This study examines student engagement in an online environment concerning the perception regarding the course and the technology used. A research model was developed from the principal tenets of the expectancy-value theory to which values and expectations are assumed to influence how students build engagement. The model conjoins student perception related to course factors (content and rigor), technology factor (technology convenience), and student engagement (psychological, cognitive, emotional, and behavioral). The model was tested using a sample composed of 328 business undergraduate students taking the courses online using the BigBlueButton e-learning system due to the global emergency caused by the COVID-19 pandemic. Hence, respondents did not voluntarily choose the online teaching delivery method. The results imply that both course content and perceived technology convenience predict overall student engagement, while course rigor influences student cognitive, emotional, and behavioral commitment, but not psychological engagement.

High penetration of renewable energy sources brings both opportunities and challenges for Smart Grid operation. Due to their high contribution to energy consumption, aggregated load flexibility of small residential and service sector consumers has a potential to address the intermittency challenge of distributed generation. Predicting aggregated load flexibility of this consumer sector involves access to sensitive smart meter data, raising data collection and sharing concerns. Federated Learning, a decentralized machine learning technique that uses data distributed on user devices to construct an aggregated, global model, offers potential solutions to tackling this challenge. This paper explores the potential of using Federated Learning for flexibility prediction in Smart Grids through an analysis of its opportunities and implications for different stakeholders involved, as well as the challenges faced. The analysis shows that Federated Learning is a promising approach for building privacy-preserving energy portfolios of aggregated demand data.

This study aimed to examine the relation between agility, sprint ability, and vertical jump performance of young basketball players. Fifty (n=50) young basketball players (mean±SD: age = 12.63±0.95; height = 160.84±6.31 cm; body mass = 50.82±6.88 kg) participated in the study. The agility T-test and 505 test were assessed to determine agility, 10m and 20m sprint was measured to determine sprint ability and countermovement jump (CMJ) for jumping performance. The results of Pearson’s Product Moment Correlation analysis indicated large to very large relation between agility tests and sprint performance (r = 0.61 to 0.85); agility and jump performance (r = - 0.64 to - 0.67); sprint and jumping performance (r = -0.59 to -0.77). The results of the study suggest that agility, sprint, and jumping performance share common physical demands, therefore it is necessary to develop them during the training.

Considering the growing global problem and the lack of obesity data in Bosnia and Herzegovina (BH) the main aim of this paper was to determine BH school-age children body composition and determine the differences in body composition between girls and boys classified in underweight, normal weight and overweight according to the body mass index (BMI) score. 2524 participants 1763 girls and 761 boys (aged 10-13 yrs.) from 32 elementary schools were randomly selected and divided to 3 BMI groups by WHO cut-off points. InBody 370 Body Composition Analyzer (BioSpace, Seoul, Korea), a segmental bioelectrical impedance analysis (BIA) device was used to gather data. The results showed ~38% of the sample were classified as overweight whilst gender differences showed higher body fat mass and fat percentages in arms, trunk and legs in underweight and normal weight girls and higher skeletal muscle mass in normal weight and overweight boys.

Nowadays, companies face numerous challenges to operate successfully and remain competitive in the market. Globalization is increasing competition in the market, allowing many companies to operate in foreign markets. Increasing competition has made companies constantly trying to increase their productivity while reducing costs. To meet all the requirements, and at the same time function in the best possible way, companies must be organized adequately, taking into account the whole set of processes from the company's internal organization to the company's appearance on the market. It means, if the end-user is to be satisfied, the company must implement quality in all phases of business, ie business ethics and company culture, through the quality of technology, personnel, etc. In other words, it must be satisfied the system quality of the company, known in the literature as QMS (Quality Management System). The main purpose of this paper is to review the multiple understanding of the concept of QMS and its different underpinning theories in a business to customer context. The design of this research is based on mere documentary analysis and some observations.

