Search Results (1,029)

Urbanization and the rapid growth of e-commerce have significantly increased delivery volumes in cities, creating challenges in terms of cost, efficiency, and sustainability in last-mile delivery (LMD). To address these challenges, this paper proposes an innovative methodological framework for selecting optimal delivery strategies in urban environments, grounded in the principles of collaboration. The framework integrates an Extended FullEx method, developed to calculate criteria weights while accounting for expert reputation based on education and experience, with the MARCOS multi-criteria decision-making (MCDM) method used to rank delivery strategies. The Extended FullEx method proposed in this paper differs from the original FullEx by providing two improvements. The first concerns the introduction of the normalization procedure in the calculation of experts’ reputations, while the second addresses the different scoring of educational degrees, providing a more precise mathematical basis for the process. Four collaborative delivery strategies are evaluated against twelve sustainability-related criteria identified through an extensive literature review. The proposed framework is applied to a real-life case study in Novi Sad, Republic of Serbia. Results indicate that the most suitable delivery strategy is a hybrid model that combines the use of a consolidation center with smaller urban delivery hubs, providing practical insights for enhancing the sustainability and efficiency of urban delivery. This study contributes both methodologically, by advancing MCDM techniques, and practically, by offering decision-makers a comprehensive tool that integrates subjective expert knowledge and objective criteria assessment in the selection of sustainable LMD solutions. Full article

This paper aims to leverage artificial intelligence (AI) to assist physicians in utilizing advanced deep learning techniques integrated into developed models within electronic health records (EHRs) in medical information systems (MISes), which have been in use for over 15 years in health centers across the Republic of Serbia. This paper presents a human-centered AI approach that emphasizes physician decision-making supported by AI models. This study presents two developed and implemented deep neural network (DNN) models in the EHR. Both models were based on data that were collected during the COVID-19 outbreak. The models were evaluated using five-fold cross-validation. The convolutional neural network (CNN), based on the pre-trained VGG19 architecture for classifying chest X-ray images, was trained on a publicly available smaller dataset containing 196 entries, and achieved an average classification accuracy of 91.83 ± 2.82%. The DNN model for optimizing patient appointment scheduling was trained on a large dataset (341,569 entries) and a rich feature design extracted from the MIS, which is daily used in Serbia, achieving an average classification accuracy of 77.51 ± 0.70%. Both models have consistent performance and good generalization. The architecture of a realized MIS, incorporating the positioning of developed AI tools that encompass both developed models, is also presented in this study. Full article

The purpose of this research is to examine employee perceptions regarding the implementation of ESG (environmental, social, and governance) practices in financial institutions, with a comparative focus on urban and rural banks in the Republic of Serbia. The study investigates how employees assess environmental, social, and governance aspects of ESG, as well as their own role in applying these principles in everyday work. The results reveal statistically significant differences between the two groups; employees in urban banks report greater engagement, more access to training, and stronger involvement in ESG decision-making. These findings suggest the existence of more developed institutional support, infrastructure, and organisational culture in urban banks. In contrast, employees in rural banks highlight the need for enhanced training, clearer ESG guidance, and improved oversight mechanisms. The study underlines the importance of investing in employee development and internal communication, particularly in rural contexts, to improve ESG outcomes. By focusing on employee-level perceptions, this research contributes to the understanding of how organisational and geographic factors influence the implementation of ESG-related practices in financial institutions. Full article

Given the environmental significance of the textile industry, especially the accumulation of nondegradable materials, there is extensive development of greener approaches to fabric waste management. Here, we investigated the biodegradation potential of three Streptomyces strains in model compost on polyamide (PA) and polyamide-elastane (PA-EA) as synthetic, and on cotton (CO) as natural textile materials. Weight change of the materials was followed, while Fourier-Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM) were used to analyze surface changes of the materials upon biodegradation. The bioluminescence-based toxicity test employing Aliivibrio fischeri confirmed the ecological safety of the tested textiles. After 12 months, the increase of 10 and 16% weight loss, of PA-EA and PA, respectively, was observed in compost augmented with Streptomyces sp. BPS43. Additionally, a 14% increase in cotton degradation was recorded after 2 months in compost augmented with Streptomyces sp. NP10. Genome exploration of the strains was carried out for potential plastic-degrading enzymes. It highlighted BPS43 as the most versatile strain with specific amidases that show sequence identity to UMG-SP-1, UMG-SP-2, and UMG-SP-3 (polyurethane degrading enzymes identified from compost metagenome). Our results showcase the behavior of Streptomyces sp. BPS43 in the degradation of PA and PA-EA textiles in composting conditions, with enzymatic potential that could be further characterized and optimized for increased synthetic textile degradation. Full article

