In research aimed at determining ways to protect the data of primary and secondary school students, as well as students and innovators who have submitted their ideas and innovations to innovation fairs in the territory of Republika Srpska, there is a lack of thoroughly analyzed methods and systems for protecting their ideas/innovations. This paper analyzes the most effective security algorithms for the protection of innovations and innovators from different categories. The objective of this work is to define the best prototype for protecting the identity database of innovators and innovations from the civil sector until their patent protection is granted in the territory of Bosnia and Herzegovina. By using the deductive method, we analyze various algorithms that function in a distributed environment. By comparing the advantages and disadvantages of existing algorithms, we suggest the application of the most appropriate one to meet the strategic decision-making needs of civil organizations.

Accurate vehicle trajectory prediction is an unsolved problem in autonomous driving with various open research questions. State-of-the-art approaches regress trajectories either in a one-shot or step-wise manner. Although one-shot approaches are usually preferred for their simplicity, they relinquish powerful self-supervision schemes that can be constructed by chaining multiple time-steps. We address this issue by proposing a middle-ground where multiple trajectory segments are chained together. Our proposed Multi-Branch Self-Supervised Predictor receives additional training on new predictions starting at intermediate future segments. In addition, the model ’imagines’ the latent context and ’predicts the past’ while combining multi-modal trajectories in a tree-like manner. We deliberately keep aspects such as interaction and environment modeling simplistic and nevertheless achieve competitive results on the INTERACTION dataset. Furthermore, we investigate the sparsely explored uncertainty estimation of deterministic predictors. We find positive correlations between the prediction error and two proposed metrics, which might pave way for determining prediction confidence.

Unlike pan-FGFR inhibitors, RLY-4008 was designed to be selective for FGFR2 and induces clinical responses in FGFR2-altered solid tumors without clinically significant FGFR1-mediated hyperphosphatemia and FGFR4-mediated diarrhea.

Recent studies of selective auditory attention have demonstrated that neural responses recorded with electroencephalogram (EEG) can be decoded to classify the attended talker in everyday multitalker cocktail-party environments. This is generally referred to as the auditory attention decoding (AAD) and could lead to a breakthrough for the next-generation of hearing aids (HAs) to have the ability to be cognitively controlled. The aim of this paper is to investigate whether cepstral analysis can be used as a more robust mapping between speech and EEG. Our preliminary analysis revealed an average AAD accuracy of 96%. Moreover, we observed a significant increase in auditory attention classification accuracies with our approach over the use of traditional AAD methods (7% absolute increase). Overall, our exploratory study could open a new avenue for developing new AAD methods to further advance hearing technology. We recognize that additional research is needed to elucidate the full potential of cepstral analysis for AAD.

Strategic management has applications in many areas of social life. One of the basic steps in the process of strategic management is formulating a strategy by choosing the optimal strategy. Improving the process of selecting the optimal strategy with MCDM methods and theories that treat uncertainty well in this process, as well as the application of other and different selection criteria, is the basic idea and goal of this research. The improvement of the process of the aforementioned selection in the defense system was carried out by applying a hybrid model of multicriteria decision-making based on methods defining interrelationships between ranked criteria (DIBR) and multiattributive ideal-real comparative analysis (MAIRCA) modified by triangular fuzzy numbers–“DIBR–DOMBI–Fuzzy MAIRCA model.” The DIBR method was used to determine the weight coefficients of the criteria, while the selection of the optimal strategy, from the set of offered methods, was carried out by the MAIRCA method. This was done in a fuzzy environment with the aim of better treatment of imprecise information and better translation of quantitative data into qualitative data. In the research, an analysis of the model’s sensitivity to changes in weight coefficients was performed. Additionally, a comparison of the obtained results with the results obtained using other multicriteria decision-making methods was conducted, which validated the model and confirmed stable results. In the end, it was concluded that the proposed MCDM methodology can be used for choosing a strategy in the defense system, that the results of the MCDM model are stable and valid, and that the process has been improved by making the choice easier for decision makers and by defining new and more comprehensive criteria for selection.

