Miracle-dz/UniFAR-FTUs huggingface dataset:
Smartphone Addiction, Personality Factors, Emotional Regulation and Mental Health: Gender Based Studies

Introduction: The present study intends to measure gender differences in smartphone addiction, emotional regulation, mental health and personality variables. Earlier studies have focused on gender differences in variables under study. Aim: It was an attempt to revalidate the findings for fulfillment of the research objectives. Sample: The sample was drawn following some predetermined inclusion and exclusion, a sample of 100 individuals ageing between 13 to 19 years were selected. Half of them were male and half of them were females. Method: Sample was administered with 1) Smartphone addiction test by Kwon et al (2013), 2) Mental Health Inventory Veit and Ware (1983), 3) Emotional Regulation Questionnaire by James J. Gross and Oliver P (2003), 4) Big Five Inventory (Personality) by Goldberg, (1993). Along with the above measures General Health Questionnaire was also administered for screening purpose. For GHQ a cut off 4 was selected below which individuals were allowed for participation in investigation. Result: Results indicated gender differences in variables under study. Females have been found to have higher level of addiction than male. Male were found to have more distress and low in psychological well-being. Male also found to have greater emotional reappraisal and lesser emotional suppression. Conclusion: In case of personality variables males were found to be more open, conscientious and agreeable while females were found to be more prone to neuroticism.
European Journal of Educational Research

: This study investigates the impact of external variables, technological pedagogical and content knowledge (TPACK) self-efficacy, and facilitating conditions on teacher adoption of online teaching technology during the COVID-19 pandemic. It employs explanatory research to characterize the effect of external variables on the variables of the technology acceptance model. 240 high school teachers filled out Google Forms survey questionnaires for six research variables and analyzed by the SmartPLS program. The result indicates that attitude and perceived usefulness significantly and positively influence behavioral intention. Perceived usefulness and ease of use have a strong positive effect on attitude. Furthermore, perceived ease of use has a considerable effect on perceived usefulness. Perceived usefulness and ease of use are not significantly influenced by external variables. Facilitating conditions significantly positively affect behavioral intention, whereas TPACK self-efficacy negatively affects behavioral intention.
Analysis Of The Effect Of Service Quality, Marketing Mix, On Interest In Service Reuse Hospitalization

The diversity of people's needs for health products and services means that hospitals are competing as much as possible to serve consumers. Hospitals must improve the quality of service and also hospitals need to design marketing programs so that products/services get a response from the target market and run successfully. The marketing mix is a set of marketing tools used by the company to continuously achieve one of the marketing goals, namely to provide satisfaction to the wants and needs of consumers and to generate profits for the company from the mix market. The purpose of this study was to determine the effect of service quality and marketing mix on the intention to reuse inpatient services at RSU Royal Prima Medan in 2022. This research is a type of quantitative research. The research design used was an analytic observational method with a cross sectional approach. The population in this study was the average patient who came for treatment at the Inpatient Installation of RSU Royal Prima Medan in the last 3 months, totaling 1,653 patients. Sampling used SEM analysis where the number of samples was 150 patients. Data analysis used univariate, bivariate and multivariate analysis. The results showed that service quality had a positive and significant effect on the intention to reuse inpatient services at RSU Royal Prima Medan p-value <0.05, the marketing mix had a positive and significant effect on the intention to reuse inpatient services at RSU Royal Prima Medan p-value < 0.05. Simultaneously or simultaneously service quality and marketing mix have a positive and significant effect on the intention to reuse inpatient services at RSU Royal Prima Medan p-value <0.05. The independent variable that has the most influence on the dependent variable in this study is the service quality variable.Keywords: Hospital, Interest in reus, Marketing mix, Quality of service
RF Transversal Planar Filters With Dual-Lowpass/Bandpass Response

