Background and purpose Running at different distances involves changes in energy systems and biomechanical demands, which affect running speed. There is a need for a more detailed study of the relationship between physiological and biomechanical factors in physical education and sports students.  Aim to analyze the fluctuations and tendency to decrease running speed at distances of 100 m, 200 m, 400 m and 800 m, as well as the physiological and biomechanical substantiation of the characteristics of this tendency in third-year students of the Faculty of Physical Education and Sports. Material and methods The participants were 25 students (average height 174.84 cm, weight 75.92 kg, BMI 22.90) attending the Athletics 1 course and regularly engaged in training. Four running distances (100 m, 200 m, 400 m, 800 m) were tested by measuring times and calculating average speeds. The runs were performed under standardized conditions with maximal effort. Data were statistically analyzed using means, variability measures, and Pearson correlation (p < 0.05). Results The highest average speed was recorded in the 100 m (7.76 ± 0.57 m/s; mean time 12.95 ± 1.00 s), followed by a slight decrease in the 200 m (7.19 ± 0.80 m/s), reflecting the predominance of the anaerobic alactic energy system. A more pronounced reduction was observed at 400 m (6.18 ± 0.61 m/s) and further at 800 m (4.59 ± 0.48 m/s), indicating a metabolic shift towards anaerobic lactic and aerobic pathways, accompanied by fatigue and lactate accumulation.  The overal decrease in average speed at a distance of 100-800 m was 40.86%. Statistically significant positive correlations were found between performances in all distances (p < 0.05), with the strongest correlation between 100 m and 200 m (r = 0.826; p = 0.000), followed by 100 m and 400 m (r = 0.739; p = 0.000), 400 m and 800 m (r = 0.719; p = 0.000), 200 m and 400 m (r = 0.665; p = 0.000), 100 m and 800 m (r = 0.642; p = 0.001), and 200 m and 800 m (r = 0.573; p = 0.003. Conclusion The students demonstrated well-developed explosive and short-term running abilities but limited aerobic endurance and speed maintenance on longer distances.  

This study aims to examine the role of community-based tourism (CBT) and local enterprise in shaping responsible travel behavior and sustainable loyalty. Through a comprehensive investigation of internal (push) and external (pull) motivational factors, this research delves into how tourists’ desire for self-development, biodiversity knowledge, nature appreciation and cultural engagement contribute to enriched travel experiences and long-term loyalty. Using a quantitative research approach, data were collected from 505 tourists via structured surveys and analyzed through SmartPLS to uncover the measurable relationships among motivational drivers, visitor experience quality and revisit intention. The findings confirm that both Pull–external and Push–internal motivational factors significantly influence tourist experiences in tourism-based communities and foster sustainable tourist loyalty. Moreover, the mediating role of tourist experience reinforces its function as a critical mechanism that translates motivation into meaningful post-visit outcomes such as loyalty, advocacy and responsible behavior. The results offer valuable insights for strategic policy making in tourism-based communities by providing a pioneering technique to develop tourist satisfaction and the sustainability of CBT enterprises. This study extends CBT research by identifying satisfaction as a key mediator and reinforcing the role of loyalty. The findings provide a deeper understanding of how tourism-based community participation and enterprise development within a biosphere reserve can foster meaningful tourist experiences and long-lasting connections to nature and culture. Also, despite the extensive literature on CBT enterprises, their role in tourism and hospitality remains underexplored in this context.

ABSTRACT Brain injuries pose ongoing challenges that require robust self-management and support systems due to cognitive, emotional, and social impacts. Many patients now turn to social media for additional support, often relying on health communities where they can share experiences and seek advice. By offering emotional support and practical self-management strategies, these communities help patients improve their overall quality of life. This study conducts a comparative analysis of how the affordances of two types of social media health communities (small and closed vs. large and open) shape self-management strategies and interpersonal relationships for individuals with traumatic brain injuries. By analysing user engagement patterns and content shared within these communities, the study shows how different affordances contribute to different forms of support. The small, closed community fosters trust and privacy, encouraging deeper connections, tailored support, and a sense of safety. Conversely, the large, open community offers anonymity, a wider range of perspectives, and broader access to information, although interactions may lack personal depth. The study contributes to the literature on social media communities and health information technologies by deepening our understanding of how digital environments mediate support systems. The findings also provide insights for healthcare providers, patients’ families, and designers of social media communities.

