Miracle-dz/UniFAR-FTUs huggingface dataset:
An Evaluation Study of Nurse Educators’ Learning Experience in a Digital Modular Course

The Covid-19 pandemic poses a new challenge in the adoption of ICT in education. The need for educational institutions to develop standards and implement quality assurance in digital education has suddenly gained new significance. The aim of this study is to evaluate the learning experiences of nurse educators in Slovenia acquired during a nine-week modular online course on the design, delivery and evaluation of online study units, based on a quality standard for digital education developed for this purpose. A mixed methods approach was used. The evaluation of the nurse educators’ learning experiences was examined quantitatively (cross-sectional study) and qualitatively (focus group). The Cronbach’s alpha for the entire questionnaire was 0.921, indicating that the internal consistency of the questionnaire developed for evaluation was excellent. The thematic analysis identified three main themes. At the end of the course, the nursing teachers expressed their desire for additional courses in which they could gain and deepen their knowledge of the preparation, implementation, and evaluation of the educational unit with the help of digital technology.
Association between Environmental Tobacco Smoke Exposure and Adaptive Behavior in Individuals with Autism Spectrum Disorder

The study focuses on current issues of adaptive behavior in individuals with autism spectrum disorder (ASD) and on the possible risk factor of environmental tobacco smoke (ETS). Children examined at the Academic Research Center for Autism (ARCA) in Bratislava were involved in the study. The study sample included 84 children (71 boys) with ASD (average age 5.35 years) and a non-ASD group of 24 children (20 boys; average age 8.10 years). The “ETS Questionnaire” focused on the detection of parental smoking habits and other ETS exposures. The concentrations of cotinine in urine were measured by ELISA kit. A significant delay in adaptive behavior of children with ASD in comparison with the non-ASD group was identified. The significant differences were in adaptive behavior, communication, and everyday skills. Children with ASD were more likely to be exposed to ETS, especially in the household. Good agreement was found between objective and subjective ETS exposure indicators (kappa = 0.613). Self-reported exposure to ETS corresponded significantly with the median levels of urinary cotinine. In addition to evaluation and assessment of the quality of adaptive behavior, an important goal of further research should be to identify, investigate, and eliminate environmental factors that interfere with adaptive behavior.
The Gunpowder Age: China, Military Innovation, and the Rise of the West in World History

Introduction - The Military Pattern of the Chinese Past 1 PART I: CHINESE BEGINNINGS Chapter 1 The Crucible: The Song Warring States Period 15 Chapter 2 Early Gunpowder Warfare 29 Chapter 3 The Mongol Wars and the Evolution of the Gun 44 Chapter 4 Great Martiality: The Gunpowder Emperor 55 PART II: EUROPE GETS THE GUN Chapter 5 The Medieval Gun 75 Chapter 6 Big Guns: Why Western Europe and Not China Developed Gunpowder Artillery 88 Chapter 7 The Development of the Classic Gun in Europe 103 Chapter 8 The Gunpowder Age in Europe 115 Chapter 9 Cannibals with Cannons: The Sino-Portuguese Clashes of 1521-1522 124 PART III: AN AGE OF PARITY Chapter 10 The Frankish Cannon 135 Chapter 11 Drill, Discipline, and the Rise of the West 144 Chapter 12 The Musket in East Asia 166 Chapter 13 The Seventeenth Century: An Age of Parity? 188 Chapter 14 A European Naval Advantage 196 Chapter 15 The Renaissance Fortress: An Agent of European Expansion? 211 PART IV: THE GREAT MILITARY DIVERGENCE Chapter 16 The Opium War and the Great Divergence 237 Chapter 17 A Modernizing Moment: Opium War Reforms 257 Chapter 18 China's Modernization and the End of the Gunpowder Age 273 Conclusions - A New Warring States Period? 297 Acknowledgments 307 Appendix 1: Timeline 311 Appendix 2: Datasets 312 Abbreviations 317 Notes 319 Bibliography 379 Index 421
The Moderating Effect of Environmental Management Accounting Practices on the Relationship Between Green Supply Chain Management Practices and Corporate Performance of Egyptian Manufacturing Firms

