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One of the most common tools for achieving optimization and adequate production process management is linear programming (LP) in various forms. However, there are specific cases of the application of linear programming when production optimization implies several potential solutions instead of one. Exactly such a problem is solved in this paper, which integrates linear programming and a Multi-Criteria Decision-Making (MCDM) model. First, linear programming was applied to optimize production and several potential solutions lying on the line segment AB were obtained. A list of criteria was created and evaluated using the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA). To obtain the final solution, a novel Rough compromise ranking of alternatives from distance to ideal solution (R-CRADIS) method was developed and verified through comparative analysis. The results show that the integration of linear programming and a Fuzzy-Rough MCDM model can be an exceptional solution for solving specific optimization problems.

Traffic management is a significantly difficult and demanding task. It is necessary to know the main parameters of road networks in order to adequately meet traffic management requirements. Through this paper, an integrated fuzzy model for ranking road sections based on four inputs and four outputs was developed. The goal was to determine the safety degree of the observed road sections by the methodology developed. The greatest contribution of the paper is reflected in the development of the improved fuzzy step-wise weight assessment ratio analysis (IMF SWARA) method and integration with the fuzzy measurement alternatives and ranking according to the compromise solution (fuzzy MARCOS) method. First, the data envelopment analysis (DEA) model was applied, showing that three road sections have a high traffic risk. After that, IMF SWARA was applied to determine the values of the weight coefficients of the criteria, and the fuzzy MARCOS method was used for the final ranking of the sections. The obtained results were verified through a three-phase sensitivity analysis with an emphasis on forming 40 new scenarios in which input values were simulated. The stability of the model was proven in all phases of sensitivity analysis.

Bovine respiratory disease complex, a complex respiratory ailment in cattle, results from a combination of viral and bacterial factors, compounded by environmental stressors such as overcrowding, transportation, and adverse weather conditions. Its impact extends beyond mere health concerns, posing significant economic threats to the cattle industry. This study presents an extensive investigation into viral pathogens associated with BRDC in Serbian cattle, utilizing serum samples and nasal swabs. A cross-sectional study was conducted in 2024 across 65 randomly selected dairy farms in Serbia, excluding farms with vaccinated cattle. The farms were categorized by their livestock count: small (≤50 animals), medium (51–200 animals), and large (>200 animals). Serum samples from adult cattle older than 24 months were tested for antibodies against BVDV, BHV-1, BRSV, and BPIV3. Nasal swab samples from the animals with respiratory signs were tested using PCR for viral genome detection. The results showed seropositivity for all four viruses across all of the farms, with BPIV3 exhibiting universal seropositivity. Medium-sized and large farms demonstrated higher levels of seropositivity for BRSV and BHV-1 compared to small farms (p < 0.05). Our true seroprevalence estimates at the animal level were 84.29% for BRSV, 54.08% for BVDV, 90.61% for BHV-1, and 84.59% for BPIV3. A PCR analysis of the nasal swabs revealed positive detections for BRSV (20%), BHV-1 (1.7%), BVDV (8%), and BPIV3 (10.9%). Influenza D virus was not found in any of the samples. This study provides critical insights into the prevalence and circulation of viral pathogens associated with BRDC in Serbian cattle, emphasizing the importance of surveillance and control measures to mitigate the impact of respiratory diseases in cattle populations.

Knowing and understanding the parameters influencing the concentration of particles created by brake wear, as one of the main contributors to non-exhaust emissions from vehicles, is important for the further development of systems on vehicles to reduce the concentration of particles, and also for further research in the field of developing new friction pairs. In this research, a brake inertial dynamometer was used to measure brake particles, and four different brake pads were examined. Based on a previous review of the applied tests and driving cycles, the braking parameters were determined, i.e., the initial simulated speed of the vehicle, the load of one-quarter of the vehicle, and the brake pressure. The ambient temperature, air humidity, coefficient of friction between friction pairs, deceleration, and braking time can have an influence depending on the brake pad. Further, during the measurement, the temperatures of the brake pads were also measured, where the initial temperature of the brake pads was always the same. In order to process the data, several methods were used, including the presentation of the obtained results in a time domain, the application of the Taguchi design of the experiment with the analysis of the parameters, and a correlation analysis using the Pearson and Spearman correlation coefficients. In this research, the authors concluded that the influences of the parameters primarily depend on the applied brake pads. The vehicle speed turned out to have a large influence in all cases, as did the load, i.e., the influence of the vehicle weight (indirectly through the kinetic energy of the vehicle). In this case, the pressure showed less influence on the particle concentration. An important braking parameter that has a significant impact on the concentrations of PM2.5 and PM10 particles is the final temperature of the brake pads.

The aim of this research is to determine the change in the spatial distribution of erosion intensity in the territory of the Jablanica River Basin in the period 1971–2016 caused by land use and demographic changes. The Erosion Potential Method (EPM) was used to quantify changes in erosion intensity and to estimate the total annual sediment yield. The research results show that the value of the erosion coefficient decreased from 0.432 in 1971 to 0.360 in 2016. Specific annual gross erosion in the Jablanica River Basin was 654.41 m3/km2/year in 1971, while in 2016 it was 472.03 m3/km2/year. The analysis of proportional changes was used to determine demographic changes and land use patterns in the basin area. In terms of the scale and intensity of the erosion process, three types and one sub-type of population dynamics of settlements and land use changes were distinguished, respectively: progressive, stagnant, regressive and dominant regressive. It was concluded that the results show the significance of demographic and land use changes in the control of the intensity of erosion. The Soil Erosion Map may be useful to planners and land use managers to take appropriate decisions for soil conservation in the basin.