This paper analyzes different approaches for the mathematical modeling and optimization of process parameters in the hard turning process of 42CrMo4 steel using a hybrid approach combining response surface methodology (RSM), multi-criteria decision making (MCDM), and machine learning through, support vector regression (SVR) with one-factor-at-a-time (OFAT) sensitivity analysis. Controlled process parameters such as cutting speed, depth of cut, feed, and insert radius are applied to conduct the experiments based on a full factorial experimental design. RSM was used to develop models that describe the effect of controlled parameters on surface roughness and cutting forces. Special emphasis was placed on the analysis of standardized residuals to evaluate the predictive capabilities of the RSM-developed model on an unseen data set. For all four outputs considered, analysis of the standardized residuals shows that over 97% of the points lie within ±3 standard deviations. A multi-criteria optimization technique was applied to establish an optimal combination of input parameters. The SVR model had high performance for all outputs, with coefficient of determination values between 89.91% and 99.39%, except for surface roughness on the test set, with a value of 9.92%. While the SVR model achieved high predictive accuracy for cutting forces, its limited generalization capability for surface roughness highlights the higher complexity and stochastic nature of surface formation mechanisms in the turning process. OFAT analysis showed that feed rate and depth of cut have been shown to be the most important input variables for all analyzed outputs.

Background: Neuromodulation encompasses a range of methods aimed at selectively modifying nervous system function to enhance motor and neurophysiological processes. Although neuromodulation suits have shown benefits in clinical populations, their application in sports remains unexplored. Therefore, the aim of this case study was to examine the acute effects of a neuromodulation suit on the contractile properties of the rectus femoris muscle in an elite football player. Methods: The subject was an 18.8-year-old male professional football player. After conducting an anthropometric evaluation, initial tensiomyography (TMG) was carried out to evaluate the contractile properties of the rectus femoris, such as delay time (Td), contraction time (Tc), sustain time (Ts), relaxation time (Tr), and maximum radial displacement (Dm), in both legs. The athlete then donned a neuromodulation suit set to 20 Hz for a duration of 60 min. Following this, the same TMG measurements were repeated to assess post-intervention changes. Results: The right leg showed a reduction in Tc from 33.33 to 31.93 milliseconds (ms); Dm increased from 6.61 to 11.17 millimeters (mm). Conversely, the left rectus femoris exhibited prolonged Tc from 26.84 to 29.45 ms. Conclusions: A single 60 min session of neuromodulation suit application produced acute changes in muscle contractile properties. Findings suggest a potential positive effect on rapid force production and reduced muscle stiffness, alongside notable inter-limb variability.