The manuscript examines the cause-and-effect relationships of fires in the Republic of Serbia over a fifteen-year period, primarily from the aspect of human safety. For this purpose, numerical variables describing the number of injuries and deaths in fires were introduced, on which various analysis and modeling techniques were implemented, which can be viewed in the context of data mining (DM). First, for both observed variables, stochastic modeling of their temporal dynamics was analyzed, and subsequently, cluster analysis of the values of these variables was performed using two different methods. Finally, by interpreting these variables as outputs (objectives) for the classification problem, several decision trees were formed that describe the influence and relationship of different fire causes on situations in which injuries or human casualties occur or not. In that way, several different types of fires have been identified, including rare but deadly incidents that require urgent preventive measures. Key risk factors such as fire cause, location, season, etc., have been found to significantly influence human casualties. These findings provide practical insights for improving fire protection policies and emergency response. Through such a comprehensive analysis, it is believed that some important results have been obtained that precisely describe the specific relationships between the causes and consequences of fires occurring in the Republic of Serbia. Full article

Dietary tannin supplementation represents a potential strategy to modulate rumen fermentation and enhance lactation performance in dairy cows, though responses remain inconsistent. A 21-day feeding trial was conducted to evaluate the effect of chestnut tannin (CNT) extract on the enteric methane emissions (EME), blood metabolites, and milk production traits in mid-lactation dairy cows. Thirty-six Holstein cows were allocated to three homogeneous treatment groups: control (CNT₀, 0 g/d CNT), CNT₄₀ (40 g/d CNT), and CNT₈₀ (80 g/d CNT). Measurements of EME, dry matter intake (DMI), milk yield (MY), and blood and milk parameters were carried out pre- and post-21-day supplementation period. Compared with the no-additive group, the CNT extract reduced methane production, methane yield, and methane intensity in CNT₄₀ and CNT₈₀ (p < 0.001). CNT₄₀ and CNT₈₀ cows exhibited lower blood urea nitrogen (p = 0.019 and p = 0.002) and elevated serum insulin (p = 0.003 and p < 0.001) and growth hormone concentrations (p = 0.046 and p = 0.034), coinciding with reduced aspartate aminotransferase (p = 0.016 and p = 0.045), and lactate dehydrogenase (p = 0.011 and p = 0.008) activities compared to control. However, CNT₈₀ had higher circulating NEFA and BHBA than CNT₀ (p = 0.003 and p = 0.004) and CNT₄₀ (p = 0.035 and p = 0.019). The blood glucose, albumin, and total bilirubin concentrations were not affected. MY and fat- and protein-corrected milk (FPCM), MY/DMI, and FPCM/DMI were higher in both CNT₄₀ (p = 0.004, p = 0.003, p = 0.014, p = 0.010) and CNT₈₀ (p = 0.002, p = 0.003, p = 0.008, p = 0.013) cows compared with controls. Feeding CNT₈₀ resulted in higher protein content (p = 0.015) but lower fat percentage in milk (p = 0.004) compared to CNT₀. Milk urea nitrogen and somatic cell counts were significantly lower in both CNT₄₀ (p < 0.001, p = 0.009) and CNT₈₀ (p < 0.001 for both) compared to CNT₀, while milk lactose did not differ between treatments. These findings demonstrate that chestnut tannin extract effectively mitigates EME while enhancing lactation performance in mid-lactation dairy cows. Full article

