For Utilities, each substation is regarded as an asset. Managing of assets is one of domains of Asset Management including Life Cycle Costing (LCC) as a decision-making criterion. However, LCC as a decision-making criterion should be applied on an entire substation taking into account all of the potential cost influences for the purpose of achieving of an effective substation management. Asset management as a decision-making process should be observed within a larger context and should be more focused on risk management, as all real decisions include an element of risk due to present uncertainties. Two promising avenues are explored in regards to more comprehensive and rigorous up-front planning through usage of Information Technology (IT). While up-front planning falls under the domain of Lean philosophy, Building Information Modeling (BIM) falls under the category of agile decision-support tools. Utilization of both is explored from a perspective of design-uncertainties under both product and process design. Standard specifications and standard designs are another form of applied Lean Philosophy that reduces design-uncertainty and variability. However, a range of technical solutions stemming out of the standardization can be quite wide. Customization involves specification and design of new / innovative designs with wide range of technical solutions as well. Due to external pressures focused on shortening of the project delivery time, there is a need for a faster project time throughput. This is reflected in the form of a requirement for more rapid engineering decision-making and faster decision cycles. Streamlining of a decision-making process related to the engineering is all about engineers’ awareness of the situation from the project level perspective coupled with utilization of decision-support tools for creation and reuse of knowledge. Plan – Do – Study – Orient (PDSO) cycle is a decision-making model that supports creation and reusability of knowledge along with providing an explanation in regards to the time dimension relating to decision-making, and as such is presented in this paper. The rigid busbar system design is an iterative process influenced by many factors, defined either as design variables or design constraints. As rigid busbars are gaining more popularity for both greenfield and brownfield investments, the rigid busbar system design is explored from a perspective of decision-making streamlining. The case of the rigid busbar system design of El Chaparral project in El Salvador is given.

Aim To investigate the influence of specific intrapopulation genetic structures on interpopulation relationships. Special focus was the influence of island population isolation on the substructuring of the Croatian population, and the influence of regional population groups on the substructuring of Southeast European populations. Methods Autosomal short tandem repeat (STR) loci were analyzed by using four forensic parameters: matching probability (PM), power of discrimination (PD), power of exclusion (PE), and polymorphic information content (PIC) on a sample of 2877 unrelated participants of both sexes. A sample set comprising 590 participants was analyzed for the first time, and 2287 participants were included from previous studies. The analysis was performed with PowerStats v. 1.2. Results The analysis of forensic parameters for all nine loci in the Croatian subpopulations showed the largest deviations in the populations of the islands of Korčula and Hvar. The smallest deviations were found in the mainland population. As for Southeast European populations, the largest deviations were found in the population of North Macedonia, followed by Romania, Albanians from Kosovo, and Montenegro, while the smallest deviations were found in the population of Hungary. Conclusion The comparison of forensic parameters between different subpopulations of Croatia and Southeast Europe indicates that the isolation of individual Croatian subpopulations and rare alleles in their gene pool affect the values of forensic parameters. Specific features of (sub)populations should be taken into account for appropriate sampling of the total population when creating a DNA database of STR markers.

Aim To use the method of meta-analysis to assess the influence of island population isolation on the sub-structuring of the Croatian population, as well as the influence of regional population groups on the sub-structuring of the Southeastern European population with regard to basic population genetic statistical parameters calculated by using STR locus analysis. Methods Bio-statistical analyses were performed for 2877 unrelated participants of both sexes from Southeastern Europe. Nine autosomal STR loci (D3S1358, vWA, FGA, TH01, TPOX, CSF1PO, D5S818, D13S317, and D7S82) were analyzed by using standard F-statistics and population structure analysis (Structure software). Results Genetic differentiation of Croatian subpopulations assessed with the FST method was higher at the level of the Croatian population (0.005) than at the level of Southeastern Europe (0.002). The island of Vis showed the most pronounced separation in the Croatian population, and Albanians from Kosovo in the population of Southeast Europe, followed by Croatia, Bosnia and Herzegovina, and Hungary. Conclusion The higher structure of Croatian subpopulations in relation to Southeastern Europe suggest a certain degree of genetic isolation, most likely due to the influence of endogamy within rural island populations.

Abstract The Logistics Performance Index (LPI) performed by the World Bank is an indicator of the logistics environment quality of a country in which logistics operators act. The LPI is an interactive tool designed to help countries identify challenges, innovative solutions, and opportunities they face in their work in the field of trade and logistics. The aim of this paper is to conduct a comparative analysis and ranking of the LPI of the countries in the Western Balkans (Bosnia and Herzegovina, North Macedonia, Albania, Serbia and Montenegro), calculated by the World Bank for 2018, using an integrated Criteria Importance Through Intercriteria Correlation (CRITIC)-Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) model and thus show the real picture of the logistics environment. In order to determine the performance of countries and show the overall logistics performance, six key dimensions are used: customs, infrastructure, international transport, logistics capability, tracking and tracing of goods and shipment delivery within scheduled or expected times. Using the CRITIC method, the weight values of the previously mentioned six criteria were calculated, whereby the criterion related to shipment delivery within scheduled times was singled out as the most significant criterion. Then, by applying the MARCOS method, the countries of the Western Balkans were ranked on the basis of the six defined criteria. Based on the results obtained, the best-ranked country is Serbia. The analysis of the sensitivity of the results to changes in the significance of the criteria does not show significant changes in the ranking.

