Miracle-dz/UniFAR-FTUs huggingface dataset:
Poster: Studying The Social Networks in Educational Forums

—This research aims to carry out a topological study of social networks located in university forums of the Moodle platform. Graphs are built visualizing the structure of the nodes and links and calculating statistical parameters such as: degree, betweenness centrality, clustering coefﬁcient, PageRank, EigenVector centrality and assortativity. The communities’ structure was also estimated. This study analyzes how students and faculties work and socialize in the educational environment, which help to know more precisely the level of involvement of each student as well as to improve some learning and methodological aspects. Several subjects and forums are analyzed (theoretical and practical contents).
European Journal of Physical Education and Sport Science-2501-1235

The aim of this study is to examine the heart rate variability (HRV) parameters, trait anxiety, and competitive state anxiety levels of active individuals. The research was conducted with a total of 28 men and women aged 18-26 who exercise regularly. Personal information form, trait anxiety inventory, and competitive state anxiety inventory (CSAI2) were applied to the volunteers. Heart Rate Variability measurement was performed using the Heart Math emWave Pro + device. In the analysis of the data, normal distribution criteria were checked using the Shapiro-Wilk test. T-test was used for variables with normal distribution, and Mann Whitney U test was used for variables that did not show normal distribution. Pearson and Spearman correlation analyzes were conducted to examine the relationship between cognitive anxiety, somatic anxiety, and HRV parameters. According to the findings, a statistically significant difference in favor of women was found between the genders in the LF / HF (log) (p = .011) parameter (p <0.05). According to the correlation analysis, a significant negative correlation was observed between somatic anxiety and the parameters SDNN, RMSSD, LF (Log) (-.457; .403; -.462 respectively). In conclusion, men and women who exercise regularly have similar anxiety states. It is observed that women have better sympathovagal balance compared to men. The absence of stress parameters that cause impairment in heart rhythm such as anxiety does not cause deterioration in the structure of HRV. In addition, there is a negative correlation between somatic anxiety and some HRV parameters.
Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles

The evaluation of the effect of burn severity on forest soils is essential to determine the impact of wildfires on a range of key ecological processes, such as nutrient cycling and vegetation recovery. The main objective of this study was to assess the potentiality of different spectral products derived from RGB and multispectral imagery collected by unmanned aerial vehicles (UAVs) at very high spatial resolution for discriminating spatial variations in soil burn severity after a heterogeneous wildfire. In the case study, we chose a mixed-severity fire that occurred in the northwest (NW) of the Iberian Peninsula (Spain) in 2019 that affected 82.74 ha covered by three different types of forests, each dominated by Pinus pinaster, Pinus sylvestris, and Quercus pyrenaica. We evaluated soil burn severity in the field 1 month after the fire using the Composite Burn Soil Index (CBSI), as well as a pool of five individual indicators (ash depth, ash cover, fine debris cover, coarse debris cover, and unstructured soil depth) of easy interpretation. Simultaneously, we operated an unmanned aerial vehicle to obtain RGB and multispectral postfire images, allowing for deriving six spectral indices. Then, we explored the relationship between spectral indices and field soil burn severity metrics by means of univariate proportional odds regression models. These models were used to predict CBSI categories, and classifications were validated through confusion matrices. Results indicated that multispectral indices outperformed RGB indices when assessing soil burn severity, being more strongly related to CBSI than to individual indicators. The Normalized Difference Water Index (NDWI) was the best-performing spectral index for modelling CBSI (R2cv = 0.69), showing the best ability to predict CBSI categories (overall accuracy = 0.83). Among the individual indicators of soil burn severity, ash depth was the one that achieved the best results, specifically when it was modelled from NDWI (R2cv = 0.53). This work provides a useful background to design quick and accurate assessments of soil burn severity to be implemented immediately after the fire, which is a key factor to identify priority areas for emergency actions after forest fires.
Motor control times and strategies in left- and right-handed participants: Behavioral evidence for the hemispheric distribution of motor planning

