Miracle-dz/UniFAR-FTUs huggingface dataset:
Parents’ Sport Socialization Values, Perceived Motivational Climate and Adolescents’ Antisocial Behaviors

Parents play a key role in young athletes’ sport experience. In particular, parents’ sport goals for children may influence young athletes’ morally relevant sport behaviors. The present study involves 172 Italian adolescents (female = 51.7%; age M = 15.41, SD = 1.73) practicing team sports and analyzed whether and the extent to which parents’ sport socialization values, those values adolescents perceived their parents wanted them to endorse (i.e., moral, competence, status values), were associated with young athletes’ antisocial behaviors towards teammates and opponents. Adolescents’ perceptions of the prominent motivational climate (i.e., mastery and performance) within their team were also considered. Participants were asked to fill out questionnaires, including the Youth Sport Values Questionnaire-2, adapted to measure adolescents’ perceptions of parental socialization values, the Perceived Motivational Climate in Sport Questionnaire and the Prosocial and Antisocial Behavior in Sport Scale. The results of multiple linear regression analysis and relative weight analysis showed that mastery motivational climate, as protective factor, and mothers’ status values, as risk factor, were the most important variables in predicting adolescents’ antisocial behavior towards teammates. As far as adolescents’ antisocial behavior towards opponents was concerned, performance motivational climate and mothers’ status values were the most relevant predictors: the more adolescents perceived their coaches and mothers as giving importance to performance and status, the higher was the frequency of their antisocial behavior in sport. Implications and further developments of the study are discussed.
Representing Modifiable and Reusable Musical Content on the Web With Constrained Multi-Hierarchical Structures

The most commonly used formats for exchanging musical information today are limited in that they represent music as flat and rigid streams of events or as raw audio signals without any structural information about the content. Such files can only be listened to in a linear way and reused and manipulated in manners determined by a target application such as a Digital Audio Workstation. The publisher has no means to incorporate their intentions or understanding of the content. This article introduces an extension of the music formalism CHARM for the representation of modifiable and reusable musical content on the Web. It discusses how various kinds of multi-hierarchical graph structures together with logical constraints can be useful to model different musical situations. In particular, we focus on presenting solutions on how to interpret, navigate and schedule such structures in order for them to be played back. We evaluate the versatility of the representation in a number of practical examples created with a Web-based implementation based on Semantic Web technologies.
Open Innovation Challenges and Coopetition-Based Open-Innovation Empirical Evidence From Malaysia

Innovation trends are a highly competitive environment, and have been changed and companies are moving towards the open innovation model rather than to follow close or in a traditional innovation model. Therefore, this chapter demonstrated various determinants of open innovation. For this purpose, a survey was carried out among Malaysian small and medium-sized enterprises (SMEs). The outcomes of the survey highlighted that, the success of open innovation model is based on five major elements, namely, 1) motivating spillovers, 2) incorporation of external knowledge, 3) intellectual property management, 4) maximization of internal innovation, and 5) financial constraints. These five elements are the major challenges for companies while adopting open innovation model. More specifically, the phenomenon of coopetition-based open-innovation is emerging rapidly among the companies. Nowadays, by following the open innovation activities, competitors are collaborating with each other rather than to compete.
A fast and accurate approach to the extraction of leaf midribs from point clouds

ABSTRACT Many studies have obtained high-quality plant point clouds but it remains difficult to extract the midrib from a leaf point cloud. In this study, a fast and accurate approach to the extraction of leaf midrib from point clouds was developed. The leaf was converted into its principal component analysis (PCA) coordinates to find the tip and base points of the leaf. A new search algorithm was proposed, which quickly searched for the approximate shortest curve between tip and base points on the leaf point cloud. The curve then was projected and fitted to eliminate the deviation between the curve and the leaf midrib. Two types of point cloud, generated using the structure-from-motion method and using a laser scanner, were obtained to verify our approach. As a result, the extracted curves were both in good agreement with the leaf midrib for the two kinds of point clouds. Compared with manual measurements of the leaf length, the root-mean-square error (RMSE) of the lengths of the two types of the extracted curve were 2.55 mm and 1.38 mm, respectively. The result shows that our method is robust and practical and may assist in the development of plant morphology measurements.
Tools for reconstructing the bilateral trade network: a critical assessment

