Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-eﬃ cacy, learning motivation, learning environment and its eﬀ ect on online learning outcomes

: This study aimed to analyze e students’ psychological factor, namely self-eﬃ cacy, learning motivation and learning environments on the results of online physical education learning during Covid-19 at Senior High School in Padang, West Sumatera. This study used a quantitative method using a path analysis approach, with structural equations to ﬁ nd out the causality of the dimensions of self-eﬃ cacy, motivation, directly on learning outcomes of physical education, or indirectly through the learning environment. The data collection was carried out using a survey technique to 160 high school students in Padang and analyzed using descriptive statistics. The results show that the power of direct inﬂ uence the self-eﬃ cacy and learning motivation and signiﬁ cantly eﬀ ect their online learning through the learning environment. It also has an impact on learning outcomes. When the teaching and learning process must be carried out through an online system, it is necessary to make improvements to various models and learning designs, so that the learning process is avoided from negative inﬂ uences that can reduce student learning outcomes.
Effects of bypass-current and out plasma current on droplet transfer behaviours during plasma-MIG hybrid arc welding

A new method, bypass-current plasma-MIG hybrid arc welding, was proposed to weld AA 5083 aluminium alloy. A comparative investigation between simulation and experiment was performed to quantify different effects of bypass-current and out plasma current on droplet transfer behaviours. The results show that when the bypass-current is 15 A, the droplets present a projected transfer mode, and its period is 22 ms. But if the outer plasma current is 15 A, the transfer frequency increases 19.1 Hz, and the sizes of the droplet show a slight increase. This is due to the reduction of electromagnetic force and arc plasma force on droplets. The research outcomes provide benefits to the droplet transfer behaviours in control and optimisation during aluminium alloy welding.
Golden Jackal Optimization With Joint Opposite Selection: An Enhanced Nature-Inspired Optimization Algorithm for Solving Optimization Problems

This paper presents the logical relationships of Aristotle’s square of opposition on four basic categorial prepositions (i.e., contrary, contradictory, subcontrary, and subaltern) of Joint Opposite Selection (JOS). JOS brings a mutual reinforcement by a joint of the two opposition strategies Dynamic Opposite (DO) and Selective Leading Opposition (SLO). The DO and SLO improve the balance of exploration and exploitation, respectively, in a given search space. We also propose an enhancement of Golden Jackal Optimization (GJO) with a Joint Opposite Selection named GJO-JOS. In the optimization process, JOS assists GJO in assaulting the prey swiftly using SLO. DO assists GJO in finding better chances to locate the fittest prey. With JOS, the GJO succeeds in elevating its performance. We evaluated the performance of GJO-JOS on the CEC 2017 benchmark functions. The benchmark includes unimodal, multimodal, hybrid, and composition functions. The evaluation results of GJO-JOS were better than GJO using each of the seven single opposition-based learning strategies (OBLs). We also compared GJO-JOS to eight nature-inspired algorithms including the original version of GJO. GJO-JOS produced promising results among seven single OBLs, eight nature-inspired algorithms, and GJO. The experimental results confirmed that GJO-JOS effectively generated equilibrium in the balance mechanism.
Approximate Controllability of Second-Order Systems with State-Dependent Delay

In this article, we consider the approximate controllability for a class of second-order nonlinear functional differential equations with state-dependent delay. Assuming the approximate controllability of the corresponding linearized equation, we obtain sufficient conditions for the approximate controllability of the nonlinear second-order equations. Examples are presented to show the application of the proposed result.
A Systematic Review of Mixed Studies Exploring the Effects of Probiotics on Gut-Microbiome to Modulate Therapy in Children With Autism Spectrum Disorder

Autism spectrum disorder(ASD) is a complex neurodevelopmental disorder characterized by social deficits, repetitive typical behaviors, insistence on the same routines, and communication impairments. The prevalence of ASD has increased in the past decade. While we are aware that there is no cure for ASD, attempts are being made to reduce its symptoms and improve the learning, overall growth, and well-being of ASD patients. Gastrointestinal (GI) symptoms are frequent occurrences in patients with ASD, but the underlying mechanisms are unknown. Recent studies show that the microbiota-gut-brain axis is the key modulator of neuropsychiatric health. Although fecal transplants have shown positive outcomes in treating dysbiosis and symptoms of autism, lifestyle modifications such as dietary intervention will prevent and treat this disorder without causing major adverse effects. Probiotics enhance the microbiome to provide necessary metabolites, which help in gut permeability, cognitive function, and immunity. In some studies, children with increased GI symptoms have also shown increased behavioral disturbances. In this study, a systematic review of mixed studies is conducted to obtain more robust and conclusive results. We included randomized controlled studies with larger sample sizes and specifications on probiotics.
A two-scale sparse grid method for a singularly perturbed reaction-diffusion problem in two dimensions

