conducted. Foucauldian Discourse Analysis and Bandura’s Moral Disengagement theory were used to interpret the data. Three main discourses reflected the context: ragging as normal and necessary, insecurity and fear of reprisal, and voices of resistance. Participants often felt unsupported and therefore adapted their moral compasses to survive in this insecure environment. These findings demonstrate a fragmented approach to ragging that not only diminished any efforts towards elimination but affected how staff were forced to adjust their behavior to work in this environment. To address ragging, there is a need to adhere to a consistent strategy focusing on increasing awareness and supporting staff by holding accountable those at all levels of the administrative hierarchy in promoting a safe working environment for all.
IMPACT OF FINANCIAL DISTRESS AND FINANCING CONSTRAINTS ON TRADE CREDIT

Purpose this study to examine the effect of (1) Financial Distress and (2) Financial Constraints on trade credit in companies listed on the Indonesia Stock Exchange (IDX). The Sampel in this study are all companies listed on the Indonesia Stock Exchange, except the banking and financing industries from 2020 to 2011. This study used the regression Fixed Effect Model to analyze secondary data from S&P Capital IQ. The study results show that (1) Financial Distress and Financial Constraint have a negative effect on Accounts Payable, (2) Financial Distress and Financial Constraint have a positive effect on Accounts Receivable.
Employing RHIC and LHC data to determine the transverse momentum dependent gluon density in a proton

Transverse momentum dependent (TMD) parton distributions in a proton are important in high energy physics from both theoretical and phenomenological points of view. Using the latest RHIC and LHC data on the inclusive soft hadron production in $pp$ and $AA$ collisions at small transverse momenta, we determine the parameters of the initial TMD gluon density, derived in the framework of quark-gluon string model at the low scale $\mu_0 \sim 1 - 2$ GeV and refine its large-$x$ behaviour using the LHC data on the $t \bar t$ production at $\sqrt s = 13$ TeV. Then, we apply the Catani-Ciafaloni-Fiorani-Marchesini (CCFM) evolution equation to extend the obtained TMD gluon density to the whole kinematical region. In addition, the complementary TMD valence and sea quark distributions are generated. The latter are evaluated in the approximation where the gluon-to-quark splitting occurs at the last evolution step using the TMD gluon-to-quark splitting function. Several phenomenological applications of the proposed TMD quark and gluon densities to the LHC processes are discussed.
IPAS Implementation in Elementary Schools: How Teachers Build Student Understanding

Merging science (IPA) and social studies (IPS) subjects into science and learning (IPAS) in elementary schools is challenging for teachers. This study aims to determine how teachers build students' understanding of IPAS subjects. The research method used is descriptive qualitative through case studies. Data collection techniques using observation, in-depth interviews, and documentation studies. The research subjects were SDIT At-Taqwa KPAD Bandung IV teachers. Data analysis utilizes Miles and Huberman's techniques. Based on the research results, the teacher's way of building student understanding is by highlighting the dominant material between Science and Social Sciences; the teacher uses a student-centered approach with cooperative learning models and scientific methods as well as various types of cooperative learning, although the combination of the two subjects (IPA and IPS) are considered less effective. However, with various creativities and innovations created by the teacher, the learning process can still run well. The implications of this research for IPAS learning in the classroom are as an alternative for teachers in carrying out science learning to build students' understanding of IPAS comprehensively. Besides that, the results of this research are expected to be input for policymakers in deciding or providing a policy in a curriculum.
Shape prior based moving object detection

In intelligent video surveillance, moving object detection plays an important role as the basis of activity understanding and gait recognition. Existing background subtraction post-processing methods don't use shape prior information and previous background subtraction results to guide current detection. As a result, one moving object splits into many connected components. Background pixels are included in foreground object in dynamic scenes. The proposed moving object detection method embeds the shape prior in a Markov random fields (MRF) energy function to improve the result of background subtraction. Gaussian mixture model (GMM) background subtraction is used to obtain the initial results, then MRF energy function with shape prior is used to correct the results. Iterated Conditional Modes (ICM) method is employed to optimize the energy function with the output of GMM as the initial labels. The demonstration shows that the proposed method performs better than GMM and GMM with MRF in dynamic and some other complex environments.
On the Potential of Discrete Time Survival Analysis Using Latent Variable Modeling: An Application to the Study of the Vascular Depression Hypothesis

Analysis and modeling of time to event data have been traditionally associated with nonparametric, semiparametric, or parametric statistical frameworks. Recent advances in latent variable modeling have additionally provided unique analytic opportunities to methodologists and substantive researchers interested in survival time modeling. As a consequence, discrete time survival analyses can now be readily carried out using latent variable modeling, an approach that offers substantively important extensions to conventional survival models. Using data from the Health and Retirement Study, the discussed approach is applied to the study of the increasingly prominent vascular depression hypothesis in gerontology, geriatrics, and aging research, allowing examination of the unique predictive power of depression with respect to time to stroke in middle-aged and older adults.
The Impact of Stability Balls, Activity Breaks, and a Sedentary Classroom on Standardized Math Scores.

