Decision making is constantly present in agriculture. Choosing the wrong variety carries the risk that the investment in terms of sowing does not pay off at all. Therefore, it is necessary to choose the variety that gives the best results. In order to achieve this, it is necessary to apply multi-criteria decision-making of available varieties, which is, in this paper, done on the example of hybrid varieties of rapeseed that were created by selection at the Institute of Field and Vegetable Crops in Novi Sad. By applying fuzzy logic, a novel integrated Multi-Criteria Decision-Making (MCDM) model is developed and rapeseed varieties were evaluated. For determining four main and 20 subcriteria, fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been applied based on fuzzy Bonferroni operator, while for ranking alternatives fuzzy MABAC (Multi-Attributive Border Approximation area Comparison) method has been used. The results obtained using the novel integrated fuzzy MCDM model showed that the variety A2 – Zorica has the best results, followed by A1 - NS Ras, while the worst results were seen by the variety A5 - Zlatna. These results were confirmed using other five fuzzy MCDM methods. Sensitivity analysis—changing criteria weights showed the worst results in the variety A6 - Jovana, which took last place in the application of 18 scenarios. The presented model and the results of this research will help farmers to solve this decision problem.

Background and Study Aim. The nutritional status of children can be assessed on the basis of clinical examination, laboratory procedures and anthropometric measurements. Height and body weight are most often used to determine nutrition. Children and adolescents who are at risk of being overweight often also become obese adults. Material and Methods. The research was conducted on a sample of 136 students (67 boys and 69 girls), with an average age of 11.56 years. The aim of the study was to determine the degree and differences in the degree of nutrition and body composition in boys and girls of pubertal age. Results. Based on the obtained results, T-test for small independent samples, it was determined that there are no statistically significant differences between boys and girls, both in the degree of nutrition and body composition, estimated by 10 variables using bioelectric impedance InBody 720. Also, it was found that 19.70% of boys are obese, as well as 17.40% of girls. Cumulatively with the percentage of malnourished respondents, a total of 61.50% of boys were not normally fed, as were 37.70% of girls. The obtained results indicate the need for a more extensive review of the analysed segments and a significantly larger sample of respondents, in order to act preventively in the fight against obesity, as the leading epidemiological health problem of today. Conclusion. It is obvious that physical activity based on physical education classes is not sufficient or is not sufficiently represented to meet the challenges of the modern way of life of children.

The study qualitatively explores the pandemic and Sarajevo War-Siege from the psychological, sociological, and political security perspectives. As a direct indicator of behavioral variability within extreme conditions, the author refers to structural interviews with war-siege participants. The citizens can recognize the 1990s in some manifestations of the pandemic, including crisis staff formation that reflects ethnopolitics (ethnic-political boundaries) rather than instills public confidence. Life in the conditions of radical changes leaves a trace that does not have to be exclusively emotional but cognitive. The state of war-siege meant deconstructing the pre-war way of life and new ways of coping with war conditions. Maintaining routines is a link to pre-war life; continuity of norms and values allows for mental stability maintenance. During the siege, people had an acute perception of space and time. Space was something where the danger came from and the time spent in that space needed to be reduced. We have similar functions during the pandemic, reflecting on people's thoughts. Those who have adequately gone through the trauma that lasted during the siege have adapted well to "extreme" conditions and can develop protective mechanisms. Human thought focuses on the repetitive and familiar in today's world, while some extreme event interprets as the exception; such exceptional events are crucial in creating the future. Regardless of the political system's axis, confidence in the political elites must be sufficient. Prevention of fear and panic in the war's geographical area should be based on quality peacetime preparation through education and psychological commitment.

