Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementasi E-Learning Sejarah Kebudayaan Islam Pada Masa Pandemi COVID-19 Di MTsN 4 Gunungkidul

The Covid-19 pandemic that hit Indonesia had an impact on the world of education so that the Central Ministry of Religion created a learning application in the form of E-Learning Madrasas for distance learning. MTs N 4 Gunungkidul stated that it was ready to learn with Madrasa E-Learning during the Covid-19 pandemic. Therefore, the purpose of this study is to describe the implementation of E-Learning during the Covid-19 pandemic at MTs N 4 Gunungkidul. This study uses a descriptive qualitative approach. Data collection techniques by conducting observations, interviews, questionnaires and documentation. The results showed that the implementation of Madrasah E-Learning in Islamic Cultural History Subjects during the Covid-19 pandemic at MTs N 4 Gunungkidul was able to implement E-Learning well. The implementation of Madrasah E-Learning is carried out in 3 stages: the preparation stage, the implementation stage and the evaluation stage. The strategy is in the use of Madrasah E-Learning features and in learning. Constraints are in the features of Madrasah E-Learning that need to be updated and perfected as well as network and internet quota constraints.
Teacher Continuing Education and Capacity Building as Correlates of the Successful Implementation of Non-Formal Education Programmes in South-South Nigeria in the Era of Society 5.0

: The study examined teacher continuing education and capacity building as correlates of the successful implementation of Non-Formal education programmes in South-South Nigeria in the era of society 5.0. Two (2) research questions and 2 hypotheses were answered and tested in the study, respectively. The design of the study was correlational ,with the population as the Non-Formal Education Units of the Ministry of Education of Akwa Ibom, Bayelsa, Cross River, Delta, Edo and Rivers States of South-South Nigeria. These units have Units and Out Stations Personnel, numbering 5550, who are involved in general administration, supervision, inspection and teaching in Non-Formal education programmes. From this number, 1388 were selected as sample, using the stratified and simple random sampling technique. The study had two sets of instruments. These were the validated 23-item Teacher Continuing Education and Capacity Building Scale (TCECBS) and the 16-item Non-Formal Education Programmes Successful Implementation Index (NFEPSII) designed by the researcher, in the modified 4-point Likert scale model, with reliability indices of 0.84 and 0.75, respectively, obtained using Cronbach Alpha statistical model. Pearson Product Moment Correlation Co-efficient was used in answering the research questions which the r-values from Pearson calculations were converted to z-values and used in testing the hypothesis at 0.05 level of significance. The results of the study show strong and positive correlations between teacher continuing education and teacher capacity building and successful implementation of Non-Formal education programmes in South-South Nigeria in the era of Society 5.0. The study also established significant correlations of teacher continuing education and capacity building and successful implementation of Non-Formal education programmes in South-South Nigeria in the era of Society 5.0. was therefore Non-Formal education programmes will attain successful as stakeholders continue to ensure education and capacity building programmes for programmes' Consequently, it was recommend that stakeholders in Non-formal education programmes should continue to ensure that teachers have access to continuing education programmes and that their capacities are built as need arises.
New Onset Atrial Fibrillation in STEMI Patients: Main Prognostic Factors and Clinical Outcome

The indications for the treatment of patients with known atrial fibrillation (AF) undergoing percutaneous coronary intervention (PCI) are clear, while less is available about the management of new-onset AF (NOAF) during ST-segment elevation myocardial infarction (STEMI). The aim of this study is to evaluate mortality and clinical outcome of this high-risk subgroup of patients. We analyzed 1455 consecutive patients undergoing PCI for STEMI. NOAF was detected in 102 subjects, 62.7% males, with a mean age of 74.8 ± 10.6 years. The mean ejection fraction (EF) was 43.5 ± 12.1% and the mean atrial volume was increased (58 ± 20.9 mL). NOAF occurred mainly in the peri-acute phase and had a very variable duration (8.1 ± 12.5 min). During hospitalization, all the patients were treated with enoxaparin, but only 21.6% of them were discharged with long term oral anticoagulation. The majority of patients had a CHA2DS2-VASc score >2 and a HAS-BLED score of 2 or 3. The in-hospital mortality was 14.2%, while the 1-year mortality was 17.2% and long-term mortality 32.1% (median follow-up 1820 days). We identified age as an independent predictor of mortality both at short- and long-term follow-ups, while EF was the only independent predictor for in-hospital mortality and arrhythmia duration for 1-year mortality. At the 1-year follow-up, we recorded three ischemic strokes and no bleeding complications.
Profile of Community Understanding and Literacy About Disaster Risk Mitigation: The Responses of Java South Coast Community Against Megathrust Earthquake and Tsunami Prediction

