Brain-computer interfaces (BCIs) allow individuals with limited speech and physical abilities to communicate with the surrounding environment. Such BCIs require calibration sessions which is burdensome for such individuals. We introduce a transfer learning approach for our novel hybrid BCI in which brain electrical activity and cerebral blood velocity are recorded simultaneously using Electroencephalography (EEG) and functional transcranial Doppler ultrasound (fTCD) respectively in response to flickering mental rotation (MR) and word generation (WG) tasks. With the aim of reducing the calibration requirements, for each BCI user, we used mutual information to identify the top similar datasets collected from other users. Using these datasets and the dataset of the current user, features derived from power spectrum of EEG and fTCD signals were calculated. Mutual information and support vector machines were used for feature selection and classification. Using the hybrid combination, an average accuracy of 93.04% was achieved for MR versus baseline whereas WG versus baseline yielded average accuracy of 90.94%. As for MR versus WG, an average accuracy of 92.64% was obtained by hybrid combination compared to 88.14% obtained by EEG only. Average bit rates of 11.45, 17.24, and 19.72 bits/min were achieved for MR versus WG, MR versus baseline, and WG versus baseline respectively. The proposed system outperforms the state of the art EEG-fNIRS BCIs in terms of accuracy and/or bit rate.

The use of Distributed Generation (DG) throughout the world increasing. DG siting and sizing is an important engineering consideration, which is inherently influenced by the system load and DG power output uncertainties. This paper presents research results of the uncertainty influence on DG allocation problem. This influence is investigated using a constrained optimization problem for power loss reduction. The optimization is performed using Genetic Algorithm. The power system load and DG power output uncertainties are addressed using a possibilistic (α – cut method). The algorithm is applied to realistic distribution system to demonstrate its practical relevance. Results indicate that DG can reduce losses. and that uncertainties play a major role in final optimisation results. This paper contributes to the existing knowledge by applying, to a realistic test power system, a DG allocation method, which considers the influence of load and generation uncertainties on optimization results.

On February 12th, 2019 passed away academician Ljubomir Berberovic. He was born in Sarajevo in 1933. He studied medicine, biology and philosophy at the universities in Ljubljana and Sarajevo. Graduated in Biology at the Faculty of Philosophy at the University of Sarajevo, in biology in 1958 from the Natural-Mathematics Department. In the same department he was elected assistant in 1959. Since 1961 he has been employed by the Department of Biology at the Faculty of Natural Sciences and Mathematics in Sarajevo. In 1964, Ljubomir Berberovic defended his doctoral dissertation on the topic „The Microevolution of the Species Eobania Vermiculata on the Central Adriatic Coast and the Islands”. For an assistant professor on the subject Organic Evolution with Genetics, he was elected in June 1964, for a professor in January 1970 and in a full professor in June 1975. In addition to the Faculty of Natural Sciences and Mathematics, he was a teacher at the subjects of Genetics, Evolution, Anthropology at several other faculties of the University of Sarajevo, including Medical faculty. He was a lecturer at several universities abroad. Academician Ljubo Berberovic is the author of a large number of academic and scientific publications from three scientific areas: Genetics Population, with an emphasis on human populations, Karyology and Cytotaxonomy, with an emphasis on studying freshwater fish and the history and philosophy of natural sciences.

Attila Naszlady, MD, PhD. (1931-2015) was born in Budapest, Hungary. He was one of the prominent and influential Medical informatics experts and most famous pioneers of Medical informatics in South-Eastern Europe, recognizable internationally (1-3). Graduated at Faculty of medicine at Semmelweis University in Budapest in the year 1958. Specialist in Internal medicine he became in 1965.

Abstract Today’s cybercrimes are much more difficult to detect and prosecute than traditional crimes. In the investigation of cybercrimes, law enforcement agencies follow similar techniques to traditional crimes that, however, have to be modified to meet the unique conditions and requirements of virtual space. This paper examines cybercrime profiling techniques prevalent today, and focuses on the feasibility of applying geographic profiling technique to cyber offenders. The primary assumption of the research is that for most types of cybercrime, the steps during the procedure of committing criminal act are not random. For example, the choice of the victim, the choice of crime location, similar characteristics, follow a certain logic, which could provide information about the offender’s crime. Testing the utility of a geographical profiling has been carried out on real cybercrime samples obtained by law enforcement agencies. This paper aims to apply the concept of geographic profiling to the issue of cybercrime that involve a physical world, targeting two types of cybercrimes: credit card skimming and spear phishing. Specially developed GeoCrime geographic profiling software designed to assist in the mapping, spatial and statistical analysis of cybercrime patterns was used. The results of the study have shown the possibility of applying geographic profiling to certain types of cybercrimes and under the certain conditions. The importance of geographic profiling is also emphasized, especially in situations where little is known about the offender, such as in cybercrime, where offenders use the Internet to hide their identities and activities.

