<p style="text-align: justify;">From the point of view of food safety, it is necessary to ensure that consumers and all other participants in the safety assurance system maintain confidence in the risk management process that is based on the existing well-structured legislative framework, which takes into account expertly based risk assessment, and which has as its ultimate goal the protection of health and interests of consumers. The paper reviewed the role of management in the implementation of new standards and common regulations in the European Union, where the so-called "Hygiene Packages" are being implemented. The production conditions from the Food Law in Bosnia and Herzegovina and common EU regulations were also considered. The results of research by the Food Safety Agency, which provides expert advice for technical support to the legislation and policy of Bosnia and Herzegovina in all areas that have a direct or indirect impact on food safety, were considered. It was concluded that food safety directly depends on the management's skills to ensure timely decision-making in the implementation of the Quality Policy and Environmental Policy by integrating lower levels. What represents a challenge in Bosnia and Herzegovina is that food production plants do not pay enough attention to waste management, which is the task of management.</p>

Adipose tissue is a metabolically active organ with both endocrine and paracrine functions. It secretes a number of cytokines (adipocytokines) that play critical roles in the development of metabolic diseases and inflammation. Previous studies have shown that the product of an obese protein (leptin), a hormone secreted by adipose tissue, is associated with obesity, type 2 diabetes mellitus (T2D), and dyslipidaemia. Moreover, leptin has been identified as a potential and valuable therapeutic molecule for the treatment of glycaemia, dyslipidaemia, and T2D. The aim of this study was to analyse the concentration of obesity protein as an adipocytokine in a population from Sarajevo, Bosnia and Herzegovina. The study included 26 partici - pants: 13 healthy subjects as the control group, and 13 untreated diabetics. Biochemical parameter, such as glucose, glycated haemoglobin, lipid profile, and concentrations of the hormones leptin and insulin were analysed. Biochemical parameters were determined using standard IFCC methods, while leptin and insulin concentrations were analysed using an ELISA assay. The measured concentration of obesity protein in plasma was significantly higher ( p < 0.001) in diabetics compared to healthy subjects, with females exhibiting higher leptin levels than males in both groups. Significant differences in concentrations of bi - ochemical characteristics between the diabetic and control groups ( p < 0.001 and p < 0.05 respectively) were also observed, with elevated values noted particularly in females. These results suggest that leptin can serve as a biomarker for glucose and lipid regulation in untreated diabetic patients.

Climate change is expected to reduce the distribution range of major tree species in Europe. As a result, rare and underutilized tree species are gaining importance, despite limited research on their ecological characteristics. One such species is wild service tree (Sorbus torminalis (L.) Crantz), which has the potential to enhance the resistance, resilience, and adaptability of forest ecosystems to climate change. This paper provides an overview of previous research on its autecology, silvicultural characteristics, dispersal potential, and response to climate change. Wild service tree is native to Europe, northwestern Africa, and southwestern Asia. It exhibits broad ecological tolerance and thrives in various soil types, with a preference for deep, humus-rich soils while avoiding dry sandy and marshy conditions. In the Balkans, it grows at altitudes between 250 and 1400 meters above sea level, predominantly in thermofillic oak and beech forests, and less frequently in pine communities on sunny exposures. The species tolerates a wide range of climatic conditions, including low winter temperatures and summer droughts. Natural regeneration occurs primarily through root suckers, with seed-based regeneration being less frequent. For successful establishment, young plants should be planted in small groups within cleared patches of oak and beech forests. Post-planting protection against browsing and damage from rodents is essential. From the sapling stage onward, it requires high light availability for optimal growth. Due to limited seed production and strong competition from other tree species, the natural spread of wild service tree is relatively slow. Its expansion is more likely in cleared thermophilic habitats and can be accelerated through targeted afforestation efforts. Wild service tree exhibits high drought tolerance, making it a valuable species for areas affected by climate change. Its range is expected to expand in sessile oak and thermophilic beech forests. When combined with other drought-resistant tree species, it may contribute to stabilizing forest structures and mitigating the impacts of climate change.

To achieve consensus on the definition and clinical approach of Monogenic Inflammatory Immune Dysregulation Disorders (MIIDDs), a collective term for rare conditions marked by inflammation, immune dysregulation, and infection susceptibility. These consensus guidelines specifically apply to pathogenic (or likely pathogenic) gene mutations affecting both innate and adaptive immunity, excluding variants of unknown significance (VUS). A multi-step, evidence-based, multidisciplinary consensus process was employed, consisting of: (1) a systematic literature review across four electronic databases (Cochrane Library, Web of Science, Scopus, and MEDLINE via PubMed), updated through December 31, 2024; (2) a pre-Delphi electronic survey completed by 95 international adult and pediatric immunologists and rheumatologists; and (3) a modified online Delphi process with an international multidisciplinary expert panel, where statements were iteratively analyzed and refined until achieving consensus (≥ 80% agreement among panelists). Fifteen experts from 12 countries participated in two rounds of the Delphi process, resulting in the development of eight overarching principles and 10 consensus statements. These were categorized into five domains: (1) definitions and conceptual framework, (2) diagnostic and monitoring considerations, (3) treatment and therapeutic strategies, (4) multidisciplinary and collaborative care, and (5) patient education and support. This consensus defines MIIDDs and provides a structured clinical framework to streamline research efforts and improve patient outcomes.

