Miracle-dz/UniFAR-FTUs huggingface dataset:
ASA-Net: Adaptive Sparse Attention Network for Robust Electric Load Forecasting

Electric load forecasting (ELF) is always employed to perform power systems management. However, it is difficult to predict electric load due to the following issues: 1) electric load prediction is prone to external interference, e.g., temperature and weather; 2) the user behaviors are random, such as family gatherings and business rush orders; and 3) electric load consumption varies significantly in different time periods. To solve such problems, an adaptive sparse attention network (ASA-Net) is proposed for ELF, where the adaptive sparse spatial attention (ASSA) module is first designed to increase the anti-interference ability by capturing the detail change caused by external interference; next, the adaptive sparse channel attention (ASCA) module is developed to enhance the tolerance to local outliers by learning their feature information; and finally, the adaptive sparse batch attention (ASBA) module is devised to model the dependencies of the timestamp to reduce the time impact on ELF. Experiments conducted on the benchmarks show the excellent performance of ASA-Net for ELF, and it can further provide valuable assistance for the smart grid.
The grammar of typically developing Oromo-speaking 3-year-olds

This study investigates the grammatical skills of typically developing Oromo-speaking preschool-age children and lays the foundation for a language assessment tool for Oromo, a Cushitic language spoken in Ethiopia. The current study used a standard picture–based elicitation task that evaluated children’s accuracy in producing grammatical utterances. Language samples were collected from 44 monolingual 3- to 4-year-old Oromo children with typical language development. The percentage of grammatical utterances (PGU) was computed and error types were analyzed. The average level of grammatical accuracy as measured by PGU was 69%, with a large amount of variability. The data for Oromo 3-year-olds showed a variety of infrequent error types. The results of the study provide crucial foundational knowledge on grammatical development in Oromo, which could form the basis of future language assessments and diagnostic materials.
Influences of Personal Driving Styles and Experienced System Characteristics on Driving Style Preferences in Automated Driving

As automated driving technology continues to advance, the question of how users prefer to be driven in their new, more passive role is becoming increasingly relevant. In this paper, a real-world study on a German motorway with 42 participants was conducted to analyze driving style preferences for conditional automated driving, taking the participants’ personal driving style into account. In the first part, participants’ personal driving style (PDS) was recorded during a manual drive in the first half on a given route. For the second half, participants were asked to demonstrate their desired driving style (DDS) for conditional automated driving. In the second part, participants were driven on the same route in a defensive automated vehicle (AV) while rating driving comfort and safety. Subsequently, the relationship between driving style differences and ratings was analyzed. Furthermore, a comparison between PDS and DDS was performed. The results show that very defensive to moderate drivers perceived the AV’s driving style, being similar to their own, as equally safe but significantly more comfortable than moderate to very aggressive drivers. No influence of driving style differences was found on the increase in trust. However, a significant increase in trust after experiencing an automated vehicle has been observed. Furthermore, the rated system characteristics of anthropomorphism, safety, and overall driving strategy had a significant influence on driving style preferences for AVs. This study makes an important contribution to answering the question of how users want to be driven in conditional automated driving.
Stabilization of a class of switched uncertain systems by active disturbance rejection control

The problem of stabilization for a class of switched uncertain non-linear systems is studied by active disturbance rejection control (ADRC). Coordinate transformation is applied to transform the system into a strict feedback system in normal form. The unknown non-linearity, parameter uncertainty and external disturbance are treated as an extended state of each subsystem, and a corresponding switched extended state observer (ESO) is designed. Based on the output of the switched ESO, a switching ADRC law is proposed. Rigorous proof is given to show that the switched ESO can estimate system states and the unknown non-linearity of each subsystem effectively. Furthermore, the proposed controller guarantees the closed-loop system be semi-globally uniformly ultimately bounded for a class of switching with average dwell time. A numerical example illustrates the effectiveness of the proposed method.
A short note on quantile and expectile estimation in unequal probability samples

The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.
Investigating the Factors Influencing Egyptian Domestic Tourists' Online Purchase Intention

