Miracle-dz/UniFAR-FTUs huggingface dataset:
Is There Any Relationship between Physical Activity Levels and Academic Achievement? A Cross-Cultural Study among Spanish and Chilean Adolescents

The current scientific literature has shown significant disparity in results when physical activity is linked to academic achievement among adolescents. Thus, the main objectives of this study were (1) to analyze the relationship among students’ academic achievement, intention to be physically active, and physical activity levels depending on the country (Spain or Chile), as well as to analyze these relationships based on students’ socio-economic status, type of school, school year, gender, and body mass index; and (2) to analyze the differences between all these variables depending on the students’ country and gender. In total, 3052 adolescents participated in the research (14.58 ± 1.39 years): 734 Chilean students (336 males and 398 females) and 2318 Spanish students (1180 males and 1138 females). Various questionnaires were used to measure the study variables. The results revealed significant relationships between academic achievement and the rest of the variables in Spanish adolescents, but in the Chilean population, academic achievement was significantly related only to socio-economic status and the type of school. Moreover, Spanish students obtained higher scores, especially the males, except for academic achievement, which was higher in females. There were also significant differences in academic achievement, intention to be physically active, physical activity levels, and socio-economic status depending on the country, with all scores being higher in Spain. Given the results, the country seems to be an important factor when comparing academic achievement and physical activity levels, besides other demographic variables.
What Factors Need to Be Considered for Adopting M-Banking Services in a Developing Economy?

The study attempts to explore the effects of key factors influencing the customer acceptance of mobile banking adoption, particularly those that affect the consumer's attitudes towards and intention to use. This study builds a comprehensive theoretical model explaining M-banking adoption in Bangladesh. To assist in identifying these factors, an empirical study was conducted among general citizens of Bangladesh to identify the acceptance of M-banking. The study revealed that the critical factors which contribute to the adoption of M-banking in Bangladesh. A consumer survey on 250 mobile bank users of different mobile network operators in Bangladesh was undertaken where respondents completed a questionnaire about their perceptions of mobile banking's usefulness, perceived ease of usefulness, perceived risk, perceived cost, and perceived trust. This study offers an insight into mobile banking in Bangladesh, focusing on influencing factors and perceived trust was found to be the most significant factor affecting the adoption of M-banking in Bangladesh.
VORTEX: Network-Driven Opportunistic Routing for Ad Hoc Networks

The potential of ad hoc networks, which enable flexible and dynamic network establishment only by mobile terminals equipped with wireless communication devices, has recently attracted attention for the coming IoT era. Although the nature of ad hoc networks shows the advantages of their autonomous and distributed network management, a manifestation of drawbacks owing to the nature of wireless communication and the mobility of terminals are inevitable. Many routing protocols have already been proposed to address the issues by adapting to nature and achieving a certain level of improvement. However, the routing protocols still suffer from difficulties in information collection for routing and adaptive route management during communication. Moreover, there is another issue that end pair-based routing procedures prevent other end pairs from reusing the routing information effectively. To address the drawbacks of conventional routing protocols, this paper proposes VORTEX, a novel routing protocol that employs an opportunistic routing strategy using hierarchization. One of the characteristic features of VORTEX is its network-driven opportunistic forwarding, in which packets travel toward destination terminals using hierarchy as a guide without conventional route discovery procedures. Moreover, another characteristic feature of VORTEX is that the hierarchical structure also contributes to adapting to communication environment changes in an autonomous manner. In other words, VORTEX enables flexible network-wide information-based routing only with the locally collected information. The simulation results show that the proposed VORTEX could provide better service quality and reliability with improved efficiency compared to the conventional routing protocols. Furthermore, the most significant contribution is not only in the communication performance but also VORTEX omits route discovery or route maintenance from routing protocols, and formed networks themselves have a function to deliver packets toward destination terminals.
Q-switched neodymium-doped phosphate glass fiber lasers