Abstract Ten species of the louse genus Myrsidea belonging to the “serini-species-group” have been reviewed. A redescription of Myrsidea quadrifasciata (Piaget, 1880), the earliest described and valid species of this species complex, is given and a neotype for this species is designated. Nine new junior synonymies of M. quadrifasciata are proposed and discussed. The new synonyms and their respective type hosts are: Myrsidea anoxanthi Price and Dalgleish, 2007 from Loxipasser anoxanthus (Gosse, 1847), Myrsidea argentina (Kellogg, 1906) from Spinus magellanicus (Vieillot, 1805), Myrsidea balati Macháček, 1977 from Passer montanus (Linnaeus, 1758), Myrsidea darwini Palma and Price, 2010 from Geospiza fuliginosa Gould, 1837, Myrsidea major (Piaget, 1880) from Plectrophenax nivalis (Linnaeus, 1758), Myrsidea serini (Séguy, 1944) from Serinus serinus (Linnaeus, 1766), Myrsidea queleae Tendeiro, 1964 from Quelea quelea lathami (Smith, A., 1836), Myrsidea textoris Klockenhoff, 1984 from Ploceus cucullatus cucullatus (Müller, 1776), and Myrsidea viduae Tendeiro, 1993 from Vidua macroura (Pallas, 1764). Intraspecific morphometric variability, relative genetic divergence (based on a 379 bp portion of the mitochondrial COI gene and a 347 bp portion of the nuclear EF-1α gene), geographical distribution, and host associations, including 8 new host records for these lice, are discussed. Taking into consideration these parameters we suggest that the only way to deal with these taxa is to follow concept of subspecies with the following taxa and their geographic distributon: Palearctic Region: M. q. quadrifasciata and M. q. serini, Neotropical Region: M. q. anoxanthi, M. q. argentina, M. q. darwini, Paleotropic Region: M. q. queleae, M. q. textoris and M. q. viduae.

The extent to which societies will globally be able to adapt to climate change is not well understood. Here we analyze socioeconomic dimensions of adaptive capacity of populations to deal with heat stress and find income, urbanization and income inequality to be important factors in explaining adaptation to heat stress with air conditioning (AC). Using the scenario framework of the Shared Socioeconomic Pathways (SSPs), we estimate the future cooling gap, which represents the difference between the population exposed to heat stress and the population able to protect against heat stress with AC. Depending on the scenario of socioeconomic development, total population affected by the cooling gap may vary between 2 billion and 5 billion people in 2050, with the scenario-dependent range widening further towards the end of the century. Our analysis shows vast regional inequalities in adaptive capacity for one of the most universal manifestations of climate change, underscoring the need to account for the different potential levels of adaptive capacity in assessments of climate change impacts.

Industry 4.0 is being enabled by a number of new wireless technologies that emerged in the last decade, aiming to ultimately alleviate the need for wires in industrial use cases. However, wireless solutions are still neither as reliable nor as fast as their wired counterparts. Closed loop communication, a representative industrial communication scenario, requires high reliability (over 99%) and hard real-time operation, having very little tolerance for delays. Additionally, connectivity must be provided over an entire industrial side extending across hundreds of meters. IEEE 802.11ah fits this puzzle in terms of data rates and range, but it does not guarantee deterministic communication by default. Its Restricted Access Window (RAW), a new configurable medium access feature, enables flexible scheduling in dense, large-scale networks. However, the standard does not define how to configure RAW. The existing RAW configuration strategies assume uplink traffic only and are dedicated exclusively to sensors nodes. In this article, we present an integer nonlinear programming problem formulation for optimizing RAW configuration in terms of latency in closed loop communication between sensors and actuators, taking into account both uplink and downlink traffic. The model results in less than 1% of missed deadlines without any prior knowledge of the network parameters in heterogeneous time-changing networks.

The purpose of this paper is to examine the relationship between ?soft? support infrastructure (SSI) and the performance of small and medium enterprises (SMEs). The study encompasses European countries? economic activity and SMEs? output in 2015 and 2018. The focus of the research is SMEs in the European Union member states and the Western Balkan countries. The analysis was conducted using partial least squares structural equation modelling (PLS-SEM). This method enabled the examination of links between variables that are not directly observable. The results show that countries investing in SSI have better SME performance. Based on the statistical analysis, among other things, the authors identify the Human Development Index and the use of information and communication technology at the company level as the two most significant factors that impact on SMEs? performance.