Concepts developed in the field of political economy offer a useful framework for explaining, from a western perspective, the phenomenon of Trumpism as an expression of anti-system politics emerging rich democracies in response to the effects of neoliberal growth models and the cartel forms of political parties. While insightful, this theory does not account for the role of media in presumed relationships. The article aims to offer, through exploratory analysis, the theoretical basis for conceptualization of the links between media, anti-system politics, and growth models. Trumpism developed, we argue, under the conditions of destabilization of traditional institutional arrangements of the news business, which enabled and limited the functions of journalism important for the democratization of the „Western“society. The paper contributes to the development of an alternative theoretical approach to the study of the media aspect of Trumpism concerning the prevailing corpus of ideas about "post-truth", "false news" and "echo chambers".

Abstract: The paper argues that the narrative of the independent Republic of Bosnia and Herzegovina and of its capital city Sarajevo under siege (1992-1995) was built on the trope of Sarajevo’s European, Western-oriented, cosmopolitan cultural identity, based on the image initially nurtured by Socialist Yugoslavia. In the new context of the implosion of the Socialist Federal Republic of Yugoslavia (1945 -1991) the siege of Sarajevo and the war in one of the Yugoslav republics, Bosnia and Herzegovina, Yugoslav socialism was replaced by the multi-ethnic and cosmopolitan character of the young Republic of Bosnia and Herzegovina. I argue that the image of Sarajevo during the siege, as a by-product of foreign attention to the plight of the country and its citizens, was built on the pre-existing premises that promoted Socialist Yugoslavia as Western oriented and therefore progressive, in contrast to other communist countries beyond the Iron Curtain.

Donald Trump's term as President of the United States was marked by, among others: nationalism, populism, rejection of democracy, political arbitrariness, exclusivity towards racial and national minorities, xenophobia expressed towards immigrants, but also close (Mexicans) and distant peoples (Chinese), forcing divisions in American society, misogyny, spreading misinformation in all spheres and especially during the pandemic, belittling the attitude towards intellectuals, and especially constantlycalling out and insulting journalists. Injustice towards media houses and journalists did not stop during the entire term of Donald Trump, who called them 'fake news media' and 'enemy of the people, thus turning the public against them and creating big problems for them, which resulted in open violence during police protests. the assassination of African-American George Floyd, but also in the attack on Capitol Hill. All of these terms, along with some other features of his rule in domestic and foreign policy, are encompassed by a common denominator called ‘trumpism’. Although he was defeated in 2020 presidential election, his legacy remained significantly present in American society, but also outside it - on the American and Asian continents, but also in Europe, and especially in the Balkans. Using qualitative content analysis and comparative analysis of Donald Trump's communication model, especially in his relationship with political opponents, media houses and journalists, and the communication model of Balkan politicians, this paper deals with information and communication matrices that have been very successfully accepted and perfected by some politicians. Balkans through a special review of the spread of 'information disorder' in its three manifestations - misinformation, misinformation, and misinformation.

This study investigates interactive behaviors and communication cues of heavy goods vehicles (HGVs) and vulnerable road users (VRUs) such as pedestrians and cyclists as a means of informing the interactive capabilities of highly automated HGVs. Following a general framing of road traffic interaction, we conducted a systematic literature review of empirical HGV-VRU studies found through the databases Scopus, ScienceDirect and TRID. We extracted reports of interactive road user behaviors and communication cues from 19 eligible studies and categorized these into two groups: 1) the associated communication channel/mechanism (e.g., nonverbal behavior), and 2) the type of communication cue (implicit/explicit). We found the following interactive behaviors and communication cues: 1) vehicle-centric (e.g., HGV as a larger vehicle, adapting trajectory, position relative to the VRU, timing of acceleration to pass the VRU, displaying information via human-machine interface), 2) driver-centric (e.g., professional driver, present inside/outside the cabin, eye-gaze behavior), and 3) VRU-centric (e.g., racer cyclist, adapting trajectory, position relative to the HGV, proximity to other VRUs, eye-gaze behavior). These cues are predominantly based on road user trajectories and movements (i.e., kinesics/proxemics nonverbal behavior) forming implicit communication, which indicates that this is the primary mechanism for HGV-VRU interactions. However, there are also reports of more explicit cues such as cyclists waving to say thanks, the use of turning indicators, or new types of external human-machine interfaces (eHMI). Compared to corresponding scenarios with light vehicles, HGV-VRU interaction patterns are to a high extent formed by the HGV’s size, shape and weight. For example, this can cause VRUs to feel less safe, drivers to seek to avoid unnecessary decelerations and accelerations, or lead to strategic behaviors due to larger blind-spots. Based on these findings, it is likely that road user trajectories and kinematic behaviors will form the basis for communication also for highly automated HGV-VRU interaction. However, it might also be beneficial to use additional eHMI to compensate for the loss of more social driver-centric cues or to signal other types of information. While controlled experiments can be used to gather such initial insights, deeper understanding of highly automated HGV-VRU interactions will also require naturalistic studies.