The operation of a short-pulse, Q-switched, neodymium-doped fiber laser operating at 1.054 mu m is described experimentally and theoretically. The laser is efficiently pumped with a single-stripe AlGaAs laser diode and emits >1 kW pulses. It is seen that due to high gain short pulses with high energy extraction efficiency can be obtained. The feature of broad emission lines associated with rare-earth-doped glasses is exploited to demonstrate tunable, Q-switched operation over a 40-nm tuning range. >
Anti-Diabetic Activities of Hydro-Methanolic Crude Extract and Solvent Fractions of Heteromorpha arborescens (Apiaceae) Leaves in Mice

Background Heteromorpha arborescens has been used to treat diabetes traditionally. There was no in vivo study to support the claim. This study aimed to confirm anti-diabetic activity of 80% methanol in water extract and solvent fractions of H. arborescens leaves in mice. Methods H. arborescens leaves were macerated and extracted in 80% methanol in water. Hydro-methanol extract of H. arborescens leaves were tested in mice models. Overnight fasted mice were randomly divided into five groups for normoglycemic and glucose-loaded models as a negative control, positive control, and three tested groups, whereas, in streptozotocin-induced diabetic models, the mice were grouped into six groups each comprised six mice: diabetic negative control and normal negative control groups treated with 10 mL/kg distilled water, diabetic positive control group treated with Glibenclamide 5 mg/kg and three diabetic tested groups treated with extract at 100, 200, and 400 mg/kg doses. A one-way ANOVA was performed to analyze the data, and the post hoc Tukey’s test was utilized for multiple comparisons. The P-value <0.05 was considered statistically significant. Results Hydro-methanol extract of H. arborescens leaves at 400 mg/kg in normoglycemic mice significantly lowered blood glucose levels (BGLs) (P< 0.01). Mice with oral glucose-loaded test lowered BGLs at dosages of 200 mg/kg (P < 0.05) and 400 mg/kg (P < 0.01) respectively. Single-dose of ethyl acetate, n-hexane fractions and hydro-methanol extract at 100 mg/kg, 400 mg/kg and 200 mg/kg reduced BGLs (P < 0.05, P < 0.001, and P < 0.01) respectively. BGL drops in diabetic mice given daily repeated doses of 200 mg/kg of hydro-methanol extract and 400 mg/kg of ethyl acetate fraction (P < 0.001). Diabetic mice gained weight at a 400 mg/kg hydro-methanol extract and ethyl acetate fraction (P < 0.05 and P < 0.01) respectively. Hydro-methanol extract and ethyl acetate fraction and at 200 mg/kg decreased total cholesterol, triglycerides, and low-density lipoprotein and increased high-density lipoprotein (P < 0.001). Conclusion 80% methanol in water extract and solvent fractions of H. arborescens leaves showed anti-diabetic effects and significantly reduced hyperlipidemia in diabetics, this study supported the traditional usage of H. arborescens for treating diabetes; however, species variation could also limit such a straightforward extrapolation of the findings of this study in humans.
Assessing the structure dependence between the Spanish stock market and some international financial markets. A time-varying copula analysis.

In this study we use time-varying copula analysis to investigate the dependence between the Spanish stock market, represented by the IBEX35 index, and some international stocks and commodities markets. The results indicate that: first, the European stock markets offer limited diversification possibilities. Second, American markets offer higher diversification possibilities than the European markets but the diversification may not work in an extreme market condition; here we find strong evidence of contagion effect. Third, the Asian markets outperform to the American markets offering higher diversifications possibilities even in extreme market conditions. Fourth, the assets negotiated in the Shanghai market may be considered hedge assets instead of diversifier assets; this feature is shared by the Bitcoin and Gold although the role of this last asset is highly volatile. These results provide useful information for those who seek to actively diversify their international portfolios and to manage their worldwide assets. Finally, we observe that degree of dependence derived from the correlation analysis is notably higher than the suggested by the copula analysis; this may be due the fact that correlation coefficient does not consider conditional heteroscedasticity so that correlations will be biased upwards.
Light-transmission aggregometer using a vibration-induced disaggregation mechanism

