The global world is in a period of "permacrisis", which is defined as a prolonged period of uncertainty and instability. Circumstances in the world in all spheres of social action are changing very quickly, and therefore the models of action must also change quickly. This is also the case with health care systems in countries. New challenges for public health and health systems is a strong health transition conditioned by demographic and epidemiological transition, then accelerated environmental changes and technological changes. We live in a time when the frequency of crises is increasing - including public health crises - climate change, the emergence of new infectious diseases - pandemics, accelerated population migration, the rise of consumerism and the significant influence of commercial determinants of health, which significantly increases the risk factors in the early onset and development of chronic diseases - diseases of the heart and blood vessels, chronic pulmonary obstructions, malignant diseases, mental health disorders, etc. In order for the health care system to provide timely and quality health care to each individual, and finally to the entire population, which is not necessarily only acute health care, but lifelong health care, from health promotion, through prevention, diagnostics, treatment and rehabilitation, it is necessary to know all the circumstances in which people live and work, the most important of which are four groups of factors: socioeconomic, environmental, genetic and cultural. Modern healthcare systems require significant change management at all levels within the system, characterized by the proactive role of healthcare services, mastery of healthcare planning techniques, healthcare needs assessment and, finally, digital health. Change management becomes a "conditio sine qua non" at all levels of health care in all countries, at all levels of health care in order to increase technical and allocative efficiency and outcomes for the health of the population. Therefore, it is necessary to develop more significant regional cooperation for the modification and refinement of educational models for health professionals, which would be in "real time" and through which everyone would quickly adapt to global changes.

This study empirically explores short run and long run causality between institutional financial inclusion and income inequality in 22 members of European Union (EU) divided in two subpanels: Old EU members and New EU Member states (NMS). A panel VECM (PVECM) approach is utilized to observe the dynamic causal relationship between financial inclusions on income inequality when control the effect of economic development on inequality. The current level of financial inclusion in the old EU members only through expansion ATMs services lead to decrease income inequality in long run while it contributes through expansion commercial bank branches in short run. On the contrary, the study finds weak and subdued effect financial inclusion on income inequality in the NMS countries in long run, while only expansion commercial bank branches lead to decrease income inequality in short run. The results show that financial inclusion measured by commercial bank branches contributes to more equal income distribution for both regions, only in the short run. In fact, deepening institutional financial inclusions by increasing availability and diversify of specialized financial products and ATM services are still needed to address impediments to financial inclusion, especially in the NMS.

Social communities are prone to evolutionary changes that are initiated sometimes by the dominant minority, and sometimes under the influence of the quantitative energy of the oppressed minority. Partnerships have been prone to change for centuries. From the traditional patriarchal family, through the recognition of the rights of extramarital unions, and the acceptance of same-sex civil unions, in order to promote samesex marriage in the last decade. The paper deals with the review of the development and implementation of the idea of recognizing the right to marriage for same-sex couples, the global attitude towards the same with special reference to the Republic of Serbia. Namely, the Republic of Serbia does not recognize same-sex marriages, nor does it recognize them by law, no matter where they were concluded, and in this sense, the paper explains the possibilities of inheritance between same-sex partners, regardless of the fact that legal inheritance is impossible.

Henry Kissinger, one of the most influential and controversial diplomats of the late 20th and early 21st centuries, played a pivotal role in shaping the geopolitical landscape of the Middle East through his shuttle diplomacy following the Yom Kippur War. This article explores the multidimensional and layered nature of Kissinger?s strategy, grounded in the geostrategic concepts of Saul Bernard Cohen. While Kissinger?s mission aimed to end hostilities between Israel and its Arab neighbours, it also sought to counterbalance the expanding Soviet influence in the region, a critical aspect often overlooked in the existing scholarly work. By examining the geopolitics of oil, power, and influence through the lens of the Carter Doctrine, this study illustrates how Kissinger?s realpolitik not only influenced the Arab-Israeli peace negotiations but also altered the dynamics of the Cold War, thereby reshaping the course of history.

This research aimed to examine the applicability of the Pivot Profile (PP) technique in detecting adulteration in acacia honey from the Tuzla region, Bosnia and Herzegovina (B&H). The PP technique captured the relative meaning of descriptors and gathered free descriptions of differences between a target product and a pivot product (PVT), which served as a standard. Four pairs of samples were evaluated: original acacia honey (PVT) versus honey samples adulterated with 20%, 40%, 60%, and 80% fructose-glucose syrup. The sensory assessment involved 72 participants (25 women and 47 men), all acacia honey producers aged from 20 to 55 years of age. The chi-square test (ch² = 3032.37, p < 0.001) revealed significant statistical differences among values, indicating that the consumer panel effectively distinguished the samples. The chi-square test per cell was used to explore variation within the data matrix, identifying descriptors significantly differing from PVT in citation frequency. A total of 48 sensory attributes were generated (5 for appearance, 14 for odours, 4 for basic tastes, 3 for aftertastes, 16 for flavours, 2 for trigeminal effects, and 4 for texture). Correspondence Analysis (CA) was employed to visually represent sensory changes in honey samples based on adulteration levels, illustrating consumer perception of samples and attributes. CA effectively explained nearly 60% of the variability observed across the initial two dimensions, thus emphasizing the connection between sensory alterations and consumer perception. The results revealed a reduction in aroma and appearance attributes, along with occurrences of sensory defects such as off-flavours, unpleasant trigeminal effects, and altered viscosity properties. PP technique provided detailed information about each sample, assessing similarities and differences compared to PVT in a single session using multivariate techniques, contrasting with traditional trained or expert assessments. The PP technique appears promising for further exploration in vocabulary use and data analysis, not only for other honey types but also for various food products susceptible to adulteration.

Sleep deprivation is a significant contributor to various diseases, leading to poor cognitive function, decreased performance, and heart disorders. Insomnia, the most prevalent sleep disorder, requires more effective diagnosis and screening for proper treatment. Actigraphic data and its combination with physiological sensors like electroencephalogram (EEG), electrocardiogram (ECG), and body temperature have proven significant in predicting insomnia using machine learning methods. Studies focusing solely on actigraphic data achieved an accuracy of 84%, combining it with other wearable devices increased accuracy to 88%, and 2-channel EEG alone yielded an accuracy of 92%, but limits scalability and practicality in real-world settings. Here we show that using the hybrid approach of incorporating both recursive feature elimination (RFE) and principal component analysis (PCA) on sleep and heart data features yields outstanding results, with the multi-layer perception (MLP) achieving an accuracy of 95.83% and an F1 score of 0.93. The top-ranked features are predominantly sleep-related and time-domain RR interval. The dependent variables in our study have been extracted from the self-report Pittsburgh Sleep Quality Index questionnaire responses. Our findings emphasize the importance of tailoring feature sets and employing appropriate reduction techniques for optimal predictive modeling in sleep-related studies. Our results demonstrate that the ensemble classifiers generalize well on the dataset regardless of the feature count, while other algorithms are hindered by the curse of dimensionality.