In this paper, a novel gamma-shadowed two-ray with diffuse power (GS-TWDP) composite fading model is proposed. The model is intended for modeling propagation in the emerging wireless networks working at millimeter wave (mmWave) frequencies, and is obtained as a combination of TWDP distribution for description of multipath effects and gamma distribution for modeling variations due to shadowing. After derivation of the exact probability density function (PDF), cumulative distribution function (CDF) and moment generating functions (MGF) expressions are obtained. Proposed model is verified by comparing the analytically obtained results with those measured at 28 GHz and reported in literature. Two upper bound average symbol error probability (ASEP) expressions are then derived for M-ary rectangular quadrature amplitude modulation (RQAM) by employing Chernoff and Chiani approximations of Gaussian Q-function, and are used to investigate relationship between GS-TWDP parameters and system performance. All the results are verified by Monte-Carlo simulation.

Introduction Domestic violence is toxic to society. With approximately one in three women on average falling victim to domestic violence, systematic solutions are needed. To further complicate the issue, mounting research shows that COVID-19 has further exacerbated domestic violence across the world. Situations could be even more pronounced in countries like China, where though domestic violence is prevalent, there is a dearth of research, such as intervention studies, to address the issue. This study investigates key barriers to domestic violence research development in China, with a close focus on salient cultural influences. Methods A review of the literature on domestic violence in China in PubMed, PsycINFO, and Scopus was conducted to answer the research question. The search was focused on three themes, domestic violence, China, research, and cultural influences. Results The study findings show that categorizing domestic violence as a “family affair” is a key barrier to domestic violence research development in China—an incremental hindrance that prevents the public and policymakers from understanding the full scale and scope of domestic violence in China. In addition to abusers, witnesses, and victims, even law enforcement in China often dismisses domestic violence crimes as “family affairs” that resides outside the reach and realm of the law. The results indicated that mistreating domestic violence crimes as “family affairs” is a vital manifestation of the deep-rooted cultural influences in China, ranging from traditional Confucian beliefs in social harmony to the assumed social norms of not interfering with other people's businesses. Conclusion Domestic violence corrupts public health and social stability. Our study found that dismissing domestic violence cases as “family affairs” is an incremental reason why China's domestic violence research is scarce and awareness is low. In light of the government's voiced support for women's rights, we call for the Chinese government to develop effective interventions to timely and effectively address the domestic violence epidemic in China.

This paper analyzes the constitutional position of Bosnia and Herzegovina (BiH) between constitutional nationalism and human rights. In its judgments in Sejdić and Finci v. BiH, and Zornić v. BiH, the European Court of Human Rights (ECtHR) found that the BiH Constitution was not in line with the European Convention on Human Rights and Fundamental Freedoms (ECHR). Namely, the privilege of the three constituent peoples in the Constitution of BiH, the ECHR was assessed as contrary to the prohibited discrimination prescribed by the ECHR. In this sense, the paper analyzes the current Bosnian constitutional model of a form of consociational democracy or constitutional nationalism. The authors analyze the presumption of the ECtHR in terms of the (non) existence of a legitimate goal for maintaining discriminatory provisions in the Constitution of BiH. Also, the paper analyzes the importance of the implementation of the ECtHR judgment for the future of the rule of law in BiH.

Analysis of reports published by the leading national centers for monitoring wildfires and other emergencies revealed that the devastation caused by wildfires has increased by 2.96-fold when compared to a decade earlier. The reports show that the total number of wildfires is declining; however, their impact on the wildlife appears to be more devastating. In recent years, deep neural network models have demonstrated state-of-the-art accuracy on many computer vision tasks. In this paper, we describe the design and implementation of a lightweight wildfire image classification model (LW-FIRE) based on convolutional neural networks. We explore different ways of using the existing dataset to efficiently train a deep convolutional neural network. We also propose a new method for dataset transformation to increase the number of samples in the dataset and improve the accuracy and generalization of the deep learning model. Experimental results show that the proposed model outperforms the state-of-the-art methods, and is suitable for real-time classification of wildfire images.

When lexemes are borrowed from a foreign language they go through different phases of integration, typically divided into four types: phonetic, orthographic, morphological, and semantic. The question of which gender to assign to a loanword and which gender assignment criteria to apply is still ambiguous in linguistics. Therefore, the aim of this paper is to determine the regularities of gender assignment to lexicalized and non-lexicalized anglicisms in German within linguistics and glottodidactics. In addition, the present study also investigates the question of whether deviations in gender assignment, in the case of lexicalized anglicisms from our corpus, can be explained by their semantic differences. The corpus for our research is composed of a total of 194 scientific articles, containing a wide range of linguistic topics and issues in the field of glottodidactics. The analysis showed that different criteria are used to assign different genders. Thus, in the case of feminine and neutral nouns, the suffixal analogy prevails, while in the case of masculine nouns, semantic analogy and monosyllabicity play a greater role.