The vibration-induced disaggregation technique of red blood cell (RBC) aggregates has been applied to design a new light-transmission aggregometer for measurement of aggregation index. For disaggregation of RBCs, the rotational shear flow in the Couette system is replaced with a simple low-frequency vibration in a disposable cavity slide glass. Using a vibration generator, one can disaggregate the RBC aggregates stored in the cavity slide glass. After applying the vibration for a specified duration, RBCs tend to reaggregate and instantaneous light-transmittance intensity is measured over time. A syllectogram (the transmitted light intensity versus time) consists of an initial decrease caused by the vibration-induced disaggregation, immediately followed by an increase in the light intensity due to RBC aggregation. The indices of aggregation are determined from the syllectogram using a curve-fitting program. The noble feature of this design is the vibration-induced disaggregation mechanism, which enables to.
The Mathematical Representation of Wind Speed and Temperature Profiles in the Unstable Atmospheric Surface Layer

Abstract Analytical expressions which specify non-dimensionalized wind speed and potential temperature gradients as functions of stability are integrated. The integrated equations are tested against Swinhank's wind and temperature profiles measured at Kerang, Australia. It is found that a representation suggested independently by Businger and by Dyer gives the best fit to temperature profiles and describes the wind profiles equally as well as a relation suggested by Panofsky et al.
Sagittal trunk excursion and lumbar repositioning error between female and male patients with patellofemoral pain syndrome

Background: Patellofemoral pain syndrome (PFPS) is a challenging clinical problem affecting adults, adolescents, and physically active populations. PFPS impacts the patient’s trunk kinematics in the frontal plane. Previous studies have found gender-based biomechanical differences in patients with PFPS; however, sagittal trunk kinematics during mini-squats and lumbar proprioception in PFPS have not been studied previously. Objectives: To investigate sagittal trunk excursion (It is defined as the sagittal trunk flexion angle from the start to the end of the mini squat) during mini-squats as well as lumbar repositioning error between individuals with and without PFPS, and determine gender differences in the outcome variables. Methods: A sample of 56 participants aged 18–25 years was enrolled; 30 with PFPS (13 males, 17 females) and 26 asymptomatic controls (11 males, 15 females). The sagittal trunk excursion during mini-squats was examined by two-dimensional (2D) photographic analysis using Surgimap software. Active lumbar flexion repositioning error was assessed using an isokinetic dynamometer. Results: For sagittal trunk excursion, no significant main effect of group was observed (p=0.136). On the other hand, the main effect was significant for gender (p=0.005), as was the interaction effect. Compared to the control group, the PFPS group showed significantly (p=0.01) lower sagittal trunk excursion in females than in males during mini-squats. For active lumbar flexion repositioning error, no evidence was found for significant main or interaction effects (p>0.05). Conclusion: Females with PFPS exhibit a more erect sagittal trunk posture than males during mini-squats. Trunk posture should be considered during weight-bearing activities in PFPS, and gender-specific assessment protocols should be developed.
Empirical evidence of type III functional responses and why it remains rare

More than 70 years after its introduction, the framework of resource density-dependent consumption rates, also known as predator-prey functional responses, remains a core concept in population and food web ecology. Initially, three types of responses were defined: linear (type I), hyperbolic (type II), and sigmoid (type III). Due to its potential to stabilize consumer-resource population dynamics, the sigmoid type III functional response immediately became a “holy grail” in population ecology. However, experimentally proving that type III functional responses exist, whether in controlled laboratory systems or in nature, was challenging. While theoretical and practical advances make identifying type III responses easier today, decades of research have brought only a limited number of studies that provide empirical evidence for type III response curves. Here, we review this evidence from laboratory- and field-based studies published during the last two decades. We found 107 studies that reported type III responses, but these studies ranged across various taxa, interaction types, and ecosystems. To put these studies into context, we also discuss the various biological mechanisms that may lead to the emergence of type III responses. We summarize how three different and mutually independent intricacies bedevil the empirical documentation of type III responses: (1) challenges in statistical modeling of functional responses, (2) inadequate resource density ranges and spacing, and (3) biologically meaningful and realistic design of experimental arenas. Finally, we provide guidelines on how the field should move forward based on these considerations.
EEI-IoT: Edge-Enabled Intelligent IoT Framework for Early Detection of COVID-19 Threats

