Abstract Introduction: Pulmonary embolism is still a challenge in diagnosis due to its variable and nonspecific symptoms. Computed tomography and ventilation/perfusion scanning are the modalities most commonly used in the diagnosis of pulmonary embolism, and both modalities have their advantages and disadvantages. One of the most important factors in the assessment and localization of pulmonary embolism is the diagnostic accuracy of these modalities, which serves to model different diagnostic strategies in the diagnosis of pulmonary embolism. Material and methods: The research was conducted as a review of professional literature available in scientific research databases. A selection of 20 professional papers was made, based on which an analysis was conducted and a database was formed. Criteria for inclusion in the research were scientific research papers that report on the sensitivity and specificity of diagnostic modalities of CT and V/P scanning as well as the results of diagnostic tests based on which the comparison of data from two modalities determined a diagnostically more accurate modality. Results: Sensitivity of 91.89% and specificity of 98.86% and diagnostic accuracy of 94.83% were determined in the case of computed tomography. Sensitivity of 90.58% and specificity of 98.33% and diagnostic accuracy of 96.43% were determined for the ventilation perfusion scanning method. We can conclude that the application of ventilation/perfusion scanning in the diagnosis of pulmonary embolism is a little more accurate compared to computed tomography. Conclusion: Ventilation/perfusion lung scanning will more accurately identify healthy individuals while on the other hand we can conclude that computed tomography is more accurate in diagnosing embolism in sick individuals. . Given that this difference between the two modalities is very small, the question is whether it is statistically significant at all. We can conclude that both diagnostic procedures have a high level of accuracy.

Moždani udar ili cerebrovaskularni inzult (CVI) je u današnje vrijeme jedan od glavnih uzroka smrtnosti i invaliditeta u svijetu. Veoma značajnu ulogu u dijagnostici CVI-a zauzima magnetna rezonanca (MR), koja se ogleda u mogućnosti klasifikacije i otkrivanju patofiziologije kako bi se pravovremeno i brzo postupilo sa terapijskim tretmanom ukoliko je došlo do pojave CVI-a. Ciljevi: Uporediti kvalitet prikaza CVI-a  između T2 FLAIR i T2 sekvence, utvrditi utjecaj lokalizacije CVI-a na intenzitet signala, utvrditi utjecaj vremena  pojave CVI-a na intenzitet signala. Utvrditi smo kategorije pacijenata kod kojih najčešće nastaje CVI, kao i korelaciju između uputne i definitivne dijagnoze. Metode istraživanja: Istraživanje je dizajnirano kao retrospektivna deskriptivna studija. Rad je realiziran u Kliničkom centru Univerziteta u Sarajevu, na Klinici za radiologiju. U studiju je uključeno 50 pacijenata kod kojih MR nalaz ukazuje na prisustvo CVI-a. Ispitivanje je obavljeno na MRI jedinicama jačine 1.5 i 3.0 T. Rezultati: Od ukupnog broja pacijenata 50 (100%), 32 su muškog pola (64%), a 18 (36%) ženskog pola. CVI je najčešće bio prisutan kod pacijenata muškog pola u grupi od 61-70 godine, dok je kod pacijenata ženskog pola najčešće bio prisutan u grupi od 71-80 godine. 52% pacijenata je imalo jedan od faktora rizika za nastanka CVI-a, HTA je bila prisutna kod 28% pacijenata a DM kod 22% pacijenata. T2 FLAIR sekvenca je imala veće vrijednosti intenziteta signala na lateralnom rubu CVI-a, dok je T2 sekvenca imala veće vrijednosti u centru i prednjem rubu CVI-a.  T2 FLAIR sekvenca je imala veći intenzitet signala na lokacijama: thalamus, mesencephalon, okcipitalno kortikalno subkortikalno i  područje kapsule interne. T2 sekvenca je imala veći intenzitet signala lokacijama: medula oblongata, parieto okcipitalno kortikalno subkortikalno, frontoparietalno paraventrikularno, parietalno kortikalno subkortikalno, frontoparietalno kortikalno subkortikalno, cerebelum i pons. Najčešća uputna  dijagnoza je bila CVI. Zaključak: T2 FLAIR sekvenca je senzitivnija kod prikaza akutnog i subakutnog CVI-a. T2 sekvenca je senzitivnija kod prikaza hroničnog CVI-a, čime radna hipoteza u ovom slučaju nije u potpunosti dokazana.