The optimization-based design of RF / microwave transversal signal-interference planar filters with composite-lowpass /bandpass transfer function is reported. As their basic constituent circuit stage, these filters exploit a transversal filtering section (TFS) composed of two stepped-impedance-transmission-line electrical paths. Thus, by means of constructive / destructive RF-signal-combination mechanisms taking place inside this class of bi-path TFS, sharp-rejection dual-lowpass/bandpass filtering responses with extended upper stopband can be realized. Higher-order designs with increased selectivity / out-of-band-attenuation levels can also be implemented by means of in-series-cascaded multi-TFS circuit arrangements. For experimental-demonstration purposes, two microstrip prototypes consisting of single- and two-TFS-based circuits are designed, fabricated, and characterized.
Direct observational evidence for disturbance dynamo on the daytime low‐latitude ionosphere: A case study based on the 28 June 2013 space weather event

A case of the westward disturbance dynamo (DD) electric field, influencing the daytime equatorial and low‐latitude ionosphere, during a geomagnetic storm that occurred on 28–29 June 2013 is presented. The GPS total electron content (TEC) observations from a network of stations in the Indian equatorial, low and middle latitude regions along with the radio beacon TEC, ionosonde, and magnetic field observations are used to study the storm time behavior of the ionosphere. Negative ionospheric storm effects were seen over the low and middle latitudes during the storm time due to the presence of a westward DD electric field. Observations show that the suppression of the equatorial ionization anomaly (EIA) from the morning hours itself on 29 June 2013 took place due to the prevailing westward DD electric field, providing evidence for the model calculations by Balan et al. (2013). Simulations using the GITM model also agree well with our results. The present study gains importance as the direct observational evidences for disturbance dynamo effects on the daytime low‐latitude ionosphere and the EIA are sparse, as it has been difficult to delineate it from the compositional disturbances.
Relationship between the Number Of Oecophylla smaragdina Fab. ant nests and the Intensity of Prays endocarpa Meyrick Attacks on Pamelo Citrus (Citrus maxima Merr)

This research on the relationship between the number of O. smaragdina nests and the intensity of P. endocarpa attacks has been conducted at the Pamelo citrus plantation of Gelengge in Pangkep Regency. The observation sample trees were those which had the O. smaragdina nests for three weeks in the Pamelo citrus trees. The sample trees were grouped into four categories namely: A) 1-2 nests per tree, B) 3-4 nests per tree, C) 5-6 nests per tree, and D) without nests (control). The observed parameters were the attack intensity of P. endocarpa on fruits on trees and on fallen fruits found under Pamelo citrus trees. The observation of the attack intensity was carried out after the Pamelo citrus fruits reached six weeks old, or after the fruits reached 50 mm-60 mm in size. The results showed the intensity of P. endocarpa attack on the fruits in the lowest tree was 36% in the trees with about 5-6 O. smaragdina nests, and the highest in the trees without nests was 66%. The attack intensity on the lowest falling fruit was 41.5% on the trees with 5-6 nests per tree, and the highest was 60.3% the in trees without the O. smaragdina nests. The regression analysis showed a relationship between the number of O. smaragdina nests with the attack intensity with the regression coefficients, respectively were r = 0.94 and r = 0.98.
A model for total volume of debris flow with intermittent surges based on maximum peak discharge and movement time

Abstract A total volume of debris flow with intermittent surges is an important design parameter for the prevention of debris flow which requires an accurate determination of total volume of debris flow. Firstly, based on the data of 63 debris flow events from 1987 to 1995 at Jiangjia gully in Dongchuan County, Yunnan Province, China, we find that the distribution of debris flow discharge can be described by the lognormal distribution. Secondly, a statistical model for the total volume of debris flow with intermittent surges is established by the most stable fractile and the lognormal distribution function. Thirdly, we verified the accuracy of Equation (15) using data of 65 debris flows events from 1996 to 2004 in Jiangjia gully. Equation (15) generated more accurate results when compared with other existing models. The results of research are as follows: The Average Relative Error and Sum of Squared Relative Errors of Equation (15) are 47.6%p and 22.3, which is 10.9%p and 8.0 lower than that of Ou model, respectively. This model can be better applied to calculate the total volume of debris flows with intermittent surges in Jiangjia gully.
Neurophysiological Evaluation of Autonomic Dysfunction in Spinal Muscular Atrophy: A Case-Control Study