The present study tests structural model statements travelers’ Online Purchase Intention of Egyptian domestic tourists using data collected from domestic travelers in Egypt. The study take the Technology Acceptance Model extend (TAM) by integrating travelers’ Perceived Risks and Trust in online-purchases with the various variables of the framework (Perceived Usefulness, Perceived Ease of Use, and Attitude). The aim of study is assessing the factors which influencing in Online Purchase Intention of the Domestic Tourists in Egypt. Therefore, this study aims to explore extend of influencing model factors (Perceived Usefulness, Perceived Ease of Use, Perceived Risks, and Trust) on Domestic tourist’s Online Purchase Intention in Egypt. The study depends on primary data collected from sample of domestic tourists in Egypt. A questionnaire as quantitative approach was distributed to domestic tourists who had reserved or purchased a travel service via the internet at least once. The total respondents of questionnaire are 216 respondents. The collecting data were coding and analyzing via SPSS v 24. The results demonstrated that there is appositive significant relation between the factors (Usefulness, Ease of Use, Online Trust, and Online Attitude) and domestic tourist’s Online Purchase Intention. Moreover, the relationship between Online Risks and Online Purchase Intention of domestic tourists is negative in Egypt. The study recommendation demonstrated on that the travel agency in Egypt should encourage domestic tourists to pay online. In addition, they should offer many types of secure online payment.
Optimal iterative solvers for linear systems with stochastic PDE origins : balanced black-box stopping tests

The central theme of this thesis is the design of optimal balanced black-box stopping criteria in iterative solvers of symmetric positive-definite, symmetric indefinite, and nonsymmetric linear systems arising from finite element approximation of stochastic (parametric) partial differential equations. For a given stochastic and spatial approximation, it is known that iteratively solving the corresponding linear(ized) system(s) of equations to too tight algebraic error tolerance results in a wastage of computational resources without decreasing the usually unknown approximation error. In order to stop optimally—by avoiding unnecessary computations and premature stopping—algebraic error and a posteriori approximation error estimate must be balanced at the optimal stopping iteration. Efficient and reliable a posteriori error estimators do exist for close estimation of the approximation error in a finite element setting. But the algebraic error is generally unknown since the exact algebraic solution is not usually available. Obtaining tractable upper and lower bounds on the algebraic error in terms of a readily computable and monotonically decreasing quantity (if any) of the chosen iterative solver is the distinctive feature of the designed optimal balanced stopping strategy. Moreover, this work states the exact constants, that is, there are no user-defined parameters in the optimal balanced stopping tests. Hence, an iterative solver incorporating the optimal balanced stopping methodology that is presented here will be a black-box iterative solver. Typically, employing such a stopping methodology would lead to huge computational savings and in any case would definitely rule out premature stopping. The constants in the devised optimal balanced black-box stopping tests in MINRES solver for solving symmetric positive-definite and symmetric indefinite linear systems can be estimated cheaply on-the-fly. The contribution of this thesis goes one step further for the nonsymmetric case in the sense that it not only provides an optimal balanced black-box stopping test in a memory-expensive Krylov solver like GMRES but it also presents an optimal balanced black-box stopping test in memory-inexpensive Krylov solvers such as BICGSTAB(l), TFQMR etc. Currently, little convergence theory exists for the memory-inexpensive Krylov solvers and hence devising stopping criteria for them is an active field of research. Also, an optimal balanced black-box stopping criterion is proposed for nonlinear (Picard or Newton) iterative method that is used for solving the finite dimensional Navier–Stokes equations. The optimal balanced black-box stopping methodology presented in this thesis can be generalized for any iterative solver of a linear(ized) system arising from numerical approximation of a partial differential equation. The only prerequisites for this purpose are the existence of a cheap and tight a posteriori error estimator for the approximation error along with cheap and tractable bounds on the algebraic error.
Etude comparative de cinq algorithmes de commande MPPT pour un système photovoltaïque

Ce travail est une tentative pour étudier et discuter cinq types de techniques MPPT. La technique du suivi du point de puissance maximale, MPPT est utilisée dans les systèmes photovoltaïques pour extraire le maximum de puissance. Les techniques MPPT les plus populaires sont revues et étudiées, telles que: Perturber et Observer, Incrément de la conductance, mesure d’une fraction de la tension en circuit ouvert, ‘FCO’, mesure d’une fraction de courant de court-circuit, ‘FCC’ et contrôle à base de la logique floue, ‘LF’. L’environnement Matlab-Simulink est utilisé pour analyser, puis interpréter les résultats de simulation de ces algorithmes, et par conséquent, montrer les performances et les limites de chaque algorithme.
Investigating the Electrochemical Properties of Alkaloids Compound Derived from Catharanthus Roseus Extract

