Introduction: The paper aims to research how the Covid-19 infection affects BPH patients, whether their PSA, prostate volume, residual urine, and quality of life have changed. Additionally, to examine whether any of these variables are a predictive factor for acute urinary retention (AUR). Methodology: The study comprised 80 patients with clinical manifestations of LUTS, an aggravation of previously diagnosed BPH, and who recovered from COVID-19. IPSS, QoL, PSA, prostate volume, and postmicturition residual urine were studied before and after COVID-19. Results: The IPSS score, PSA, prostate volume, and residual urine were signicantly higher after recovering from COVID-19. Additionally, greater IPSS-QoL scores were discovered. Nine patients (mostly older than 60) suffered acute retention during or after the COVID-19 infection. Residual urine was found to be a signicant predictor of AUR. Conclusion: COVID-19 infection is caused by aggravating LUTS symptoms associated with BPH. Consequently, the increase postmicturition residual urine can be considered a predictive factor for the occurrence of AUR

Workplace stress or professional stress is a specific type of stress that is highly prevalent among police officers. Police officers are exposed to high levels of stress and its negative impact ontheir physical and mental health, as well as their social lives. The aim of this research is to determine the attitudes regarding the connection between physical fitness and stress prevention among police officers. The sample consists of 516 employees from police departments in the Central Bosnia Canton. The sample is structured with 312 male participants and 204 female participants. Both descriptive and analytical methods were applied in this research, as the descriptive method was used to describe the distribution of the studied phenomenon, while the analytical part followed the logic of the research. Analyzing all the results, it can be concluded that there is a high level of satisfaction with the management of work processes among police officers and with stress reduction in the workplace. The conclusion arises about the necessity of increasing the number of hours of police training, primarily for basic and investigative police work, in stress prevention among police officers. The results of comparative analysis indicate that there is no statistically significant difference among participants based on gender. The results show that the age of the participants significantly influences their attitudes towards overall satisfaction with management quality. Theresults suggest that participants who have been employed the longest and make the most use of the existing infrastructure express more positive attitudes.Key words:police, stress, physical fitness, burnout, prevention.

Modern business systems have the expectations and requirements of users and stakeholders for safer and better services that are constantly growing. The increasing use of information technology in business increases the threats and vulnerabilities to which information resources are exposed, which causes an increase in information risks. Many business institutions must constantly monitor their activities to establish an organized and sustainable information security management system and services. The requirements of the international standard ISO/IEC 27001 and the generally accepted COBIT management framework are important for the application of such a system. The paper presents a model of a sustainable information security management system (ISMS) at universities.

Millimeter wave (mmWave) systems need beam management to establish and maintain reliable links. This complex and time-consuming process seriously affects communication efficiency. Benefiting from data-driven technology in deep learning, the beam can be predicted from the waveform without coordination between transceivers. By passively listening enough waveforms that are transmitted from the base station (BS) to other receivers, the BS can predict which beam is suitable for transmitting in the downlink. However, training such a waveform learning neural network usually requires a large number of labeled training samples. This is a huge challenge, because it is difficult for the receiver to get the precise signal parameters from the transmitter in advance in the non-cooperative mmWave system. As a result, the limited samples may cause overfitting and seriously restrict the performance. Although the data augmentation technology can improve the performance under limited samples, existing data augmentation methods are mostly based on strong prior knowledge which cannot further exploit the potential characteristics of data in the real environment. This paper proposes a mixed regularization training method for training the beam prediction neural network under limited training samples. Specifically, data augmentation is implemented in the data pre-processing procedure with prior knowledge and then the signal splicing strategy is proposed in the training procedure. In order to mine the time correlation characteristics of signals, the cyclic time shift (CTS) based data augmentation method is proposed in the data augmentation step. The simulation results show that our proposed deep regularized waveform learning method needs less training samples under the same performance. Moreover, the proposed method can achieve best performance compared with existing data augmentation methods.

Unsupervised learning (UL) is widely used in the wireless resource allocation problems due to its lower computational complexity and better performance compared with traditional optimization algorithms. Since wireless resource allocation problems usually have several constraints, primal-dual learning based UL framework are widely adopted. However, the primal-dual learning approach has the problem of oscillation around the constraint threshold while training and there may be serious constraint violations when deployment. In addition, although the output of the neural network can also be restricted to the feasible region by the penalty function method, the optimality of such training methods cannot be guaranteed. In this article, we combine the primal dual learning method with the penalty function method and propose a regularized unsupervised learning (RUL) framework to enhance the robustness of the primal-dual learning based UL framework. In the proposed RUL framework, we use regularization techniques to improve the robustness of primal-dual learning by reducing the risk of constraint violations while training. A quadratic penalty term is introduced into the Lagrangian function of the wireless optimization problem where the constraints can be equivalent to equality constraints to form its augmented Lagrangian function. In the simulation, we give a simple point to point power optimization problem as an example to show that the proposed RUL can improve the robustness of constraint convergence, and can also accelerate training speed.