Introduction. Spinal muscular atrophy (SMA) is an autosomal recessive disorder causing lower motor neuron degeneration leading to weakness and muscle atrophy due to reduction of survival motor neuron (SMN) protein. Although SMA was considered an exclusively motor neuron disease, few reports indicate the involvement of nonmotor neurons. The aim of this study is to investigate autonomous nervous system (ANS) involvement in SMA. Materials and Methods. We investigated 9 SMA adult patients and 36 age- and sex-matched controls. ANS was evaluated by sympathetic skin response (SSR). Results. SSR was not elicited in 28% of measurements in cases and in 0% of measurements in controls (p<0.001). Both palmar (p<0.001) and plantar (p<0.001) SSR latencies were significantly longer in cases than controls. Palmar SSR amplitudes were smaller (p=0.036) in patients compared to controls. Conclusions. This study provides new evidence of ANS dysfunction in SMA patients.
A Novel Concept-Driven Negative Sampling Mechanism for Enhancing Semanticity and Interpretability of Knowledge Graph Completion Task

In recent years, it has witnessed the revival of knowledge engineering, which is characterized by the rapid growth of Knowledge Graph (KGs). Currently, Knowledge Graph Representation (KGR) and Completion (KGC) methods all use the methodology of scoring triple ($e_{h},r, e_{t}$) to judge its correctness. Wherein, in the procedure of conventional Negative Sampling (NS) and reasoning, it is easy to be affected by the low-quality and uncertainty of negative triples related to the given KG, resulting in some unpredictable and inexplicable wrong results that do not conform to commonsense. On the contrary, human beings with commonsense could easily solve this problem. For this reason, this paper proposes a novel mechanism to automatically capture commonsense (concept emphasized here) associated with current KG to provide more deterministic and interpretable semantic information from the fact triple, and further designs a concept-driven negative sampling strategy for commonsense understanding. Overall, a hybrid reasoning approach jointly driven by concept constraints (inter with KG) and fact triple guides (intra with KG), is presented to promote more effective learning and training procedure of KG's representation and completion. Experiments on real-world datasets, show that the proposed work could be used as a flexible plug-in unit to enhance the previous KG representation and completion models.
Metabolic syndrome, HOMA-IR and adiponectin in obese adolescents

Background: Homeostasis model assessment (HOMA) is a method used to measure insulin resistance (IR). Adiponectin is involved in the development of atherosclerosis. Objectives: This study aimed to assess metabolic syndrome (MetS) prevalence in adolescents with obesity; correlate HOMA-IR and IR incidence with MetS biochemical parameters and MetS components; as well as correlate adiponectin levels and hypoadiponectinemia incidence with MetS biochemical parameters and MetS components. Methods: This study was conducted at the Outpatient Installation Unit of Nutrition and Metabolic Diseases, Child Health Department, Dr. Soetomo General District Hospital, Surabaya, Indonesia with a cross-sectional study design. It lasted for nine months and focused on obese adolescents aged 13-18 years. Anthropometric measurements and blood biochemistry analyses were done. HOMA-IR was calculated using the formula [glucose (mg/dL) x Insulin (µu/L)]/405. Results: A total of 216 obese adolescents took part in the study. MetS was found in 81 subjects (37.96%). There was weak correlation between HOMA-IR ​​with anthropometric measurements, lipid profiles, fasting blood glucose, and serum adiponectin levels (p<0.05). IR was found to increase the risk of MetS development by 1.661-times, dyslipidemia by 1.845-times, and abdominal obesity by 3.077-times. IR increased the risk of MetS incidence with more than three IDF criteria by 9.368-times. There was a correlation between adiponectin levels with the HDL-c. Hypoadiponectinemia was correlated with the incidence of MetS, abdominal obesity, and hypertriglyceridemia. It also increased the risk of developing MetS by 2.220-times. There was a positive relationship between IR HOMA value ​​and the anthropometric parameters of obesity and MetS parameters. Conclusions: IR was found to be associated with dyslipidemia, abdominal obesity, and MetS incidence with more than three IDF criteria. There was a relationship between hypoadiponectinemia and waist circumference, hip circumference, HDL-c, and triglycerides. Insulin resistance and hypoadiponectinemia were associated with Mets and hypertriglyceridemia incidence.
Development and Characterization of Wideband Power Divider for Sub-THz Transceiver Modules