Using recent advancements in high-performance computing data assimilation to combine satellite InSAR data with numerical models, the prolonged unrest of the Sierra Negra volcano in the Galápagos was tracked to provide a fortuitous, but successful, forecast 5 months in advance of the 26 June 2018 eruption. Subsequent numerical simulations reveal that the evolution of the stress state in the host rock surrounding the Sierra Negra magma system likely controlled eruption timing. While changes in magma reservoir pressure remained modest (<15 MPa), modeled widespread Mohr-Coulomb failure is coincident with the timing of the 26 June 2018 moment magnitude 5.4 earthquake and subsequent eruption. Coulomb stress transfer models suggest that the faulting event triggered the 2018 eruption by encouraging tensile failure along the northern portion of the caldera. These findings provide a critical framework for understanding Sierra Negra’s eruption cycles and evaluating the potential and timing of future eruptions.

Background: Nowadays, most women of reproductive age utilize various methods of contraception to avoid undesired pregnancy and regulate menstrual cycles. Objective: The aim of this study is to evaluate current sexual patterns, menstrual health status and use of contraceptive methods in reproductive aged females in Bosnia and Herzegovina during the COVID-19 pandemic. Methods: This cross-sectional study was conducted in the period between February 21st and March 5th 2022 via an online anonymous questionnaire which was distributed using social media platforms. Results: Menstrual periods were normally regular in 269 (85.7 %) of the females, whereas 45 (14.3 %) experienced irregular menstrual cycles. Females report having either one sexual partner 149 (47.5%) or no sexual partners 76 (24.2%) and typically no 92 (29.3%) or frequent (more than 8 sexual intercourses) sexual intercourses per month. The usage of contraceptive methods was reported among the majority 212 (67.5%) and mostly by using of male condom 104 (33.1%), followed by the withdrawal method 64 (20.4%), oral contraceptive pills 35 (11.1%), emergency contraceptive pills “after 24h” 2 (0.6%) and intrauterine device 7 (2.2%). The usage of contraceptive methods was higher among younger females (X2=18.07, p<0.001) and among those who were employed (X2=10.86, p<0.001). Those who used oral contraceptive pills used mostly pills that are combination of progesterone and oestrogen 32 (91.4%) and for the purpose of regulation of menstrual cycles 26 (74.2%) and to prevent unwanted pregnancies 9 (25.8%). Females who had no sexual intercourses per month (OR+0.27, 95% CI 0.09-0.79, p=0.018) were less likely, while those who had irregular menstrual cycles (OR=2.44, 95% CI 1.04-5.71, p=0.039) were more prone to use oral contraceptive pills. Conclusion: Bosnia and Herzegovina reproductive aged female had relatively regular menstrual cycles, the majority used modern contraceptive methods to prevent unwanted pregnancies or for the regulation of menstrual cycles during the COVID-19 pandemic.

Background: COVID-19 has different presentations from mild flu like symptoms such as anosmia, dysgeusia, fever, sore throat, cough, dyspnea, headache, abdominal pain and diarrhoea to severe COVID-19 with the development of acute respiratory syndrome (ARDS), septic shock, metabolic acidosis, coagulation dysfunction, multiorgan failure or even death. Objective: The aim of this research project was to present and highlight the outcomes of the vaccination against COVID-19 and the widespread use of antibiotics during the initial admission and treatment of COVID-19 patients in out of hospital settings. Methods: This observational cross-sectional study was conducted between September 1st and September 24th 2021, during the fourth wave of COVID-19 outbreak in Bosnia and Herzegovina, among the patients admitted to the primary health care COVID-19 centre of Canton Sarajevo in Bosnia and Herzegovina. Results: Patients were mostly female 213 (53.3%), with a mean age of 48.8±18.6, with hypertension 129 (32.3%) or diabetes mellitus 35 (8.7%) as comorbidities and being COVID-19 unvaccinated 236 (59.0%) COVID-19 unvaccinated patients expressed more fever (X2=9.93, p<0.05), had typical COVID-19 chest X ray presentation (X2=6.08, p<0.05) and abnormal lung auscultation sounds (X2=5.43, p<0.05). Out of all patients, 312 (78.0%) have received antibiotics and 3 (0.75%) antivirotics such as favipiravir as therapy for the treatment of COVID-19. The mean duration of the antibiotic regime was 10.2 ± 7.5 days with a minimum of 3 days and maximum of 62 days. The minimum CRP value when antibiotics were prescribed was 0.1 (ref. value <5mg/l). The most prescribed antibiotic was doxycycline 172 (43.0%), followed by ceftriaxone 139 (34.7%) and azithromycin 108 (27.0%). Conclusion: Our study showed that vaccination acts protective for the development of severe COVID-19 forms, as well as that antibiotics were overused among COVID-19 infected. The outcome of such malpractice could lead to antimicrobial resistance which will be seen in further years. Governmental agencies should advise physicians to change these trends.