This study is the first report on the mtDNA profile of human settlements of the Konjuh and Majevica mountains of northeastern Bosnia. The aims of this study were: a) determination of mitochondrial genetic structure of populations of the Konjuh and Majevica mountains of northeastern Bosnia; b) detection of trace of ancient of mtDNA variations; and c) assessment of genetic relations with other Bosnian and Herzegovina populations and neighboring populations from the Balkan region. The genetic structure of populations of Konjuh and Majevica is shaped by western Eurasian maternal signals, which may trace their ancestry to the Paleolithic, pre-Neolithic and Neolithic. Especially interesting is the feature of the Neolithic expansion in this area. This applies especially to the presence of the pre-Neolithic lineages HV*and N1a in northeastern Bosnia, which can indicate an early settlement of this region of Bosnia by pre-Neolithic populations from the Middle East. This region abounds with resources of salt sites, which might suggest in favor of the thesis that the early-Neolithic colonists needed a safe source of salts so as to settle in the Balkan area. The populations of mountains of northeastern Bosnia indicate elements of the local population history, but they do not show strict genetic closure in relation to the neighboring populations of the Balkans. This may be a consequence of the population size, degree of geographic isolation and events of migration.

The use of anticoagulant therapy is a part of the daily work of clinicians and a reason for fear, primarily due to the risk of bleeding. The use of anticoagulant drugs in rheumatology remains a challenge. first, a large number of clinicians consider rheumatic conditions as a hypercoagulable state, which often leads to wrong decisions. second, the use of drugs in the treatment of rheumatic diseases may be associated with an increased risk of venous thromboembolism (vte), and they can have effect on dose of anticoagulant agent. The aim of this paper is to present the properties of anticoagulant therapy through the prism of rheumatological pathology.

Beauvoir’s existentialist ethics relates to and informs eminently contemporary accounts of feminist ethics in the Western continental feminist canon. To date only a few scholars have emphasized this connection. In this work, I show the centrality of Beauvoirian philosophy to contemporary philosophical discussions by elucidating the influence of Beauvoir’s existentialist ethics on Judith Butler’s feminist philosophy. While I acknowledge other possible influences, especially by French philosophers, on Butler’s work, I find it important to emphasize Beauvoir’s contributions as they have not received the attention they deserve. My paper shows how Beauvoir’s account of agency as an ambiguous becoming reverberates in Butler’s theory of gender performativity developed in her early writings. I consider Butler’s theory of gender performativity to have existentialist roots based on the existentialist perception of the subject as a becoming that never coincides with itself. I also discuss how Butler takes on some basic ethical questions which Beauvoir already accentuates in her writings. I focus on three main points of intersection between the two philosophers, which are vulnerability and interconnectedness, violence and inevitability of ethical failure, and finally the ambiguity and opaqueness that come with situated ethics.

With the explosive growth of advanced wireless technologies and computing device platforms, mobile sensing has gained huge attention. Indoor localization is actually considered as one of most valuable techniques in the field of contactless sensing. In this paper, we propose a novel graph convolutional network (GCN) empowered indoor localization method, which aggregates channel state information (CSI) features extracted from multiple multiple-input multiple-output (MIMO) links. CSI features from multiple antennas are basically converted into graph nodes in order to adopt GCN classification model. At the same time, graph attention mechanism is introduced to study and transfer spatial and frequency of CSI features. Eventually, output of graph is mapped with multiple measurement points through prediction network to provide final estimate position. 5GHz commercial Wi-Fi equipment is respectively utilized for data collection and experimental evaluation in two representative indoor scenarios. Experimental result shows that the proposed method has better performance in robust localization compared to other state-of-the-art deep learning methods.

Radio frequency fingerprint (RFF) identification is an emerging physical layer security technique, which provokes many promising applications in the internet of things (IoT). However, traditional machine learning-based RFF identification methods rely on complex manual feature extraction, while it is difficult for methods based on deep learning to deal with RFF identification under different channel environments. To solve these problems, we propose three different transfer learning-based RFF identification methods based on ConvMixer network, which is a mixture of different convolutional layers, using pre-trained model in the previous channel environment to assist in training under the new channel environment. Experimental results show that, compared with the previous retraining method, our proposed method reduces the number of training parameters and improves the identification performance at low SNR. Moreover, the proposed method can still have a certain performance guarantee with less training data.

Radio frequency-based device-free passive perception (RF-DFPP) is considered as one of the most promising techniques for ubiquitous smart applications in the WiFi field due to its extremely low deployment cost. Existing RF-DFPP methods typically employ received signal strength indicator (RSSI), ignoring the potential benefits of fine-grained sensing accuracy of channel state information (CSI). In addition, the robustness of such sensing methods is not good at present. To solve the problem, in this paper, we propose a robust CSI-based RF-DFPP method using a combination network of convolutional neural networks (CNN) and attention-based bi-directional long short term memory (LSTM). The combined network can extract the signal features of the collected CSI through CNN, and then realize RF-DFPP recognition through the training of LSTM and attention layers. Simulation results show that the proposed method significantly improves the recognition accuracy compared with the existing methods. Moreover, it performs robustly even if the model training is done under the different datasets.