The linear reaction-diffusion problem -e 2 Δu + bu = f is considered on the unit square with homogeneous Dirichlet boundary conditions. Here e is a small positive parameter and the problem is in general singularly perturbed. The numerical solution of this problem is analysed on a Shishkin mesh that has N intervals in each coordinate direction, using the Galerkin finite-element method with bilinear trial functions. The accuracy of this method, measured in the associated energy norm, is shown to be O(N -2 + e 1/2 N -1 lnN). It is proved that a two-scale sparse grid method achieves the same order of accuracy while reducing the number of degrees of freedom from O(N 2 ) to O(N 3/2 ). These results are then generalized to systems of reaction-diffusion equations.
Convergence of sequences of pairwise independent random variables

In spite of the fact that the tail σ-algebra of a sequence of pairwise independent random variables may not be trivial, we have discovered that if such a sequence converges in probability or almost everywhere, then the limit has to be a constant. This enables us to provide necessary and sufficient conditions for its convergence, in terms of its marginal distribution functions.
Study of identifying factors for the developing measuring instrument on the psychological readiness of athletic athletes

In sports psychology, to improve athlete achievement, in addition to physiological factors, other factors influence an athlete's success, namely psychological factors. Psychological readiness is the readiness possessed by athletes before a match or during a match. Psychological readiness is one of the determining factors for the success of athletes in achieving achievements during matches. This study aims to analyze the determinants of the psychological readiness of athletic athletes. The research method uses descriptive qualitative methods with data collection techniques through focus group discussions. In the competition, psychological factors are needed more than physiological factors. This study showed that 90% of psychological factors affect performance in matches, and physiological factors influence 10%. This study found factors related to the psychological readiness of athletic athletes, namely coping, emotional regulation, self-regulation, and self-confidence. Athletes in training and competition need these factors. Problems that can disrupt the psychology of athletes in competing will result in achievements. This study's results can benefit trainers in integrating psychological approaches into physical exercise programs.
Functional Divergence of the N-Lobe and C-Lobe of Transferrin Gene in Pungitius sinensis (Amur Stickleback)

Simple Summary As an iron-binding glycosylated protein, transferrin plays key roles in iron metabolism and immune response. Here, a transferrin transcript was identified from Amur stickleback, which encoded 679 amino acid peptides harbored obvious N-lobe and C-lobe domains. This transferrin was highly expressed in liver and increased by pathogen stimulation. Molecular evolution was performed on the N-lobe and C-lobe domains. Iron-binding capacity and antibacterial characteristics were also compared between N-lobe and C-lobe. These results will have important reference significance for the subsequent functional research. Abstract Transferrin is an important iron-binding glycosylated protein and plays key roles in iron-binding and immune response. Here, a 2037-bp open reading frame was obtained from our previous transcriptome sequencing data of Amur stickleback, which encoded a 679 amino acid putative transferrin protein harbored obvious N-lobe and C-lobe domains. The tissue-specific expression pattern showed that the transcript was detected in a variety of tissues, with the highest signal in liver. Moreover, Streptococcus iniae pathogen stimulation can increase the expression level of this transcript, implying important immune properties for organisms. Next, N-lobes and C-lobes were obtained from 45 fish species. The phylogenetic tree showed that N-lobes and C-lobes were in two different evolutionary branches, and they had different motif composition. Functional divergence indicated a higher evolutionary rate or site-specific alteration among the N-lobe and C-lobe groups. Ka/Ks value of C-lobe group was relatively higher than that of N-lobe group, indicating a faster change rate of C-lobe sequences in evolution. Moreover, some sites experiencing positive selection were also found, which may be involved in the iron- or anion-binding, pathogen resistance and diversification of transferrin protein. Differential iron-binding activity was also detected between N-lobe and C-lobe of Amur stickleback transferrin protein with Chrome Azurol S assay. Compared with the C-lobe, the N-lobe showed stronger growth inhibitory activity of Escherichia coli, implying their potential antibacterial properties. This study will give a reference for subsequent research of transferrin proteins.
KOMPARASI ANALISIS GEROMBOL (CLUSTER) DAN BIPLOT DALAM PENGELOMPOKAN

One of functions of multivariate analysis is to group data. Multivariate analysis often used in grouping data are cluster analysis and biplot analysis. In this paper, a comparative analysis will be made between clusters analysis and biplot analysis for grouping the data. Technique used in the cluster analysis is kmean method and biplot analysis used two-dimensional display. The results ware that biplot analysis produces are better in grouping accuracy than clusters analysis. But in general, biplot analysis can not be said to be better than clusters analysis in grouping the data and vice versa.
Area-Efficient Number Theoretic Transform Architecture for Homomorphic Encryption