Two structurally tunable (propyl-3-ol)triphenyltin(IV) (Ph3SnL1) and (butyl-4-ol)triphenyltin(IV) (Ph3SnL2) compounds were investigated at the human serum transferrin (Tf) molecular interface to resolve how ligand architecture and protein metallation modulate organotin(IV) biocompound stability and lobe-selective binding. Steady-state fluorescence spectroscopy revealed efficient quenching of native Tf emission (λex = 280 nm, 296–310 K, pH 7.4) without significant spectral displacement, indicating the predominant formation of non-fluorescent ground-state complexes. Calculated bimolecular quenching constants (Kq ~1012 M−1 s−1) exceeded the diffusion-controlled aqueous limit, ruling out a collisional dynamic quenching mechanism and confirming static complexation as the principal origin of fluorescence suppression. Double-log binding analysis revealed moderate affinity (Ka ~102–103 M−1) and an approximately single dominant binding event per protein (n ≈ 0.65–0.90). Temperature-dependent van’t Hoff evaluation yielded positive ΔH° and ΔS° values, supporting a spontaneous, entropy-favored association process largely governed by hydrophobic and dispersion-type contributions, consistent with lipophilic organotin(IV) scaffold accommodation. Iron (Fe3+) loading of Tf markedly enhanced ligand engagement, especially for Ph3SnL1, evidencing that metallation-induced lobe closure reshapes pocket accessibility and local polarity relevant for organotin(IV) binding presentation rather than simply strengthening empirical docking scores. Molecular docking localized the most stable Ph3SnL2 poses in the sterically confined, rigid C-lobe, while Ph3SnL1 preferentially penetrated the more adaptive N-lobe. ONIOM QM/MM refinement of docking poses confirmed strong interfacial stabilization (ΔEint ≈ –38 to –62 kcal mol−1) and clarified charge–packing interplay without invoking frontier orbital analysis. The results map multiscale structure–interaction relationships defining lobe preference and complex stability at the transferrin interface.

Ransomware core capability, unauthorized encryption, demands controls that identify and block malicious cryptographic activity without disrupting legitimate use. We present a probabilistic, risk-based access control architecture that couples machine learning inference with mandatory access control to regulate encryption on Linux in real time. The system builds a specialized dataset from the native ftrace framework using the function_graph tracer, yielding high-resolution kernel-function execution traces augmented with resource and I/O counters. These traces support both a supervised classifier and interpretable rules that drive an SELinux policy via lightweight booleans, enabling context-sensitive permit/deny decisions at the moment encryption begins. Compared to approaches centered on sandboxing, hypervisor introspection, or coarse system-call telemetry, the function-level tracing we adopt provides finer behavioral granularity than syscall-only telemetry while avoiding the virtualization/VMI overhead of sandbox-based approaches. Our current user-space prototype has a non-trivial footprint under burst I/O; we quantify it and recognize that a production kernel-space solution should aim to address this. We detail dataset construction, model training and rule extraction, and the run-time integration that gates file writes for suspect encryption while preserving benign cryptographic workflows. During evaluation, the two-layer composition retains model-level detection quality while delivering rule-like responsiveness; we also quantify operational footprint and outline engineering steps to reduce CPU and memory overhead for enterprise deployment. The result is a practical path from behavioral tracing and learning to enforceable, explainable, and risk-proportionate encryption control on production Linux systems.

The paper explores a more comprehensive approach to assessing text-level difficulty by combining quantitative readability metrics with qualitative analyses of content and context which help in reading comprehension and reading-for-translation. It compares two excerpts using eight readability scores formulas (Automated Readability Index, Flesch Reading Ease, Gunning Fog Index, Flesch-Kincaid Grade Level, Coleman-Liau Readability Index, Smog Index, Original Linsear Write Formula, Linsear Write Grade Level Formula) to explore how topic, content, and context may be used as indicators of text-level difficulty. Using authentic texts, specifically interviews from Humans of New York, the paper aims to demonstrate that other (extra)linguistic features must be considered beyond the numerical scores provided by readability formulas.