Widiyantoro et al., as Institut Teknologi Bandung (ITB) scientists, predict the worst possibility that in the south of Java Island, a megathrust earthquake with a maximum magnitude of up to 9.1 on the Richter scale and a tsunami of up to 20 meters. So understanding and literacy about mitigation of the megathrust earthquake and tsunami need to be improved so that the South Coast of Java Island (Pansela) community has prepared for these disasters. This study aims to analyze the understanding and literacy of the Pansela community of the earthquake and tsunami disaster against the predictions made by ITB scientists. This study uses a qualitative descriptive method with a total of 57 community respondents living in Pansela. The study results show that most communities believe in this prediction and have fewer mitigation efforts against this disaster. However, the respondents still did not know the specifics of the megathrust earthquake. They considered an earthquake in the south of Java Island related to the megathrust earthquake. Therefore, it is necessary to increase community understanding and literacy regarding mitigation efforts against megathrust earthquakes and tsunami.
Antecedents and Outcomes of Work-Family Conflict among Chinese Employees:The Cultural Difference Perspective

The study reported in this paper conducted a preliminary study on antecedents and outcomes of work-family conflict among Chinese employees.Influenced by Chinese social and cultural context,Chinese employees generally regard work as the core of their life.This study upholds that work-family conflict contains two dimensions.Antecedents and outcomes were selected from the Western literatures.The findings show that some antecedents and outcomes have different relationships with work-family conflict.The difference was interpreted and discussed from the perspective of Chinese social and cultural background.
Parental ecological history can differentially modulate parental age effects on offspring physiological traits in Drosophila

Abstract Parents adjust their reproductive investment over their lifespan based on their condition, age, and social environment, creating the potential for inter-generational effects to differentially affect offspring physiology. To date, however, little is known about how social environments experienced by parents throughout development and adulthood influence the effect of parental age on the expression of life-history traits in the offspring. Here, I collected data on Drosophila melanogaster offspring traits (i.e., body weight, water content, and lipid reserves) from populations where either mothers, fathers both, or neither parents experienced different social environments during development (larval crowding) and adulthood. Parental treatment modulated parental age effects on offspring lipid reserves but did not influence parental age effects on offspring water content. Importantly, parents in social environments where all individuals were raised in uncrowded larval densities produced daughters and sons lighter than parental treatments which produced the heaviest offspring. The peak in offspring body weight was delayed relative to the peak in parental reproductive success, but more strongly so for daughters from parental treatments where some or all males in the parental social environments were raised in crowded larval densities (irrespective of their social context), suggesting a potential father-to-daughter effect. Overall, the findings of this study reveal that parental ecological history (here, developmental and adult social environments) can modulate the effects of parental age at reproduction on the expression of offspring traits.
The Relationship between Autonomous Extrinsic Motivation of Salespeople and Work Performance: An Empirical Study from Vietnam

This study explores the direct relationship between challenge and hindrance demands affecting autonomous extrinsic motivation and sales performance. In addition, we examine the mediating role of autonomous extrinsic motivation in the relationship between challenge demands, hindrance demands, and sales performance. This study explores the direct relationship between challenge and hindrance demands affecting autonomous extrinsic motivation and sales performance. In addition, we examine the mediating role of autonomous extrinsic motivation in the relationship between challenge demands, hindrance demands, and sales performance. This study proceeded in two phases comprising preliminary and prime research. First, preliminary quantitative research was conducted through face-to-face interviews with 125 observations to analyze the reliability of the scale and exploratory factor analysis to evaluate the measurements. The data collected from 431 real estate market employees shows that both challenge and hindrance demands positively and negatively affect sales performance through autonomous extrinsic motivation. Furthermore, challenge demands and hindrance demands affect positive and negative sales performance through autonomous extrinsic motivation, respectively. This study suggests that business organizations should design job demands to ensure that challenging work is suitable for employees’ job positions. Thus, they will contribute to motivation and help employees achieve job performance.
Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction

Video recordings of speech contain correlated audio and visual information, providing a strong signal for speech representation learning from the speaker's lip movements and the produced sound. We introduce Audio-Visual Hidden Unit BERT (AV-HuBERT), a self-supervised representation learning framework for audio-visual speech, which masks multi-stream video input and predicts automatically discovered and iteratively refined multimodal hidden units. AV-HuBERT learns powerful audio-visual speech representation benefiting both lip-reading and automatic speech recognition. On the largest public lip-reading benchmark LRS3 (433 hours), AV-HuBERT achieves 32.5% WER with only 30 hours of labeled data, outperforming the former state-of-the-art approach (33.6%) trained with a thousand times more transcribed video data (31K hours). The lip-reading WER is further reduced to 26.9% when using all 433 hours of labeled data from LRS3 and combined with self-training. Using our audio-visual representation on the same benchmark for audio-only speech recognition leads to a 40% relative WER reduction over the state-of-the-art performance (1.3% vs 2.3%). Our code and models are available at https://github.com/facebookresearch/av_hubert
On the parameter refinement of inflated exoplanets with large radius uncertainty based on TESS observations

