Miracle-dz/UniFAR-FTUs huggingface dataset:
Pendidikan Karakter pada Pembelajaran Daring

Pendidikan karakter adalah upaya mewujudkan generasi bangsa yang cerdas dan baik (smart and good citizenship) atau memiliki ahlak mulia dan berkepribadian Indonesia. Keberhasilan pendidikan karakter mengisyaratkan pembelajaran tidak serta merta dilihat dari pesepektif ranah kognitif saja melainkan bagaimana keseimbangan ranah kognitif, afektif, dan psikomotor yang muaranya adalah mewujudkan manusia seutuhnya. Kondisi pandemi Covid-19 saat ini menjadi tantangan bagi dunia pendidikan khususnya pendidikan formal dalam upaya pendidikan karakter bangsa. Pembelajaran dominan tidak dilakukan dengan tatap muka, sehingga menjadi tantangan guru dalam proses pendidikan karakter tersebut. Disisi lain akan memberikan kesempatan bagai peserta didik dalam mengaktualisasikan nilai-nilai karakter di masyarakat dalam upaya keikutsertaan pencegahan dan penanggulangan Covid-19. Penelitian ini bersifat deskriptif kualitatif dengan studi literatur yang berusaha memberikan solusi bagaimana pendidikan karakter dilakukan ketika pembelajaran masih berlangsung dengan metode daring pada sekolah menengah pertama. Strategi yang ditawarkan adalah strategi pendidikan karakter multiplle intelligences berbasis portofolio.
Investigation on high transmission efficiency 7 × 1 pump combiner

Abstract. The 7×1 end-pumped combiner employing 105/125 μm multimode fibers as pump fibers is investigated. The theoretical analysis reveals that sufficient taper length and low refractive index of the capillary should be adopted to fabricate high transmission efficiency combiners. Based on the simulation results, we fabricate a 7×1 end-pumped pump combiner with an average transmission efficiency of 98.9% and a total return loss of 1.1‰. The measured internal operating temperature of this combiner indicates it can endure pump power of the order of kilowatts.
The Use of Three Steps Interview to Increase Students’ Self-Confidence at Speaking Skill

This research aims to increase students’ self-confidence at speaking skill by using Three Step Interview at The Second Grade of MA Hadil Islah Bilebante. This research used Classroom Action Research (CAR) which was taken from Kemmis and McTaggarat’s design. This research was finished in one cycle that consisted of four phases, those were: planning, acting, observing, and reflection. The subject of this research was XI A class which consist 20 students. The method of this research was Three Step Interview which run into some steps; a) students made a group consists of 4 persons, b) teacher gave the topic to the students, c) students were in pairs, one was the interviewer and the other was the interviewee, d) students A interviewed students B and student C interviewed student B, e) students reserved roles and each shared with team member what was learned during the two interviews, f) the teacher gave the reward to the best group. The instruments used in this study were observation checklist and questionnaire. This action research was done in two cycles the standard students’ successful 80% or 80 from 20 students exceed criteria of success. The result of the study showed that students’ average score was 83.15 and 90% of students’ percentage or 18 from 20 students agree with application of Three Step Interview Technique in increase students’ self-confidence at speaking skill. Thus, the researcher concluded that this research was successful to increase students’ self-confidence at speaking skill.
Modulation of gut microbiota by diet and probiotics: potential approaches to prevent gestational diabetes mellitus

Abstract Gestational diabetes mellitus (GDM) is a rising global health problem that affects approximately 6% of pregnant women. Lifestyle interventions, particularly diet, and exercise are the first-line treatment, followed by pharmacotherapy, but with associated side effects to both mother and offspring. Modulation of gut microbiota may help prevent or manage GDM. Some gut bacterial groups associated with GDM are also associated with inflammatory biomarkers and gut dysbiosis. Available literature reports that low-glycaemic index diet reduces maternal fasting and 2-hour postprandial glucose and maintains a beneficial gut bacterial composition. Pre- and probiotics can aid GDM therapy by modulating gut microbiota to eubiotic status and improving glucose metabolism. Probiotics as adjuvant GDM therapy should consider bacterial strains, dosage, and treatment duration. Limitations in their use require further studies to develop specific probiotic-based GDM supplement therapy that impacts glycaemic control and inflammatory status by reducing fasting plasma glucose, insulin resistance, and improving lipid profiles of pregnant women.
Processing Concrete and Abstract Relationships in Word Pairs