Abstract The outbreak of the coronavirus disease 2019, caused by the SARS-CoV-2 virus, has prompted global health concerns. In response, researchers have been conducting investigations on active compounds in plants that may hold the potential to inhibit the proliferation of the virus. The aim of this study was to simulate and predict structural interactions of selected compounds isolated from 28 endemic plants of Bosnia and Herzegovina against the main protease (Mpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), spike glycoprotein and uridylate-specific endoribonuclease (NendoU) of SARS-CoV-2. The majority of compounds, especially hesperidin, showed great binding affinity to the target proteins. The highest affinity for Mpro was observed for genistein and hesperidin, while in terms of structural interactions, both compounds achieved interactions of interest. Hesperidin and luteolin were the compounds with the highest binding affinity for PLpro, but no significant interactions were observed. For RdRp, hesperidin and quercetin showed the highest binding affinity, where both compounds formed interactions of interest. Hesperidin and fisetin were the compounds with the highest binding affinity for spike glycoprotein, and both compounds achieved significant interactions. The highest affinity for NendoU was obtained for hesperidin and isorhamnetin, where both compounds formed interactions of interest. Although these findings appear encouraging, further research is needed, which includes in vitro and in vivo assessments, along with clinical trials, to provide evidence for the potential therapeutic uses of these plants.

Flood quantile estimation in ungauged basins is often performed using regional analysis. A regionalization procedure consists of two phases: the definition of homogeneous regions among gauged basins, i.e., clusters of stations, and information transfer to the ungauged sites. Due to its simplicity and widespread use, a combination of hierarchical clustering by Ward’s algorithm and the index-flood method is applied in this research. While hierarchical clustering is very efficient, its shortcomings are the lack of flexibility in the definition of clusters/regions and the inability to transfer objects/stations from one cluster center to another. To overcome this, using silhouette width for induced clustering of stations in flood studies is proposed in this paper. A regionalization procedure is conducted on 53 gauging stations under a continental climate in the West Balkans. In the induced clustering, a negative silhouette width is used as an indicator for the relocation of station(s) to another cluster. The estimates of mean annual flood and 100-year flood quantiles assessed by the original and induced clustering are compared. A jackknife procedure is applied for mean annual flood estimation and 100-year flood quantiles. Both the Hosking–Wallis and Anderson–Darling bootstrap tests provide better results regarding the homogeneity of the defined regions for the induced clustering compared to the original one. The goodness-of-fit measures indicate improved clustering results by the proposed intervention, reflecting flood quantile estimation at the stations with significant overestimation by the original clustering.

Only several cases of postprocedural choleresis (biliary hyperproduction) were reported, and guidance on management is scarce, although an application of octreotide was anecdotally described. We herein present a rare post-obstructive choleresis complicated with acute kidney injury due to dehydration, successfully treated with an off-label application of octreotide. A 58-year-old female, following cholecystectomy and choledochotomy with numerous stones extraction, developed excessive bile loss via a T-tube complicated with acute kidney injury. Despite aggressive fluid replacement, the patient continued to deteriorate, prompting a trial of subcutaneous octreotide 0.1 mg three times per day over five days. Therapy yielded a rapid decline in bile production with improved diuresis and normalizing kidney function. The patient was discharged with a ligated T-tube, which we removed a month later. The followup was unremarkable, with normalized laboratory findings and symptom-free. Early use of octreotide could help resolve complicated biliary hyperproduction; however, further research is required to determine the risks and benefits of such an approach.

Aim: To present a very rare case of empyema cavuma septi pellucidi. Case report: A 5-year-old male child was admitted to the Department of Infectious Diseases Cantonal Hospital Zenica because of fever (38.30C), headache and vomiting. The patient developed intracranial hypertension as a result of a compressive purulent collection formed due to meningitis between the lamine of the septum pelucidum with consequent intracranial hypertension. Conclusion: The decision regarding the modality of treatment was not easy. We considered that empyema evacuation using the transcallosalinterhemispheric approach allows the complete removal of purulent collection and the placement of drainage, which allows additional emptying of the empyema cavity and prevents empyema recurrence. Empyema evacuation with drainage and antibiotic therapy have shown beneficial results.

Objective – The aim of the study was to establish the prevalence of hearing and sight impairment, and the differences in relation to school grade and sex in school children in the area of the Jajce municipality.Materials and Methods – Screening of sight and hearing impairment in school children took place in 2018 and 2019. Vision screening covered a total of 1002 students from 1st to 5th grades, and hearing screening 768 students from 2nd to 5th grades in all central and district (rural) schools in the area of the municipality of Jajce.Results – Of the total number of students covered by the vision screening, in 163 (16%) some impairment was noticed, and they were sent for further diagnostic testing by a specialist. In relation to sex, there was a higher percentage of girls, 60%, than boys, 40%. In relation to screening of hearing, 44 (6%) of the students were sent for further diagnostics, of which 57% were boys and 43% girls. During the vision screening, 5% of the students were wearing dioptric glasses. In relation to age, the largest number of students were in first grade, 14 (27%), then in second grade, 10 students (19%). Conclusion – In this study, the results showed that a large percentage of school children were found with hearing and vision impairment, which indicates the pressing need to continue running these preventive programmes.