The flexibility introduced with the Open Radio Access Network (O-RAN) architecture allows us to think beyond static configurations in all parts of the network. This paper addresses the issue related to predicting the power consumption of different radio schedulers, and the potential offered by O-RAN to collect data, train models, and deploy policies to control the power consumption. We propose a black-box (Neural Network) model to learn the power consumption function. We compare our approach with a known hand-crafted solution based on domain knowledge. Our solution reaches similar performance without any previous knowledge of the application and provides more flexibility in scenarios where the system behavior is not well understood or the domain knowledge is not available.

Pelotherapy is the application of thermal muds (peloids) for therapeutic purposes. Artificial peloids were prepared usingpyrophilite shale maturated in three different types of thermal water in terms of their pH values. The samples after 30and 60 days of maturation were examined by X-ray diffraction. No significant variations in the mineralogical compositionand diffractograms of pyrophillite peloids were detected after maturation. Only the influence of the maturation processof pyrophillite on the pH value of mineral water with high and low pH value is noticed.

This book provides a solution to the control and motion planning design for an octocopter system. It includes a particular choice of control and motion planning algorithms which is based on the authors' previous research work, so it can be used as a reference design guidance for students, researchers as well as autonomous vehicles hobbyists. The control is constructed based on a fault tolerant approach aiming to increase the chances of the system to detect and isolate a potential failure in order to produce feasible control signals to the remaining active motors. The used motion planning algorithm is risk-aware by means that it takes into account the constraints related to the fault-dependant and mission-related maneuverability analysis of the octocopter system during the planning stage. Such a planner generates only those reference trajectories along which the octocopter system would be safe and capable of good tracking in case of a single motor fault and of majority of double motor fault scenarios. The control and motion planning algorithms presented in the book aim to increase the overall reliability of the system for completing the mission.

Congenital anomalies (CA) are any abnormality present at birth, either structural or functional, that may potentially affect an infant’s health, development, and/or survival. There is a paucity of studies on clinical characteristics and outcomes of CA in Bosnia and Herzegovina, mainly due to the lack of a nationwide congenital malformations monitoring system. A 5-year hospital-based study was conducted to determine the prevalence at birth and clinical characteristics of selected major CA in Sarajevo Canton, Bosnia and Herzegovina. Ninety-one CA were observed from 2012 to 2016 (the overall prevalence was 39.6 cases/10,000 live births). The mean age of neonates at diagnosis was 3 days. The gastrointestinal tract was the most commonly affected system (76.9%), with esophageal atresia (EA) being the most frequent (17.6% of all CA). Major CA were more prevalent among preterm infants than term infants (P = .001), particularly in males (61.5% vs. 38.5%; P = .028; M:F ratio was 1.59). Multiple CA were seen in 37.4% of neonates. The overall mortality rate of neonates was 11%, and the median length of hospital stay was 19.8 days. Our study revealed the distribution and clinical patterns of common major CA in the largest tertiary care facility in Bosnia and Herzegovina. It also confirmed a relatively high mortality rate, which requires further efforts to improve the quality of neonatal care in the country.

Polygenic risk scores (PRSs) are a promising approach to accurately predict an individual’s risk of developing disease. The area under the receiver operating characteristic curve (AUC) of PRSs in their population are often only reported for models that are adjusted for age and sex, which are known risk factors for the disease of interest and confound the association between the PRS and the disease. This makes comparison of PRS between studies difficult because the genetic effects cannot be disentangled from effects of age and sex (which have a high AUC without the PRS). In this study, we used data from the UK Biobank and applied the stacked clumping and thresholding method and a variation called maximum clumping and thresholding method to develop PRSs to predict coronary artery disease, hypertension, atrial fibrillation, stroke and type 2 diabetes. We created case-control training datasets in which age and sex were controlled by design. We also excluded prevalent cases to prevent biased estimation of disease risks. The maximum clumping and thresholding PRSs required many fewer single-nucleotide polymorphisms to achieve almost the same discriminatory ability as the stacked clumping and thresholding PRSs. Using the testing datasets, the AUCs for the maximum clumping and thresholding PRSs were 0.599 (95% confidence interval [CI]: 0.585, 0.613) for atrial fibrillation, 0.572 (95% CI: 0.560, 0.584) for coronary artery disease, 0.585 (95% CI: 0.564, 0.605) for type 2 diabetes, 0.559 (95% CI: 0.550, 0.569) for hypertension and 0.514 (95% CI: 0.494, 0.535) for stroke. By developing a PRS using a dataset in which age and sex are controlled by design, we have obtained true estimates of the discriminatory ability of the PRSs alone rather than estimates that include the effects of age and sex.