Malhi (2015) found a reverse concreteness, or abstractness, effect for word pairs in an iconicity judgment task. Per Vigliocco et al.’s (2009) theory of embodied abstract semantics, Malhi and Buchanan (2017) hypothesized that participants were taking a visualization approach (time-costly) towards the concrete word pairs and an emotional valence approach (time-efficient) towards the abstract word pairs. It was also hypothesized that the abstractness effect emerged not by considering single words in isolation but rather by considering the relationship between them. The goal of the present study was to test these hypotheses and to further investigate this reverse concreteness, or abstractness, effect. Results generally provided support for these hypotheses. An event-related potential (ERP) experiment revealed a dissociation between behavioural abstractness and neural concreteness. The results are interpreted using a proposed theory of flexible abstractness and concreteness effects (FACE).
The Influence of Participatory Leadership and Teacher Competence on Performance with Organizational Commitment

This study examines the mediating role of organizational commitment on the effect of participatory leadership and competency on teacher performance. This research consists of two independent variables, participatory leadership and competence, one mediating variable, organizational commitment, and one dependent variable, teacher performance. The research method used is quantitative. Explanative research approach with a survey approach. The test was carried out at the Tulungagung State Aliyah Madrasah with a total sample of 100. Data analysis in this study used Partial Least Square (PLS) analysis using Smart PLS. The results of the survey show that participatory leadership has a significant effect on teacher performance. Thus the higher the participatory leadership, the higher the teacher's performance. Teacher competence has a significant impact on teacher performance. Thus, the higher the teacher's competence, the higher the teacher's performance; this proves that teacher competence substantially affects organizational commitment. Likewise, the higher the teacher's competence, the higher the organizational commitment, as evidenced by the significant effect organizational commitment has on teacher performance. Meanwhile, as a mediating variable, the higher the organizational commitment, the higher the teacher's performance. These results can be a reference for anyone involved in the world of work, especially teachers, to strengthen commitment so that version can run well continuously.
EFSR: Ensemble Forecast Sensitivity to Observation Error Covariance

AbstractData assimilation (DA) methods require an estimate of observation error covariance as an external parameter that typically is tuned in a subjective manner. To facilitate objective and systematic tuning of within the context of ensemble Kalman filtering, this paper introduces a method for estimating how forecast errors would be changed by increasing or decreasing each element of , without a need for the adjoint of the model and the DA system, by combining the adjoint-based -sensitivity diagnostics presented by Daescu previously with the technique employed by Kalnay et al. to derive ensemble forecast sensitivity to observations (EFSO). The proposed method, termed EFSR, is shown to be able to detect and adaptively correct misspecified through a series of toy-model experiments using the Lorenz ’96 model. It is then applied to a quasi-operational global DA system of the National Centers for Environmental Prediction to provide guidance on how to tune the . A sensitivity experiment in which the prescribe.
Electron Acceleration by Dipolarization Fronts and Magnetic Reconnection: A Quantitative Comparison

Suprathermal electrons with energy from tens to hundreds of keV are frequently observed in the Earth's magnetotail. The generation of such electrons is typically attributed to magnetic reconnection, dipolarization fronts (DFs), or flux transport. However, which of these contributes more to this generation remains unclear. In this study, we quantitatively compare the electron acceleration by these processes, using the Cluster data. We analyze an event detected in the midtail and find that the suprathermal electrons there are first accelerated by magnetic reconnection and transported earthward, and then further accelerated locally at the DF. The acceleration process by reconnection and transport, resulting in an isotropic pitch angle distribution, contributes ∼70% to the total flux enhancement, while the acceleration process by the DF, resulting in a pancake distribution, contributes ∼30% to the flux enhancement. The electron acceleration at the DF is primarily attributed to a local betatron process that is successfully reproduced using an analytic model. In order to better understand this phenomenon, we examine an additional 16 similar events and find that the DFs and magnetic reconnection statistically contribute 11% ∼ 38% and 62% ∼ 89% to the total flux enhancement, respectively. This study greatly improves our understanding of the electron energization process in the magnetotail.
Assessment of the effect of tissue motion in diffusion MRI: Derivation of new apparent diffusion coefficient formula

We investigate in this paper the diffusion magnetic resonance imaging (MRI) in deformable organs such as the living heart. The difficulty comes from the hight sensitivity of diffusion measurement to tissue motion. Commonly in literature, the diffusion MRI signal is given by the complex magnetization of water molecules described by the Bloch-Torrey equation. When dealing with deformable organs, the Bloch-Torrey equation is no longer valid. Our main contribution is then to introduce a new mathematical description of the Bloch-Torrey equation in deforming media. In particular, some numerical simulations are presented to quantify the influence of cardiac motion on the estimation of diffusion. Moreover, based on a scaling argument and on an asymptotic model for the complex magnetization, we derive a new apparent diffusion coefficient formula. Finally, some numerical experiments illustrate the potential of this new version which gives a better reconstruction of the diffusion than using the classical one.
EXPLORING THE NATURE OF CORPORATE GOVERNANCE RELATED CLIMATE CHANGE DISCLOSURE OF THE MALAYSIAN COMPANIES