The purpose of the study was to determine if standardized math test scores improve by administering different types of exercise during math instruction. Three sixth grade classes were assessed on the Measures of Academic Progress (MAP) and the Minnesota Comprehensive Assessment (MCA) standardized math tests during the 2012 and 2013 academic year. The MAP standardized test was given at the beginning and end of the academic year. The MCA test was given every spring. The classes used the same math curriculum. Each class had a different math teacher, but each teacher taught the same class all year. One math classroom (n=23) did no physical exercise during instruction, another (n=29) conducted two 5-min physical activity breaks during each math period, and the third math classroom (n=29) always sat on stability balls. A one-way ANOVA was computed for both MAP and MCA improvement scores across the three classrooms to determine if exercise affected standardized math test scores. MAP improvement scores were significantly higher for the class that sat on stability balls (mean = 11.6, SD = 6.9) when compared to the sedentary class (M = 5.5, SD = 7.0). MCA improvement scores were also significantly higher for the stability ball class (M = 104.9, SD = 19.7) when compared to the class that conducted activity breaks (M = 92.6, SD = 7.4). The results indicate that stability balls may provide better focus for learning than short duration vigorous physical activity or no physical activity during math instruction. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif";}
Vision-Based Methods for Food and Fluid Intake Monitoring: A Literature Review

Food and fluid intake monitoring are essential for reducing the risk of dehydration, malnutrition, and obesity. The existing research has been preponderantly focused on dietary monitoring, while fluid intake monitoring, on the other hand, is often neglected. Food and fluid intake monitoring can be based on wearable sensors, environmental sensors, smart containers, and the collaborative use of multiple sensors. Vision-based intake monitoring methods have been widely exploited with the development of visual devices and computer vision algorithms. Vision-based methods provide non-intrusive solutions for monitoring. They have shown promising performance in food/beverage recognition and segmentation, human intake action detection and classification, and food volume/fluid amount estimation. However, occlusion, privacy, computational efficiency, and practicality pose significant challenges. This paper reviews the existing work (253 articles) on vision-based intake (food and fluid) monitoring methods to assess the size and scope of the available literature and identify the current challenges and research gaps. This paper uses tables and graphs to depict the patterns of device selection, viewing angle, tasks, algorithms, experimental settings, and performance of the existing monitoring systems.
A rock physics model in vertical transverse isotropy media and its application to Eagle Ford shale

Shales are rocks with a complex structure. Shales contain high clay content, which constitutes a load‐bearing skeleton. In this study, we present a novel rock physics model to obtain elastic stiffness coefficients of both clays and shales. The robustness of the model is then verified by a field dataset from Eagle Ford shale. We utilize the extended Maxwell homogenization scheme as a rock physics model for transversely isotropic media, which honours the aspect ratio of each inhomogeneity embedded in an effective inclusion domain. Estimated anisotropy parameters ε, γ and δ, on average, are 0.19, 0.29 and 0.04, respectively, based on our modelling results in Eagle Ford shale. Anisotropic modelling results exhibit a good correlation with dipole sonic logs. Both dipole sonic log analysis and rock physics results demonstrate that clay content is the main driver of anisotropy in the field, and there is a direct relationship between clay volume and anisotropy parameters of ε and γ. The method shown here can be readily applied to other unconventional reservoirs.
On the Use of Wireless Technologies for Wildlife Monitoring: Wireless Sensor Network Routing Protocols