Correspondence *Email: xalexoudi@aip.de We revisited ten known exoplanetary systems using publicly available data provided by the Transiting Exoplanet Survey Satellite (TESS). The sample presented in this work consists of short period transiting exoplanets, with inflated radii and large reported uncertainty on their planetary radii. The precise determination of these values is crucial in order to develop accurate evolutionary models and understand the inflation mechanisms of these systems. Aiming to evaluate the planetary radius measurement, we made use of the planet-to-star radii ratio, a quantity that can be measured during a transit event. We fit the obtained transit light curves of each target with a detrending model and a transit model. Furthermore, we used emcee, which is based on a Markov chain Monte Carlo approach, to assess the best fit posterior distributions of each system parameter of interest. We refined the planetary radius of WASP-140 b by approximately 12%, and we derived a better precision on its reported asymmetric radius uncertainty by approximately 86% and 67%. We also refined the orbital parameters of WASP-120 b by 2σ. Moreover, using the high-cadence TESS datasets, we were able to solve a discrepancy in the literature, regarding the planetary radius of the exoplanet WASP-93 b. For all the other exoplanets in our sample, even though there is a tentative trend that planetary radii of (near-) grazing systems have been slightly overestimated in the literature, the planetary radius estimation and the orbital parameters were confirmed with independent observations from space, showing that TESS and ground-based observations are overall in good agreement.
Equilibrium fluctuations for totally asymmetric interacting particle systems

Abstract. We study equilibrium fluctuations for a class of totally asymmetric zero-range type interacting particle systems. As a main result, we show that density fluctuation of our process converges to the stationary energy solution of the stochastic Burgers equation. As a special case, microscopic system we consider here is related to q-totally asymmetric simple exclusion processes (q-TASEPs) and our scaling limit corresponds to letting the quantum parameter q to be one.
Numerical Solutions of the External Field Effect on the Radial Acceleration in Disk Galaxies

In modified Newtonian dynamics (MOND)-based theories, the strong equivalence principle is generically broken in an idiosyncratic manner, manifested in the action of an “external field effect” (EFE). The internal dynamics in a self-gravitating system is affected even by a constant external field. In disk galaxies, the EFE can induce warps and modify the rotational speeds. Due to the nonlinearity of MOND, it is difficult to derive analytic expressions of this important effect in a disk. Here we study numerically the EFE in two nonrelativistic Lagrangian theories of MOND: the “Aquadratic–Lagrangian” theory (AQUAL) and “Quasilinear MOND” (QUMOND). For AQUAL, we consider only the axisymmetric field configurations with the external field along the disk axis, or a spherical galaxy with test-particle orbits inclined to the external field. For the more manageable QUMOND, we also calculate the three-dimensional field configurations, with the external field inclined to the disk axis. We investigate in particular to what degree an external field modifies the quasi-flat part of rotation curves. While our QUMOND results agree well with published numerical results in QUMOND, we find that AQUAL predicts weaker EFE than published AQUAL results. However, AQUAL still predicts stronger EFE than QUMOND, which demonstrates current theoretical uncertainties. We also illustrate how the MOND prediction on the rising part of the rotation curve, in the inner parts, depends largely on disk thickness but only weakly on a plausible external field for a fixed galaxy model. Finally, we summarize our results for the outer parts as an improved, approximate analytic expression.
Egocentric Deep Multi-Channel Audio-Visual Active Speaker Localization

Augmented reality devices have the potential to enhance human perception and enable other assistive functionalities in complex conversational environments. Effectively capturing the audio-visual context necessary for understanding these social interactions first requires detecting and localizing the voice activities of the device wearer and the surrounding people. These tasks are challenging due to their egocentric nature: the wearer's head motion may cause motion blur, surrounding people may appear in difficult viewing angles, and there may be occlusions, visual clutter, audio noise, and bad lighting. Under these conditions, previous state-of-the-art active speaker detection methods do not give satisfactory results. Instead, we tackle the problem from a new setting using both video and multi-channel microphone array audio. We propose a novel end-to-end deep learning approach that is able to give robust voice activity detection and localization results. In contrast to previous methods, our method localizes active speakers from all possible directions on the sphere, even outside the camera's field of view, while simultaneously detecting the device wearer's own voice activity. Our experiments show that the proposed method gives superior results, can run in real time, and is robust against noise and clutter.
Efficient Global Optimization of Two-layer ReLU Networks: Quadratic-time Algorithms and Adversarial Training