Background: There is conflicting evidence in favor of the hemispheric distribution of motor planning. Some studies supported the left-hemisphere-dominance hypothesis for motor planning and claimed that the left-hemisphere has a crucial function in motor control even in left-handers. The present study aimed to compare the right- and left-handed participants on motor planning ability and to investigate the performance of their dominant hands in a specific action selection task. Also, the effect of task complexity was assessed. Methods: Twenty right-handers and 20 left-handers performed an action selection task. The participants had to grasp a hexagonal knob with their dominant hand and consequently rotated it 60° or 180 ° clockwise or counterclockwise. Depending on our objects, we used mixed factorial ANOVA and the groups were examined in terms of the planning time, grasping time, releasing time and planning pattern for initial grip selection. The SPSS 19 was used for analyzing the data and p≤0.05 was considered as the significant level. Results: No significant differences were observed between the two groups. The movement-related measures revealed a main effect of rotation (p˂0.001). However, a significant interaction between direction × planning pattern × group (p˂0.001) indicated a preferential bias for rotatory movements in the medial direction which is consistent with the "medial over lateral advantage". Conclusion: Both left- and right-handed participants had a similar motor planning ability while performing a planning task with their dominant hands. Because our study was behavioral, it only provided a test of the left-hemisphere hypothesis of motor planning.
Post-editing for Professional Translators: Cheer or Fear?

Currently, post-editing of machine translation (MT) has been introduced as a regular practice in the translation workflow, especially since the good results in quality obtained by neural MT (NMT). This fact is linked to the efforts LSPs and customers have done to reduce costs due to the recent global crisis and the increasing globalization, which has had a negative impact on translators' revenues and on their working practices. In this context, post-editing is often perceived with a negative bias by translators. We study attitudes of translators post-editing for the first time and relate them to their productivity rates. We also compare the results with a survey answered by professional post-editors assessing their perception of the task in the current marketplace.
Assessment of Dementia Caregiver Burden in Karachi, Pakistan using 10/66 Protocol

INTRODUCTION: Care arrangements and caregiver burden of people with dementia (PWD) are different in low and middle income countries (LMICs) than in developed countries. This is the first study in Pakistan assessing caregiver burden using the 10/66 protocol. METHOD: PWD were recruited from outpatient clinics and from the community in Karachi and were diagnosed according to DSM-IV TR. Three scales were used: 1. Zarit Burden Interview (ZBI) to assess caregiver burden. 2. Caregiver Activity Survey (CAS) to assess activities that the caregiver engaged in the last 24 hours to care for PWD and 3. General Health Questionnaire12 (GHQ 12) to assess caregiver emotional distress. The scales were translated, back translated, and tested for conceptual validity in Urdu. The data was entered using EPIDATA and was assessed using SPSS version 22.0. Ethical approval was obtained from institutional review board of Aga Khan University, Karachi. RESULTS: Mean Zarit Burden Interview score was 11.5 and had significant positive correlation with the caregiver’s level of education (p=0.04) and age (p=0.008) and negative correlation with the mini mental status exam (MMSE) score. An average of 40 minutes per day were spent by the caregivers with PWD in communicating. The mean General Health Questionnaire score was 2.3 with a standard deviation of 3.1. CONCLUSION:Caregiver training and education methods should be devised especially for older caregivers, those with low level of education, and those taking care of people with moderate stages of dementia. Caregiver support strategies should be devised to manage caregiver distress.
SrVARM: State Regularized Vector Autoregressive Model for Joint Learning of Hidden State Transitions and State-Dependent Inter-Variable Dependencies from Time Series Data

Many applications, e.g., healthcare, education, call for effective methods methods for constructing predictive models from high dimensional time series data where the relationship between variables can be complex and vary over time. In such settings, the underlying system undergoes a sequence of unobserved transitions among a finite set of hidden states. Furthermore, the relationships between the observed variables and their temporal dynamics may depend on the hidden state of the system. To further complicate matters, the hidden state sequences underlying the observed data from different individuals may not be aligned relative to a common frame of reference. Against this background, we consider the novel problem of jointly learning the state-dependent inter-variable relationships as well as the pattern of transitions between hidden states from multi-dimensional time series data. To solve this problem, we introduce the State-Regularized Vector Autoregressive Model (SrVARM) which combines a state-regularized recurrent neural network to learn the dynamics of transitions between discrete hidden states with an augmented autoregressive model which models the inter-variable dependencies in each state using a state-dependent directed acyclic graph (DAG). We propose an efficient algorithm for training SrVARM by leveraging a recently introduced reformulation of the combinatorial problem of optimizing the DAG structure with respect to a scoring function into a continuous optimization problem. We report results of extensive experiments with simulated data as well as a real-world benchmark that show that SrVARM outperforms state-of-the-art baselines in recovering the unobserved state transitions and discovering the state-dependent relationships among variables
Blockchain-enabled Charging Scheduling for Unmanned Vehicles in Smart Cities

