Background and purpose Physical activity has been shown to produce numerous beneficial effects, including improved cardiovascular function, reduced body fat percentage, increased muscular strength, enhanced endurance, and greater flexibility. Accordingly, physical activity is considered a crucial factor in enhancing the quality of life in older adults. The aim of this study was to analyze literature that investigates the effects of resistance training on fitness parameters in older adults. Material and methods A systematic search was conducted using databases such as Google Scholar, PubMed, and Research Gate, focusing on studies published between 2015 and December 31, 2024. Keywords used included: elderly, physical fitness, strength training, health outcomes. The inclusion criteria comprised original scientific studies, tested at least one measure of fitness parameters and involving older adult participants and experimental interventions with resistance training. A total of 17 studies met the criteria and were analyzed in detail. Results The findings indicate that resistance training regardless of intensity level (low, moderate, or high) has a consistently positive effect on muscle strength, endurance, flexibility, cardiovascular function, body composition, balance, and overall functional mobility in older individuals. Training modalities included the use of weights, bodyweight exercises, resistance bands, and unstable surfaces. The frequency of interventions ranged from 8 weeks to 2.3 years, with training frequency mostly between two and three sessions per week. Studies combining resistance training with balance training or aerobic exercises demonstrated additional benefits. Conclusions The reviewed evidence suggests that resistance training is an effective and safe strategy for improving the physical fitness and health of older adults, potentially reducing the risk of falls and chronic diseases. It is recommended that resistance training be incorporated into regular physical activity routines, ideally alongside aerobic and flexibility exercises, to maximize overall health outcomes in the aging population.

This paper introduces affordance-based explanations of robot navigational decisions. The rationale behind affordance-based explanations draws on the theory of affordances, a principle rooted in ecological psychology that describes potential actions the objects in the environment offer to the robot. We demonstrate how affordances can be incorporated into visual and textual explanations for common robot navigation and path-planning scenarios. Furthermore, we formalize and categorize the concept of affordance-based explanations and connect it to existing explanation types in robotics. We present the results of a user study that shows participants to be, on average, highly satisfied with visual-textual, i.e., multimodal, affordance-based explanations of robot navigation. Furthermore, we investigate the complexity of different types of textual affordance-based explanations. Our research contributes to the expanding domain of explainable robotics, focusing on explaining robot actions in navigation.

Future wireless multiple-input multiple-output (MIMO) systems will integrate both sub-6 GHz and millimeter wave (mmWave) frequency bands to meet the growing demands for high data rates. MIMO link establishment typically requires accurate channel estimation, which is particularly challenging at mmWave frequencies due to the low signal-to-noise ratio (SNR). In this paper, we propose two novel deep learning-based methods for estimating mmWave MIMO channels by leveraging out-of-band information from the sub-6 GHz band. The first method employs a convolutional neural network (CNN), while the second method utilizes a UNet architecture. We compare these proposed methods against deep-learning methods that rely solely on in-band information and with other state-of-the-art out-of-band aided methods. Simulation results show that our proposed out-of-band aided deep-learning methods outperform existing alternatives in terms of achievable spectral efficiency.

The application of additive manufacturing technologies for producing parts from polymer composite materials has gained significant attention due to the ability to create fully functional components that leverage the advantages of both polymer matrices and fiber reinforcements while maintaining the benefits of additive technology. Polymer composites are among the most advanced and widely used composite materials, offering high strength and stiffness with low mass and variable resistance to different media. This study aims to experimentally investigate the impact of selected process parameters, namely, wall thickness, raster angle, printing temperature, and build plate temperature, on the flexural properties of carbon fiber reinforced polyamide (CFrPA) fused deposition modeling (FDM) printed samples, as per ISO 178 standards. Additionally, regression and artificial neural network (ANN) models have been developed to predict these flexural properties. ANN models are developed for both normal and augmented inputs, with the architecture and hyperparameters optimized using random search technique. Response surface methodology (RSM), which is based on face centered composite design, is employed to analyze the effects of process parameters. The RSM results indicate that the raster angle and build plate temperature have the greatest impact on the flexural properties, resulting in an increase of 51% in the flexural modulus. The performance metrics of the optimized RSM and ANN models, characterized by low MSE, RMSE, MAE, and MAPE values and high R2 values, suggest that these models provide highly accurate and reliable predictions of flexural strength and modulus for the CFrPA material. The study revealed that ANN models with augmented inputs outperform both RSM models and ANN models with normal inputs in predicting these properties.

This paper aims to examine the lightfastness of yellow water-based ink using a light-accelerated aging chamber. Mondy Maestro Print uncoated offset paper (120 g/m²) was used as printing substrate. The printing was carried out on an inkjet printing machine using water-based inks, and the light exposure was tested within the Solarbox climate chamber. The study was conducted through the analysis of colour differences, as well as changes in chroma and lightness, across light, mid and dark tonal patches, as well as the paper substrate. It is hypothesised that the paper substrate will influence the tonal patches through its changes, and that the colour differences will be greater with higher tonal coverage. Experimental results obtained throught spectrophotometric measurements indicate significant color differences. It was found that the paper substrate, through its alterations, influenced the yellow tonal patches. Furthermore, higher tonal coverage resulted in more pronounced colour changes. An exception was observed in the 70% tonal value (TV), which exhibited greater changes compared to the solid patch. These studies are crucial for better understanding of the application and efficiency of this type of ink in the graphic arts industry.

<p style="text-align: justify;">The convergence of advanced materials science and circular economy principles is redefining the future of sustainable engineering. This paper explores the transformative role of biocomposites, nanomaterials, and smart materials in minimizing environmental impact and fostering resource-efficient production systems. By integrating these materials into industrial processes, manufacturers can significantly enhance product durability, recyclability, and energy efficiency. A critical aspect of this transition lies in the redesign of production chains, aligning them with circular economy frameworks to reduce waste, extend product lifecycles, and create closed-loop systems. Through a multidisciplinary lens, this study examines the synergy between material innovation and circular economy strategies, offering insights into how engineering advancements can mitigate environmental footprints while fostering economic resilience. By embracing cutting-edge technologies and sustainable design principles, industries can pave the way for a future where efficiency, adaptability, and ecological responsibility are seamlessly integrated into manufacturing ecosystems.</p>

<p style="text-align: justify;">The progress of modern society is directly linked to advancements and innovations in information and communication technologies. The new economic and social opportunities that are part of this progress have transformed the urban landscape and led to the emergence of smart cities. Residential buildings, vehicles, and social systems strive to achieve complete connectivity known as the "Internet of Things" (IoT). The use of the IoT in smart cities generates a massive amount of data that must be collected and analyzed. To do this effectively, artificial intelligence (AI) applications are used, as they are the only ones capable of processing such large volumes of data from various sources. Through AI algorithms, it is possible to continuously monitor data, analyze it, optimize resource usage, simplify decision-making, and facilitate the resolution of key urban life challenges in smart cities. This paper explores the ways in which the integration of AI and IoT can contribute to the improvement of various urban aspects. The primary focus of the paper is to highlight the transformative potential of such integration in the scenarios of smart cities.</p>

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.

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.

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.