Abstract Language in the Balkan region of Southeastern Europe has a complex and turbulent history, acutely embodied in the tripartite and trilingual state of Bosnia and Herzegovina (BiH) in which Bosniaks, Croats, and Serbs all make claim to their own mutually-intelligible varieties of local “languages”. This study utilizes a linguistic landscape methodology to consider language use in Sarajevo, the capital of BiH, approximately 20 years after a brutal war that led to the establishment of the country. Data originate from three municipalities within the Sarajevo Canton – namely, Old Town, Center, and Ilidža – because of their representation of the region’s diversity and history. Signs were classified according to the three primary language varieties, i.e., Bosnian, Croatian, Serbian; BCS, representing a common core among the three varieties, as well as English, other languages, and mixed languages. The application of BCS uniquely positions the present research in comparison to other studies of language use in the region and allows for a more nuanced, less politically and ethnolinguistically fraught analysis of the communicative tendencies of users. More specifically, data indicate that actors in the linguistic landscape transcend the boundaries of their national, ethnic, and religious identities by tending towards the more neutral BCS, suggesting an orientation towards more translingual dispositions than previous variety-bound approaches have indicated. Thus, instead of the divisiveness of linguistic identity politics, the linguistic landscape of Sarajevo indicates a tendency toward inclusion and linguistic egalitarianism.

Summary Background/Aim: This study aimed to evaluate the effects of Lactobacillus reuteri lozenges as an adjunctive therapeutic agent in combination with scaling and root planing in a randomized, clinical trial of volunteers with periodontitis stage IV. Material and Methods: The study included 40 patients diagnosed with periodontitis divided into 2 groups of 20 patients by random sample method. The first group of patients used Lactobacillus reuteri lozenges after nonsurgical periodontal therapy for a period of 40 days while the second group of patients was treated with non-surgical periodontal therapy without lozenges. Periodontal clinical parameters were registered for all patients before treatment and after 40 days. Samples of saliva from patients before and 40 days after treatment were analyzed by the PCR method for pathogens Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, and Prevotella intermedia. Assessments were made on day 0 before treatment for patients of both groups and after 40 days. Results: Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis show a statistically significant difference between the two study groups. Results were not statistically significant for Prevotella intermedia (P= 0.5598). Conclusions: The present study confirms the positive effects of L. reuteri lozenges after non-surgical periodontal therapy and the maintenance phase of periodontal treatment. Considering the beneficial effects of probiotics, L.reuteri could serve as a useful adjunct or maybe even as an alternative to periodontal treatment when scaling and root planing might be contraindicated or has to be postponed.

Abstract Objective: We assessed the ability of the Prime Diet Quality Score (PDQS) to predict mortality in the US population and compared its predictiveness with that of the Healthy Eating Index-2015 (HEI-2015). Design: PDQS and HEI-2015 scores were derived using two 24-h recalls and converted to quintiles. Mortality data were obtained from the 2015 Public-Use Linked Mortality File. Associations between diet quality and all-cause mortality were evaluated using multivariable Cox proportional hazards models, and predictive performance of the two metrics was compared using a Wald test of equality of coefficients with both scores in a single model. Finally, we evaluated associations between individual metric components and mortality. Setting: A prospective analysis of the US National Health and Nutrition Examination Survey (NHANES) data. Participants: Five-thousand five hundred and twenty-five participants from three survey cycles (2003–2008) in the NHANES aged 40 years and over. Results: Over the 51 248 person-years of follow-up (mean: 9·2 years), 767 deaths were recorded. In multivariable models, hazard ratios between the highest and lowest quintiles of diet quality scores were 0·70 (95 % CI 0·51, 0·96, Ptrend = 0·03) for the PDQS and 0·77 (95 % CI 0·57, 1·03, Ptrend = 0·20) for the HEI-2015. The PDQS and HEI-2015 were similarly good predictors of total mortality (Pdifference = 0·88). Conclusion: Among US adults, better diet quality measured by the PDQS was associated with reduced risk of all-cause mortality. Given that the PDQS is simpler to calculate than the HEI-2015, it should be evaluated further for use as a diet quality metric globally.

Nitrate is one of the focal water quality indices in aquatic systems. However, proper estimation of nitrate concentration is a complicated task. In this article, capabilities of deep neural networks (DNN) and conventional artificial neural networks (ANN) to model and predict nitrate concentration in the Klokot River, Bosnia and Herzegovina were investigated. The measured data includes nitrate and pH values. Different scenarios were considered as the potential models for DNN and ANN structuring. The result showed DNN and ANN networks are incapable of precisely modeling the nitrate concentration in the Klokot River based on the designed scenarios. In addition, DNN was slightly superior to ANN in different terms of estimation accuracy.