Traditional methods for wildlife monitoring are labor-intensive and time-consuming. Therefore, advanced technologies and remote monitoring methods are becoming increasingly popular. This paper presents a study on wireless technologies for wildlife monitoring. In the study, a review of the literature was done to identify the most commonly used wireless technologies. Various technologies were explored including unmanned aerial vehicles (UAVs), Internet of Things (IoT), wireless sensor networks (WSNs), artificial intelligence (AI), global positioning system (GPS), and very high frequency (VHF) radio. Then, a more detailed study was done on WSN technology. Investigations were done to observe the performance of routing protocols in WSNs. The use of source location privacy (SLP) routing protocols was considered for secure wildlife monitoring in areas such as game reserves. In such areas, sensor node energy consumption minimization and battery lifetime maximization are crucial. Hence, energy-efficient SLP protocols are more suitable for deployment. Using MATLAB simulation environment, performance analysis of various phantom- based SLP protocols was done to identify effective and energy-efficient SLP protocols. Simulation results show that two-level phantom with a backbone route protocol (TBP) and phantom with angle protocol (PAP) exhibit advantageous performance features in terms of SLP protection, energy efficiency, effective long-term SLP protection, and scalability. Thus, TBP and PAP are suitable for deployment in wildlife monitoring WSNs.
DG-GAN: A High Quality Defect Image Generation Method for Defect Detection

The surface defect detection of industrial products has become a crucial link in industrial manufacturing. It has a series of chain effects on the control of product quality, the safety of the subsequent use of products, the reputation of products, and production efficiency. However, in actual production, it is often difficult to collect defect image samples. Without a sufficient number of defect image samples, training defect detection models is difficult to achieve. In this paper, a defect image generation method DG-GAN is proposed for defect detection. Based on the idea of the progressive generative adversarial, D2 adversarial loss function, cyclic consistency loss function, a data augmentation module, and a self-attention mechanism are introduced to improve the training stability and generative ability of the network. The DG-GAN method can generate high-quality and high-diversity surface defect images. The surface defect image generated by the model can be used to train the defect detection model and improve the convergence stability and detection accuracy of the defect detection model. Validation was performed on two data sets. Compared to the previous methods, the FID score of the generated defect images was significantly reduced (mean reductions of 16.17 and 20.06, respectively). The YOLOX detection accuracy was significantly improved with the increase in generated defect images (the highest increases were 6.1% and 20.4%, respectively). Experimental results showed that the DG-GAN model is effective in surface defect detection tasks.
BALANCING RELIGIOUS TRADITIONS AND LEGAL NEUTRALITY: THE INDEPENDENCE OF INDONESIA'S CONSTITUTIONAL COURT

This article examines the independence of the Indonesian Constitutional Court in relation to religious issues, particularly regarding religious freedom and marriage regulations. Utilizing a socio-legal approach, the article analyzes five judgments and assesses whether the Court accommodates the aspirations of the religious majority while still maintaining neutrality. Results show that the Court's legal decisions tend to accommodate societal aspirations, but this does not necessarily indicate a lack of neutrality. The article asserts that the independence and neutrality of the judiciary are crucial in a rule of law state, and the Court must balance societal aspirations with its role as a legal decision-making body. The Court's independence should be evaluated based on the methodological consistency of its legal decisions. Overall, the article highlights the importance of judicial independence and neutrality in a rule of law state, with implications for Indonesia's Constitutional Court and other similar legal systems.
YIELD VARIATION IN SUMMER GREEN GRAM WITH RESPECT TO EFFECTIVE FLOWER PRODUCTION IN DIFFERENT DATES OF SOWING

A trial was undertaken in 1992 with six green gram varieties in four dates of sowing to identify the best performing varieties and the most suitable time for sowing with respect to effective flower production in the summer season. The best varieties in terms of flower production and grain yield were AAU-39 and ML-131. Flower drop and poor pod setting were the most serious problem limiting crop yield. Total number of flower produced, percentage flower retention and total number of pods harvested were positively correlated with grain yield. The best period for sowing summer green gram was identified as the period between last week of February and first fortnight of March.
Search for multiple neutrino flares from Active Galactic Nuclei with the IceCube detector

Active Galactic Nuclei are among the best candidate sources for high-energy cosmic rays. High-energy neutrinos are expected to be produced in these sources via interactions of cosmic rays with matter or photon fields present in the source vicinity. The resulting neutrino flux may exhibit time variability on the same time scales than the ones observed in the electromagnetic radiation that is emitted from these sources with flare durations ranging from minutes to several days depending on the photon energy. Time variability can be taken into account in high-energy neutrino searches in order to increase their detection probability with respect to search methods that include only energy and spatial information. In this work, two new methods are developed to look for highenergy neutrino flares emitted from Active Galactic Nuclei: the Multi-flare and Multi-flare stacking method. The Multi-flare method is designed to be sensitive not only to one bright flare emitted from a single source, as considered in other existing search methods, but also to several weak flares that might not be detected individually. This is achieved by developing a likelihood stacking approach that analyzes the cumulative neutrino emission from several flares. This method does not assume a-priori time coincidences with photon flares observed in the electromagnetic spectrum, allowing uncorrelated neutrino emission with different flare durations as considered in some emission models. The Multi-flare stacking method is an extension of the Multi-flare method to include several sources that might be too weak for individual detection. The two search methods are applied to a pre-selected list of Active Galactic Nuclei, composed of Flat Spectrum Radio Quasars and BL-Lacs, using data of the IceCube Neutrino Observatory taken between May-2009 and May-2012. No statistically significant neutrino flares are detected and fluence upper limits are calculated for each selected source. These limits are on average a factor of two better than previous upper limits from single-flare searches.
GPS Loss of Lock Events and Their Dependence on the Interplanetary Magnetic Field Orientation