In this work, the development and characterization of a wideband power divider for Sub-THz applications have been presented. The divider is aimed to be used for dividing the IF signal at 50 GHz with a bandwidth of 40 GHz. The design is implemented on a low transmission loss 8-layers PCB whose modeling methodology will be highlighted. The design conceptually is based on shifting down the isolation plane below 90 degree length while utilizing a radial stub for compensating the change in the isolation element. The preliminary analysis for the design had been studied for a single stage model while the optimized design is measured back-to-back configuration and showed a good agreement to the simulation. The proposed design is implemented in a 275 GHz receiver module of multiple CMOS mixer chips fed from phased array antenna for enabling beamforming capability.
Spatial Analysis Along Networks: Statistical and Computational Methods

In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Processes on a Network and Network Voronoi Diagrams, to Network K-function and Point Density Estimation Methods, and the Network Huff Model. The authors also discuss and illustrate the undertaking of the statistical tests described in a Geographical Information System (GIS) environment as well as demonstrating the user-friendly free software package SANET.
Development of a Machine Learning Algorithm to Correlate Lumbar Disc Height on X-rays with Disc Bulging or Herniation

Lumbar disc bulging or herniation (LDBH) is one of the major causes of spinal stenosis and related nerve compression, and its severity is the major determinant for spine surgery. MRI of the spine is the most important diagnostic tool for evaluating the need for surgical intervention in patients with LDBH. However, MRI utilization is limited by its low accessibility. Spinal X-rays can rapidly provide information on the bony structure of the patient. Our study aimed to identify the factors associated with LDBH, including disc height, and establish a clinical diagnostic tool to support its diagnosis based on lumbar X-ray findings. In this study, a total of 458 patients were used for analysis and 13 clinical and imaging variables were collected. Five machine-learning (ML) methods, including LASSO regression, MARS, decision tree, random forest, and extreme gradient boosting, were applied and integrated to identify important variables for predicting LDBH from lumbar spine X-rays. The results showed L4-5 posterior disc height, age, and L1-2 anterior disc height to be the top predictors, and a decision tree algorithm was constructed to support clinical decision-making. Our study highlights the potential of ML-based decision tools for surgeons and emphasizes the importance of L1-2 disc height in relation to LDBH. Future research will expand on these findings to develop a more comprehensive decision-supporting model.
Enhancing Water Status and Nutrient Uptake in Drought-Stressed Lettuce Plants (Lactuca sativa L.) via Inoculation with Different Bacillus spp. Isolated from the Atacama Desert

Drought is a major challenge for agriculture worldwide, being one of the main causes of losses in plant production. Various studies reported that some soil’s bacteria can improve plant tolerance to environmental stresses by the enhancement of water and nutrient uptake by plants. The Atacama Desert in Chile, the driest place on earth, harbors a largely unexplored microbial richness. This study aimed to evaluate the ability of various Bacillus sp. from the hyper arid Atacama Desert in the improvement in tolerance to drought stress in lettuce (Lactuca sativa L. var. capitata, cv. “Super Milanesa”) plants. Seven strains of Bacillus spp. were isolated from the rhizosphere of the Chilean endemic plants Metharme lanata and Nolana jaffuelii, and then identified using the 16s rRNA gene. Indole acetic acid (IAA) production, phosphate solubilization, nitrogen fixation, and 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity were assessed. Lettuce plants were inoculated with Bacillus spp. strains and subjected to two different irrigation conditions (95% and 45% of field capacity) and their biomass, net photosynthesis, relative water content, photosynthetic pigments, nitrogen and phosphorus uptake, oxidative damage, proline production, and phenolic compounds were evaluated. The results indicated that plants inoculated with B. atrophaeus, B. ginsengihumi, and B. tequilensis demonstrated the highest growth under drought conditions compared to non-inoculated plants. Treatments increased biomass production and were strongly associated with enhanced N-uptake, water status, chlorophyll content, and photosynthetic activity. Our results show that specific Bacillus species from the Atacama Desert enhance drought stress tolerance in lettuce plants by promoting several beneficial plant traits that facilitate water absorption and nutrient uptake, which support the use of this unexplored and unexploited natural resource as potent bioinoculants to improve plant production under increasing drought conditions.
Classification of Images with Linear Objects in All-Sky Astronomical Survey Data using Convolutional Neural Networks