PurposeLiterature suggests that open innovation approach of large firms shows different characteristics with small- and medium-sized enterprises (SMEs), so this paper tends to shed light on these structural differences. With the aim to gain a deeper understanding of the adoption of inbound innovation practices among firms in one small transition economy, this study is focused on the question of how different dimensions of inbound innovation practices affect the innovative performances of SMEs and large firms and how, eventually, these practices should be framed and managed differently.Design/methodology/approachThis paper develops a research model which analyses inbound innovation practices on a data set of 227 SMEs and large firms operating in Bosnia and Herzegovina. The data were collected by using a questionnaire specifically designed for this research. Association between the level of innovation of products in firms and inbound practices, between exploit and explore strategies, between types of industry and different types of collaborations with partners outside the firm is assessed by canonical correlation.FindingsThe research results revealed that inbound innovation practices of manufacturing firms in different stages of innovation development process starting from idea generation, experimentation, up to the commercialization, have positive influence on their innovative performances.Originality/valueThis study contributes to the existing research on open innovation by providing empirical evidences for different dimensions of inbound innovation practices in SMEs and large firms. We offer a very important insight into open innovation practices and challenges beyond well-researched developed countries.

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 “ML4Microbiome” that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.

The exposure of the body to stress, regardless of whether it comes from physical, chemical or emotional stimuli from the environment, causes an inadequate adaptation of the organisms which can contribute to the development of various diseases. Abnormally high blood concentrations of cortisol, known as stress hormone, lead to the development of a hormonal disorder called hyperadrenocorticism or Cushing’s syndrome. In the majority of cases, Cushing’s syndrome is diagnosed when symptoms are apparent, and screening endocrinological test confirms the existence either of increased cortisol production or decreased sensitivity of the hypothalamic-pituitary-adrenal axis to negative glucocorticoid feedback. In our research, we examined a total of 23 male and 7 female dogs that were suspected to have Cushing’s syndrome, based on history and clinical signs. A total of 15 male and 5 female dogs were positive for Cushing’s syndrome (HAC group), whereas the remaining dogs were used to form non-HAC group. Using the apparatus IDEXX “Vet Test 8008”, the following biochemical parameters were determined: glucose, urea, creatinine, phosphorus, calcium, total protein, albumin, globulin, alanine aminotransferase, alkaline phosphatase, bilirubin, cholesterol, and amylase. Regarding haematological parameters, the following parameters were investigated: erythrocytes, leukocytes, platelets, erythrocyte indices (MCV, MCH, MCHC, RDW), white blood cell count, haemoglobin and haematocrit, using “Laser cite vet lab Station” (IDEXX). No significant differences in haematological and biochemical blood parameters were noticed between the HAC and the non-HAC group of dogs. However, dogs suffering from Cushing’s syndrome had a higher value in the number of erythrocytes compared to the control group. The finding that has to be payed attention to is the difference in platelet count between the control group of dogs and dogs suffering from Cushing’s syndrome.

In view of the urgency and multiple targets for biodiversity conservation, and the scarcity of financial resources and political will, it is important to reach a consensus on which actions should be given priority. Multicriteria techniques can contribute to the improvement of the conservation prioritization process and different initiatives and approaches could benefit from their use. Here we present an exercise in prioritizing and seeking consensus using a multicriteria technique to rank the objectives proposed by three national action plans in Brazil. This ranking allowed: 1) to compare whether the order of appearance of the actions in these plans are in fact considered to be priorities by the public that drafted these documents; 2) to identify idiosyncrasies between what an official public policy document says and what the people responsible for execution think of these actions; and 3) to identify priority actions common to more than one plan – which can optimize the biodiversity conservation process. We identified a lack of congruence between the order of objectives identified in the action plans and the ranking of priorities made by the specialists who prepared these same plans. A set of common objectives was identified as a priority among different Plans. However, these common objectives were not always a priority in their respective Action Plans. We warn that the lack of congruence observed can compromise the execution of some of the general objectives, humpering or even preventing the conservation of the target species of these documents.