Introduction: : Diastasis recti abdominis is consequence of mechanical forces that, proportionally to uterus and fetus augmentation, make pressure on anterior abdominal wall. Muscle tonus in pregnancy is significantly impaired. Stress relaxation of connective tissues and modified statics often cause back and leg pain. Aim: To evaluate whether pregnancy augment the spinal column and abdominal muscles loading and to what extent, based on anthropometric measurements and software analysis. Methods: Twenty women participated in the study, having similar anthropometric measurements. Average height was 170 cm (mean), and weight 68.0 kg (mean). Three working postures were analyzed: upright (working posture 1), semi-bent (working posture 2) and bent (working posture 3) working postures by both non-pregnant and pregnant women. Simulation was made in software package CATIA. Results: Analysis was done for working postures at workplace in pre-pregnancy period (height 170 cm, weight 68 kg) and during pregnancy (height 170 cm, weight 80 kg). From analysis of posture 2 and posture 3 in pregnant woman, conclusion can be drawn that despite of the fact that our examinees did not carry any external/additional loads, in these two working postures the abdominal muscles suffered overloading. Conclusion: It is crucial to strengthen the entire musculature for women who wish to get pregnant. The pre-pregnancy exercises might improve the posture, tonus and boost chances for safe labor and delivery. Strong abdominal muscles are needed to unload the spine. It is highly recommended to prepare their musculature for pregnancy through various pre-pregnancy exercises.

Background: Multiple myeloma (MM) is a disease of B cell population with excessive secretion of immunoglobulins and presence of free light chains (FLCs) that are by products of immunoglobulin synthesis. Free light chains play crucial role in causing renal damage. Interleukine-6 (IL-6) supports the survival and/or expansion of MM cells by stimulating cells as well as by preventing programmed cell death. Aims and Objectives: The aim of this study was to evaluate serum and urine free light chains (FLC)measurement and compare with IL-6 levels in patients with different stages of Multiple Myeloma (MM) and control group of subjects and to determine their relevance in acute kidney injury occurrence. Materials and Methods: Recruitment of patients with MM (n=62) made the hematologist that followed clinical Solomon-Durie MM classification. Control group consisted of 20 healthy individuals. Results: Patients with MM and renal function injury had significantly higher concentration of urine κ chains compared to control group and group of MM without renal function injury (p<0.005), whereas this difference was not observed when the patients were divided into disease stages groups. Concentration of IL-6 was significantly higher in patients at MM steady stage compared to control group (p<0.001) and significant difference was also detected in patients with MM at relapse stage and control group (p<0.0005). Concentration of IL-6 in MM patients without renal function and with renal function injury was significantly higher compared to control group (p< 0.001; p<0.0005 respectively). Statistically significant correlation was determined between sera κ and urine κ chains (rho=0.437; p<0.01) as well as between urine λ and sera λ chains (rho=0.505; p<0.01) and between urine κ and urine λ chains (rho=0.364; p<0.01). Conclusion: Results showed that urine κ chains, sera κ chains and IL-6 are constructing a fine tuned net and point to conclusion that FLC and IL-6 are important for an early treatment response detection for patients with potentially reversible renal failure.

Aim: The aim of the study was to determine the differences in nutritional status and risk for malnutrition between nursing home and community-dwelling residents. Methods: Cross-sectional study included 146 nursing home residents and 300 community-dwelling elderly adults from four municipalities in Bosnia and Herzegovina. Anthropometric measurements, biochemical analyses, nutritive, functional and cognitive assessments were carried out. Nutritional status and risk for malnutrition were assessed by Mini Nutritional Assessment (MNA), Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II (Screen II) and the food intake analysis for the past 24 hours. Functional status was assessed by the Lawton scale, the Katz Independence Index, Timed Up and Go test, the Functional Reach Test. Mini Cog test and Six-item cognitive impairment test were used for the evaluation of cognitive functioning. Results: The incidence of high nutritive risk by SCREEN II (100%) and being “at risk for malnutrition” by MNA (81.60%) was higher among nursing home residents compared to community-dwellers. Community-dwelling elderly people had higher BMI (27.94 ± 4.73), weight (78.40 ± 13.99), height (167.69 ± 9.74), waist circumference (97.77 ± 12.88), hip circumference (104.61 ± 11.47), mid-arm arm (27.54 ± 3.58), hip (27.54 ± 3.58) and calf circumference (34.02 ± 5.16 ). Statistical differences in regards to place of living were found in functional status (p<0.001), cognitive functioning (p<0.001) and hand grip strength (p<0.001). Conclusion: The frequency of malnutrition and high nutritional risk was higher in respondents who were living in the nursing homes compared to community-dwellers. The results of this study showed that health professionals involved in the care for institutionalized elderly people should implement routine screening of malnutrition within the comprehensive geriatric assessment in their daily practice.