With the move towards 6G and associated technology deployment in higher frequency bands, measurements of directionally-resolved channels and sounders capable of performing such measurements are a necessity. In this paper, we present a new concept of channel sounding based on a Redirecting Rotating Mirror Arrangement (ReRoMA), capable of performing double-directional channel measurements at millimeter wave frequencies by mechanical beam steering orders of magnitude faster than existing rotating-horn arrangements. We present this new concept, describe a prototype operating at 60 GHz, and use it to perform, as proof-of-principle, a dynamic cart-to-cart channel measurements at a T-intersection scenario. We show that this sounding principle works and allows the directional evaluation of the channel. We visualize the different resolvable propagation paths in terms of dynamic angular and delay power spectrum, and relate them to the environmental geometry.

One of the key factors critical to the advancements of IoT systems in remote areas today are energy-efficient IoT deployment and the integration with IoT /edge/continuum. An energy-efficient IoT deployment requires finding adequate solutions for applications that require remote area devices and the related replacement and charging of batteries. On the other hand, an efficient integration of different communication technologies spanning the IoT, edge and cloud continuum that at the same time can integrate energy harvesting devices in remote areas is still an open challenge. In this paper, we integrate energy harvesting with wearable remote IoT devices on freely roaming farm animals within the edge/cloud continuum along its powerful application layer protocols, MQTT and AMQP. We experimentally investigate the performance of kinetic energy harvester used to power a LoRa module to send application layer messages from IoT to cloud. From the functional system testing perspective, we show that these messages can be successfully forwarded for further processing and evaluation in the edge and cloud setting even from the remote areas. We engineered an inexpensive and first open-source multi-protocol MQTT based communication gateway, as an alternative to today's proprietary and expensive gateway solutions, and we built a system that can not only power the capturing of animal movement patterns outdoors, but also the related application-layer protocol messages.

This paper explores the contribution of custom-trained Large Language Models (LLMs) to developing Open Education Resources (OERs) in higher education. Our empirical analysis is based on the case of a custom LLM specialized for teaching business management in higher education. This custom LLM has been conceptualized as a virtual teaching companion, aimed to serve as an OER, and trained using the authors’ licensed educational materials. It has been designed without coding or specialized machine learning tools using the commercially available ChatGPT Plus tool and a third-party Artificial Intelligence (AI) chatbot delivery service. This new breed of AI tools has the potential for wide implementation, as they can be designed by faculty using only conventional LLM prompting techniques in plain English. This paper focuses on the opportunities for custom-trained LLMs to create Open Educational Resources (OERs) and democratize academic teaching and learning. Our approach to AI chatbot evaluation is based on a mixed-mode approach, combining a qualitative analysis of expert opinions with a subsequent (quantitative) student survey. We have collected and analyzed responses from four subject experts and 204 business students at the Faculty of Economics, Business and Tourism Split (Croatia) and Faculty of Economics Mostar (Bosnia and Herzegovina). We used thematic analysis in the qualitative segment of our research. In the quantitative segment of empirical research, we used statistical methods and the SPSS 25 software package to analyze student responses to the modified BUS-15 questionnaire. Research results show that students positively evaluate the business management learning chatbot and consider it useful and responsive. However, interviewed experts raised concerns about the adequacy of chatbot answers to complex queries. They suggested that the custom-trained LLM lags behind the generic LLMs (such as ChatGPT, Gemini, and others). These findings suggest that custom LLMs might be useful tools for developing OERs in higher education. However, their training data, conversational capabilities, technical execution, and response speed must be monitored and improved. Since this research presents a novelty in the extant literature on AI in education, it requires further research on custom GPTs in education, including their use in multiple academic disciplines and contexts.

Heuristic search is often used for motion planning and pathfinding problems, for finding the shortest path in a graph while also promising completeness and optimal efficiency. The drawback is it's space complexity, specifically storing all expanded child nodes in memory and sorting large lists of active nodes, which can be a problem in real-time scenarios with limited on-board computation. To combat this, we present the Search with Learned Optimal Pruning-based Expansion (SLOPE), which, learns the distance of a node from a possible optimal path, unlike other approaches that learn a cost-to-go value. The unfavored nodes are then pruned according to the said distance, which in turn reduces the size of the open list. This ensures that the search explores only the region close to optimal paths while lowering memory and computational costs. Unlike traditional learning methods, our approach is orthogonal to estimating cost-to-go heuristics, offering a complementary strategy for improving search efficiency. We demonstrate the effectiveness of our approach evaluating it as a standalone search method and in conjunction with learned heuristic functions, achieving comparable-or-better node expansion metrics, while lowering the number of child nodes in the open list. Our code is available at https://github.com/dbokan1/SLOPE.

