Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of E-Servqual and E-Trust on E-Loyalty : The Role of E-Satisfaction as an Intervening on Islamic Mobile Banking Customer

Research Aims: This study aims to analyze the effect of e-trust and e-service quality on loyalty through e-satisfaction of Islamic mobile banking users. The purpose of this study is to investigate the impact of trust and service quality on consumer loyalty through consumer satisfaction in the context of mobile banking. Design/methodology/approach: The sampling method used in this study was nonprobability sampling with a purposive sampling technique. The data was collected from 151 respondents who met the assessment criteria and were supposed to use mobile banking at least twice. This study used Structural Equation Model (SEM) analysis techniques, which were estimated by SmartPLS 3.0. Research Findings: The results show that e-service quality and e-trust have a positive effect on e-satisfaction; e-trust and e-satisfaction have a positive effect on e-loyalty; e-service quality does not affect e-loyalty; e-satisfaction can mediate the relationship between e-service quality and e-trust to e-loyalty; age and gender cannot moderate the relationship between e-satisfaction and e-loyalty Keywords: e-trust, e-service quality, e-satisfaction, e-loyalty, age, gender, Islamic mobile banking
Diagnosis and Treatment of Tremor in Parkinson’s Disease Using Mechanical Devices

Background: Parkinsonian tremors are sometimes confused with essential tremors or other conditions. Recently, researchers conducted several studies on tremor evaluation using wearable sensors and devices, which may support accurate diagnosis. Mechanical devices are also commonly used to treat tremors and have been actively researched and developed. Here, we aimed to review recent progress and the efficacy of the devices related to Parkinsonian tremors. Methods: The PubMed and Scopus databases were searched for articles. We searched for “Parkinson disease” and “tremor” and “device”. Results: Eighty-six articles were selected by our systematic approach. Many studies demonstrated that the diagnosis and evaluation of tremors in patients with PD can be done accurately by machine learning algorithms. Mechanical devices for tremor suppression include deep brain stimulation (DBS), electrical muscle stimulation, and orthosis. In recent years, adaptive DBS and optimization of stimulation parameters have been studied to further improve treatment efficacy. Conclusions: Due to developments using state-of-the-art techniques, effectiveness in diagnosing and evaluating tremor and suppressing it using these devices is satisfactorily high in many studies. However, other than DBS, no devices are in practical use. To acquire high-level evidence, large-scale studies and randomized controlled trials are needed for these devices.
Comparing Comparators in Generalization Bounds

We derive generic information-theoretic and PAC-Bayesian generalization bounds involving an arbitrary convex comparator function, which measures the discrepancy between the training and population loss. The bounds hold under the assumption that the cumulant-generating function (CGF) of the comparator is upper-bounded by the corresponding CGF within a family of bounding distributions. We show that the tightest possible bound is obtained with the comparator being the convex conjugate of the CGF of the bounding distribution, also known as the Cram\'er function. This conclusion applies more broadly to generalization bounds with a similar structure. This confirms the near-optimality of known bounds for bounded and sub-Gaussian losses and leads to novel bounds under other bounding distributions.
Commercial Seaweed Liquid Extract as Strawberry Biostimulants and Bioethanol Production