ABSTRACT This study critically assesses the performances of the Gravity Model (GM) and of the RAS algorithm for the bilateral flow intensity estimations and link prediction. The main novelty is the application of these methodologies to reconstruct the network topology with a minimum amount of information. Moreover, we implement a multi-layer analysis to provide a comprehensive and robust framework, by testing several food commodities, over the period 1986–2013. The main outcomes suggest that the RAS algorithm outperforms the Gravity Model in the estimations of the bilateral trade flows, importantly guaranteeing the balance constraints (i.e. global import equals global export), while GM generates lower relative errors, but it underestimates total global flows. Both RAS and GM can be applied to accurately recover the network architecture. The implications of our study encompass a wide range of applications: systemic-risk assessment, creation of new databases, and scenario analyses to support policy decisions.
Virtual Texture Generated Using Elastomeric Conductive Block Copolymer in a Wireless Multimodal Haptic Glove

Haptic devices are in general more adept at mimicking the bulk properties of materials than they are at mimicking the surface properties. Herein, a haptic glove is described which is capable of producing sensations reminiscent of three types of near‐surface properties: hardness, temperature, and roughness. To accomplish this mixed mode of stimulation, three types of haptic actuators are combined: vibrotactile motors, thermoelectric devices, and electrotactile electrodes made from a stretchable conductive polymer synthesized in the laboratory. This polymer consists of a stretchable polyanion which serves as a scaffold for the polymerization of poly(3,4‐ethylenedioxythiophene). The scaffold is synthesized using controlled radical polymerization to afford material of low dispersity, relatively high conductivity, and low impedance relative to metals. The glove is equipped with flex sensors to make it possible to control a robotic hand and a hand in virtual reality (VR). In psychophysical experiments, human participants are able to discern combinations of electrotactile, vibrotactile, and thermal stimulation in VR. Participants trained to associate these sensations with roughness, hardness, and temperature have an overall accuracy of 98%, whereas untrained participants have an accuracy of 85%. Sensations can similarly be conveyed using a robotic hand equipped with sensors for pressure and temperature.
THE CONSIDERATION OF STUDENTS’ AS WORKERS AND THE ROLE OF UNIVERSITY DEPARTMENT ALONG WITH THE YEAR OF STUDY TOWARDS THE EXAMINATION OF BURNOUT

The role of the university department and students’ year of birth and year of study in relation to burnout syndrome has been examined thoroughly. In this paper it is assumed that students are considered as workers and that the studies are analogously their work. Correspondingly, the years of study are proportional to both the student's age and the characteristics of the workload to. In this regard, a structured questionnaire was answered by 582 students of the University of Patras whose answers were analysed via an exploratory factor analysis. The aim was to deconstruct the phenomenon of students’ burnout in its causal structural elements and to examine the impact of the university department and the year of study on each of these elements. The results showed that the university department affects the students' burnout syndrome via three channels: efficacy and self-accomplishment of studies, lack of interest in university studies and via the difficulty in collaborating with their fellow students and their tutors. Additionally, it appeared that the year of study had a significant effect on students’ burnout syndrome, mainly because of physical and psycho-emotional exhaustion· the greatest effect was found in the penultimate year of study.
A guide to monitoring and evaluation of capacity-building interventions in the health sector in developing countries.

This guide has grown out of the collective experience of health and development organizations working to build health sector capacity in developing countries. The focus of the Guide is the measurement of capacity for the purpose of monitoring and evaluating capacity- building interventions. It responds to a demand among public health planners evaluators and practitioners for advice on assessing the many aspects of health programming that fall under the rubric of capacity building. The purpose of this guide is to assist health planners and evaluators to: gain a clear understanding of the concepts of capacity and capacity building; critically evaluate the strengths and limitations of current approaches to capacity measurement design a capacity-building M&E plan that outlines a systematic approach to measuring capacity and assessing the results of capacity-building interventions in the health sector. (excerpt)
Sky twilight brightness at zenith expressed in magnitudes

ABSTRACT Most of the previously published results of the zenith sky twilight brightness, obtained by different investigators, are given in different units. These results have been converted to (mag/arcsec2) to make a comparison between them. The variation of the colour indices (B-V) and (B-R) of the zenith sky twilight with the sun’s depression will be studied. The present photometric results of the zenith sky twilight brightness expressed in mag/arcsec2, have been obtained for the first time for blue, yellow and red colours.
Applying Nanoparticles in the Treatment of Viral Infections and Toxicological Considerations