This paper focuses on the classification of astronomical data, specifically images with or without linear features, which can be of different origin like meteors, asteroids, or satellites. Such models might be helpful in fast recognition of contaminated images from astronomical surveys, where satellites or other phenomena might decrease scientific value of survey for astrophysicists. It is quite large problem in astronomy today, due to increasing number of new satellites. On the other hand, such identification might also bring information on objects that pass through cameras field of view. Therefore, any fast way to recognize such cases is helpful. To achieve our goal of classification, we propose two main methods. Firstly, we focus on annotation project of images to create a dataset divided into two classes based on the occurrence of linear objects. Secondly, we suggest three different experiments utilizing convolutional neural networks. The results of each experiment are crucial as we create a sequence of experiments, with the best result serving as input for the subsequent experiment. To determine the success of our experiments, we define a threshold value of 98% for accuracy, which we were able to achieve in the final of the three experiments.
Synthesis of AZO-Coated ZnO Core–Shell Nanorods by Mist Chemical Vapor Deposition for Wastewater Treatment Applications

AZO-coated ZnO core–shell nanorods were successfully fabricated using the mist chemical vapor deposition method. The influence of coating time on the structural, optical, and photocatalytic properties of zinc oxide nanorods was investigated. It was observed that the surface area of AZO-coated ZnO core–shell nanorods increased with an increase in coating time. The growth orientation along the (0001) crystal plane of the AZO thin film coating was the same as that of zinc oxide nanorods. The crystallinity of AZO-coated ZnO core–shell nanorods was significantly improved as well. The optical transmittance of AZO-coated ZnO core–shell nanorods was greater than 55% in the visible region. The degradation efficiency for methyl red dye solution increased with an increase in coating time. The highest degradation efficiency was achieved by AZO-coated ZnO core–shell nanorods with a coating duration of 20 min, exhibiting a degradation rate of 0.0053 min−1. The photodegradation mechanism of AZO-coated ZnO core–shell nanorods under ultraviolet irradiation was revealed.
Traversability Estimation for Off-Road Autonomous Driving Under Ego-Motion Uncertainty

The accurate and stable estimation of traversability is a crucial task for unmanned ground vehicle (UGV) driving in off-road environments. However, the complexity of off-road environments increases the difficulty of the task. Moreover, the stability of traversability estimation is adversely affected by ego-motion uncertainty caused by the violent jolts when the UGV is traveling fast on uneven surfaces. The lack of prior information also poses a significant challenge to the task. To address these challenges, this article proposes a novel framework for cost map (CM) generation, which uses light detection and ranging (LiDAR)-inertial odometry (LIO) and historically observed frames to generate local CMs with no need for any prior information. To describe the traversability of complex environments, we design a cost calculation method that includes a variety of factors affecting UGV driving. Not only terrain features such as slope and roughness, but also potential slip risks are considered in it. In consideration of ego-motion uncertainty, terrain continuity is modeled as a spatial constraint to enhance sparse laser scans, and historical observations are fused to filter out noises in the temporal dimension. Real-world experimental results demonstrate that the proposed method can generate stable CM with detailed traversability descriptions even with violent UGV jolts.