The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method was used to extract alkaloid compounds from the Catharanthus roseus plant and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles (CSNPs). The extracted alkaloids were linked with Chitosan nanoparticles by maleic anhydride to get the final product (CSNPs-Linker-alkaloids). The pure Chitosan, Chitosan nanoparticles, and CSNPs-Linker-alkaloids were characterized by X-ray diffractometer, and Fourier Transform Infrared spectroscopy. X-ray results show that all samples have an orthorhombic structure with crystallite size in nanodimensions. FTIR spectra prove that the P=O is the cross-linkage between chitosan and phosphate groups by ionic bond, which indicate that the Chitosan nanoparticle has been formed in the solution. FTIR spectrum for CSNPs - Linker - alkaloids appear a new distinct band at 1708.93 cm-1 which demonstrates the presence of C = O esterification. Atomic Force Microscope images of the Chitosan nanoparticles and CSNPs-Linker-alkaloids show that they have almost spherical shapes with average sizes of 90 and 92.6 nm respectively. The electroactive surface area of glassy carbon electrodes (GCE), extract plant, and Linker-alkaloids were calculated in KCl solution containing K3[Fe (CN)6]. The presence of CSNPs-Linker-alkaloids in modified glassy carbon electrodes about 3 times. The successful synthesis of organic nanoparticles from the Catharanthus roseus plant can be used safely in biosensors, environmental monitoring, and biomedical applications.
The first CCD photometric study of the open cluster NGC 744

We present the first CCD photometric observations of open cluster NGC 744, as part of the 50BiN Open Cluster Survey. The color-magnitude diagrams of this cluster were derived from absolute BV RI photometry on a good photometric night. A brief isochrone fitting gives a distance modulus of (m − M)V = 11.58 ± 0.2 and a reddening of E(B − V) = 0.35 ± 0.05 with an age of log t = 8.30 ± 0.05. By carefully examining the BV time-series data, we discovered four new variable stars in a 20′ × 20′ field around the cluster. We classified them as three eclipsing binary stars and one δ Scuti pulsating star, mainly based on the light-curve shape, the detected periods and the positions on the color-magnitude diagrams.
Biochemical characterization of defense responses in rose genotypes in response to artificial inoculation with black spot pathogen Diplocarpon rosae

Resistance responses in the leaves of eight rose genotypes, Knock Out (highly resistant), Arka Nishkant (moderately resistant), R. multiflora (highly susceptible), Arka Swadesh (highly susceptible), IIHRR 13-4 (susceptible), Arka Parimala (susceptible), R. indica (susceptible) and IIHRR 4-15-12 (moderately susceptible), exhibiting varied levels of resistance against black spot were investigated post artificial inoculation with black spot pathogen, Diplocarpon rosae. There was consistent increase in the activities of defense related enzymes such as catalase, peroxidase, polyphenol oxidase, superoxide dismutase and phenylalanine ammonia lyase and other defense related secondary metabolites like phenols and flavonoids at different phases of black spot progression and increase was high in resistant genotypes Knock Out and Arka Nishkant. The peak activity of defense enzymes and high concentration of other metabolites was witnessed during early stages of infection in the resistant genotypes while it was during later phase in the susceptible genotypes. These results suggested that the faster and stronger activation of defense system is associated with the resistance against black spotin the rose genotypes.
Using Statistical Techniques and Replication Samples for Missing Values Imputation with an Application on Metabolomics

Background: Data preparation, such as missing values imputation and transformation, is the first step in any data analysis and requires crucial attention. We take advantage of availability of replication samples to identify the empirical distribution of missing values through utilization of statistical techniques. We apply these techniques to metabolomics data for imputation. Results: Using replication samples, we obtained the empirical distribution of missing values. After application of the techniques on metabolites, we observed that the rate of missing values is approximately distributed uniformly across metabolite range. Therefore, the missing values cannot be imputed with the lowest values. To have a realistic simulation, we designed a simulation study based on empirical distribution of missing values to find an optimal imputation approach. Our findings validated the optimal approach introduced previously for metabolomics. Conclusions: Our analysis utilized replication samples as a new approach to metabolite imputation and found empirical distribution of missing values, designed a simulation study close to reality, and compared different approaches for selecting an optimal imputation approach. The result of this study validated the optimal approach for metabolite imputation through a different data set and different approach, and the aim was to encourage researchers to pay more attention to metabolite imputation since imputing metabolomic missing values with lowest value is going to be a common approach, for example in genomic-metabolomic data analysis.
Stress and Mental Health Among Racial Historically Marginalized and Advantaged Undergraduate Students