In this study, whole grain sorghum flour was used to partially substitute the gluten-free flour blend in cookie formulation at 20% (C20) and 40% (C40) replacement levels. The goal was to explore its potential to improve the nutritional value and sensory appeal of cookies relative to conventional and commercially available gluten-free alternatives. Nutritional analysis revealed that cookies with added sorghum flour showed increased levels of protein, ash, and polyphenolic compounds, while maintaining favorable macronutrient profiles. Notably, several bioactive compounds, such as gallic acid, caffeic acid, and apigenin, were detected exclusively in sorghum-containing samples, suggesting enhanced functional properties. Despite these compositional changes, textural measurements showed no significant differences in hardness or fracturability compared with the control. Sensory profiling using the Rate-All-That-Apply (RATA) method demonstrated that both samples (C20 and C40) achieved balanced results in terms of aroma as well as texture and were generally well accepted by the panel. The results indicate that moderate inclusion of sorghum flour (20% and 40%) can improve the sensory and nutritional profiles of gluten-free cookies without compromising product acceptability. Sorghum thus offers a promising pathway for the development of high-quality, health-oriented, gluten-free bakery products. Full article

Background/Objectives: Vedolizumab is a gut-selective anti-integrin monoclonal antibody approved for the treatment of inflammatory bowel disease (IBD). While clinical trials have demonstrated a favorable safety profile, real-world studies are essential for identifying rare adverse events (AEs) and evaluating post-marketing safety. This study assessed vedolizumab’s safety in a real-world cohort and supported the detection of potential safety signals. Methods: A retrospective chart review was conducted on adult IBD patients treated with vedolizumab at a tertiary center in the Republic of Serbia between October 2021 and August 2022. Data included demographics, AEs, and newly reported extraintestinal manifestations (EIMs). Exposure-adjusted incidence rates were calculated per 100 patient-years (PYs). Disproportionality analysis using the FDA Adverse Event Reporting System (FAERS) was performed to identify safety signals, employing reporting odds ratios (RORs) and proportional reporting ratios (PRRs) for AEs also observed in the cohort. Prior IBD therapies and reasons for discontinuation were evaluated. Results: A total of 107 patients (42.1% Crohn’s disease, 57.9% ulcerative colitis) were included, with a median vedolizumab exposure of 605 days. There were 92 AEs (56.51/100 PYs), most frequently infections (23.95/100 PYs), gastrointestinal disorders (4.30/100 PYs), and skin disorders (4.30/100 PYs). The most frequently reported preferred terms (PTs) included COVID-19, COVID-19 pneumonia, nephrolithiasis, and nasopharyngitis. Arthralgia (12.90/100 PYs) was the most frequent newly reported EIM. No discontinuations due to vedolizumab AEs occurred. FAERS analysis revealed potential signals for events not listed in prescribing information but observed in the cohort: nephrolithiasis, abdominal pain, diarrhea, malaise, cholangitis, gastrointestinal infection, blood pressure decreased, weight decreased, female genital tract fistula, respiratory symptom, and appendicectomy. Most patients had received three prior therapies, often stopping one due to AEs. Conclusions: Vedolizumab demonstrated a favorable safety profile in the IBD cohort. However, FAERS-identified signals, such as nephrolithiasis, gastrointestinal infections, and decreased blood pressure, warrant further investigation in larger, more diverse populations. Full article

Human milk has been used for over 70 years to monitor pollutants such as polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs). Despite the growing body of data, our understanding of the pollutant exposome, particularly co-exposure patterns and their interactions, remains limited. Artificial intelligence (AI) offers considerable potential to enhance biomonitoring efforts through advanced data modelling, yet its application to pollutant dynamics in complex biological matrices such as human milk remains underutilized. This study applied an AI-based framework, integrating machine learning, metaheuristic hyperparameter optimization, explainable AI, and postprocessing, to analyze PCB-170 levels in breast milk samples from 186 mothers in Zadar, Croatia. Among 24 analyzed POPs, the most influential predictors of PCB-170 concentrations were hexa- and hepta-chlorinated PCBs (PCB-180, -153, and -138), alongside p,p’-DDE. Maternal age and other POPs exhibited negligible global influence. SHAP-based interaction analysis revealed pronounced co-behavior among highly chlorinated congeners, especially PCB-138–PCB-153, PCB-138–PCB-180, and PCB-180–PCB-153. These findings highlight the importance of examining pollutant interactions rather than individual contributions alone. They also advocate for the revision of current monitoring strategies to prioritize multi-pollutant assessment and focus on toxicologically relevant PCB groups, improving risk evaluation in real-world exposure scenarios. Full article