In this study, polyphenolic compounds from pomegranate peel (Punica granatum) were extracted using different extraction methods. Three techniques were applied for polyphenol extraction: Soxhlet extraction, ultrasound-assisted extraction, and maceration. These methods varied in the time required for extraction and the yield of dry extract. For Soxhlet and ultrasound-assisted extraction, two solvents were used: methanol and ethanol. While maceration is simple and cost-effective, it was found to be the least efficient method for extraction. The removal of ethanol and methanol from the extracts was successfully achieved through evaporation, ensuring the purity of the extracts.The results obtained showed that Soxhlet extraction with methanol gave the highest yield of 33.5% compared to the ethanol solvent with 30.45%.Ultrasound-assisted extraction also yielded significant results, but the difference in yield was more pronounced depending on the solvent used. The goal of this study was to determine and present the efficiency of each extraction method. Further research will focus on assessing the antioxidant capacity of the extracted polyphenolic compounds.

In this article, we review the extensive and complex fabric of literature concerning the ontogenesis of spatial representations from earliest childhood to the elderly, including normal and abnormal aging (dementia and Alzheimer’s disease). We also revisit fundamental concepts of the neuronal representations of space, egocentric vs. allocentric reference frames, and path integration. We highlight a thread of contradictions in spatial cognition from infant cognition to the first breakthrough at around the age of four. The contradictions reemerge in the literature on age-related decline in spatial cognition. We argue that these contradictions derive from the incorrect assumption that path integration is exclusively associated with allocentric frames of references, hence, signatures of path integration are often taken as evidence for allocentric perspective-taking. We posit that several contradictions in the literature can be resolved by acknowledging that path integration is agnostic to the type of reference frame and can be implemented in both egocentric and allocentric frames of reference. By freeing the frames of reference from path integration, we arrive at a developmental trajectory consistent across cognitive development studies, enabling us to ask questions that may dissolve the obscurity of this topic. The new model also sheds light on the very early stage of spatial cognition.

This study presents a digital twin approach to quantifying the durability and failure risk of concrete gravity dams by integrating advanced numerical modelling with field monitoring data. Building on a previously developed finite element model for dam–reservoir interaction analysis, this research extends its application to the assessment of existing, fully operational dams by using digital twin technology. One such case study of a digital twin is given for the concrete gravity dam, Salakovac. The numerical model combines finite element formulations representing the dam as a nonisothermal saturated porous medium and the reservoir water as an acoustic fluid, ensuring realistic simulation results of their interactions. The selected finite element discrete approximations enable the detailed analysis of the dam failure mechanisms under varying extreme conditions, while simultaneously ensuring the consistent transfer of all fields (displacement, temperature, and pressure) at the dam–reservoir interface. A key aspect of this research is the calibration of the numerical model through the systematic definition of boundary conditions, external loads, and material parameters to ensure that the simulation results closely align with observed behaviour, thereby reflecting the current state of the ageing concrete dam. For the given case study of the Salakovac Dam, we illustrate the use of the digital twin to predict the failure mechanism of an ageing concrete dam for the chosen scenario of extreme loads.

Objectives Generative artificial intelligence (GAI) tools can enhance the quality and efficiency of medical research, but their improper use may result in plagiarism, academic fraud and unreliable findings. Transparent reporting of GAI use is essential, yet existing guidelines from journals and institutions are inconsistent, with no standardised principles. Design and setting International online Delphi study. Participants International experts in medicine and artificial intelligence. Main outcome measures The primary outcome measure is the consensus level of the Delphi expert panel on the items of inclusion criteria for GAMER (Rreporting guideline for the use of Generative Artificial intelligence tools in MEdical Research). Results The development process included a scoping review, two Delphi rounds and virtual meetings. 51 experts from 26 countries participated in the process (44 in the Delphi survey). The final checklist comprises nine reporting items: general declaration, GAI tool specifications, prompting techniques, tool’s role in the study, declaration of new GAI model(s) developed, artificial intelligence-assisted sections in the manuscript, content verification, data privacy and impact on conclusions. Conclusion GAMER provides universal and standardised guideline for GAI use in medical research, ensuring transparency, integrity and quality.