During the 2020/2021 academic year, the working conditions of students during online classes, the levels of depressive, anxiety, and stress symptoms, and their correlations with resilience and sleep quality were examined on a sample of students from the University of Sarajevo (UNSA). The results of the research show that most students have satisfying working conditions from home, but also that a large number of them still feel fear and anxiety that something will happen to the internet connection or computer during online classes and exams. About 50% of students have increased symptoms of depression, anxiety, and stress, which are significantly in correlation with poorer sleep quality. Higher levels of resilience in students are correlated with lower levels of depression, anxiety, and stress and better sleep quality. The level of student depression is a variable that is the best predictor in explaining the criterion variable quality of sleep.

The recent B-meson anomalies are coherently explained at the TeV scale by 4321 gauge models with hierarchical couplings reminiscent of the Standard Model Yukawas. We show that such models arise as the low-energy limit of a complete theory of flavor, based on a warped fifth dimension where each Standard Model family is quasi-localized in a different brane. The Higgs is identified as a pseudo-Nambu-Goldstone boson emerging from the same dynamics responsible for 4321 symmetry breaking. This novel construction unifies quarks and leptons in a flavor non-universal manner, provides a natural description of flavor hierarchies, and addresses the electroweak hierarchy problem.

Abstract: The paper presents results of the measurements of the sulfur dioxide (SO2) and nitrogen dioxide (NO2) concentration and meteorological parameters: temperature, air pressure, relative humidity and wind speed. The data were collected from January 2019 to December 2020 at two stations, namely Center and Heating plant, in the City of Bijeljina, Republic of Srpska, Bosnia and Herzegovina. SO2 and NO2 are one of the major air pollutants that could negatively affect the human health. Levels of SO2 and NO2 in air samples and meteorological variables from urban zone of Bijeljina were determined at both localities, which represent a highly-populated area with intensive traffic. This topic has not been studied up to now in Bijeljina, although the recent research data indicates that there is a correlation between meteorological parameters and air pollutants. Statistical analysis confirms direct corelation between SO2 and NO2 and meteorological parameters, specially temperature in locality Center (r = -0.639), the wind speed in locality Heating plant (r = 0.399) and relative humidity (r = 0.162). Correlation of NO2 with temperature is not confirmed in both localities. The wind speed increase is followed by rises of the NO2 concentration values and vice versa. Correlation of NO2 with pressure is confirmed in locality Center (r = 0.128) but it is not confirmed in locality Heating plant. Correlation between NO2 and relative humidity found to be negative in locality Center (r = -0.062). These parameters are the most important meteorological factors influencing the variation in SO2 and NO2 concentration in the air during the research. Depending on the obtained correlation, meteorological parameters had a positive or negative impact on air pollution.

The aim of the study was to determine the differences in the level of fat, sugar and body structure based on the level of functional abilities. The sample of respondents are students of the University of Bihać who also completed the shuttle run test (BEEPT). T-test for independent samples revealed the existence of statistically significant differences between the arithmetic means of the two groups of subjects for (AMAS, p = 0 .011), (BMI p = 0 .000), (FAT%, p = 0.000), (FMKG p) = 0.000). A statistically significant difference was also found in the variable triglycerides (TRIGL p = 0.019), while in the other variables no statistically significant difference was found in the two groups of subjects in favor of subjects who had better results in functional abilities. The coefficient of discriminant canonical correlation is (0.512), as is Wilks lambda, (0.738), which indicates very high discrimination between groups (sig. 000). The greatest contribution to the formation of the discriminatory function was given by the variables FMKG - .801, FATPR -.760, BMI - .707, AMAS - .390, TRIGL - .358, HOLE - .235. The centroids of the groups show a large distance between the results of the groups because they are located at both ends of the coordinate system. The first group consists of positive results of a total of 7 variables, which means that the respondents of the first group had significantly better results in these variables. Based on the results, it can be concluded that the increase in cholesterol triglycerides and some parameters of body structure affected the level of health status as well as body composition in students.

In this paper, we deal with the potential applications of Artificial Intelligence in educational institutions. One of the main goals of applying the mentioned technology is to make the education system more efficient if possible. Based on research in this area in the world, our impression is that there is a long-term plan for introducing AI in schools, as a new kind of learning standard. The idea is not for artificial intelligence to completely take over the domain of education, but for some processes to be better organized or improved, so that the result of learning would be of better quality. New technologies, in the form of modern learning platforms that incorporate AI as one of the most important components of the system, significantly improve the communication and research work of students. It is evident that new generations are coming whose experience will be significantly different from ours, and that the new technologies from the domain of AI that we consider in this paper will significantly affect the design processes in the future.