Homomorphic encryption (HE) has emerged as an ideal cryptographic technology for meaningful computations on encrypted data. Not only does HE secure private information even if the ciphertext is leaked, but it also maintains data integrity when inferring cloud-side services. However, homomorphic computations include expensive polynomial arithmetic, especially polynomial multiplication. Prior studies proposed number theoretic transform (NTT) hardware designs to accelerate polynomial multiplication. However, the trade-off between hardware complexity and throughput of NTT designs was not considered carefully. This paper proposes an area-efficient NTT architecture suitable for HE schemes. Center of the proposed NTT architecture is a high-throughput butterfly unit array, which communicates with a single data memory unit through a conflict-free memory access pattern. Additionally, we developed a twiddle factor generator to reduce memory consumption. The proposed NTT architecture was successfully accelerated on the Xilinx FPGA devices. Performing with a large number of moduli, the proposed NTT design achieves higher hardware efficiency than the prior arts. Especially, our NTT design consumes less on-chip memory with efficiency improvement of $8.8\times $ over the most related work. The implementation results confirm that our design methodology has advantages to deploy many NTT accelerators on an FPGA device for practical HE-based applications.
Subdivision Surfaces for CAD

AbstractSubdivision surfaces refer to a class of modelling schemes that define an object through recursive subdivision starting from an initial control mesh. Similar to B-splines, the final surface is defined by the vertices of the initial control mesh. These surfaces were initially conceived as an extension of splines in modelling objects with a control mesh of arbitrary topology. They exhibit a number of advantages over traditional splines. Today one can find a variety of subdivision schemes for geometric design and graphics applications. This paper provides an overview of subdivision surfaces with a particular emphasis on schemes generalizing splines. Some common issues on subdivision surfaces modelling are addressed. Several key topics, such as scheme construction, property analysis and parametric evaluation, are discussed. Some other important topics are also summarized for potential future research and development.
Automatic Group-Based Structured Pruning for Deep Convolutional Networks

Structured pruning methods have been used in several convolutional neural networks (CNNs). However, group-based structured pruning is a challenging task. In previous methods, the number of groups is manually determined for all layers, which is suboptimal. Moreover, which kernels should be appropriately removed? Model accuracy may be significantly reduced when a large number of kernels are deleted. To address these challenges, we propose an automatic group-based structured pruning method with reinforcement learning, named AGSPRL, which can generate pruned models with different compression rates automatically. We first develop a reinforcement learning (RL) framework to learn the pruning rate for group-based channel pruning layer by layer. Then, based on the learned kernel pruning rate, we propose an efficient group configuration algorithm to adaptively determine the number of groups for each convolution layer. Finally, we introduce a channel pruning method with an attention mechanism as a tiny auxiliary filter selector for each group to dynamically determine which part of the kernels should be selected into the group convolution and which part of the kernels should be removed. To demonstrate the efficiency of our method, we apply it to a variety of CNNs in classification and detection datasets. The experimental results show that the AGSPRL not only adaptively but also accurately configures the number of groups. The accuracy is reduced by less than 1%. Moreover, compared to other state-of-the-art methods, AGSPRL is more effective and has less accuracy loss.
Principals’ leadership strategy to improve “link and match” quality for vocational education

This study aimed to identify, analyze, and reflect on vocational school leadership strategies for improving the quality of vocational education. The result achieved is forming the principal’s leadership strategy in improving the quality of education. This study used a qualitative approach so that the data collection was carried out through observation, document analysis, interviews, and questionnaires. This study can be developed to improve the quality of learning at the vocational school level in line with the implementation process. Academically, the results of this study can be used as a guideline for the development of vocational education management. The development of the school into an educational service organization with high-quality sustainability. The results show that the principal’s leadership strategy in improving the quality of education at SMK Negeri 1 Mataram includes articulation of the vision and mission of the school, leadership values of the leaders, awards in the school, social-emotional relationships of principals, and the quality of the “Link and Match” education in schools.
Efficacy of psychosocial interventions for pregnancy rates of infertile women undergoing in vitro fertilization: a systematic review and meta-analysis

Abstract Purpose This study aimed to analyze the efficacy of psychosocial interventions for improving pregnancy rates in infertile women undergoing in vitro fertilization (IVF) treatment through a systematic review and meta-analysis. Methods Twelve studies were included in the meta-analysis. To estimate the effect size, a meta-analysis of the studies was performed using RevMan 5.3. The possibility of publication bias was evaluated using funnel plots and Egger’s method. Results A statistically significant effect size (standardized mean difference [SMD] = 1.39; 95% confidence interval [CI] = 1.11–1.71; p = 0.004; I2 = 19%) was found for the 12 studies that investigated the effects of psychosocial interventions on clinical pregnancy rates. The psychosocial interventions that had a significant effect on pregnancy rates were mind-body interventions (SMD = 1.37; 95% CI = 1.01–1.85; p = 0.040; I2 = 0%) and cognitive behavioral therapy (SMD = 2.19; 95% CI = 1.17–4.13; p = 0.010). Conclusions The results suggest that psychosocial interventions affect pregnancy rates. Moreover, they indicate that mind-body interventions and cognitive behavioral therapy are beneficial for improving the pregnancy outcome in infertile women undergoing IVF.
Stability of Jupiter Trojans investigated using frequency map analysis: the MATROS project

