Introduction: The coronavirus disease 2019 (COVID-19) pandemic has caused a worldwide emergency. The disease is characterized primarily by symptoms of the respiratory system, but also by systemic inflammation. Since the onset of the disease, there has been a need for biomarkers to predict the severity of the clinical picture and the outcome of the disease. The aim of this study is to evaluate systemic inflammatory markers for predicting severity of COVID-19. Methods: The study was conducted at the Sarajevo Canton Health Center on a total of 170 adults suffering from COVID-19. 70 subjects had mild clinical picture, while the control group consisted of 100 subjects with moderate clinical picture. The results of complete and differential blood counts, C-reactive protein (CRP), and systemic inflammatory indexes (SII) (neutrophil/lymphocyte ratio [NLR], derived NLR [dNLR], platelet/lymphocyte ratio [PLR], and SII) were used to compare the groups. IBM SPSS Ver. 23 was used for statistical analysis and data processing. Results: The proportion of male patients in the group with a milder clinical picture was higher than the proportion of male patients with a moderate clinical picture, p = 0.016. The values of leukocytes and neutrophils were higher in patients with a moderate clinical picture (p = 0.006 and p < 0.001, respectively). The values of all inflammatory indexes (NLR, dNLR, PLR and SII) were higher in patients with a moderate clinical picture of COVID-19 than in patients with a mild clinical picture (p < 0.001 for NLR, dNLR, and SII; p = 0.023 for PLR). In the research, patient age showed no correlation and CRP showed no correlation with SII. Conclusion: SII show higher values in patients with a moderate compared with a mild clinical picture of COVID-19. These parameters can be cost-effective and useful indicators in patient classification, diagnosis, and probably in monitoring patients with COVID-19.

This paper presents some results of analysis of using several types of common Ethernet cables (LAN cables) in last section of access networks. The main goal of the article is to answer the question whether (if so, under what conditions and to what extent) we should consider the type of specific Ethernet cable when using it in a FTTB environment. Four branded and two unbranded CAT5e Ethernet cables are used for measurements. Additionally, a DSL cable with diameter of 0.4 mm is used for comparison purposes. The results are collected and mutually compared under similar loop conditions (good loop). All of the results of measurements are collected in operating conditions.

The aim of the paper is the quality of video streaming analysis in cases of using different video codecs in the environment of distributed computer systems with different QoS (Quality of Service). For the purposes of the analysis, several scenarios were set up in which video encoded with different codecs is transmitted by a virtual video streaming server to virtual clients. For each of the scenarios, an environment with different QoS (packet losses, latency, jitter) was simulated and the quality of the received video stream was evaluated for each video codec. The quality of the received decoded video stream was calculated using SSIM (Structural Similarity) and VMAF (Video Multimethod Assessment Fusion) video objective metrics and compared to the original video stream.

Cryptocurrencies represent a new form of property that exists only on the Internet. The first cryptocurrency to appear on the global market was Bitcoin, and its appearance is linked to the first financial crisis in 2008. The market capitalization of Bitcoin grew very quickly and in 2017 reached the highest capitalization in history (334 billion US dollars). Later, there was an expansion of new cryptocurrencies, of which there are currently over 1500 (e.g. Ethereum, Tether, BNB, USD Coin, etc.). The emergence of cryptocurrencies as a new concept affects the change in the perception of payments and money as a means of payment in general. The development of the global cryptocurrency market is indeed rapid and dynamic, and it is becoming an increasingly popular method of payment. Since the emergence of cryptocurrencies is not related to central banks, the need to change the classical systems and economic policies of countries is also expressed. The dynamic development of the mentioned market takes place in parallel with the development of information technologies, so there is a trend of capital outflow from classic capital markets to emerging global cryptocurrency markets. The question arises of the survival of traditional banks in the future, as more users trust cryptocurrencies. Global cryptocurrency markets are expected to expand more and more in the future. The paper will analyze the development of the global cryptocurrency market based on a sample of five of the most significant cryptocurrencies today.

In multi-attribute group decision-making (MAGDM), the attributes can be placed into independent groups based on their properties through partitioning. First, the partitioned dual Hamy mean (PDHM) operator is introduced, along with its essential properties. This operator integrates these separate groups while preserving the relationships between the attributes within each group. Furthermore, the partitioned Hamy mean (PHM) and the PDHM operators are also constructed in the generalized orthopair fuzzy environment, namely the q-rung orthopair fuzzy PHM (q-ROFPHM), the q-rung orthopair fuzzy PDHM (q-ROFPDHM), and their weighted forms. Their essential properties are verified to ensure the validity of the proposed aggregation operators (AOs). Subsequently, a new MAGDM approach is developed, employing the proposed AOs. The MAGDM problem of selecting the best person is examined. Moreover, the research includes a sensitivity analysis in three directions and a comparative analysis of the proposed MAGDM approach with five different approaches. The findings indicate that applying attribute partitioning in the proposed approach mitigates the adverse impact of irrelevant attributes, leading to more feasible and reliable outcomes. Additionally, a practical case study focuses on selecting a suitable industry for investment among the five available options. This case study demonstrates the approach’s effectiveness by considering five distinct qualities and results that make the Internet industry the best place to invest. Furthermore, a comparative analysis with four similar papers is also performed, indicating that the developed method’s results are more reliable and consistent.