: As an important management strategy for effective environmental improvement activities and performance, Green Supply Chain Management (GSCM) techniques and Environmental Management Accounting Practices (EMAP) are gaining prominence. Despite this, many organizations are unaware of their importance in achieving ecologically sustainable growth. The goal of this study is to create a structural framework to empirically test the relationship between GSCM practices and EMAPs, which may have an impact on economic, environmental, and operational performance, and to better understand the key sustainability drivers when making decisions related to the protection of the environmental and saving costs. Data collected using a questionnaire survey of 33 Egyptian manufacturing companies listed on the Egyptian Stock Exchange were analyzed using multivariate regression analysis. Respondents provide information on how well their companies collaborate with suppliers and consumers to enhance the supply chain's environmental sustainability, the extent to which several EMAPs are applied, and how the application of GSCM techniques and EMAPs would affect their economic, environmental, and operational performance. A complete performance model for GSCM activities and EMAPs is presented and rigorously tested. The empirical results showed that industrial firms that use GSCM techniques and EMAPs individually enhance their environmental, operational, and economic performance. However, the study failed to prove that EMAPs moderate the impact of GSCM practices on economic, environmental, and operational performance.
First experimental evidence of oxygen ordering in dilute titanium–oxygen alloys

Small addition of oxygen is currently used to improve the mechanical properties of titanium. It has been thought, until now, that oxygen fully dissolves in the titanium matrix, thus leading to a solid solution. However, we show here, with transmission electronic microscopy and X-ray diffraction, that oxygen can also form ordered precipitates with a Ti6O-type structure, even for a concentration as low as 0.15 wt% O. The ordered precipitates found in a series of pure binary Ti–O alloys are also visible in commercially pure titanium, including grades 2 and 4, two compositions widely used for technological applications. GRAPHICAL ABSTRACT IMPACT STATEMENT Oxygen-ordered precipitates are experimentally evidenced in a series of Ti–O alloys and in CP titanium. These findings question the paradigm defining oxygen only as a solute atom in titanium alloys.
Automated evaluation of Tuberculosis using Deep Neural Networks

INTRODUCTION: Tuberculosis (TB) is a chronic, progressive infection that often has a latent period after the initial infection period. Early awareness from those period to have better prevention steps becomes an indispensable part for patients who want to lengthen their lives. Hence, applying cutting-edge technologies to support the medical business domain plays a key role in improving speed and accuracy in methods of diagnosis. Deep Neural Network-based technique (DNN) is one of such methods which offers positive results by leveraging the advantages of analyzing deeply the data, especially image data format via tons of deep layers of the neural networks. Our study was wrapped up by objectively assessing the performance of modern Deep Neural Network approaches and suggesting a model offering good results in terms of the selected metrics as defined later. In order to achieve optimized results, the chosen model must adapt well to the datasets but require less hardware and computational resources.OBJECTIVES: Our objective is to pick up and train a Deep Neural Network architecture which is highly trusted and flexibly fitted and applied to various datasets with minimum configurations. This will be used to produce good predictions based on the input data which are Chest X-ray images retrieved from the published datasets.METHODS: We have been approaching this problem by using the recognized datasets which have already been published before, then resizing them to the consistent input data for training purposes. In terms of Deep Neural Networks, we picked up VGG16 as the baseline network architecture, then use other ones which are state-of-the-art networks for comparison purposes. After all, we recommend the neural network architecture offering the most positive results based on accuracy and recall measurements. So that, this network architecture will show flexibility when fitting into diverse datasets representing different areas in the world that suffered from Tuberculosis before.RESULTS: After conducting the experiments, we observed that the Mobilenet model produced great results based on the predefined metrics for most of the proposed datasets. It shows the versatility which is applicable to all CXR datasets, especially for the Tuberculosis ones.CONCLUSION: Tuberculosis is still one of the most dangerous illnesses in the world that needs vital methods to prevent and detect soon so that patients are able to keep their lives longer. After this research, we are constantly improving the current accuracy of the models and applying the current results of this research for later problems such as detecting the Tuberculosis areas in real-time and supporting doctors to make decisions based on the current status of patients.
Experimental Investigation of the Photovoltaic Performance Using Porous Media based Cooling System

Cooling photovoltaic panels (PV) is considered one of the most important ways to enhance its performance. Photons with wavelength above the threshold are converted into heat in the PV cells. The ambient temperature acts a key base in the photovoltaic conversion process, where the output power decreases with increasing the temperature than the ambient temperature. In this study, experiment is conducted to study the cooling effect of using a porous material on the electrical performance. The temperature of the front surface of the PV panel is measured at the twenty-eight points without cooling and with cooling. It is found that the temperature decreases when compared to PV panel without cooling. The maximum decrease in the temperature is 9.8%. In addition, the electric current of the PV increases with cooling. The maximum increase of the measured electric current is 16.4 % at a specific voltage, 19.6V. Furthermore, the maximum gain of the output power is about 15 %.
Verification of the Relationship between Redox Regulation of Thioredoxin Target Proteins and Their Proximity to Thylakoid Membranes