The non-convexity of the artificial neural network (ANN) training landscape brings inherent optimization difficulties. While the traditional back-propagation stochastic gradient descent (SGD) algorithm and its variants are effective in certain cases, they can become stuck at spurious local minima and are sensitive to initializations and hyperparameters. Recent work has shown that the training of an ANN with ReLU activations can be reformulated as a convex program, bringing hope to globally optimizing interpretable ANNs. However, naively solving the convex training formulation has an exponential complexity, and even an approximation heuristic requires cubic time. In this work, we characterize the quality of this approximation and develop two efficient algorithms that train ANNs with global convergence guarantees. The first algorithm is based on the alternating direction method of multiplier (ADMM). It solves both the exact convex formulation and the approximate counterpart. Linear global convergence is achieved, and the initial several iterations often yield a solution with high prediction accuracy. When solving the approximate formulation, the per-iteration time complexity is quadratic. The second algorithm, based on the"sampled convex programs"theory, is simpler to implement. It solves unconstrained convex formulations and converges to an approximately globally optimal classifier. The non-convexity of the ANN training landscape exacerbates when adversarial training is considered. We apply the robust convex optimization theory to convex training and develop convex formulations that train ANNs robust to adversarial inputs. Our analysis explicitly focuses on one-hidden-layer fully connected ANNs, but can extend to more sophisticated architectures.
The dynamics of representation learning in shallow, non-linear autoencoders

Autoencoders are the simplest neural network for unsupervised learning, and thus an ideal framework for studying feature learning. While a detailed understanding of the dynamics of linear autoencoders has recently been obtained, the study of non-linear autoencoders has been hindered by the technical difficulty of handling training data with non-trivial correlations—a fundamental prerequisite for feature extraction. Here, we study the dynamics of feature learning in non-linear, shallow autoencoders. We derive a set of asymptotically exact equations that describe the generalisation dynamics of autoencoders trained with stochastic gradient descent (SGD) in the limit of high-dimensional inputs. These equations reveal that autoencoders learn the leading principal components of their inputs sequentially. An analysis of the long-time dynamics explains the failure of sigmoidal autoencoders to learn with tied weights, and highlights the importance of training the bias in ReLU autoencoders. Building on previous results for linear networks, we analyse a modification of the vanilla SGD algorithm, which allows learning of the exact principal components. Finally, we show that our equations accurately describe the generalisation dynamics of non-linear autoencoders trained on realistic datasets such as CIFAR10, thus establishing shallow autoencoders as an instance of the recently observed Gaussian universality.
Uniqueness of the partial travel time representation of a compact Riemannian manifold with strictly convex boundary

In this paper a compact Riemannian manifold with strictly convex boundary is reconstructed from its partial travel time data. This data assumes that an open measurement region on the boundary is given, and that for every point in the manifold, the respective distance function to the points on the measurement region is known. This geometric inverse problem has many connections to seismology, in particular to microseismicity. The reconstruction is based on embedding the manifold in a function space. This requires the differentiation of the distance functions. Therefore this paper also studies some global regularity properties of the distance function on a compact Riemannian manifold with strictly convex boundary.
No self-concordant barrier interior point method is strongly polynomial

It is an open question to determine if the theory of self-concordant barriers can provide an interior point method with strongly polynomial complexity in linear programming. In the special case of the logarithmic barrier, it was shown in [Allamigeon, Benchimol, Gaubert and Joswig, SIAM J. on Applied Algebra and Geometry, 2018] that the answer is negative. In this paper, we show that none of the self-concordant barrier interior point methods is strongly polynomial. This result is obtained by establishing that, on parametric families of convex optimization problems, the log-limit of the central path degenerates to a piecewise linear curve, independently of the choice of the barrier function. We provide an explicit linear program that falls in the same class as the Klee–Minty counterexample for the simplex method, i.e., in which the feasible region is a combinatorial cube and the number of iterations is Ω(2n).
Planted Dense Subgraphs in Dense Random Graphs Can Be Recovered using Graph-based Machine Learning

Multiple methods of finding the vertices belonging to a planted dense subgraph in a random dense G(n, p) graph have been proposed, with an emphasis on planted cliques. Such methods can identify the planted subgraph in polynomial time, but are all limited to several subgraph structures. Here, we present PYGON, a graph neural network-based algorithm, which is insensitive to the structure of the planted subgraph. This is the first algorithm that uses learning tools for recovering dense subgraphs. We show that PYGON can recover cliques of sizes Θ (√ n), where n is the size of the background graph, comparable with the state of the art. We also show that the same algorithm can recover multiple other planted subgraphs of size Θ (√ n), in both directed and undirected graphs. We suggest a conjecture that no polynomial time PAC-learning algorithm can detect planted dense subgraphs with size smaller than O ( √ n), even if in principle one could find dense subgraphs of logarithmic size.