In a ternary mixture with the Soret effect, the interplay between cross-diffusion, thermodiffusion, and convection can lead to rich and complex dynamics including spatial patterns and oscillations. We present an experimental and three-dimensional numerical study of dynamic regimes in the toluene-methanol-cyclohexane ternary mixture with the Soret effect in the geometry of a thermogravitational column. An important feature of the system is that for the first component, toluene, the Soret and thermodiffusion coefficients have opposite signs, which triggers the oscillatory instability. Our experiments and numerical analysis show that the primary long-wave instability manifests itself in the form of a standing wave, and the secondary one emerges in the form of a swinging pattern. The computational model provides insight into the role of cross-diffusion coefficient D12 in the emergence and development of oscillatory instability. This study demonstrates that the long-wave oscillatory instability in transverse direction occurs only within a limited range of the D12 values and outside of this range it decays to a stationary pattern of either Turing-like or monotonic instability.

Objective: To investigate the arterial stiffness and risk factors in adolescence. Arterial stiffness often (AS) results from the degenerative process of the media layer of elastic arteries causing rigidity of the arteries. Arterial stiffness increases with age and it is associated with several risk factors as a disease predictor. But, arterial stiffness can be also increased in a healthy arteries as well. The increased sympathetic activity promotes vasoconstriction of resistant blood vessels i.e. arteries and arterioles that result in peripheral vasoconstriction. Adolescence age is the most important period of life for promoting future health. The certain dynamic risk factors in adolescence like, emotional dysregulation, psychological family stress, education pressure, lack of sleep, gambling, substance abuse, smartphone overuse and obesity can cause arterial stiffness. Design and method: The prospective open randomized study was designed. Adolescence age between 10 and 19 years have been investigated for increased arterial stiffness and risk factors. The inclusion criteria was healthy adolescence, while exclusion criteria was any disorder present. Arterial stiffness, non-invasive blood pressure and pulse wave datas have been measured using Agedio device. The risk factors were evaluated in every subject. The vascular age have been outlined as the final measure. Results: The preliminary results indicate the increase of Augmentation Index and Coefficient of Reflection. The average percentage of Augmentation Index was 40% and Coefficient of Reflection 65% (normal value 28% and 60% respectively). The main risk factors were educational pressure, lack of sleep and smartphone influence. The vascular age was on average, 3 years higher than biological age. Conclusions: Arterial stiffness in adolescence is increased mainly by peripheral vasoconstriction, manifested with Augmentation index and Coefficient of wave Reflection.

Abstract Advances in robotic technology have improved standard techniques in numerous surgical and endovascular specialties, offering more precision, control, and better patient outcomes. Robotic-assisted interventional neuroradiology is an emerging field at the intersection of interventional neuroradiology and biomedical robotics. Endovascular robotics can automate maneuvers to reduce procedure times and increase its safety, reduce occupational hazards associated with ionizing radiations, and expand networks of care to reduce gaps in geographic access to neurointerventions. To date, many robotic neurointerventional procedures have been successfully performed, including cerebral angiography, intracranial aneurysm embolization, carotid stenting, and epistaxis embolization. This review aims to provide a survey of the state of the art in robotic-assisted interventional neuroradiology, consider their technical and adoption limitations, and explore future developments critical for the widespread adoption of robotic-assisted neurointerventions.

Connected, Cooperative, and Autonomous Mobility (CCAM) will take intelligent transportation to a new level of complexity. CCAM systems can be thought of as complex Systems-of-Systems (SoSs). They pose new challenges to security as consequences of vulnerabilities or attacks become much harder to assess. In this paper, we propose the use of a specific type of a trust model, called subjective trust network, to model and assess trustworthiness of data and nodes in an automotive SoS. Given the complexity of the topic, we illustrate the application of subjective trust networks on a specific example, namely Cooperative Intersection Management (CIM). To this end, we introduce the CIM use-case and show how it can be modelled as a subjective trust network. We then analyze how such trust models can be useful both for design time and run-time analysis, and how they would allow us a more precise quantitative assessment of trust in automotive SoSs. Finally, we also discuss the open research problems and practical challenges that need to be addressed before such trust models can be applied in practice.