Search Results (751)

Background/Objectives: High-intensity interval training (HIIT) is considered an effective way in improving aerobic capacity and selected health parameters. Ashwagandha is an herb with possible health-promoting properties that may affect metabolism and performance. The aim of this study was to evaluate the effects of ashwagandha supplementation (600 mg/day) during an 8-week HIIT on body composition, lipid profile and hormone levels related to energy homeostasis in healthy young men. Methods: The study was randomised, double-blind and placebo-controlled (Placebo group, PL, n = 20; ashwagandha, A, n = 18). HIIT was conducted on a rowing ergometer (3 times per week, 5–7 series of 1.5 min at 85–95% of maximum power, with intervals of 1.5 min at 70 W). Body composition (BIA, Tanita TBF 300P), serum lipid profile (tChol, HDL-cholesterol, LDL-cholesterol, TG) and serum levels of adiponectin, asprosin and irisin were analysed before (term 1) and after the8-week study (term 2). Both the lipid and hormonal profiles were measured in three time points: pre- and post-graded exercise test and after 24 h recovery period. Results: Analysis showed no effect of training or supplementation on body composition and lipid profile (p > 0.05). In turn, the 8-week HIIT decreased resting levels of adiponectin and increased irisin levels post-exercise and after 24 h (p < 0.05). Conclusions: In young, healthy men, an 8-week HIIT programme significantly affects selected hormones related to energy metabolism of adipose (adiponectin) and muscle (irisin) tissues, but ashwagandha supplementation did not significantly affect any of the hormonal parameters analysed. Full article

The significance of human capital (HC) has been gaining attention worldwide. However, practices of human resource management (HRM) vary across countries. In Japan, these HRM practices have been shaped by top-down initiatives such as the Charter of Work–Life Balance, the Work Style (WS) Reform, and the mandatory disclosure of HC for publicly listed companies. This study examines the evolution of HRM perceptions in Japanese companies from 2008 to 2024, as well as the quantitative trends and semantic shifts in the mentions of a series of institutional reforms. This study performed text analysis on 51,666 narrative disclosure documents from 3970 listed Japanese companies. Results show that mandatory HC disclosure marked a semantic turning point, shifting the corporate focus from short-term productivity to long-term sustainability. Moreover, the sequential introduction of new concepts has fostered coexistence and semantic reconstruction, rather than competition or exclusion between HC and WS. This study empirically demonstrates that top-down institutional reforms can reshape corporate perceptions beyond mere compliance. It clarifies the dynamics of conceptual coexistence and semantic evolution when related ideas are introduced sequentially. In addition, the findings highlight the value of large-scale narrative disclosure documents in analyzing semantic change. Full article

The advent of artificial intelligence marks a decisive turning point in the evolution of Industry 5.0, redefining the paradigms of industrial performance. This holistic transformation affects not only technological aspects but also the entire industrial ecosystem. Industrial performance is amplified by AI through two major axes: operational excellence and strategic differentiation of solutions. These drivers of performance are structured around concrete strategic advantages, particularly in terms of technological leadership and operational resilience. However, this transformation raises significant challenges on both the human, technical, and financial levels. The managerial implications require a structured approach to the adoption of AI, supported by appropriate organizational development. Future prospects suggest an ever-deeper integration of AI within the industrial ecosystem, paving the way for new models of performance and innovation. In this paper, we strive to make a scientific contribution aimed at shedding light on the impact of artificial intelligence on Industry 5.0, highlighting its implications for the pillars of industrial transformation: operational efficiency and optimization of industrial processes, technological innovation, and competitiveness. We have opted for a theoretical analysis of research related to the integration of AI into industrial systems, in order to provide a synthetic and critical review of this phenomenon. Full article

There has been significant interest in deploying unmanned aerial vehicles (UAVs) for their ability to perform precise and rapid remote mapping and inspection of critical environmental assets for structural health monitoring. This case study investigates the use of UAV-based LiDAR and photogrammetry at Melbourne Water’s Western Treatment Plant (WTP) to routinely monitor high-density polyethylene floating covers on anaerobic lagoons. The proposed approach integrates LiDAR and photogrammetry data to enhance the accuracy and efficiency of generating digital elevation models (DEMs) and orthomosaics by leveraging the strengths of both methods. Specifically, the photogrammetric images were orthorectified onto LiDAR-derived DEMs as the projection plane to construct the corresponding orthomosaic. This method captures precise elevation points directly from LiDAR, forming a robust foundation dataset for DEM construction. This streamlines the workflow without compromising detail, as it eliminates the need for time-intensive photogrammetry processes, such as dense cloud and depth map generation. This integration accelerates dataset production by up to four times compared to photogrammetry alone, while achieving centimetre-level accuracy. The LiDAR-derived DEM achieved higher elevation accuracy with a root mean square error (RMSE) of 56.1 mm, while the photogrammetry-derived DEM achieved higher in-plane accuracy with an RMSE of up to 35.4 mm. An analysis of cover deformation revealed that the floating cover had elevated rapidly within the first two years post-installation before showing lateral displacement around the sixth year, which was also evident from a significant increase in wrinkling. This approach delivers valuable insights into cover condition that, in turn, clarifies scum accumulation and movement, thereby enhancing structural integrity management and supporting environmental sustainability at WTP by safeguarding methane-rich biogas for renewable-energy generation and controlling odours. The findings support the ongoing collaborative industry research between Monash University and Melbourne Water, aimed at achieving comprehensive structural and prognostic health assessments of these high-value assets. Full article