Giardia duodenalis is a protozoan parasite with worldwide distribution and recognized zoonotic potential. Data on its molecular epidemiology in Bosnia and Herzegovina (BiH) are scarce, particularly in wild mesocarnivores. This study aimed to investigate the occurrence and genetic characterization of G. duodenalis in domestic and wild mesocarnivores across BiH. A total of 520 fecal samples were collected between 2023 and 2025, including dogs (Canis lupus familiaris, n = 433), cats (Felis catus, n = 21), red foxes (Vulpes vulpes, n = 39), golden jackals (Canis aureus, n = 17), European pine martens (Martes martes, n = 5), grey wolves (Canis lupus, n = 1), European badgers (Meles meles, n = 2), and European wildcats (Felis silvestris, n = 1). Screening was performed using fecal flotation and immunofluorescence assay (IFAT), with selected samples further analyzed by high-resolution melting (HRM) real-time PCR (qPCR-HRM) and targeted next-generation sequencing (NGS). Overall, G. duodenalis was detected in 20.96 % (109/520) of samples by flotation and IFAT. Cats showed the highest positivity rate (71.43 %), followed by dogs (21.02 %), whereas wild mesocarnivores exhibited substantially lower detection rates (5.13 % in red foxes and 5.88 % in golden jackals). Among dog subpopulations, hunting dogs showed the highest positivity (49.52 %) compared with shelter dogs (6.72 %). Molecular typing revealed assemblage D as predominant (65.91 %), followed by assemblages B (18.18 %), C (6.82 %), and F (4.55 %), with occasional mixed profiles. Assemblage D occurred across multiple hosts, while the zoonotic assemblage B was detected exclusively in wild canids. This study provides the first molecular epidemiological evidence of G. duodenalis assemblage circulation among domestic and wild mesocarnivores in Bosnia and Herzegovina. The findings identify cats and hunting dogs as key hosts contributing to parasite circulation and demonstrate limited but epidemiologically meaningful involvement of wild mesocarnivores, underscoring the importance of integrated One Health surveillance to assess transmission risks at the domestic-wildlife-human interface.

We assess what the prevalence of share buybacks can tell us about the relationship between the firm and its stakeholders in an environment in which ownership is increasingly concentrated in the hands of a small number of large asset managers. While the finance literature has put forward several reasons for the current prevalence of buybacks, we posit that without the significant institutional changes outlined in this paper, namely the rise of index investing, these triggers by themselves cannot explain their popularity. We present a game theory model in which three players vie for the cash flow of the company: managers, shareholders, and other stakeholders. We show how in a constellation in which all three players have equal power the expected outcome would be to invest the company’s surplus cash in growth opportunities. This contradicts what is observable in practice: the prevalence of buybacks. We identify ’asset manager capitalism’ as the cause and conclude that changes in the shareholder ownership structure are partly responsible for this. Shareholders have used their increased influence to supervise managers and to shape corporate policy in their favour. This paper adds to the literature on stakeholder theory an understanding of how the relative power of stakeholder groups has changed under asset manager capitalism. We do not, however, seek to take sides in the debate as to whether share buybacks are desirable or not.

Acute and chronic abdominal pain are widespread and debilitating symptoms of inflammatory bowel disease (IBD) that substantially decrease patients’ quality of life. Opioids are powerful drugs yet activation of their traditional target, the μ-opioid receptor (MOR) in the central nervous system, is accompanied by severe adverse effects including dependence, sedation and respiratory depression. In recent years, targeting the κ-opioid receptor (KOR) in the periphery emerged as a promising strategy for the development of safer opioid-based analgesics to treat IBD-related pain. We generated cyclized analogues of dynorphin, the endogenous peptide ligand of KOR, and characterized them in pharmacological assays. Our efforts yielded thioether cyclized dynorphin (TCD) showing binding affinity to the KOR in the nanomolar range, with 16- and 150-fold selectivity over the MOR and δ-opioid receptor (DOR), respectively, as determined in radioligand binding assays. In the [35S]GTPγS binding assay, TCD acted as a partial agonist at the KOR when compared to the KOR agonist U69,593, while in the cAMP accumulation assay the peptide had an efficacy exceeding that of dynorphin A1-13. Importantly, TCD exhibits a strong KOR-mediated antinociceptive effect after subcutaneous administration in mouse models of inflammatory pain (formalin-induced inflammatory pain) and visceral pain (acetic acid-induced abdominal writhing test) with an ED50 of around 1.5 μmol/kg, being equipotent to U50,488. Furthermore, TCD did not produce KOR-mediated liability of motor dysfunction/sedation in the rotarod test when given to mice in a 7-fold higher dose than the antinociceptive doses. To obtain a lead compound suitable for oral application, we investigate to increase the stability of TCDs in gastric and intestinal fluids utilizing a medicinal chemistry strategy. Our research has the potential to improve IBD patient care by providing innovative and safer pain drug candidates.