Introduction Between 2021 and 2023, a project was funded in order to explore the mortality burden (YLL–Years of Life Lost, excess mortality) of COVID-19 in Southern and Eastern Europe, and Central Asia. Methods For each national or sub-national region, data on COVID-19 deaths and population data were collected for the period March 2020 to December 2021. Unstandardized and age-standardised YLL rates were calculated according to standard burden of disease methodology. In addition, all-cause mortality data for the period 2015–2019 were collected and used as a baseline to estimate excess mortality in each national or sub-national region in the years 2020 and 2021. Results On average, 15–30 years of life were lost per death in the various countries and regions. Generally, YLL rates per 100,000 were higher in countries and regions in Southern and Eastern Europe compared to Central Asia. However, there were differences in how countries and regions defined and counted COVID-19 deaths. In most countries and sub-national regions, YLL rates per 100,000 (both age-standardised and unstandardized) were higher in 2021 compared to 2020, and higher amongst men compared to women. Some countries showed high excess mortality rates, suggesting under-diagnosis or under-reporting of COVID-19 deaths, and/or relatively large numbers of deaths due to indirect effects of the pandemic. Conclusion Our results suggest that the COVID-19 mortality burden was greater in many countries and regions in Southern and Eastern Europe compared to Central Asia. However, heterogeneity in the data (differences in the definitions and counting of COVID-19 deaths) may have influenced our results. Understanding possible reasons for the differences was difficult, as many factors are likely to play a role (e.g., differences in the extent of public health and social measures to control the spread of COVID-19, differences in testing strategies and/or vaccination rates). Future cross-country analyses should try to develop structured approaches in an attempt to understand the relative importance of such factors. Furthermore, in order to improve the robustness and comparability of burden of disease indicators, efforts should be made to harmonise case definitions and reporting for COVID-19 deaths across countries.

BACKGROUND Left atrial strain (LAS) analysis represents a newer non-invasive, sensitive and specific technique for assessing left atrial (LA) function and early detection of its deformation and dysfunction. However, its applicability in mitral regurgitation (MR) in pediatric population remains unexplored, raising pertinent questions regarding its potential role in evaluating the severity and progression of the disease. OBJECTIVE To investigate the impact of chronic MR in children and adolescents on LA remodeling and function. METHODS The study included 100 participants. Patients with primary and secondary chronic MR lasting at least 5 years fit our inclusion criteria. The exclusion criteria from the study were: patients with functional mitral regurgitation due to primary cardiomyopathies, patients with artificial mitral valve, patients with MR who had previously undergone surgery due to obstructive lesions of the left heart (aortic stenosis, coarctation of the aorta), patients with significant atrial rhythm disorders (atrial fibrillation, atrial flutter). The echocardiographic recordings were conducted by two different cardiologists. Outcome data was reported as mean and standard deviation (SD) or median and interquartile range (Q1-Q3). RESULTS The study included 100 participants, of whom 50 had MR and the remaining 50 were without MR. The average age of all participants was 15.8 ± 1.2 years, with a gender distribution of 37 males and 63 females. There was a significant difference in the values of LA volume index (LAVI), which were higher in patients with MR (p= 0.0001), S/D ratio (and parameters S and D; p= 0.001, p= 0.0001, p= 0.013), mitral annulus radius (p= 0.0001), E/A ratio (p= 0.0001), as well as septal e' (m/s), lateral e' (m/s), and average E/e' ratio, along with the values of TV peak gradient and LV global longitudinal strain (%). There was no significant difference in LA strain parameters, nor in LA stiffness index (LASI). CONCLUSION Our findings revealed significant differences in several echocardiographic parameters in pediatric patients with MR relative to those without MR, providing insight into the multifaceted cardiac structural and functional effects of MR in this vulnerable population.