The psychophysical preparation program for pregnant women includes physical exercises and theoretical lectures aimed at preparing the pregnant woman for childbirth and that the benefits far outweigh the risks. Exercise is an essential element of pregnancy, and OB-GYNs and other obstetric care providers should encourage their patients to continue or begin exercise. The aim of this work is to understand the impact of psychophysical preparation of pregnant women on health during and after pregnancy, birth outcomes and postpartum recovery. Twenty scientific research papers/articles including 5517 respondents were reviewed, based on databases: Web of Science, EBSCO, Scopus, Medline, PubMed, ScienceDirect, Google Scholar, and others. Works published from 2017-2022 were reviewed. The results of this study show that pregnant women who attended the program of psychophysical preparation for childbirth had a chance to experience childbirth in a more beautiful light, to be prepared, so that they would go to the maternity hospital with less fear, how to use breathing techniques during childbirth, and how to have the easiest and most beautiful childbirth without the use of drugs and interventions. Pregnant women had significantly more positive outcomes of childbirth as well as postpartum recovery and mental health. Psychological support and education have positive outcomes on the mental health of pregnant women because they reduce fear of the unknown and reduce the risk of postpartum depression. Higher rates of intact perineum, reduction of episiotomy and less damage of perineal tears are recorded. The preparation itself significantly affects the outcome of the test subjects’ births, where vaginal births are much more common, and the rate of instrumental methods of birth and caesarean section is reduced. A positive outcome was recorded during postpartum recovery.

In this paper, a novel method for the double heat treatment of ductile iron was applied. Ten sets of specimens (three specimens in each set) of ductile cast iron (DCI) containing 0.51% wt. Cu were prepared and converted to austenitic ductile iron. All specimens were austenitized at 850 °C for 60 min and annealed at 420 °C, 331 °C and 250 °C for 120, 68 and 30 min, respectively. Five sets of samples were then annealed at 500 °C for 60 min, creating a novel double heat treatment process for annealing. Finally, all specimens were slowly cooled in air at ambient temperature. Tensile strength, hardness and elongation were measured in all specimens to compare the specimens with and without subsequent tempering. A microstructural analysis was also performed, which showed that the microstructure changed for the specimens that were subsequently tempered with. The results show that specimens with subsequent tempering have slightly higher hardness, a small decrease in tensile strength and significantly higher elongation. In addition, specimens with subsequent tempering exhibit more uniform mechanical properties compared to specimens without subsequent tempering. The use of neutron beam techniques was proposed to further characterize the newly formed microstructure after subsequent tempering.

BACKGROUND: The ADAMTS7 locus was genome-wide significantly associated with coronary artery disease. Lack of the ECM (extracellular matrix) protease ADAMTS-7 (A disintegrin and metalloproteinase-7) was shown to reduce atherosclerotic plaque formation. Here, we sought to identify molecular mechanisms and downstream targets of ADAMTS-7 mediating the risk of atherosclerosis. METHODS: Targets of ADAMTS-7 were identified by high-resolution mass spectrometry of atherosclerotic plaques from Apoe−/− and Apoe−/−Adamts7−/− mice. ECM proteins were identified using solubility profiling. Putative targets were validated using immunofluorescence, in vitro degradation assays, coimmunoprecipitation, and Förster resonance energy transfer–based protein-protein interaction assays. ADAMTS7 expression was measured in fibrous caps of human carotid artery plaques. RESULTS: In humans, ADAMTS7 expression was higher in caps of unstable as compared to stable carotid plaques. Compared to Apoe−/− mice, atherosclerotic aortas of Apoe−/− mice lacking Adamts-7 (Apoe−/−Adamts7−/−) contained higher protein levels of Timp-1 (tissue inhibitor of metalloprotease-1). In coimmunoprecipitation experiments, the catalytic domain of ADAMTS-7 bound to TIMP-1, which was degraded in the presence of ADAMTS-7 in vitro. ADAMTS-7 reduced the inhibitory capacity of TIMP-1 at its canonical target MMP-9 (matrix metalloprotease-9). As a downstream mechanism, we investigated collagen content in plaques of Apoe−/− and Apoe−/−Adamts7−/− mice after a Western diet. Picrosirius red staining of the aortic root revealed less collagen as a readout of higher MMP-9 activity in Apoe−/− as compared to Apoe−/− Adamts7−/− mice. To facilitate high-throughput screening for ADAMTS-7 inhibitors with the aim of decreasing TIMP-1 degradation, we designed a Förster resonance energy transfer–based assay targeting the ADAMTS-7 catalytic site. CONCLUSIONS: ADAMTS-7, which is induced in unstable atherosclerotic plaques, decreases TIMP-1 stability reducing its inhibitory effect on MMP-9, which is known to promote collagen degradation and is likewise associated with coronary artery disease. Disrupting the interaction of ADAMTS-7 and TIMP-1 might be a strategy to increase collagen content and plaque stability for the reduction of atherosclerosis-related events.