The identification of cancer drivers is a cornerstone to delivery of precision oncology. So far sequencing of renal cell cancer (RCC) has largely been confined to the clear cell subtype of RCC. In contrast, sequencing analyses of the less common forms of RCC, papillary RCC (pRCC) and chromophobe RCC (ChRCC), have so far been limited. We analysed whole genome sequencing data on 164 tumour-normal pairs from the Genomics England 100,000 Genomes Project, providing a comprehensive, high-resolution map of copy number alterations, structural variation, and key global genomic features, including mutational signatures, intra-tumour heterogeneity and analysis of extrachromosomal DNA formation. Our research establishes correlations between genomic alterations and histological diversification and the extent to which genetically-mediated immune escape contributes to the development of these RCC subtypes. Implications: We demonstrate the distinctive genetics which characterises pRCC and ChRCC and how this information has the potential to inform patient treatment and clinical trials.

Everyday communication is dynamic and multisensory, often involving shifting attention, overlapping speech and visual cues. Yet, most neural attention tracking studies are still limited to highly controlled lab settings, using clean, often audio-only stimuli and requiring sustained attention to a single talker. This work addresses that gap by introducing a novel dataset from 24 normal-hearing participants. We used a mobile electroencephalography (EEG) system (44 scalp electrodes and 20 cEEGrid electrodes) in an audiovisual (AV) paradigm with three conditions: sustained attention to a single talker in a two-talker environment, attention switching between two talkers, and unscripted two-talker conversations with a competing single talker. Analysis included temporal response functions (TRFs) modeling, optimal lag analysis, selective attention classification with decision windows ranging from 1.1s to 35s, and comparisons of TRFs for attention to AV conversations versus side audio-only talkers. Key findings show significant differences in the attention-related P2-peak between attended and ignored speech across conditions for scalp EEG. No significant change in performance between switching and sustained attention suggests robustness for attention switches. Optimal lag analysis revealed narrower peak for conversation compared to single-talker AV stimuli, reflecting the additional complexity of multi-talker processing. Classification of selective attention was consistently above chance (55-70% accuracy) for scalp EEG, while cEEGrid data yielded lower correlations, highlighting the need for further methodological improvements. These results demonstrate that mobile EEG can reliably track selective attention in dynamic, multisensory listening scenarios and provide guidance for designing future AV paradigms and real-world attention tracking applications.

Incorporating noble-metal nanoparticles into semiconductors offers a powerful means to tailor their functional properties. Here, we demonstrate that embedding ordered three-dimensional lattices of Au nanoparticles (Au NPs) into MoO3 thin films via magnetron sputtering enables broad tunability of the optical and thermo-electrical behavior. The formation of regular Au NP lattices, with controlled particle sizes, interparticle separations, and ordering, is achieved through precise adjustment of the deposition temperature and layer thickness conditions. Localized surface plasmon resonances (LSPR) arising from Au NPs-and their coupling at small separations-induce a strong modulation of the optical absorption across a wide spectral range. Simultaneously, the film's electrical resistance can be tuned by up to six orders of magnitude, while the activation energy and temperature coefficient of resistance (TCR) are reduced by up to fifty-fold compared to pure MoO3. These findings offer relevant information for designing oxide-plasmonic hybrid materials, highlighting their potential for next-generation optoelectronic, sensing, and energy-harvesting devices.

We introduce BallotRank, a ranked preference aggregation method derived from a modified PageRank algorithm. It is a Condorcet-consistent method without damping, and empirical examination of nearly 2,000 ranked choice elections and over 20,000 internet polls confirms that BallotRank always identifies the Condorcet winner at conventional values of the damping parameter. We also prove that the method satisfies many of the same social choice criteria as other well-known Condorcet completion methods, but it has the advantage of being a natural social welfare function that provides a full ranking of the candidates.