Narcotics trafficking is a fundamental part of organized crime, posing significant and evolving challenges for forensic investigations. Addressing these challenges requires rapid, precise, and scientifically validated analytical methods for reliable identification of illicit substances. Over the past five years, forensic drug testing has advanced considerably, improving detection of traditional drugs—such as tetrahydrocannabinol, cocaine, heroin, amphetamine-type stimulants, and lysergic acid diethylamide—as well as emerging new psychoactive substances (NPS), including synthetic cannabinoids (e.g., 5F-MDMB-PICA), cathinones (e.g., α-PVP), potent opioids (e.g., carfentanil), designer psychedelics (e.g., 25I-NBOMe), benzodiazepines (e.g., flualprazolam), and dissociatives (e.g., 3-HO-PCP). Current technologies include colorimetric assays, ambient ionization mass spectrometry, and chromatographic methods coupled with various detectors, all enhancing accuracy and precision. Vibrational spectroscopy techniques, like Raman and Fourier transform infrared spectroscopy, have become essential for non-destructive identification. Additionally, new sensors with disposable electrodes and miniaturized transducers allow ultrasensitive on-site detection of drugs and metabolites. Advanced chemometric algorithms extract maximum information from complex data, enabling faster and more reliable identifications. An important emerging trend is the adoption of green analytical methods—including direct analysis, solvent-free extraction, miniaturized instruments, and eco-friendly chromatographic processes—that reduce environmental impact without sacrificing performance. This review provides a comprehensive overview of innovations over the last five years in forensic drug analysis based on the ScienceDirect database and highlights technological trends shaping the future of forensic toxicology. Full article

This study provides an assessment of BTEX compounds—benzene, toluene, ethylbenzene, and xylene isomers—in urban precipitation collected in the city of Novi Sad, Republic of Serbia, during autumn and winter 2024, analyzed by gas chromatography-mass spectrometry (GC-MS). By combining chemical analysis with meteorological observations and HYSPLIT backward trajectory modeling, the study considers the mechanisms of BTEX removal from the atmosphere via wet scavenging and highlights the role of local weather conditions and long-range atmospheric transport in pollutant concentrations. During the early observation period (September to late November), average concentrations were 0.45 µg/L benzene, 3.45 µg/L ethylbenzene, 4.0 µg/L p-xylene, 2.31 µg/L o-xylene, and 1.32 µg/L toluene. These values sharply dropped to near-zero levels in December for benzene, ethylbenzene, and xylenes, while toluene persisted at 1.12 µg/L. A pronounced toluene spike exceeding 6 µg/L on 28 November was likely driven by transboundary air mass transport from Central Europe, as confirmed by trajectory modeling. The environmental risks posed by BTEX deposition, especially from toluene and xylenes, underline the need for regulatory frameworks to include precipitation as a pathway for pollutant deposition. It should be clarified that the identified risk primarily concerns aquatic organisms, due to the potential for BTEX infiltration into surface waters and subsequent ecotoxicological impacts. Incorporating such monitoring into EU policies can improve protection of air, water, and ecosystems. Full article

Silica/alumina composite particles were synthesized via the sol–gel method to promote fine dispersion and homogenous mixing. Aluminum chloride hydroxide served as the alumina precursor, while amorphous silica, obtained from rice husk, was directly incorporated into the alumina sol. Following synthesis, the material was calcined at 1000 °C, yielding an α-cristobalite form of silica and corundum-phase alumina. These hybrid particles were introduced into polymer composites at reinforcement levels of 1 wt.%, 3 wt.%, and 5 wt.%. Mechanical behavior was evaluated through three-point bending tests, Shore D hardness measurements, and controlled-energy impact testing. Among the formulations, the 3 wt.% composite exhibited optimal performance, displaying the highest flexural modulus and strength, along with enhanced impact resistance. Hardness increased with rising particle content. Fractographic analysis revealed that the 3 wt.% loading produced a notably rougher fracture surface, correlating with improved energy absorption. In contrast, the 5 wt.% composite, although harder than the matrix and other composites, exhibited diminished toughness due to particle agglomeration. Full article