The objective of this paper is to explore the governance related climate change disclosure in the corporate reports of award nominated Malaysian companies. For this, the corporate reports of twenty two (22) Malaysian companies (shortlisted for ACCA Malaysia Sustainability Reporting Award 2016) were analyzed. Content analysis was conducted on the sustainability award nominated reports of the companies under consideration. The findings were explained from legitimacy perspective. It was found that though these award-nominated Malaysian companies arereporting on climate change issues, the extent of governance related disclosure is less. The format of reporting varies from company to company. Also, few governance related climate change issues were reported by these companies. Reporting was mostly done in narrative form. However, through strategic presentation styles, these companies triedto legitimize their activities. This study seeks to contribute to the scant literature on climate change disclosure from the perspective of developing economies (in particular, Malaysia). Another important contribution of this study is that, here, the ‘governance related’ climate change disclosures were taken under consideration. Abstrack Objektif makalah ini adalah untuk meneroka pendedahan perubahan iklim berkaitan tadbir urus dalam laporan korporat syarikat Malaysia yang dicalonkan untuk anugerah. Untuk ini, laporan korporat dari dua puluh dua (22) syarikat Malaysia (disenarai pendek untuk ACCA Malaysia Sustainability Reporting Award 2016) dianalisis.Analisis kandungan dilakukan berdasarkan laporan penamaan syarikat yang dipertimbangkan. Penemuan ini dijelaskan dari perspektif kesahan. Didapati bahawa walaupun syarikat-syarikat Malaysia yang dicalonkan untuk anugerah ini melaporkan masalah perubahan iklim, tahap pendedahan berkaitan pemerintahan kurang. Format pelaporan berbeza dari syarikat ke syarikat. Juga, beberapa masalah perubahan iklim yang berkaitan dengan pemerintahan dilaporkan oleh syarikat-syarikat ini. Pelaporan kebanyakannya dibuat dalam bentuk naratif. Namun,melalui gaya persembahan yang strategik, syarikat-syarikat ini berusaha untuk mengesahkan kegiatan mereka. Kajian ini bertujuan untuk menyumbang kepada literatur yang sedikit mengenai pendedahan perubahan iklim dari perspektif ekonomi membangun (khususnya, Malaysia). Sumbangan penting lain dari kajian ini adalah bahawa, di sini, pendedahan mengenai perubahan iklim 'berkaitan dengan pemerintahan' telah dipertimbangkan.
Combination of Throughput-Optimal Scheduling and Network Utility Maximization in NOMA Systems With Flow-Level Dynamics

In wireless networks, the network queue stability (throughput-optimality) and the network utility maximization are two crucial tasks for network operators. Besides, new techniques of mobile communications, e.g. the non-orthogonal multiple access (NOMA), have emerged endlessly to meet coming challenges. In this article, we for the first time, investigate a downlink NOMA system with flow-level dynamics, where long-lived flows and short-lived flows exist simultaneously, and formulate an optimization problem of user selection and power allocation. We aim to maximize the network utility at each time slot and simultaneously guarantee the throughput-optimality, under the quality of service (QoS) constraints. Considering the practicability of algorithm, the suboptimal algorithm containing two stages, is proposed. And we analyze the complexity of proposed algorithm. In the performance evaluation, the benchmark algorithm is provided for comparison. And we take the energy efficiency (EE) as an example of the network utility and define the scheduling delay (SD). Simulation results show that the suboptimal algorithm is throughput-optimal, and understandably, its performances could be better than those in the benchmark algorithm in terms of EE and SD, as long as the appropriate parameter is set.
DETERMINING THE VALUE OF DOUBLE BARRIER OPTION USING STANDARD MONTE CARLO, ANTITHETIC VARIATE, AND CONTROL VARIATE METHODS

In this paper, we applied the standard Monte Carlo, antithetic variate, and control variates methods to value the double barrier knock-in option price. The underlying asset used in the calculation of double barrier knock-in option is the share of ANTM from April 1, 2019 until March 1, 2022. The value of the double barrier knock-in option is simulated using standard Monte Carlo, antithetic variate, and control variates methods. The results showed that all the methods converge to the exact solution, with the control variate method to be the fastest. Standard Monte Carlo method has the least computational time, followed by control variate and antithetic variate method. Compared to the other methods, control variate is the most effective and efficient in determining the value of double barrier knock-in option, based on the option value, relative error and computational time. Antithetic variate method converges faster to the exact solution compared to standard Monte Carlo. However it has the longest computation time compared to the other methods.
Neural network‐based optical flow versus traditional optical flow techniques with thermal aerial imaging in real‐world settings