Seaweeds are increasingly intriguing as a sustainable source of bioactive compounds. They have applications in agriculture, fuels, feed, and food products. To become a cost-competitive product with zero waste, a biorefinery approach is applied, where several products are valorized at the same time. True-Algae-Max (TAM®) has been investigated for its ability to improve the yield and nutritional facts of a strawberry plant. Three concentrations of TAM (0, 50, and 100%) were examined by foliar spray in 2017 with 50% NPK chemical fertilizer. Results indicated that growth, yield, chlorophyll, and potassium content were significantly improved by TAM treatments. TAM50 % resulted in maximum root length, leaf area, plant fresh weight, fruit weight, and yield with an increase ranging from 10 to 110% compared to control. Compared to the NPK control, strawberries grown with TAM50% improved total soluble solids (TSS) from 7.58 to 10.12% and anthocyanin from 23.08 to 29.42 mg CGE 100 g−1. Noteworthily, this reduced total sugar, and total phenolics were boosted by TAM applications, while non-reducing sugar was reduced compared to control. On the other hand, whole seaweed biomass and TAM residuals were used for bioethanol production by acid scarification. The maximum bioethanol yield was observed in residual biomass (0.34 g g−1 dw), while the whole seaweed biomass showed only 0.20 g g−1 dw. These results proved the biorefinery concept of using seaweed extract as a biostimulator and bioethanol production.
An Overview of The Psychological Well-Being Of Entrepreneurs In Riau Province

At this time when competition in the economy is increasing and the COVID-19 pandemic situation, not all entrepreneurs in entrepreneurship are able to reach the level of psychological well-being because no one can guarantee whether the business will be successful or not. This study aims to give the description of psychological well-being on entrepreneurs in Riau Province during the COVID-19 pandemic and to determine the differences on psychological well-being among entrepreneurs in Riau Province base on the demographic data of entrepreneurs. The method used to collect the data of psychological well-being and a demographic scale is distribute the questioners to 130 entrepreneurs in Riau Province. The sampling technique used is cluster random sampling. The analytical method used is descriptive analysis and different test using program SPSS 23.0. Based on the analysis test, it was found that the level of psychological well-being in entrepreneurs in Riau Province was classified as moderate. The dimensions of self-acceptance, positive relationships with others, autonomy, purpose in life and environmental mastery in entrepreneurship in Riau Province are moderate, while the dimensions of personal growth in entrepreneurship in Riau Province are high. The results also show that the hypothesis is rejected with no significant difference in the psychological well- being of Riau Province entrepreneurs based on the demographic factors tested.
Optical Spectroscopy and Ionization Models of the Diffuse Ionized Gas in M33, M51/NGC 5195, and M81

We report the results of a spectroscopic investigation of the diffuse ionized gas (DIG) in M33, M81, and M51. All three galaxies have enhanced [S II]/Hα and [N II]/Hα ratios in the DIG compared to H II regions, in agreement with the predictions of photoionization models. The DIG in all three galaxies also has [O III]/Hβ ratios equal to or greater than that in neighboring H II regions. The [S II]/[N II] ratio does not vary with Hα surface brightness and is similar in both H II regions and DIG. We have tentatively detected the He I λ5876 line in the bright DIG near NGC 604, indicating a contribution from O7 and hotter stars to the ionizing spectrum in the DIG at that location. The DIG in M33 has lower [N II]/Hα ratios than M51 or the Galaxy, most likely because of low N abundance in M33. We used CLOUDY models to test the feasibility of two photoionization sources for the DIG: (1) the diluted ionizing continua of massive stars ("standard" models) and (2) the transmitted ionizing continua of density-bounded H II regions ("leaky H II region" models). The leaky H II region models produce higher [S II]/Hα, [N II]/Hα, and [O III]/Hβ ratios than standard DIG models for the same stellar temperatures. This alleviates somewhat the problem of producing high [O III]/Hβ ratios in the DIG. However, no single model can simultaneously reproduce all three line ratios. We conclude that either a combination of models is necessary or other ionization or heating mechanisms play a role in powering the DIG. Finally, we report on the spectrum of ionized gas associated with the companion to M51, NGC 5195. The gas in and around NGC 5195 has very high forbidden-line ratios and broad line widths (~ 500 km s-1 FWHM), indicative of shock-ionized gas. At some locations the emission lines split into two velocity components, suggesting an expanding structure or outflow. The line ratios, morphology, and kinematics show that the interstellar medium in NGC 5195 is very disturbed.
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification

Meta-learning has demonstrated promising results in few-shot classification (FSC) by learning to solve new problems using prior knowledge. Bayesian methods are effective at characterizing uncertainty in FSC, which is crucial in high-risk fields. In this context, the logistic-softmax likelihood is often employed as an alternative to the softmax likelihood in multi-class Gaussian process classification due to its conditional conjugacy property. However, the theoretical property of logistic-softmax is not clear and previous research indicated that the inherent uncertainty of logistic-softmax leads to suboptimal performance. To mitigate these issues, we revisit and redesign the logistic-softmax likelihood, which enables control of the \textit{a priori} confidence level through a temperature parameter. Furthermore, we theoretically and empirically show that softmax can be viewed as a special case of logistic-softmax and logistic-softmax induces a larger family of data distribution than softmax. Utilizing modified logistic-softmax, we integrate the data augmentation technique into the deep kernel based Gaussian process meta-learning framework, and derive an analytical mean-field approximation for task-specific updates. Our approach yields well-calibrated uncertainty estimates and achieves comparable or superior results on standard benchmark datasets. Code is publicly available at \url{https://github.com/keanson/revisit-logistic-softmax}.
Correlation of oscillations in a quantum dot with three contacts

Results of transport measurements on a GaAs quantum dot are presented in which the gate geometry allows the dot to be accessed by three, rather than two, contacts. In the Coulomb blockade regime, conductance oscillations periodic in gate voltage are measured concurrently at two contacts in response to a small excitation voltage at the third contact. When the dot is in the strongly blockaded regime, we obtain the expected result from single electron tunneling theory that oscillations at the two output contacts are correlated with each other in gate voltage. As the tunnel barriers are made softer by changing the gate voltage, a strikingly different phenomenon is observed: conductance peaks at the two output leads evolve from perfect correlation to perfect anticorrelation with each other.
Fabrication and integration of micro/nano-scale photonic devices and optical waveguide arrays for optical printed circuit board (O-PCB) and VLSI photonic applications (Invited Paper)

We report on the recent progresses of our work on the design, fabrication and integration of micro/nano-scale photonic devices and optical waveguide arrays for optical printed circuit boards (O-PCBs) and VLSI photonic applications. The waveguides are designed and fabricated by thermal embossing and ultraviolet (UV) radiated embossing of polymer materials. The photonic devices include vertically coupled surface emitting laser (VCSEL) microlasers, microlenses, 45-degree reflection couplers, directional couplers, arrayed waveguide grating structures, multimode interference (MMI) devices and photodetectors in micro/nano-scale. These de-vices are optically interconnected and integrated for O-PCB assembly and VLSI micro/nano-photonics. De-tailed procedures of fabricating and implementing these devices and assembly of O-PCB are described. The O-PCBs are to perform the functions of transporting, switching, routing and distributing optical signals on flat modular boards or substrates. We report on the result of the optical transmission performances of these as-sembled O-PCBs up to 2.5 Gbps and 10 Gbps. For the design, fabrication, and VLSI integration of nano-scale photonic devices, we used photonic crystal structures. Characteristics of these devices are also described.
Comparisons of Stellar Scintillation with Image Motion

Stellar scintillation and stellar-image motion are shown by three types of observations to be essentially independent criteria of astronomical “seeing,” In particular, it is demonstrated that scintillation is not produced in the immediate neighborhood of the telescope whereas image motion is strongly affected by local air disturbances. It appears therefore that stellar scintillation may be a useful probe for atmospheric studies.
An Interpretable Deep-Learning Framework for Predicting Hospital Readmissions From Electronic Health Records