As technology is the driver of the economy, it is necessary to follow emerging technological trends and to create appropriate conditions for its adoption and implementation as a human-centred technology. In this regard, rules and standards for the Internet of Things (IoT) and Artificial Intelligence (AI) should be established to best use the benefits of technology and to prevent or minimize the consequences of technology misuse. The fifth industrial revolution (Industry 5.0) has already begun, although Industry 4.0 is still developing. Consequently, the original attention has shifted from IoT to AI, with the IoT debate now being a prerequisite for the AI debate. As AI is transforming our lives, a growing number of countries have considered or already adopted national AI strategies. However, in many developing countries, national AI strategies and initiatives for establishing AI and IoT regulation and legislation frameworks yet need to be discussed. The subject of this article is the research of existing initiatives related to establishing the IoT and AI regulatory and legislative framework in the EU and its applicability in developing countries.

Upravljanje kvalitetom u javnom sektoru je znatno dobilo na značaju poslednjih godina. Istina, dugi niz godina javni sektor se držao izvan ovog koncepta, a pod pojmom upravljanja kvalitetom podrazumevala se samo isporuka usluga u skladu sa zakonskim propisima. Međutim, kriza javne uprave i područja javnih usluga dovela je do preispitivanja uloge i upravljačkih mehanizama javnog sektora, te se vremenom u sve većoj mjeri, jednostavnim preuzimanjem ili eventualno uz odgovarajuća prilagođavanja, koja uzimaju u obzir specifičnosti i karakteristike istog u odnosu na privatni sektor, mogu uočiti pokušaji uvođenja i prilagođavanja sistema upravljanja kvalitetom usluga u organizacije javnog sektora. U BiH, kao zemlji u kojoj specifičnost državnog uređenja, zakonskih procedura, političkih previranja i uopšte društvene organizacije dodatno usložnjava posmatranu problematiku, važno je dijagnosticirati postojeće stanje primene sistema upravljanja kvalitetom i performansi poslovanja jedinica lokalne samouprave, te identifikovati područja mogućeg unapređenja. S tim u vezi, cilj rada je istražiti razlike u performansama poslovanja jedinica lokalne samouprave sa implementiranim standardom kvaliteta ISO 9001 i jedinica lokalne samouprave koje nisu primenile ovaj međunarodni standard u svom poslovanju. Primarni podaci za potrebe ovog istraživanja prikupljeni su primenom tehnike anketiranja, korištenjem anketnog upitnika kao obrasca za prikupljanje podataka. Razlika je testirana korištenjem t-testa nezavisnih uzoraka, a dobijeni rezultati ukazuju na značaj implementacije standarda ISO 9001, budući da je u jedinicama lokalne samouprave sa implementiranim standardom ISO 9001 zabilježen viši nivo performansi perspektive internih poslovnih procesa, performansi perspektive učenja i rasta i performansi perspektive korisnika u odnosu na jedinice lokalne samouprave koje nisu implementirale isti.

This study offers a comprehensive examination of environmental governance within the European Union (EU), focusing on the comparative experiences of Bosnia and Herzegovina (a non-EU member) and Croatia (an EU member). The research uses policy transfer theory to investigate the practicality and effectiveness of EU-led environmental initiatives when implemented at state and local levels. The study reveals a disconnect between these initiatives and their execution, with corruption and fragile political arrangements identified as significant barriers to environmental protection. The research further underscores the complex nature of EU-driven environmental governance policies and the impact of post-war political agreements and transitional struggles on Bosnia and Herzegovina’s and Croatia’s governance structures. The methodology involves a detailed analysis of the legal frameworks, policies, and plans employed by the EU and the countries under study. The results highlight the importance of context and capacity in evaluating the effectiveness of environmental governance. The study contributes to understanding environmental governance in the EU context and provides insights into the challenges and opportunities for policy transfer to state-level governments.

we assessed 12 lifestyle-related epigenetic scores for their association with

<p style="text-align: justify;"><span lang="BS-LATN-BA">The automotive industry represents an important segment of the overall industrial development in the world. In order to respond to the ever-increasing demands of customers, the automotive industry tries to keep up with the most modern technologies, and in recent times this primarily refers to information and communication technologies. Software-implemented functions in new vehicles are constantly increasing and are absolutely at the top of all innovations implemented in new vehicles. Thanks to artificial intelligence technologies, new concepts such as self-driving cars are being developed, as well as various driver monitoring systems, road condition monitoring systems, etc. There is an increasing number of artificial intelligence-based systems that enable new vehicles with different functions. The mentioned systems imply the use of a large number of networked IoT devices that exchange large amounts of data. By increasing the degree of networking and information exchange, the number of cyberattacks on vehicles also increases, which affects vehicle safety. Also, proportionally with the increase in the number of such systems, the need for designing security methods, mechanisms, architectures and protocols for detecting and mitigating attacks on car communication grows. This paper presents the challenges of cyber security in the application of artificial intelligence in the automotive industry.</span></p>