The study explores the feasibility of optical flow‐based neural network from real‐world thermal aerial imagery. While traditional optical flow techniques have shown adequate performance, sparse techniques do not work well during cold‐soaked low‐contrast conditions, and dense algorithms are more accurate in low‐contrast conditions but suffer from the aperture problem in some scenes. On the other hand, optical flow from convolutional neural networks has demonstrated good performance with strong generalization from several synthetic public data set benchmarks. Ground truth was generated from real‐world thermal data estimated with traditional dense optical flow techniques. The state‐of‐the‐art Recurrent All‐Pairs Field Transform for the Optical Flow model was trained with both color synthetic data and the captured real‐world thermal data across various thermal contrast conditions. The results showed strong performance of the deep‐learning network against established sparse and dense optical flow techniques in various environments and weather conditions, at the cost of higher computational demand.
Exponential stability for 2D systems: the linear case

This short paper deals with a 2D discrete linear Roesser model. The results introduced here are a follow-up of a paper we proposed recently and where we explained and motivated the reasons we need to adopt a new definition of exponential stability for 2D systems. However this previous result left aside a crucial point that we would like to asses here: is our new definition of exponential stability coherent with the existing stability criterion in the linear case? We hereby show that, in the linear case, 1. our new definition of exponential stability is equivalent to asymptotic stability and 2. the characteristic polynomial-based stability criterion is a sufficient and necessary condition for the exponential stability we have introduced.
Modeling Human Motion Using Binary Latent Variables

We propose a non-linear generative model for human motion data that uses an undirected model with binary latent variables and real-valued “visible” variables that represent joint angles. The latent and visible variables at each time step receive directed connections from the visible variables at the last few time-steps. Such an architecture makes on-line inference efficient and allows us to use a simple approximate learning procedure. After training, the model finds a single set of parameters that simultaneously capture several different kinds of motion. We demonstrate the power of our approach by synthesizing various motion sequences and by performing on-line filling in of data lost during motion capture.
Damage detection using transmissibility compressed by principal component analysis enhanced with distance measure

Detecting structural damage in operational conditions still encounters some difficulties, especially in early-stage, as environmental varieties impose challenges in real engineering applications and may require large computational efforts in the structural health monitoring and potential maintenance. Unlike conventional strategies employing frequency response function or response data, a damage detection methodology is addressed in this study by employing transmissibility functions that retains a strong interrelation with structural damage or deterioration, in order to avoid the measurement of excitation, together with principal component analysis that leads to reduction in computational costs. In this procedure, transmissibility is extracted from the structural responses and main features are selected by principal component analysis for less computational costs. Then, via distance measures damage indicators are constructed for both intact and damaged states, and finally a numerical simulation with a clamped-clamped beam and a four-story benchmark are adopted to verify the applicability of the proposed procedure. The results demonstrate a good performance in structural damage detection.
The effect of entrepreneurial orientation and knowledge management on organizational performance through innovation

This study aims to examine the effect of entrepreneurial orientation, knowledge management, and innovation on organizational performance. This study uses explanatory research with a quantitative approach. The population in this study was made up of Malang City consumer cooperatives. The study employed the purposive sampling technique. The sample in the study was 60 consumer cooperatives. Data was collected through surveys, documentation, and the use of Likert scales to test instruments. The data was analyzed using Structural Equation Model Partial Least Squares (SEM-PLS) modeling. The results of this study indicate that entrepreneurial orientation and knowledge management can directly improve organizational performance. However, unlike knowledge management, entrepreneurial orientation cannot increase innovation. Organizational performance can be directly improved by innovation. Innovation is unable to mediate between entrepreneurial orientation and organizational performance. However, innovation is able to mediate the relationship between knowledge management and organizational performance. The findings of this study suggest that consumer cooperatives in Malang City can improve organizational performance by optimizing entrepreneurial organizations and knowledge management.
The Level of Dyscalculia in Children with Special Needs in Understanding Mathematical Concepts : Learning Difficulties Experienced

This study aims to analyze the difficulties of students with special needs (mentally retarded, deaf, and blind children) in understanding mathematical concepts, which will be described by levels. The research uses descriptive method. Data collection technique used observations of students with special needs to see the difficulties in understanding mathematical concepts (dyscalculia), and interviews conducted with mathematics teachers to complement the results of the observations. The research sample is deaf students, blind students, and mentally retarded students in the Jember district. The data analysis technique in this study uses the flow model. The results of this study were that the level of achievement with good assessment categories was dominated by blind students, namely from 10 aspects of the assessment only weak in the section on grouping the shape dimensions, while the deaf achieved good assessments, namely 1) sorting objects based on the length and short size, 2) understanding the number of objects, 3) understanding numbers, and 4) writing and saying numbers. Meanwhile, mentally retarded students only have 1 good assessment aspect, namely understanding the length of objects. The conclusion is that dyscalculia is mostly suffered by mentally retarded children, deaf children suffered moderate level, and the best level of the subject is blind children.