Thioredoxin (Trx) is a key protein of the redox regulation system in chloroplasts, where it modulates various enzyme activities. Upon light irradiation, Trx reduces the disulfide bonds of Trx target proteins (thereby turning on their activities) using reducing equivalents obtained from the photosynthetic electron transport chain. This reduction process involves a differential response, i.e., some Trx target proteins in the stroma respond slowly to the change in redox condition caused by light/dark changes, while the ATP synthase γ subunit (CF1-γ) located on the surface of thylakoid membrane responds with high sensitivity. The factors that determine this difference in redox kinetics are not yet known, although here, we hypothesize that it is due to each protein’s localization in the chloroplast, i.e., the reducing equivalents generated under light conditions can be transferred more efficiently to the proteins on thylakoid membrane than to stromal proteins. To explore this possibility, we anchored SBPase, one of the stromal Trx target proteins, to the thylakoid membrane in Arabidopsis thaliana. Analyses of the redox behaviors of the anchored and unanchored proteins showed no significant difference in their reduction kinetics, implying that protein sensitivity to redox regulation is determined by other factors.
Improved C5D Electronic Realization of Conductivity Detector for Capillary Electrophoresis

The axial C4D (Capacitively Coupled Contactless Conductivity Detection) measurement electronics for capillary electrophoresis is considered and a new improved C5D compensated detection concept is proposed and tested. Using the idle compensation channel with inversed signal and immediate analogue summation of the active and idle channel currents yields effective suppression of the influence of the parasitic stray capacitance. Preliminary experiments have confirmed at least three-fold improvements of measurement resolution. Realisation of electronics allows flexible tuning of frequency from 0.2 MHz to 2 MHz. The relatively high voltage supply of 15 V for the AC measurement units together with 24-bit accurate analogue-to-digital converter yields additional improvement for the sensitivity. DOI: http://dx.doi. org/10.5755/j01.eie. 22.3. 15311
Effectiveness of English Online Learning Based on Deep Learning

With the popularization of the Internet lifestyle and the innovation of learning methods, more and more online learning systems have emerged, allowing users to study in the system anytime and anywhere. While providing convenience to users, online learning systems also bring troubles to users, who cannot quickly find the resources they are interested in from the huge amount of learning resources. In this paper, we apply deep learning to an English online learning platform and analyze learners and learning contents by clustering algorithm and association rules. Based on this, a content organization system is developed using genetic algorithms, which is applied to the case of this paper to provide learners with personalized learning content. With the hope that the system can be extended to other online learning platforms in the future, three data mining techniques were selected to solve the problems found in the English online learning platform, and we designed how these techniques should be applied to the online learning platform. The first technique is the cluster mining technique, which is used to analyze learners' profiles, classify learners in different categories, provide them with personalized learning content, and organize group learning. The second technique is association rules, which is used to analyze the correlation between learning contents. For the adaptive student-teacher knowledge migration strategy, the teacher model can guide the student model to track online and migrate the task-specific knowledge to the online tracking student model through the network parameters. Finally, a case study is selected and the above design is applied to this case study, and the results are analyzed in detail. The data mining technology is applied to the English online learning platform, and an innovative English learning content organization system is developed. It is hoped that the results of this study will have some practical value for promotion and provide an idea for the construction of the online learning platform, and it is also expected that the idea can improve the quality of online learning to a certain extent. Specifically, the online student model is adaptively updated by the teacher model parameters and the online student model parameters together.
Cyber victimization and cyber aggression among high school students: Emotion regulation as a moderator

Adolescents of Bangladesh today are facing significantly higher rates of stressors with differing severity and frequency of anxiety, depression, internalizing, and externalizing problems to mention a few (cited in Mullick et al., 2019). Many of them use cyberspace where their limited capacity for emotion regulation may put them at the risk of cyber aggression as well as cyber victimization. However, the true dynamics of the relationship between cyber aggression, cyber victimization, and emotion regulation are largely unknown. The present study is therefore undertaken to address the issue by testing the effect of two components of emotion regulation on the relationship between cyber victimization and cyber aggression. A questionnaire package including Bangla translated versions of Cyber-Victimization Questionnaire for Adolescents (CYVIC), Emotion Regulation Questionnaire (ERQ), Cyber-Aggression Questionnaire for Adolescents (CYBA), and Personal Information Form (PIF) was administered to a purposive-convenience sample of 250 high school students (48% boys and 52% girls). The students were between the ages of 11 through 17 years with a mean age of 14.77 years (SD = 1.41). Independent sample t-tests revealed significant gender differences in all major variables; hence subsequent analyses were conducted on subsamples of boys and girls. Pearson product-moment correlation showed a significant association between key variables where the association of expressive suppression with cyber victimization and cyber aggression was negative for girls and positive for boys. Hierarchical regression analyses manifested buffering effect of both cognitive reappraisal and expressive suppression weakening the relationship between cyber victimization and cyber aggression for girls. A similar pattern was observed for boys where cognitive reappraisal only weakened the relationship between cyber victimization and cyber aggression but not for expressive suppression in boys. The findings have been interpreted in the light of past studies.
A Novel Encoder-Decoder Model for Multivariate Time Series Forecasting