Undergraduate students are a high-stress population with a high prevalence of psychopathology. Further, students from historically marginalized racial groups face additional stressors and challenges. The aim of this study was to investigate the impact of identifying with a historically marginalized racial group on the relationship between stress and mental health outcomes. We used archival data, in which 528 college students were originally recruited to complete surveys on college-related stress and symptoms of psychopathology. Analyses of variance were employed to study differences in rates between a historically marginalized racial group and a historically advantaged racial group. Regression analyses were employed to study the moderating effect of identity group on the relationship between stress and mental health outcomes. The historically marginalized racial group was more likely to report performance stress (p = .008) and the historically advantaged racial group was more likely to report internalized symptoms of psychopathology including anxiety (p = .007) and depression (p = .02). Furthermore, group marginalization moderated the relationship between total stress (p < .001), financial stress (p < .001), and performance stress (p < .001) with symptoms of internalized psychopathology. Our findings may be explained by a difference in resilience, interpretation of stress, or limitations to survey methods. Recommendations for researchers and clinicians are offered.
Determinants of United States - Indonesia Equity Market’s Dynamic Correlation: The Role of Commodities and Exchange Rate’s Volatilities

This study aims to analyze the effect of oil price volatility, gold price volatility and exchange rate volatility on the dynamic relationship between Indonesian and United States capital market. The data used in this study are daily closing prices of oil, gold and exchange rates (USD/IDR) as well as Indonesian capital market (JKSE) and United States capital market (DJIA) composite indices during period of January 2005 to October 2020. This study uses DCC-GARCH method to calculate the dynamic correlation between two capital markets and GARCH with the GED parameter to analyze oil volatility, gold volatility and exchange rate volatility on the integration of Indonesian capital market and United States capital market. The results of this study show positive and strong results on the integration of Indonesian and United States capital markets, thus proving that the movements of Indonesian market and American market tend to be strong and mutually influence the two capital markets. Moreover, the oil, gold and exchange rates volatilities have a negative effect on the integration of the Indonesia capital market and the US capital market. This finding implies investors should take oil, gold and exchange rates volatilities in their investment consideration.
Analysis of a Converging, Annular, Isothermal Melt Blowing Jet Using Computational Fluid Dynamics

An unconventional melt blowing die was analyzed using computational fluid dynamics (CFD). This die has an annular configuration wherein the jet inlet is tapered (the cross-sectional area decreases) as the air approaches the die face. It was found that the flow characteristics of this die are different from conventional slot and annular dies. In particular, for the tapered die the near-field normalized turbulent kinetic energy was found to be lower at shallow die angles. Also, it was found that the peak mean velocity behavior was intermediate between that of conventional annular and slot dies. The centerline turbulence profiles were found to be qualitatively similar to those of annular dies; quantitatively, higher values were present for tapered dies.
Comparing the use of number sense strategies based on student achievement levels

ABSTRACT The aim of this study is to compare students’ use of number sense strategies based on their mathematics success levels. Participants were 129 seventh graders from three elite secondary schools in Trabzon. Data were collected through a written examination with 10 problems and semi-structured interviews. Interview data were analyzed by considering students’ mathematics success and the differences and similarities among responses. Interviews were held with six students from two schools with different levels of mathematics success. The findings showed that students rarely used number sense strategies and mostly solved problems by using rules and algorithms. Even successful students seemed to have adopted the rule- and algorithm-based solution approach, making it necessary to investigate teacher criteria of mathematical competence. Another noteworthy finding from the interviews with students was teachers’ embrace of rule- and algorithm-based solutions when solving problems. The study finishes with an evaluation of the inclusion of number sense dimensions in secondary school mathematics textbooks in Turkey and recommendations for improving students’ number sense.
Modular Framework for the Solution of Boundary-coupled Multiphysics Problems

This paper presents a modular multiphysics framework developed for OpenFOAM. The framework is built around an iterative implicit coupling scheme based on a multi-region partitioned approach. This scheme allows the implementation of formal implicit time-marching schemes, which improves the stability of strongly interacting coupled problems. This methodology allows physical interactions to be handled through specifically designed interface boundary conditions. It also allows region-specific solvers to be implemented as modular class solvers. The coupling methodology is handled with a main program that manages solver-specific actions. The aim of this framework is to facilitate the implementation and testing of new multiphysics coupling problems in an integrated code structure. To show the capabilities of the framework to integrate new physics, solvers and boundary conditions requirements are discussed. Also, three validated examples involving fluid-structure interactions, conjugate heat transfer, and fluid-structure-thermal interactions are presented. Although all these problems are boundary-coupled multiphysics problems, the framework is conceptually not limited to this kind of problems. The benefit of this work to the OpenFOAM community is a general and modular framework that facilitates the setup and solution of diversified multiphysics problems, and that illustrates the implementation of modular interface boundary conditions between physics regions.