Abstract Background: Owing to the heaviness of setbacks and shocks companies frequently face from the internal/external business environment, building solid organizational resilience and shifting towards strategic sustainability have become the top demands in today’s wavering business world. Objectives: This study aimed to determine whether strategic sustainability orientation influences organizational resilience and how this relationship is moderated by firm size. Methods/Approach: This study uses a methodology structured around the stakeholder theory and embraces multiple regression analysis grounded on collected data from 124 enterprises in Bosnia and Herzegovina ambience. Results: Findings from the research revealed that strategic sustainability orientation significantly and positively influences organizational resilience and its three sub-components: anticipation, coping and adaptation capabilities. Results also uncovered that the Small size firms were significantly diverse from the Large and Medium size firms in terms of the influence of strategic sustainability orientation on three capabilities of organizational resilience. Conclusions: In addition to literature enriching in sustainability and organization by supplying empirical evidence of strategic sustainability orientation influence on organizational resilience, this study proposes and validates instruments for measuring strategic sustainability orientation and organizational resilience.

Background: Lipids and lipoproteins are significantly involved in maintaining structural and functional components of the human brain and neurons, but their role in the development of Alzheimer’s disease (AD) and vascular dementia (VD) remains unclear. Objective: The aim of the present study was to explore the differences in the standard and novel lipid profile parameters in patients with AD and VD, stratified by the degree of cognitive impairment (CI). Methods: Present study included 66 patients with AD, 50 patients with VD, and 60 control subjects. For an evaluation of the global cognitive function the Montreal Cognitive Assessment (MoCA) test was used. In order to distinguish patients with VD from those with AD the Hachinski ischemic score was used. Plasma total cholesterol (TC), high-density lipoprotein -cholesterol (HDL-C), and triglycerides (TG) levels were determined using standard enzymatic colorimetric techniques, whereas the Friedewald formula was used to calculate low-density lipoprotein-cholesterol (LDL-C) levels. The non-traditional lipid indices such as TG/HDL-C, TC/HDL-C, and LDL-C/HDL-C ratio were separately calculated. The differences between the groups were analyzed with the Kruskal Wallis test followed by the Mann-Whitney test or with ANOVA followed by the Tuckey posthoc test. Results: Results of the conducted study have found that the patients in AD group with moderate CI and patients in AD group with severe CI exhibited significantly lower levels of serum TC, TG, LDL-C, VLDL-C, Non- HDL-C, atherogenic index, TG/HDL-C, TC/HDL-C and LDL-C/HDL-C compared to cognitively normal control subjects. Moreover, patients in VD group with severe and moderate CI had significantly lower level of TG compared to control group of subjects. Our results have also shown that patients in AD group with moderate CI had significantly lower level of TC, TG, LDL-C, Non-HDL-C, atherogenic index, TG/HDL-C, TC/HDL-C compared to VD patients with moderate CI. In addition, patients in AD group with severe CI had significantly lower level of TC, LDL-C, Non-HDL-C and TC/HDL-C compared to VD patients with severe CI. Conclusion: The results of this study have shown dysregulation of lipid metabolism in AD and VD patients with different degree of CI. In both moderate and in severe CI, patients with AD had lower levels of majority of standard and novel lipid parameters compared to patients with VD. Further larger prospective studies are required to elucidate the accuracy of standard and novel lipid parameters in the assessment of different degree of CI in AD and VD.

Neural Combinatorial Optimization approaches have recently leveraged the expressiveness and flexibility of deep neural networks to learn efficient heuristics for hard Combinatorial Optimization (CO) problems. However, most of the current methods lack generalization: for a given CO problem, heuristics which are trained on instances with certain characteristics underperform when tested on instances with different characteristics. While some previous works have focused on varying the training instances properties, we postulate that a one-size-fit-all model is out of reach. Instead, we formalize solving a CO problem over a given instance distribution as a separate learning task and investigate meta-learning techniques to learn a model on a variety of tasks, in order to optimize its capacity to adapt to new tasks. Through extensive experiments, on two CO problems, using both synthetic and realistic instances, we show that our proposed meta-learning approach significantly improves the generalization of two state-of-the-art models.