The time series is a kind of complex structure data, which contains some special characteristics such as high dimension, dynamic, and high noise. Moreover, multivariate time series (MTS) has become a crucial study in data mining. The MTS utilizes the historical data to forecast its variation trend and has turned into one of the hotspots. In the era of rapid information development and big data, accurate prediction of MTS has attracted much attention. In this paper, a novel deep learning architecture based on the encoder-decoder framework is proposed for MTS forecasting. In this architecture, firstly, the gated recurrent unit (GRU) is taken as the main unit structure of both the procedures in encoding and decoding to extract the useful successive feature information. Then, different from the existing models, the attention mechanism (AM) is introduced to exploit the importance of different historical data for reconstruction at the decoding stage. Meanwhile, feature reuse is realized by skip connections based on the residual network for alleviating the influence of previous features on data reconstruction. Finally, in order to enhance the performance and the discriminative ability of the new MTS, the convolutional structure and fully connected module are established. Furthermore, to better validate the effectiveness of MTS forecasting, extensive experiments are executed on two different types of MTS such as stock data and shared bicycle data, respectively. The experimental results adequately demonstrate the effectiveness and the feasibility of the proposed method.
The Feasibility and Acceptability of Neurologic Music Therapy in Subacute Neurorehabilitation and Effects on Patient Mood

Music interventions support functional outcomes, improve mood, and reduce symptoms of depression in neurorehabilitation. Neurologic music therapy (NMT) has been reported as feasible and helpful in stroke rehabilitation but is not commonly part of multidisciplinary services in acute or subacute settings. This study assessed the feasibility and acceptability of delivering NMT one-day-per-week in a subacute neurorehabilitation centre over 15 months. Data were collected on the number of referrals, who referred, sessions offered, attended, and declined, and reasons why. Staff, patients, and their relatives completed questionnaires rating the interventions. Patients completed the Visual Analog Mood Scales (VAMS) pre and post a single session. Forty-nine patients received 318 NMT sessions (83% of sessions offered). NMT was rated as helpful or very helpful as part of the multidisciplinary team (n = 36). The highest ratings were for concentration, arm and hand rehabilitation, and motivation and mood. VAMS scores (n = 24) showed a reduction in ‘confused’ (−8.6, p = 0.035, effect size 0.49) and an increase in ‘happy’ (6.5, p = 0.021, effect size = 0.12) post NMT. The data suggest that a one-day-per-week NMT post in subacute neurorehabilitation was feasible, acceptable, and helpful, supporting patient engagement in rehabilitation exercises, mood, and motivation.
Prêt-à-Loger : Zero-energy home with maximum living quality increase

At the Solar Decathlon Europe 2014 (SDE2014) competition (Versailles, France), the team from the Delft University of Technology (TU Delft) took a stance by not constructing a new-built house but demonstrating the energy renovation of a typical Dutch terraced house. Around a quarter of Dutch housing consists of terraced houses built between 1946 and 1975, which have a poor energy performance, endure moist and mould problems and to modern-day standards offer too little living space. Nonetheless, inhabitants cherish these homes; almost everyone in the Netherlands once spent a part of their life in them. The TU Delft team chose a real house as the reference for their retrofit design, the home to one of the students’ grandfather and father, currently vacant. All actual features, unfavourable as they are, were taken as the basis: few existing houses are optimally designed for energy neutrality. The team worked on a gentle plan that enables inhabitant to stay in the house during intervention. Hence the name Pret-a-Loger, ready to live in. Basis of the Pret-a-Loger concept is a new skin around the house: thermal insulation in the facade and roof, a greenhouse structure to the south-east, and phase change materials in the crawlspace. The smart and bioclimatic design ensures the use of local circumstances, optimised by an intelligent application of modern technology. The eye-catching feature, the greenhouse, integrates several elements of the house’s climate design. Its greatest importance however lies in the added value to the dwellers: in spring and autumn it can be used as living space, in winter it is a winter garden buffer, and in summer it can be fully opened, becoming the terrace to the garden. The garden was redesigned with the help of NL Greenlabel, a foundation that promotes sustainable gardening. At SDE2014 Pret-a-Loger was awarded five prizes, among which the Sustainability award, based on the holistic perspective on people, planet and prosperity in the everyday life of common people. This is also reflected by the many public visits to the project. The house was rebuilt on the TU Delft campus, serving demonstration, educational and research purposes.