100 nm thick TiO₂/TiN bilayers with varying thickness ratios were deposited via reactive sputtering of a Ti target in controlled oxygen and nitrogen atmospheres. Post-deposition annealing in air at 600 °C was performed to induce nitrogen diffusion through the oxygen-deficient TiO₂ layer. The resulting changes in morphology and chemical environment were investigated in detail using transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and UV-Vis spectroscopy. Detailed TEM and XPS analyses have confirmed nitrogen diffusion across the TiO₂ layer, with surface nitrogen concentration and the ratio of interstitial to substitutional nitrogen dependent on the TiO₂/TiN mass ratio. Optical studies demonstrated modifications in optical constants and a reduction of the effective bandgap from 3.2 eV to 2.6 eV due to new energy states introduced by nitrogen doping. Changes in surface free energy induced by nitrogen incorporation showed a correlation to nitrogen doping sites on the surface, which had positive effects on overall photocatalytic activity. Photocatalytic activity, assessed through methylene blue degradation, showed enhancement attributed to nitrogen doping. Additionally, deposition of a 5 nm gold layer on the annealed sample enabled investigation of synergistic effects between nitrogen doping and gold incorporation, resulting in further improved photocatalytic performance. These findings establish the TiO₂/TiN bilayer as a versatile platform for supporting thin gold films with enhanced photocatalytic properties. Full article

This study evaluates the influence of general anesthesia (GA) and spinal anesthesia (SA) on physiological and oxidative stress in parturients undergoing elective cesarean section, one of the most frequently performed surgical procedures worldwide. A total of 101 pregnant women were included, categorized into GA (n = 51) and SA (n = 50) groups. Blood samples were collected at three time points: one hour before surgery (Measurement 1), at umbilical cord clamping (Measurement 2), and two hours post-surgery (Measurement 3). Biomarkers of oxidative stress, complete blood count, and levels of biochemical parameters were measured. In second and/or third measurement, biochemical blood analysis showed increased prolactin and cortisol levels, followed by spike of glucose and insulin in the GA group. However, levels of tri-iodothyronine were reduced in both groups in the third measurement. Glutathione S-transferase (GST) activity was increased in both groups in third measurement. The results showed increased concentrations of total SH groups and decreased concentrations of non-protein SH groups in the GA group during Measurement 2. Lymphocyte count was found to be predictor of GST levels. The results indicate more a pronounced endocrine response in GA group and speak in favor of spinal anesthesia. Both kinds of anesthesia are equally safe in terms of the oxidative status of the tissue. Full article

Metal chelation to bioactive small molecules is a well-established strategy to enhance the biological activity of the resulting complexes. Among the widely explored structural motifs, the combination of prominent metal centers with naturally inspired derivatives has attracted considerable attention. One such promising platform is the flavone scaffold, derived from flavonoids and studied since ancient times. Flavones are plant-derived compounds known for their diverse biological activities and health benefits. They exhibit significant structural variability, primarily through backbone modifications such as hydroxylation. Importantly, coordination of metal ions to hydroxylated flavone cores often improves their natural bioactivities, including anticancer and antimicrobial effects. In this review, we summarize transition metal complexes incorporating hydroxyflavone (OH–F) ligands reported over the past 15 years. We provide a concise overview of synthetic approaches and structural characterization, with a particular emphasis on coordination modes (e.g., maltol-type, acetylacetonate-type, catechol-type, and others). Furthermore, we discuss biological evaluation results, especially anticancer and antimicrobial studies, to highlight the therapeutic potential of these complexes. Finally, we suggest directions for the future development of metal-based agents bearing hydroxyflavone moieties through several critical points in terms of the accuracy, reproducibility, and relevance of biological studies involving metal-based compounds. Full article