Recently, mobile crowd sensing (MCS) has been widely used in smart cities with the help of unmanned aerial vehicles (UAVs) and autonomous cars. To ensure long-term, long-distance sensing tasks of UAVs, mobile unmanned charging stations, called “ Carriers ”, are scheduled to reach preset charging locations in a city to provide charging services. However, existing methods not only have difficulty in serving a large number of UAVs, but also face a big challenge of potential security vulnerabilities in the charging transactions. To address the above issues, this paper explores the blockchain technology to design an auction-based framework for scheduling charging services for UAVs while improving the security of charging transactions. In particular, considering the revenues of Carriers and the utilities of UAVs, we develop a new auction mechanism based on the emerging deep reinforcement learning technique to improve the auction performance. Experimental results demonstrate that our method can enhance charging transactions’ security and optimize the system performance.
Teaching Design by Contract using Snap!

With the progress in deductive program verification research, new tools and techniques have become available to support design-by-contract reasoning about non-trivial programs written in widely-used programming languages. However, deductive program verification remains an activity for experts, with ample experience in programming, specification and verification. We would like to change this situation, by developing program verification techniques that are available to a larger audience. In this paper, we present how we developed prototypal program verification support for Snap! Snap! is a visual programming language, aiming in particular at high school students. We added specification language constructs in a similar visual style, designed to make the intended semantics clear from the look and feel of the specification constructs. We provide support both for static and dynamic verification of Snap! programs. Special attention is given to the error messaging, to make this as intuitive as possible.
A SURVEY OF CONSUMER SATISFACTION WITH MOBILE PAYMENT SYSTEM: AN EMPIRICAL STUDY OF A UNIVERSITY IN ZHEJIANG PROVINCE

Based on the extended study of online payment and settlement, we investigated interesting research on the use of online payment by students. This study mainly investigates the use of mobile payment consumers in a university in Haining, Zhejiang Province in 2020. The research object of this time is a university in Haining, Zhejiang Province. Mobile payment is very popular among young people. In this study, a college student was taken as the object of investigation, with 436 samples N, and the effective questionnaires reached 96%. The correlation was investigated through factor analysis. In recent years, mobile payment system has been more and more popular and used by consumers. Mobile payment is mainly applied to online and offline payment such as two-dimensional barcode shopping (purchased from vending machines and supermarkets), payment by public transportation (bus and subway), and game of grabbing red envelopes. In this study, Likert five-point scale was used to conduct factor analysis, and reliability and validity analysis of this action payment on consumer satisfaction was conducted. Convenience, security, credibility and consumer satisfaction brought by mobile payment system are the main research directions of this study. In the process of research design, we designed three hypothesis models, hoping to verify whether the hypothesis has causal correlation through this model.
LOCATION DETERMINATION WITH ASSIGNMENT METHOD IN DESIGN SEAWEED SUPPLY CHAIN

Assignment methods are widely used to determine the suitability of several supply and demand choices if the availability of each option is one. Property owned by the assignment method can also be used to determine the suitability of the location of the placement that has resources with its production capabilities, so that the assignment method can be used to determine the exact location adapted to the capabilities of the location. This study aims to obtain an industrial location in accordance with the capabilities of the industry in an area consisting of four locations, which have the ability to be a location of agriculture (plant), processor (producer), basic materials (distributors), and finished products (main industry). Industry capability is measured by factors that influence the success of the supply chain, namely: procurement cycle, manufacturing cycle, replenishment cycle, customer order cycle. Each location has advantages and disadvantages to carry out industrial activities, in order to obtain information on the advantages of each location, weighting is done using the Analytical Hierarchy Process (AHP). After obtaining the next weight, determining the location is predicted to have a strong preference to be used as an area for the development of the seaweed commodity industry, by obtaining the maximum amount of weight from the four observation locations, using the assignment method. Results of this research showed that in supplier side and the producer side, the quality dimension must be emphasized on the performance. Meanwhile, in the distributor have to focused on performance of excellence in packaging, likewise, in the main industry, the conformance aspect is the main focus where the main industry is able to follow the schedule made by consumer.
MASTERARBEIT / MASTER’S THESIS

