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.

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.

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.

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.

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.

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.

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.

Aim: To identify the clinicopathological factors associated with five year mortality in patients with colorectal cancer (CRC) treated at Cantonal Hospital Zenica, Bosnia and Herzegovina. Methods: A retrospective cohort of 64 consecutively operated CRC patients (2019 2024) was analysed. The base-line variables included age, sex, tumor stage, histology, metastatic burden, local infiltration, and comorbidities. Five year cumulative mortality was the primary outcome. Risk ratios (RR) with 95 % confidence intervals (CI) were calculated by two by two contingency analysis.Results: The cohort comprised 26 women (40.6 %) and 38 men (59.4 %); their median age was 64 years (IQR 58.8–73.0). Eleven patients (17.2 %) died within five years. Mortality was strongly linked to tumor spread and cardiometabolic disease. Any distant metastasis conferred a fifteen fold increase in risk (9/15 vs 2/49; RR 14.7, 95 % CI 3.6–60.8, p < 0.001), and the involvement of two or more metastatic sites remained prognostic (RR 5.6, 95 % CI 1.9–16.9,p = 0.014). Infiltration of more than two adjacent organs quadrupled mortality (RR 4.4, 95 % CI 1.7–11.6, p = 0.032). Hypertension was present in 10 of the 11 deaths, yielding an RR of 12.1 (95 % CI 1.6–88.8, p = 0.002).Type 2 diabetes also increased risk (RR 3.5, 95 % CI 1.3–9.6, p = 0.040). Patients with three or more comorbid conditions had a nearly four times higher mortality (RR 3.9, 95 % CI 1.3–11.7, p = 0.027).Conclusion: The five year death rate in this Bosnian Herzegovinian CRC cohort was driven chiefly by distant metastasis, extensive local invasion, and cardiometabolic comorbidities—especially hypertension and type 2 diabetes. Early detection of metastatic spread and proactive management of vascular risk factors may improve survival in similar settings.

Jejunal diverticulosis is a rare condition that often presents asymptomatically, but can occasionally lead to severe complications, such as obstruction, perforation or bleeding. We report a case of an incarcerated ventral hernia resulting from massive jejunal diverticulosis, an unusual cause of bowel obstruction. An 80-year-old female patient presented with acute abdominal pain, nausea and vomiting. Physical examination revealed a tender, irreducible mass in the epigastric region. Exploratory surgery was performed and confirmed the presence of multiple jejunal diverticula, with one segment incarcerated in the epigastric hernia. The patient underwent successful surgical repair, including liberation of the affected jejunal segment and hernia repair. This case highlights the importance of considering jejunal diverticulosis in the differential diagnosis of bowel obstruction, and emphasizes the need for prompt surgical intervention in cases of complicated diverticulosis. Early diagnosis and appropriate management are critical inpreventing the severe morbidity and mortality associated with this condition.

Rapid industrialization has led to the creation of large amounts of wastewater containing various pollutants, among which heavy metals stand out. Heavy metals such as Cd (II) ions cause serious chronic diseases and even death if they are present in high concentrations. Therefore, this manuscript investigates the possibility of Cd (II) ion removal by precipitation method using Ca(OH)2. In order to optimize the precipitation process, the following were investigated: initial pH, initial concentration of Cd (II) ions, dose of added Ca(OH)2, stirring speed and contact time, as well as the influence of competing ions on the removal efficiency of Cd (II) ions. The optimization of the precipitation process was performed by varying one operational parameter at a time, while keeping all other parameters constant. Results of Cd(II) ion removal efficiency and optimal conditions are: pH 5 (99.961%), stirring speed of 0 rpm (99.985%), contact time metal-precipitant 5 minutes (99.965%), added dose of Ca(OH)2 60 mg (99.965%). Complete removal of Cd (II) ions was achieved at a Cd(II) ion concentration of 10 ppm, and high removal efficiency was achieved at concentrations of 50-300 ppm (98.231-99.994%). The removal efficiency of over 99% of Cd (II) ions was achieved during individual tests of ion competitiveness. Therefore, it can be concluded that under the tested conditions, Ca(OH)2 is an effective agent for removing Cd (II) with an efficiency above 99%.

Background and purpose This study investigates the influence of pedagogical qualification on the teaching of gymnastics in primary education, focusing on Slovak teachers’ instructional practices, resource utilization, and perceptions of teaching difficulty. Gymnastics is a foundational component of physical education (PE), promoting critical motor skills such as coordination, balance, and strength. Despite its benefits, gymnastics is often perceived as a difficult subject to teach, largely due to gaps in teacher training. Material and methods An online survey was completed by 1 189 actively employed primary school teachers across Slovakia during the 2023/2024 school year. Respondents were grouped by pedagogical background: 52.23% held preschool/elementary education qualifications, while 47.77% had alternative pedagogical training such as PE specialization. Results Results showed that “Gymnastics/Dance” was rated as the second most challenging thematic unit by both groups, with 28.18% of preschool/elementary-qualified teachers and 34.54% of other-qualified teachers selecting it, following “Health/Fitness” (38.49% and 37.18%, respectively). Although differences were not statistically significant (χ ²(3) = 7.56, p = 0.055), they highlight widespread difficulty with gymnastics instruction. Apparatus use was similarly high in both groups, with 66.34% of preschool/elementary-trained and 66.20% of other-qualified teachers reporting use of traditional gymnastics equipment. However, significant differences were observed in broader equipment use (χ²(3) = 12.84, p = 0.005), where 23.35% of preschool/elementary-trained teachers reported using both traditional and non-traditional tools compared to 17.96% of other-qualified teachers. Perceptions of facility adequacy also varied significantly (χ²(3) = 9.86, p = 0.018), with more critical ratings from preschool/ elementary-trained respondents. Conclusions These findings suggest that pedagogical training influences teaching diversity, expectations, and perceived support in gymnastics education. The study highlights the need for more robust, practice-focused training in gymnastics during teacher preparation, as well as improved access to equipment and facilities to support high-quality instruction.

Unambiguous identification of active sites in heterogeneous catalysis remains a major challenge, particularly for materials with ultrathin, chemically mixed surface layers. Here, we demonstrate a generalizable approach that combines time-of-flight secondary ion mass spectrometry (ToF-SIMS) with multivariate statistical analysis (principal component analysis [PCA] and multivariate curve resolution [MCR]) to resolve catalytically relevant motifs at the nanoscale. Using Ni electrodes as a model system, PCA distinguished hydroxide-enriched domains from oxide- and metal-rich regions, while MCR decomposed depth profiles and 3D images into hydroxide, oxide, and metallic layers with nanometer resolution. A unique secondary-ion fragment, NiO3H3 - (m/z 108.94), emerged as a marker of hydroxide-rich environments and correlated with hydrogen evolution reaction (HER) activity across a series of Ni electrodes. Complementary density functional theory (DFT) calculations revealed that Ni(OH)2 clusters adjacent to metallic Ni offer the most favorable water dissociation energetics, establishing the structural origin of the marker. While illustrated here for Ni-based HER, this workflow provides a broadly applicable framework to isolate and rank near-surface patterns that govern catalytic activity, thereby extending ToF-SIMS from a qualitative probe to a predictive tool for active site identification.