Background: Despite the tremendous progress in human medicine, viral infections can cause death in them. Due to the high prevalence of viruses, it is required to develop novel treatment strategies and provide the site-specific delivery of antiviral agents at the viral reservoirs. Objectives: Particle size is a vital physical characteristic that can affect the bioavailability and circulation time of nanoparticles. The ratio of large surface area and volume of nanoparticle could enhance the solubility of poorly soluble drug compounds. Methods: Therefore, the optimum surface charge of the nanoparticle with the possibility of encapsulation and large drug cargo, are some of the nanoformulation advantages of these agents. Results: This study reviewed various nanocarriers and modern smart delivery technologies, such as liposomes and immunoliposomes, polymeric nanoparticles, nanoemulsions, nanosuspensions, dendrimers, solid lipid nanoparticles, and so on. Conclusion: We aimed to overcome the problems of traditional formulations and resistance to currently available therapies in various infections. Moreover, the concerns about the potential toxicities of nanoparticles to humans have been raised; therefore, the present study has reviewed the toxicity effects of nanoparticles used in controlling viral infections.
Application of a neural network model to forecasting of El Niño and La Niña

In this paper, a possibility to forecast El Niño and La Niña by using an artificial intelligence model based on neural networks is studied. The quality of such a long-term climate forecast is assessed too. A set of global climatic indices of atmosphere-ocean system oscillations in 1950-2019 is used as input parameters of the model. The Nino3.4 index is calculated by using monthly average 500mb geopotential height and sea surface temperature fields from NCEP/NCAR reanalysis data sets. A verification of the model is carried out by using a control sample of 1950–1957. Additionally, the same indices of 1872-1947 are calculated by using 20th Century Reanalysis (20CR) data sets to test the model. A possibility to predict the Nino3.4 index for 2 to 7 months is shown. However, in spite of a high-level reconstruction of the index dynamics, increasing the time of forecasting is accompanied by decreasing its quality. With 20CR data it is shown that the model is able to successfully predict the beginning of 75% of El Niño and La Niña for 3 months, 66% of the events for 5 months, and only 52% for 7 months in advance.
Blockchain-Driven Secure and Transparent Audit Logs

In enterprise business applications, large volumes of data are generated daily, encoding business logic and transactions. Those applications are governed by various compliance requirements, making it essential to provide audit logs to store, track, and attribute data changes. In traditional audit log systems, logs are collected and stored in a centralized medium, making them prone to various forms of attacks and manipulations, including physical access and remote vulnerability exploitation attacks, and eventually allowing for unauthorized data modification, threatening the guarantees of audit logs. Moreover, such systems, and given their centralized nature, are characterized by a single point of failure. To harden the security of audit logs in enterprise business applications, in this work we explore the design space of blockchain-driven secure and transparent audit logs. We highlight the possibility of ensuring stronger security and functional properties by a generic blockchain system for audit logs, realize this generic design through BlockAudit, which addresses both security and functional requirements, optimize BlockAudit through multi-layered design in BlockTrail, and explore the design space further by assessing the functional and security properties the consensus algorithms through comprehensive evaluations. The first component of this work is BlockAudit, a design blueprint that enumerates structural, functional, and security requirements for blockchain-based audit logs. BlockAudit uses a consensusdriven approach to replicate audit logs across multiple application peers to prevent the singlepoint-of-failure. BlockAudit also uses the Practical Byzantine Fault Tolerance (PBFT) protocol to achieve consensus over the state of the audit log data. We evaluate the performance of BlockAudit using event-driven simulations, abstracted from IBM Hyperledger. Through the performance evaluation of BlockAudit, we pinpoint a need for high scalability and high throughput. We achieve those requirements by exploring various design optimizations to
Deep Learning-Based DDoS-Attack Detection for Cyber–Physical System Over 5G Network

With the advent of 5G, cyber–physical systems (CPSs) employed in the vertical industries and critical infrastructures will depend on the cellular network more than ever; making their attack surface wider. Hence, guarding the network against cyberattacks is critical not only for its primary subscribers but to prevent it from being exploited as a proxy to attack CPSs. In this article, we propose a consolidated framework, by utilizing deep convolutional neural networks (CNNs) and real network data, to provide early detection for distributed denial-of-service (DDoS) attacks orchestrated by a botnet that controls malicious devices. These puppet devices individually perform silent call, signaling, SMS spamming, or a blend of these attacks targeting call, Internet, SMS, or a blend of these services, respectively, to cause a collective DDoS attack in a cell that can disrupt CPSs’ operations. Our results demonstrate that our framework can achieve higher than $91\%$ normal and underattack cell detection accuracy.
Value Sensitive Analysis of the Persuasion Context: Case Micro-entrepreneurs' Health Promotion