With the increasing availability of patients' data, modern medicine is shifting towards prospective healthcare. Electronic health records contain a variety of information useful for clinical patient description and can be exploited for the construction of predictive models, given that similar medical histories will likely lead to similar progressions. One example is unplanned hospital readmission prediction, an essential task for reducing hospital costs and improving patient health. Despite predictive models showing very good performances especially with deep-learning models, they are often criticized for the poor interpretability of their results, a fundamental characteristic in the medical field, where incorrect predictions might have serious consequences for the patient health. In this paper we propose a novel, interpretable deep-learning framework for predicting unplanned hospital readmissions, supported by NLP findings on word embeddings and by neural-network models (ConvLSTM) for better handling temporal data. We validate our system on the two predictive tasks of hospital readmission within 30 and 180 days, using real-world data. In addition, we introduce and test a model-dependent technique to make the representation of results easily interpretable by the medical staff. Our solution achieves better performances compared to traditional models based on machine learning, while providing at the same time more interpretable results.
Partition Models for Variable Selection and Interaction Detection

Variable selection methods play important roles in modeling high-dimensional data and are keys to data-driven scientific discoveries. Traditional variable selection methods are derived from a forward modeling angle on the conditional distribution of the response given predictors. Instead of building a predictive model of the response given combinations of predictors, we start by modeling the conditional distribution of predictors given the response. This inverse modeling perspective motivates us to propose a stepwise procedure that is effective and computationally efficient in detecting interaction with little assumptions on its parametric form. The proposed procedure is able to detect pairwise interactions among p predictors with a computational time of O(p) instead of O(p) under moderate conditions. Consistency of the proposed procedure in variable selection under a diverging number of predictors and sample size is established. Its excellent empirical performance in comparison with some existing methods is demonstrated through simulation studies as well as applications in high throughput biological studies. We will further explore a Bayesian generalization of the proposed procedure --Bayesian partition model that combines forward and inverse modeling perspectives for selecting both response and predictor variables. In particular, we will discuss the application of partition models in two biological problems: identifying transcription factor subclasses on protein binding microarray, which can be viewed as a high-dimensional clustering with variable selection, and detecting pleiotropic and epistasis effects in expression quantitative trait loci (eQTLs) study, which can be viewed as a multivariate regression with variable selection on both responses and predictors, including also multi-way interactions among correlated predictors.
The impact of sodium on the sub-bandgap states in CZTSe and CZTS

We compare the optically active sub-bandgap states in polycrystalline Cu2ZnSnSe4 (CZTSe) and Cu2ZnSnS4 (CZTS) thin films as a function of sodium content. In all samples studied, we find that CZTSe has a lower concentration of radiative defect-derived states compared to CZTS and that the states are also shallower in CZTSe compared to CZTS. Further, we find that sodium impacts the relative ratios of two sub-bandgap peaks in the 4 K photoluminescence (PL) spectra of CZTSe (one at ∼0.85 eV and another at ∼0.92 eV). We propose that both of these sub-bandgap peaks stem from intrinsic point defects in CZTSe rather than from electronic states introduced by sodium; this is supported by a measurement on a sodium-free single-crystal of CZTSe. We also show that films with stronger emission through the shallower sub-bandgap states at 4 K display room-temperature PL closer to the bandgap energy. For all sodium quantities studied, one broad PL peak is observed in the 4 K PL spectrum of CZTS which also shifts towards the.
Regiospecific Photochemical Synthesis of Methylchrysenes

Methylated polycyclic aromatic hydrocarbons (PAHs) are suspected to be some of the toxic compounds in crude oil towards marine life and are needed as single compounds for environmental studies. 1-, 3- and 6-methylchrysene (3a,b,c) were prepared as single isomers by photochemical cyclization of the corresponding stilbenoids in the Mallory reaction using stoichiometric amounts of iodine in 82-88% yield. 2-methylchrysene (3d) was prepared by photochemical cyclization where the regioselectivity was controlled by elimination of an ortho-methoxy group under acidic oxygen free conditions in 72% yield. These conditions failed to form 4-methylchrysene from the corresponding stilbenoid. All stilbenoids were made from a common naphthyl Wittig salt and suitably substituted benzaldehydes. We have also demonstrated that methylchrysenes can be oxidized to the corresponding chrysenecarboxylic acids by KMnO4 in modest yields.
On the Population Size in Stochastic Differential Games