Talent management is an essential area within human resource management and has been increasingly receiving attention over the past several decades. The focus of talent management is on the most crucial employees within an enterprise. Therefore, it is vital to have a specialized and tailored management system for them to maximize business results. This paper addresses the connection between talent management and enterprise competitiveness. It aims to examine the relationship between these two variables within the business environment of Bosnia and Herzegovina. This paper significantly contributes to both theory and practice because it proposes a new, more comprehensive process model of talent management based on a detailed analysis and synthesis of all available scientific and research works. Following this, the paper tests the proposed model in practice and measures its success by examining enterprise competitiveness. The research was conducted on 101 service enterprises in Bosnia and Herzegovina in the second quarter of 2023. Managers of service enterprises involved in human resource management were surveyed. The questionnaire was formulated based on a combination of existing research in the specified fields. The data were subjected to correlation and regression analysis, and the research results were presented according to the previously set objectives and hypotheses. The research results showed that talent management is a significant predictor of competitive advantage. Additionally, a positive impact on competitiveness was confirmed for each individual group of talent management activities presented in the proposed process model.

The transition process from fossil fuels to environmentally friendly renewable energy sources carries the risk of creating new environmental damages. Photovoltaic technology represents one of the alternatives with the least risk of harmful environmental impact. However, this technology has two important drawbacks: the significant land occupation for the installation of PV systems and the uncontrollability of production. By constructing floating photovoltaic plants on hydroelectric reservoirs, both of these problems can be reduced to an acceptable level. Some artificial reservoirs, originally built for hydroelectric power plants, have acquired a significant secondary function as recreational areas and fish breeding sites. Therefore, there is justified resistance from the local community to change the existing appearance and purpose of such reservoirs. This paper proposes a completely new concept of integrating the interests of the local community into such objects. In addition to preserving existing uses, the concept also offers new features. This can make the entire system environmentally friendly and sustainable. This paper details the technology behind the construction of floating photovoltaic power plants on artificial reservoirs and emphasizes their various advantages. These benefits include the non-utilization of cultivable land, the ease of assembly and construction, integration into existing power grids, and the potential to address electricity storage issues. For instance, Buško Lake, covering an area of 55.8 km2, may host 2.93 km2 of installed floating photovoltaic (FPV) facilities, enabling a total installed capacity of 240 MW. With an average of 5.5 h of daily sunshine, this totals 2007 annual hours, equivalent to a 55 MW thermal power plant. An analysis showed that, with losses of 18.2%, the average annual production stands at 302 GWh, translating to an annual production value of 18 million € at 60 €/MWh. The integration of this production into an existing hydroelectric power plant featuring an artificial reservoir might boost its output by 91%. The available transmission line capacity of 237 MW is shared between the hydroelectric power plant (HPP) and FPV; hence during the FPV maximum power generation time, the HPP halts its production. HPP Orlovac operates a small number of hours annually at full capacity (1489 h); therefore in combination with the FPV, this number can be increased to 2852 h. This integration maintains the lake’s functions in tourism and fishing while expanding its capabilities without environmental harm.

Significance S-layer proteins (SLPs) are self-assembling, crystalline proteins coating the cell surfaces of many prokaryotes. This study presents experimental atomic resolution structures of lactobacilli SLPs, deriving functional insight into key probiotic Lactobacillus strains. The structures of SlpA and SlpX proteins highlight the domain swapping critical for SlpX integration, particularly in response to environmental stress. Two binding regions are identified as crucial for attachment of the S-layer to (lipo)teichoic acid. The structure of assembled S-layer provides a foundation for employing (designed) SLPs as a therapeutic agent in the treatment of inflammatory diseases. Additionally, it opens broad avenues for the use of SLPs in vaccine development and in crafting nanostructures with tailored properties, including those designed for targeted drug delivery.

BACKGROUND Despite improvements, survival rates for gastric cancer remain low, even in developed countries, confirming the role of primary and secondary prevention. OBJECTIVE This study aims to demonstrate the role of additional suspension sutures on the esophagojejunal anastomosis (EJA) to strengthen the anastomosis, i.e., relieve the mechanical suture. METHODS A retrospective cohort study was conducted from 2011 to 2022 at the Clinic for Surgery, University Clinical Center Tuzla, Bosnia and Herzegovina. The experimental group consisted of patients placed with a suspension suture at the esophagojejunal anastomosis (EJA) site after total gastrectomy. The control group was patients without a suspension suture. The clinical and laboratory parameters available from the medical history were analyzed, X-ray passage, surgical complications, non-surgical complications, the length of hospitalization, the postoperative course, time of onset of postoperative complications, postoperative radiological follow-up and endoscopic postoperative follow-up were then analyzed. RESULTS A total of 212 patients were included in the study: 87 in the experimental group with suspension sutures on the EJA and 125 in the control group without suspension sutures on the EJA. The two cohorts did not differ in other clinicopathologic parameters except perineural invasion, which was more prevalent in the control group. Patients in both groups were anemic and elevated values of C reactive protein (CRP) and decreased levels of proteins, albumin and globulin, with no significant difference between the two groups. The most common general complication was pleural effusion (28%), followed by pneumonia (∼22%). The most common complication in the experimental group was an intraabdominal abscess, while in the control group, it was a surgical wound infection. CONCLUSION Our study did not show a statistically significant difference between the two analyzed EJA techniques created with a circular stapler, when it comes to postoperative course and outcome in patients with gastric cancer.