The saddle-point solutions for strong-laser-field-induced high-order above-threshold ionization, the complete classification of which was recently presented in , are considered classically. In the limit of vanishing ionization potential the system of saddle-point equations simplifies, allowing a semi-analytical treatment. For a monochromatic field, the analytical nonlinear equations obtained this way allow one to determine the maximum (cutoff) photoelectron energies for the backward- and forward-scattering saddle-point solutions for all values of the multi-indices introduced by our classification scheme. These cutoffs are determined for all photoelectron momenta and it is shown how the backward-scattering solutions from one half of the momentum plane are related to the forward-scattering solutions from the other. The case of a bichromatic linearly polarized field is analyzed in detail. The results are rederived with the help of a simple graphical method, which can be used to qualitatively discuss the effect of varying the field parameters. Published by the American Physical Society 2025

This article provides an overview of Direct Energy Deposition – Arc technology (DED-Arc), also known as Wire Arc Additive Manufacturing (WAAM), which involves the deposition of metal wire using an arc power source and a CNC or robotic manipulator. The high deposition rate of WAAM justifies its use for the manufacturing of small to large-size components with lower resolution and less complex geometry. However, the use of wire as feedstock in the WAAM process has certain advantages and disadvantages, which are explained in detail. The WAAM specialties are in-situ alloying and the production of functionally graded materials (FGMs). Various sensors, path planning, process control, and FEM simulation from WAAM are used to reduce material and energy consumption and make the process more sustainable. Post-processing techniques are also discussed as a method of improving the quality of the final product. Finally, the prospects of the WAAM process are presented.

Introduction The aim of the TALENT project is to promote equality in education, prevent exclusion, support dual careers (sport and school), create new role models for the benefit of young talents and prepare them for lifelong learning and professional sport from an early age. It is promoted by a European consortium of 7 partner institutions and runs from December 2022 to May 2025. It consists of five work packages. In the first work phase, developing the WP2 (from December 2022 to October 2023), under the coordination of UNIPA, NIS University, KMOP and EAS standards for talent recognition were identified and validated. Methods Initially, 12 focus groups were conducted with teachers (77 teachers) and coaches (73 coaches) on creating talent identification standards; subsequently, workshops were held with dual career experts to validate these standards. This was a key piece of work that enabled the establishment of clear guidelines and protocols to identify and support talented young people in their dual careers. Results A final list of 41 shared statements was identified: 20 related to teachers and 21 related to coaches. For example, teachers emphasized the need for multidisciplinary approaches and early identification of talent, while coaches underlined the importance of psychological readiness and collaboration with schools and families. Discussion These statements not only provide structured reference points for talent identification but also highlight actionable needs across educational and sport systems. As such, they represent a solid foundation for developing standard operating procedures in talent recognition and dual career support.

In competitive organizations and projects, assessing risks related to human capital is essential for improving workplace conditions and ensuring project success. This study evaluates primary, secondary, and residual human capital risks in urban water transfer projects using an innovative hybrid DEMATEL–MARCOS approach. The DEMATEL method was employed to analyze causal relationships and interdependencies among risks, while the MARCOS method ranked their significance. The key findings reveal that “accidents during material transportation” (primary risk), “corrosion” (secondary risk), and “pipeline pressure” (residual risk) are the most critical factors influencing human capital in such projects. The study provides a structured framework for prioritizing risk mitigation strategies, offering actionable insights for policymakers and project managers to enhance safety, efficiency, and workforce well-being. By integrating multi-criteria decision-making techniques, this research bridges a gap in the water industry’s risk management practices and contributes to safer, more sustainable infrastructure development.

Pertaining to goal orientation and achievement, agency is a fundamental aspect of human cognition and behavior. Accordingly, detecting and quantifying linguistic encoding of agency are critical for the analysis of human actions, interactions, and social dynamics. Available agency-quantifying computational tools rely on word-counting methods, which typically are insensitive to the semantic context in which the words are used and consequently prone to miscoding, for example, in case of polysemy. Additionally, some currently available tools do not take into account differences in the intensity and directionality of agency. In order to overcome these shortcomings, we present BERTAgent, a novel tool to quantify semantic agency in text. BERTAgent is a computational language model that utilizes the transformers architecture, a popular deep learning approach to natural language processing. BERTAgent was fine-tuned using textual data that were evaluated by human coders with respect to the level of conveyed agency. In four validation studies, BERTAgent exhibits improved convergent and discriminant validity compared to previous solutions. Additionally, the detailed description of BERTAgent's development procedure serves as a tutorial for the advancement of similar tools, providing a blueprint for leveraging the existing lexicographical data sets in conjunction with the deep learning techniques in order to detect and quantify other psychological constructs in textual data. (PsycInfo Database Record (c) 2025 APA, all rights reserved).