The study investigates the influence of interplanetary magnetic field (IMF) orientation on loss of lock (LoL) events in Global Positioning System signals. We analyzed LoLs recorded on two Swarm satellites between July 2014 and December 2021, examining how the signs of the IMF Bx, By, and Bz components affect the distribution of events at high latitudes. Our results reveal an asymmetric distribution of LoL events over 75° magnetic latitude. In the Northern hemisphere, more events occur in the post‐noon sector with negative IMF By, and in the pre‐noon sector with positive IMF By. Conversely, in the Southern hemisphere, pre‐noon events increase with negative IMF By, while post‐noon events increase with positive IMF By. At lower latitudes (50°–75°), IMF By does not significantly affect the event distribution, which mainly concentrates in the night sector for both hemispheres. Additionally, we found a connection between IMF By and Bx, primarily due to the IMF spiral structure. Finally, we discuss our findings in the context of the SuperDARN data‐driven model of ionospheric convection patterns, which shows that LoL events frequently cluster in the cusp region, as well as the area where the two convection cells separate.
Evaluation of Manual Log Measurement Errors and Its Implications on Harvester Log Measurement Accuracy

Abstract Previous studies of harvester measurement accuracy assumed traditional manual log measurements were accurate and represented true log dimensions, which relies heavily on the assumption that logs are regular in shape. The objective of this study was to quantify the level of variability in manual log measurements and consider its impact on harvester calibration and accuracy assessments. Log length was measured along the top and each side and small-end diameter with callipers, a diameter tape, and a steel ruler in two radiata pine stands near Mt. Gambier in Southern Australia. Observed variability in manual log measurements was sufficient to affect harvester accuracy studies and calibration. Length variability on different sides of a log occurs mainly from non-square log ends. Differences due to observer were minor. Diameter measurement variability occurs mainly from the effect of stem eccentricity on each instrument, which is dependent on its number of stem contact points. Callipers have fewer contact points than a diameter tape and hence more variability. This variability was evident in comparisons between observers and instruments. Harvester accuracy studies need to minimize manual measurement variability to identify harvester measurement errors. Length should be measured on the same side measured by the harvester. Diameter should be measured with a diameter tape in preference to callipers as they have greater stem contact and less variability. Harvester calibration needs to minimize manual and harvester measurement variability to identify harvester measurement bias with the least number of logs to minimize the time required for these activities. In addition to the above suggestions relating to harvester accuracy study measurements, logs selected for calibration must be the most uniform in shape available to highlight harvester measurement biases.
Optimal panel unit root testing with covariates

SummaryThis paper provides asymptotic optimality results for panel unit root tests with covariates by deriving the Gaussian power envelope. The main conclusion is that the use of covariates holds considerable promise in the panel data context, much more so than in the time series context. In fact, the use of the covariates not only leads to increased power, but can actually have an order effect on the shrinking neighbourhoods around unity for which power is non-negligible.
APPROXIMATE ANALYTICAL SOLUTIONS OF MHD VISCOUS FLOW DUE TO A SHRINKING SHEET

The paper presents the semi-numerical solution for the magnetohydrodynamic (MHD) viscous flow due to a shrinking sheet caused by boundary layer of an incompressible viscous flow. The governing three partial differential equations of momentum equations are reduced into ordinary differential equation (ODE) by using a classical similarity transformation along with appropriate boundary conditions. Both nonlinearity and infinite interval demand novel mathematical tools for their analysis. We use fast converging Dirichlet series and Method of stretching of variables for the solution of these nonlinear differential equations. These methods have the advantages over pure numerical methods for obtaining the derived quantities accurately for various values of the parameters involved at a stretch and also they are valid in much larger parameter domain as compared with HAM, HPM, ADM and the classical numerical schemes.