Coronavirus disease 2019 (COVID-19) has caused severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across the globe, impacting effective diagnosis and treatment for any chronic illnesses and long-term health implications. In this worldwide crisis, the pandemic shows its daily extension (i.e., active cases) and genome variants (i.e., Alpha) within the virus class and diversifies the association with treatment outcomes and drug resistance. As a consequence, healthcare-related data including instances of sore throat, fever, fatigue, cough, and shortness of breath are given due consideration to assess the conditional state of patients. To gain unique insights, wearable sensors can be implanted in a patient’s body that periodically generates an analysis report of the vital organs to a medical center. However, it is still challenging to analyze risks and predict their related countermeasures. Therefore, this paper presents an intelligent Edge-IoT framework (IE-IoT) to detect potential threats (i.e., behavioral and environmental) in the early stage of the disease. The prime objective of this framework is to apply a new pre-trained deep learning model enabled by self-supervised transfer learning to build an ensemble-based hybrid learning model and to offer an effective analysis of prediction accuracy. To construct proper clinical symptoms, treatment, and diagnosis, an effective analysis such as STL observes the impact of the learning models such as ANN, CNN, and RNN. The experimental analysis proves that the ANN model considers the most effective features and attains a better accuracy (~98.3%) than other learning models. Also, the proposed IE-IoT can utilize the communication technologies of IoT such as BLE, Zigbee, and 6LoWPAN to examine the factor of power consumption. Above all, the real-time analysis reveals that the proposed IE-IoT with 6LoWPAN consumes less power and response time than the other state-of-the-art approaches to infer the suspected victims at an early stage of development of the disease.
Differentiating depression using facial expressions in a virtual avatar communication system

Depression has a major effect on the quality of life. Thus, identifying an effective way to detect depression is important in the field of human-machine interaction. To examine whether a combination of a virtual avatar communication system and facial expression monitoring potentially classifies people as being with or without depression, this study consists of three research aims; 1) to understand the effect of different types of interviewers such as human and virtual avatars, on people with depression symptoms, 2) to clarify the effect of neutral conversation topics on facial expressions and emotions in people with depression symptoms, and 3) to compare verbal and non-verbal information between people with or without depression. In this study, twenty-seven participants—fifteen in the control group and twelve in the depression symptoms group—were recruited. They were asked to talk to a virtual avatar and human interviewers on both neutral and negative conversation topics and to score PANAS; meanwhile, facial expressions were recorded by a web camera. Facial expressions were analyzed by both manual and automatic analyses. In the manual analysis, three annotators counted gaze directions and reacting behaviors. On the other hand, automatic facial expression detection was conducted using OpenFace. The results of PANAS suggested that there was no significance between different interviewers’ types. Furthermore, in the control group, the frequency of look-downward was larger in negative conversation topics than in neutral conversation topics. The intensity of Dimpler was larger in the control group than in the depression symptoms group. Moreover, the intensity of Chin Raiser was larger in neutral conversation topics than in negative conversation topics in the depression symptoms group. However, in the control groups, there was no significance in the types of conversation topics. In conclusion, 1) there was no significance between human and virtual avatar interviewers in emotions, facial expressions, and eye gaze patterns, 2) neutral conversation topics induced less negative emotion in both the control and depression symptoms group, and 3) different facial expressions’ patterns between people with, or without depression, were observed in the virtual avatar communication system.
Marker-based quadri-ocular tracking system for surgery