Commuters looking for the shortest path to their destinations, the security of networked computers, hedge funds trading on the same stocks, governments and populations acting to mitigate an epidemic, or employers and employees agreeing on a contact, are all examples of (dynamic) stochastic differential games. In essence, game theory deals with the analysis of strategic interactions among multiple decision-makers. The theory has had enormous impact in a wide variety of fields, but its rigorous mathematical analysis is rather recent. It started with the pioneering work of von Neumann and Morgenstern published in 1944. Since then, game theory has taken centre stage in applied mathematics and related areas. Game theory has also played an important role in unsuspected areas: for instance in military applications, when the analysis of guided interceptor missiles in the 1950s motivated the study of games evolving dynamically in time. Such games (when possibly subject to randomness) are called stochastic differential games. Their study started with the work of Issacs, who crucially recognised the importance of (stochastic) control theory in the area. Over the past few decades since Isaacs's work, a rich theory of stochastic differential game has emerged and branched into several directions. This paper will review recent advances in the study of solvability of stochastic differential games, with a focus on a purely probabilistic technique to approach the problem. Unsurprisingly, the number of players involved in the game is a major factor of the analysis. We will explain how the size of the population impacts the analyses and solvability of the problem, and discuss mean field games as well as the convergence of finite player games to mean field games.
Kaitan Moral Disengagement dan Aggressive Driving Behavior : Tinjauan Pada Remaja Pengendara Sepeda motor

ABSTRAK One of the factors of high traffic accidents is the growing rate of vehicles. In Indonesia, traffic accidents that occur are dominated by two-wheeled vehicles, namely motorcycles and often involve young drivers. One of the causes of adolescent involvement in accidents is aggressive driving behavior which can be influenced by moral disengagement. This quantitative study aims to determine the role of moral disengagement on aggressive driving behavior in adolescent motorcyclists. The hypothesis of this research is that moral disengagement plays a role to aggressive driving behavior on adolescent motorcyclist. This research uses purposive sampling as a sampling technique. The respondents range from 14-19 year old motorcyclists in Palembang, amounting to about 150 respondents. The instrument used is the Aggressive Driving Behavior Scale (ADBS) by Houston et al. (2003) and the Moral Disengagement Scale by Bandura et al. (1996), both modified. Simple regression technique was used to analyze the research data and with the help of IBM SPSS 22. Based on the results of the regression analysis, the R square value between moral disengagement and aggressive driving behavior is 0.107, the F value is 17.682, and the significance value is 0.000 (p<0.005). This shows that moral disengagement has a significant role in aggressive driving behavior. Thus, the hypothesis proposed by this study can be accepted.
Openness Personality as a Mediator of the Influence Social Support Toward Subjective Well-Being

Subjective well-being was originally considered to be an individual benchmark in achieving satisfaction in a stable life. However, there are several factors that affect the decrease and increase in subjective well-being, such as social support and personality. This study aims to determine the effect of personality openness as a mediator of the relationship between social support and subjective well-being. This type of research is ex-post facto. The research location was at SMAN 1 Pacitan Regency with a total sample of 237 students. The sample collection technique uses simple random sampling. The data collection technique uses a scale consisting of a personality openness scale, a social support scale, and a subjective welfare scale. The instrument validation technique uses the previous measuring instrument validity and reliability based on the Cronbach Alpha coefficient. Data analysis used multiple regression with a significance level of 0.05. The results showed that there was a significant positive influence on personality openness as a mediator of the relationship between social support and subjective well-being. The mediation model in this study is known as perfect mediation because the value on path c', namely the variable social support with subjective well-being and then included the openness personality variable, found insignificant results. The percentage of the contribution of the social support variable to the subjective welfare variable which was initially 22.7% became 49.2% after including openness personality as a mediator