Contemporary neighborhood livability differs across countries due to implementation of sustainable policies within the building sector. This paper aims to showcase these differences among Germany, Croatia, and Bosnia and Herzegovina through a comparative case study analysis of two contemporary housing developments from each country. Representative neighborhoods from the aforementioned countries that were selected for analysis were located in Munich, Rijeka, and Sarajevo. The residential environment livability analysis method was used in order to pinpoint and compare results of each of these cases, and to assess their livability. The highest number of livability criteria among analyzed cases were found in Munich, while the lowest were found in Sarajevo. The conclusion is that this is happening due to German authorities actually implementing sustainable building standards in housing development prescribed by sustainability policies, while the authorities of Bosnia and Herzegovina completely, and Croatian authorities partially, go around these policies and bend to the will of investors, regulating residential urban development to the detriment of end users.

The growing awareness of environmental sustain-ability has led to new investments in the field of electric vehicles. One of the most expensive and important components of electric vehicles are their batteries, with battery management systems (BMS) being responsible for their control. New regulations, such as those of the European Union, aim to introduce battery passports as a way to track battery lifecycle from manufacturing, over second-life use, to recycling. Given the vast amount of data generated during the lifecycle of a battery, the current research is focused on combining BMS with cloud connectivity. However, not much research has yet been done in the area of BMS cloud security and secure data logging. To address this gap, we propose a novel solution for secure BMS data acquisition for on-premise and cloud environments. In this paper, we make two main contributions: a secure data structure for BMS logging and a secure architecture for transferring BMS data from its source to cloud and end systems. We demonstrate the feasibility of the design by developing a prototype with real components and evaluate it in terms of security and performance.

Abstract Migration’s impact spans various social dimensions, including demography, sustainability, politics, economy, and gender disparities. Yet, the decision-making process behind migrants choosing their destination remains elusive. Existing models primarily rely on population size and travel distance to explain the spatial patterns of migration flows, overlooking significant population heterogeneities. Paradoxically, migrants often travel long distances and to smaller destinations if their diaspora is present in those locations. To address this gap, we propose the diaspora model of migration, incorporating intensity (the number of people moving to a country), and assortativity (the destination within the country). Our model considers only the existing diaspora sizes in the destination country, influencing the probability of migrants selecting a specific residence. Despite its simplicity, our model accurately reproduces the observed stable flow and distribution of migration in Austria (postal code level) and US metropolitan areas, yielding precise estimates of migrant inflow at various geographic scales. Given the increase in international migrations, this study enlightens our understanding of migration flow heterogeneities, helping design more inclusive, integrated cities.

Hardware channel emulators are essential for developing and testing transceiver prototypes in laboratory settings. They should be able to monitor the dynamic motion of the mobile terminal. This paper presents a narrowband Multiple-Input Multiple-Output (MIMO) channel emulator implemented on Field-Programmable Gate Array (FPGA). The proposed emulator is based on Non-Line-of-Sight (NLoS) non-isotropic scattering with arbitrary motion dynamics of the mobile terminal. Its standalone hardware architecture ensures the flexibility and scalability of further hardware realization. Our proposed emulator is validated by comparing the emulated statistics of the channel gain against simulated results under a circular antenna trajectory. The Probability Density Function (PDF) of the fading envelope is observed to perfectly match the theoretical Rayleigh distribution(stationary channel) and the auto-correlation function(non-isotropic scattering) also shows a close agreement. The successful alignment of the eigenvalue of the channel gain matrix indicates our proposed emulator can perform correct MIMO characteristics.

This paper considers an application of deep learning for channel estimation with imperfect frame synchronization in mobile communication systems. Without prior knowledge of the channel model and its characteristics, the proposed method can dynamically estimate and track channel transfer function variations based on received pilot symbols. Furthermore, this method is applicable in practical scenarios, as it considers imperfect frame synchronization and channel estimation for high-speed wireless communication scenarios. The performance and practical feasibility of the deep learning (DL)-based models are assessed by taking into account realistic frequency-selective fading scenarios. Numerical results demonstrate that the proposed method performs better for practical signal-to-noise ratios than the state-of-the-art approaches. In addition, the fine frame offsets are estimated and compensated in the synchronization block with a DL-based algorithm, which outperforms the traditional fine frame synchronization algorithms.