This study presents a quadri-ocular tracking system, which is based on PC and infrared reflective markers, for a spine surgical robot. The authors mainly focus on four tasks of the system. First of all, a two-step strategy for point correspondence of the multi-ocular system is introduced. The strategy enhances the traditional epipolar constrain for a bi-ocular system, and it decomposes the point correspondence of the multi-ocular system into several bi-ocular systems and corresponding steps to improve the speed of the system. Second, this paper proposes a fast algorithm of three-dimensional point reconstruction based on the perpendicular feet of back-projection lines. A marker constraint is also dug up to solve the combination problem of target recognition. Finally, this study uses a generalised inverse and singular value decomposition-based method to locate the pose of the target. The experiments show that the speed and accuracy of the system are satisfactory.
Super-twisting sliding mode control for brushless doubly fed reluctance generator based on wind energy conversion system

Introduction. Recently, wind power generation has grown at an alarming rate in the past decade and will continue to do so as power electronic technology continues to advance. Purpose. Super-twisting sliding mode control for brushless doubly-fed reluctance generator based on wind energy conversion system. Methods. This paper deals with the robust power control of a grid-connected brushless doubly-fed reluctance generator driven by the variable speed wind turbine using a variable structure control theory called sliding mode control. The traditional sliding mode approach produces an unpleasant chattering phenomenon that could harm the system. To eliminate chattering, it is necessary to employ a high-order sliding mode controller. The super-twisting algorithm is one type of nonlinear control presented in order to ensure the effectiveness of the control structure we tested these controllers in two different ways reference tracking, and robustness. Results. Simulation results using MATLAB/Simulink have demonstrated the effectiveness and robustness of the super-twisting sliding mode controller.
When Tangibles Become Deformable: Studying Pseudo-Stiffness Perceptual Thresholds in a VR Grasping Task

Pseudo-Haptic techniques, or visuo-haptic illusions, leverage user's visual dominance over haptics to alter the users' perception. As they create a discrepancy between virtual and physical interactions, these illusions are limited to a perceptual threshold. Many haptic properties have been studied using pseudo-haptic techniques, such as weight, shape or size. In this paper, we focus on estimating the perceptual thresholds for pseudo-stiffness in a virtual reality grasping task. We conducted a user study (n = 15) where we estimated if compliance can be induced on a non-compressible tangible object and to what extent. Our results show that (1) compliance can be induced in a rigid tangible object and that (2) pseudo-haptics can simulate beyond 24 N/cm stiffness (k > 24N/cm, between a gummy bear and a raisin, up to rigid objects). Pseudo-stiffness efficiency is (3) enhanced by the objects' scales, but mostly (4) correlated to the user input force. Taken altogether, our results offer novel opportunities to simplify the design of future haptic interfaces, and extend the haptic properties of passive props in VR.
Dynamic Correlation Adjacency-Matrix-Based Graph Neural Networks for Traffic Flow Prediction

Modeling complex spatial and temporal dependencies in multivariate time series data is crucial for traffic forecasting. Graph convolutional networks have proved to be effective in predicting multivariate time series. Although a predefined graph structure can help the model converge to good results quickly, it also limits the further improvement of the model due to its stationary state. In addition, current methods may not converge on some datasets due to the graph structure of these datasets being difficult to learn. Motivated by this, we propose a novel model named Dynamic Correlation Graph Convolutional Network (DCGCN) in this paper. The model can construct adjacency matrices from input data using a correlation coefficient; thus, dynamic correlation graph convolution is used for capturing spatial dependencies. Meanwhile, gated temporal convolution is used for modeling temporal dependencies. Finally, we performed extensive experiments to evaluate the performance of our proposed method against ten existing well-recognized baseline methods using two original and four public datasets.