The Lithium-Ion battery at the end of life represents a valuable source of secondary raw materials such as lithium, nickel, cobalt etc. Deep discharging, as a part of battery recycling, is a time-consuming process in which the battery's thermal dependency on the discharge parameters and voltage recovery effect is manifested. Adjusting the discharging process adequately to address those two phenomena leads to a safety increase and discharging time decrease. This paper treats two aspects. It is observed the effect of the constant and variable discharging current along with the depth of the discharge in the form of discharge end voltage parameter on the maximal cell temperature reached during the process. The second aspect is the battery recovery voltage trend after the discharging process and its dependency on the same parameters. The impact of these parameters is demonstrated experimentally on two battery cell types.

Network slicing enables multiple virtual networks to share physical resources, allowing network operators to deliver highly customizable and efficient networking solutions that meet the diverse requirements of modern applications. The automated management of network slices has been studied in the last years to make such solutions more flexible, ready to support new applications, and capable of optimizing network resource utilization. Many works in the literature give a top-down approach, focusing on the high-level decision processes, and relying on abstracted infrastructure managers and simulation tools to apply/execute such decisions. In this work, we leverage components that we previously developed for network monitoring, flexible traffic shaping, and Software-Defined Time-Sensitive Networking control, to create a bottom-up approach toward automated slice management. We describe the intricate coordination of elements required for an automated control loop and present the results achieved with a proof-of-concept executed in a real testbed of wired and Wi-Fi nodes. The results show the capability of the system to correctly identify the bottleneck of a flow and apply corrective actions to reestablish its intended performance level.

Intent-driven network management has become an important part of autonomous systems in Beyond 5G (B5G) towards Sixth-Generation (6G) networks, by enabling flexibility in the interaction among applications, operators and users. Intents play an important role in the communication of road users like autonomous vehicles and pedestrians to edge computing services. As sensor technologies for modern vehicles are cheaper, smaller, diverse and computing capable, more demand for applications and services on the road is increasing. A flexible intent interpretation and coordination are needed to deal with the dynamic environment and constantly changing goals. This paper presents a proof-of-concept of Zero-touch Network and Service Management (ZSM) for vehicular communication services, using an Intent Management Entity (IME) to translate user objectives into actionable directives. This paper describes a realistic testbed setup at the Smart Highway, where a Deep Reinforcement Learning (DRL) algorithm is used to optimize the selection of Roadside Units (RSUs) for service orchestration. This paper also discusses the challenges and opportunities of enhancing the IME with time-based intent coordination, using Artificial Intelligence and Machine Learning (AI/ML) techniques to estimate the waiting time and priority in intent coordination. The paper aims to demonstrate the benefits of ZSM and Intent-driven Management for vehicular edge computing and B5G/6G autonomous network management frameworks.

The challenge of ensuring safety in autonomous driving or sailing involves predicting and replicating various potential scenarios on roads and waterways, posing difficulties and high costs. In response, the European project 5G-Blueprint addresses this by introducing a complementary technology, i.e., teleoperation, which leverages 5G connectivity to enable human interventions in complex situations beyond autonomous capabilities, thereby removing the physical link between the human operator and the remotely controlled vehicle/vessel. This operational mode brings stringent connectivity requirements, including high uplink bandwidth for transmitting video streams from onboard cameras to the teleoperation center, low latency, and an ultra-reliable connection for relaying commands from the teleoperator to the remote vehicle/vessel. Additionally, it emphasizes minimal interruption time when the teleoperated vehicle/vessel crosses international borders, ensuring seamless connectivity and uninterrupted remote operation. Therefore, this paper summarizes extensive evaluations of network and service performance, highlighting key results across pilot locations and providing conclusions and analysis of 5G-enhanced teleoperation in various use cases. Additionally, it outlines lessons learned from pilot activities.