Even though the definition of persuasive systems rules out using coercion or deception, in practice it is a challenge to design ethically sound information systems, especially when the use context deals with personal matters such as one’s health or lifestyle. The objective of our study was to investigate how to conduct such design through a value sensitive analysis of the persuasion context, in this case for micro-entrepreneurs. The analysis revealed special characters of the persuasion context that are critically important to address early in the development of the application. This study applies a useful method for designers to use in their analysis of the ethical considerations in their persuasive system design efforts.
Investigation of thermal properties of spacer fabrics with phase changing material by finite element model and experiment

This study presents the developed computational finite element models for transient heat transfer analysis in fabrics enriched by phase change materials along with efforts to provide validation on the basis of obtained experimental results. The environment-friendly butyl stearate is used as a phase change material. Its melting/heating absorption takes place in temperature range from 19℃ to 34℃, and the solidification/heat release occurs from 34℃ to 19℃. An important aspect in this analysis is the investigation of appropriateness of the material samples dimensions selected for effective heat capacity against temperature measurements. For this purpose, we used the combined experimental and finite element simulation-based analysis. A similar computational procedure enabled us to estimate the effective latent specific heat relationship of the fabric with phase change materials coating. The direct usage of differential scanning calorimetry (DSC) measurement-based specific heat relationships against temperature in the finite element models ensured good compliance of the computed results with the experiment. For validation of the developed computational models the infrared radiation heating-cooling experiments on fabrics with different deposits of a phase change material were performed. The noticeable influence of content of phase change materials for transient thermal behavior during heating-cooling cycles was determined. The experimental results have been compared against the finite element simulation results.
Education and training of the teacher librarians in Sri Lanka

This study was designed to find out the current status of Sri Lankan teacher librarians' training and education. A random sample of 108 respondents comprising teacher librarians, principals, and education officers was selected for this survey. Questionnaires were sent to these schools by mail. A total of 63 (68.04%) questionnaires were returned on due date. The data obtained was examined to assess the teacher librarians' training programmes and drawbacks of these programmes. Based on the findings, most of the respondents indicated that they were not satisfied with available training programmes. It was found that most of the teacher librarians are limited to very few library activities and focused to classroom teaching. They are not well trained in the library works. They do not have enough training facilities such as school library activities, computer based activities, Internet and web based activities, and use of technological equipments. Most of the drawbacks were identified by the survey. The requirements of the training of teacher librarians are also revealed by the study. The main problem faced by the teacher librarians is lack of training opportunities in Island wide. This resulted in limited knowledge of the profession. Therefore they are limited to perform only a few activities at their school libraries. It was also noted that most of the teacher librarians in Sri Lanka are not trained in library science. Although most of them are interested in doing school library work, they do not get the necessary training. The school libraries in Sri Lankan schools need much improvement to keep pace with the current development taking shape in information technology. Based on the findings, recommendations are proposed to design the training programmes for the teacher librarians in Sri Lanka.
Diagnostik der Fettleber

Zusammenfassung Die verschiedenen Ausprägungen der Fettleber gehören in den Industrienationen zu den häufigsten Ursachen für chronische Lebererkrankungen. Da eine Leberverfettung prinzipiell reversibel ist, kann eine frühe Diagnose die Voraussetzung dafür schaffen, dass therapeutische Maßnahmen rechtzeitig eingeleitet werden. Die vorliegende Arbeit beschreibt die wesentlichen diagnostischen Methoden und die jeweiligen Vor- und Nachteile der einzelnen Verfahren. Abstract Fatty liver disease is defined as an abnormal accumulation of lipids into the cytoplasm of hepatocytes. Different kinds of fatty liver diseases are becoming the most important etiologies of end-stage liver disease in the western world. Because fatty liver is a theoretically reversible process, timely and accurate diagnosis is a prerequisite for potential therapeutic options. This work describes major diagnostic methods and discusses particular advantages and disadvantages of various techniques.