Using the frequency map analysis (FMA) method we investigate the stability properties of Trojan-type orbits in the proximity of the L 4 and L 5 Lagrangian points of Jupiter. This study is part of the MATROS project. The orbits of about 2 x 10 4 virtual Trojans with random initial conditions have been computed numerically and for each body the diffusion rate in frequency space has been determined by spectral analysis. The diffusion portraits show where stable orbits are located in the space of proper elements for different values of inclination. For low inclined orbits we reproduce the stability region outlined by Levison, Shoemaker & Shoemaker and, due to our fast sampling capability, we find additional resonant features in the libration amplitude versus proper eccentricity space. At higher inclinations, the stability region gradually shrinks and it disappears for inclinations of about 40°. The maximal Lyapunov characteristic exponent is computed for a limited number of Trojan orbits in our sample and the predictions concerning the chaotic behaviour of each orbit are compared with those given by the FMA method. A good agreement is obtained and the value of the Lyapunov exponent may be used to tune the results of the FMA analysis. A synthetic secular theory for the proper frequencies of Jupiter Trojans is obtained by numerically fitting the outcome of the frequency map analysis.
Effective Onset Duration of Auditory Stimuli

In analyzing interaural temporal relations, the binaural system may receive information from one or more of three separate stimulus aspects: (1) difference in time of the start of stimulation, (2) difference in time between similar portions of the continuing wave form at the two ears, and (3) difference in time of the end of stimulation. In this study, the first and third kinds of difference were combined for convenience as “transient disparity”; the second was called “ongoing disparity. ” The relative effectiveness of these two temporal relations in producing changes in auditory localization was investigated by finding, for various values of transient disparity, a value of ongoing disparity that brought the sound back to center. For a given value of transient disparity, the necessary ongoing disparity value varies as a function of stimulus duration. Transient disparity loses its effectiveness for stimulus durations greater than about 150 msec. For a duration of 100 msec, it takes roughly 35 times as much .
Essays in Likelihood-Based Computational Econometrics

textabstractThe theory of probabilities is basically only common sense reduced to a calculus. Pierre Simon Laplace, 1812 The quote above is from Pierre Simon Laplace’s introduction to his seminal work Th´eorie analytique des probabilit´es, in which he lays the groundwork for what is currently known as Bayesian analysis. He proceeds to describe probability theory, and statistical inference, as a method that makes one estimate accurately what right-minded people feel by a sort of instinct, often without being able to give a reason for it. (translation from French: Dale, 1995) This statement contains a profound truth and insight: Probability theory offers a clean and simple recipe for reasoning under uncertainty which I experienced as eyeopening when I first learned about it. As my knowledge of probability theory increased, however, I also realized that in isolation this quote presents things to be much simpler than they actually are: Reducing common sense to a calculus is extremely difficult to do well in practice. Translating our common sense into the language of probabilities takes a lot of practice, and if done accurately it often leads to a calculus without any exact solutions. It is therefore the task of statisticians and econometricians to find practical ways of reducing our common sense to calculus, and to devise smart new methods for efficiently doing the resulting calculations. This work represents my contribution towards these goals.
Is Triple Therapy the New Standard for Metastatic Hormone-sensitive Prostate Cancer?

The treatment of metastatic hormone-sensitive prostate cancer has rapidly changed over the last decade. Currently, standard of care (SOC) options for first-line treatment are androgen deprivation therapy (ADT) in combination with either docetaxel chemotherapy or an androgen receptor pathway inhibitor such as abiraterone, enzalutamide or apalutamide. Recent results from both the PEACE-1 and ARASENS trials show an overall survival and progression-free survival benefit from the addition of an androgen-receptor pathway inhibitor for patients in whom the SOC option of ADT plus docetaxel has been chosen in de novo metastatic hormone-sensitive prostate cancer, with a more pronounced benefit in those with high-volume metastatic disease. However, many clinicians now preferentially use ADT plus an androgen-receptor pathway inhibitor as SOC first-line treatment, and no prospective trial has addressed whether there is a benefit from the addition of docetaxel to this version of SOC combination therapy. The benefit of triplet combination therapy in those with recurrent or low-volume metastatic disease is less clear and longer follow-up is required before conclusions can be drawn about these patient groups.