When athletes fail to execute automatic or well-learned motor tasks, it is assumed that their focus of attention lies on task irrelevant stimuli and they are considered to choke under pressure. Left-hand contractions have been shown to alleviate choking under pressure in different sports. The present study aimed to replicate these findings and tested whether lefthand contractions (clenching a soft ball) can be used as an intervention method against choking in soccer. The effect of left-hand contractions was investigated in a within-subjects design testing right-handed players from the youth academy of SK Rapid Wien, a professional soccer club in the Austrian Bundesliga. 30 semi-professional soccer players performed penalty shootouts on a goal wall. The study examined whether participants who squeezed their left hand contrasted from a control condition in shot accuracy in a high-pressure phase when compared with a low-pressure phase. The participants’ heart rates and shot accuracy were measured during both phases. Results revealed significantly higher heart rate levels for both groups during the high-pressure phase compared to the low-pressure phase. While lefthand contractions showed an alleviating effect on performance decrease after pressure induction when compared with the control condition, the obtained effects on task performance were not significant. The results only showed a tendency towards the hypothesis that left-hand contractions may prevent motor skill failure and alleviate choking under pressure.
CT-Net: Channel Tensorization Network for Video Classification

3D convolution is powerful for video classification but often computationally expensive, recent studies mainly focus on decomposing it on spatial-temporal and/or channel dimensions. Unfortunately, most approaches fail to achieve a preferable balance between convolutional efficiency and feature-interaction sufficiency. For this reason, we propose a concise and novel Channel Tensorization Network (CT-Net), by treating the channel dimension of input feature as a multiplication of K sub-dimensions. On one hand, it naturally factorizes convolution in a multiple dimension way, leading to a light computation burden. On the other hand, it can effectively enhance feature interaction from different channels, and progressively enlarge the 3D receptive field of such interaction to boost classification accuracy. Furthermore, we equip our CT-Module with a Tensor Excitation (TE) mechanism. It can learn to exploit spatial, temporal and channel attention in a high-dimensional manner, to improve the cooperative power of all the feature dimensions in our CT-Module. Finally, we flexibly adapt ResNet as our CT-Net. Extensive experiments are conducted on several challenging video benchmarks, e.g., Kinetics-400, Something-Something V1 and V2. Our CT-Net outperforms a number of recent SOTA approaches, in terms of accuracy and/or efficiency. The codes and models will be available on https://github.com/Andy1621/CT-Net.
Child safety: a validated GC-MS method to determine formamide in EVA foam mats

Recent studies on EVA products sold in Europe and manufactured in Asia have shown that puzzle mats and other EVA toys contained up to 1266 mg kg−1 of formamide, a substance classified as carcinogenic, mutagenic or toxic for reproduction. Considering this risk, France has restricted formamide in mats to no more than 200 mg kg−1, while the European Commission accepts 5000 mg kg−1. Since there is no information regarding the formamide content in EVA mats from the Brazilian market, this study aimed to first develop and validate a method for formamide determination, then analyze the best-selling EVA foam mats produced and sold in Brazil. Formamide was ultrasound-extracted three times with methanol to ensure maximum extraction. After the addition of acetamide as the internal standard, the samples were analyzed by GC-MS. This method was fully validated and presented a limit of quantification of 0.19 mg kg−1 of formamide in the chromatographed extract, recovery between 88 and 101% and RSD below 3% for concentration levels higher than 1.5 mg kg−1. Five commercial foam EVA puzzle mats made in Brazil were analyzed and presented 32 to 1364 mg kg−1 of formamide. Subsequent tests showed that usually more than 50% of the formamide amount is released and could be inhaled from the mats in the first two weeks after opening the package. Considering the exposure to formamide demonstrated in this work, we recommend that the Brazilian regulation for toy safety includes a limit for formamide content in EVA foam toys.
MOTIVATION FACTORS OF ENGINEERS IN PRIVATE SECTOR CONSTRUCTION INDUSTRY

Human resource in today’s world is recognized as a strategic asset which drives organizations to superior in the industrial competition. With the effective identification of employee attributes, all the determinants of productivity can be obtained. This research assesses engineers’ motivation factors in the construction industry’s private sector and further examined their response to various attributes, including age and gender. A structured and self-administrated systematic qualitative approach was utilized to collect data from 120 engineers. Twenty-six motivational factors were grouped according to Maslow’s need theory, and the paper presents a comprehensive analysis based on the relative importance and response percentages of the identified factors. The most influential need level among them was statically determined as the esteem needs to be followed by basic needs, belonging needs, safety needs, and self-actualization needs. Out of the twenty-six factors, good work discipline is the most influential motivational factor for female engineers, whereas company name and stability have become the most important factor for male engineers. A variation of those factors' relative importance is also determined for various age groups. These results would help senior management to formulate effective policies to improve employee retention in the construction industry.