This study explored how AI affects the sustainability of competitive advantage in the tourism and hospitality sector, with a particular focus on the mediating roles of digital culture and digital skills in the lens of the Technology Acceptance Model (TAM). Data were collected via a structured questionnaire distributed to a purposive sample of 488 managers and supervisors working in five-star hotels, travel agencies, and DMCs across Saudi Arabia. The findings revealed that AI has a significant direct effect on sustainable competitive advantage and also exerts strong positive effects on both digital culture and digital skills. In turn, both of these internal enablers significantly contribute to sustaining a competitive advantage. Mediation analysis further showed that both digital culture and digital skills partially mediate the relationship between AI and sustainable competitiveness. The study addresses a notable gap in tourism research by providing localized evidence from a market undergoing rapid transformation under Vision 2030, and, taken together, extends TAM to an organizational lens by demonstrating AI’s role in shaping culture and skills that underpin a durable advantage while pointing to actionable priorities—targeting high-value AI use cases, conducting capability audits, institutionalizing continuous learning through visible leadership and role-based upskilling, and embedding culture- and skills-oriented KPIs within AI governance. Full article

Open-pit mining often induces geological hazards such as slope instability, surface subsidence, and ground fissures. To support sustainable mine operations and safety, high-resolution monitoring and mechanism-based interpretation are essential tools for early warning, risk management, and compliant reclamation. This study focuses on the Baorixile open-pit coal mine in Inner Mongolia, China, where 48 Sentinel-1 images acquired between 3 March 2017 and 23 April 2021 were processed using the Small-Baseline Subset and Distributed-Scatterer Interferometric Synthetic Aperture Radar (SBAS-DS-InSAR) technique to obtain dense and reliable time-series deformation. Furthermore, a Trend–Periodic–Residual Subspace-Constrained Regression (TPRSCR) method was developed to decompose the deformation signals into long-term trends, seasonal and annual components, and residual anomalies. By introducing Distributed-Scatterer (DS) phase optimization, the monitoring density in low-coherence regions increased from 1055 to 338,555 points (approximately 321-fold increase). Deformation measurements at common points showed high consistency ($R^2$ = 0.97, regression slope = 0.88; mean rate difference = −0.093 mm/yr, standard deviation = 3.28 mm/yr), confirming the reliability of the results. Two major deformation zones were identified: one linked to ground compaction caused by transportation activities, and the other associated with minor subsidence from pre-mining site preparation. In addition, the deformation field exhibits a superimposed pattern of persistent subsidence and pronounced seasonality. TPRSCR results indicate that long-term trend rates range from −14.03 to 14.22 mm/yr, with a maximum periodic amplitude of 40 mm. Compared with the Seasonal-Trend decomposition using LOESS (STL), TPRSCR effectively suppressed “periodic leakage into trend” and reduced RMSEs of total, trend, and periodic components by 48.96%, 93.33%, and 89.71%, respectively. Correlation analysis with meteorological data revealed that periodic deformation is strongly controlled by precipitation and temperature, with an approximately 34-day lag relative to the temperature cycle. The proposed “monitoring–decomposition–interpretation” framework turns InSAR-derived deformation into sustainability indicators that enhance deformation characterization and guide early warning, targeted upkeep, climate-aware drainage, and reclamation. These metrics reduce downtime and resource-intensive repairs and inform integrated risk management in open-pit mining. Full article

In the context of rising uncertainty and financial crises, the roles of financial advisors are evolving beyond technical compliance, particularly in household contexts. This article introduces a novel perspective by highlighting how these professionals contribute to resilience and stability at all levels of society by building financial literacy and acting as human barriers against systemic risk. From the datasets retrieved from Web of Science and Scopus, a final curated sample of 102 peer-reviewed articles was retained following thematic refinement and in-depth human filtering. After data harmonisation, a bibliometric analysis was conducted through VOSviewer, identifying five key thematic clusters. Beyond cartographic description, a rigorous thematic exploration was conducted. We advance an interpretive architecture consisting of mechanisms (M1–M4), advice-to-outcome pathways (P1–P3), and a conditional context (Conditions of Success (CS), Failure points (F) and Moderating Factors (MF)), enabling integrative inference and cumulative explanation across an otherwise heterogeneous corpus. Results show that financial advisors mitigate risk by educating clients, guiding decisions, and turning complexity into usable judgment. They also bear risk; as human barriers, they channel and transform these pressures through their professional practice, returning stabilizing effects to households and, by extension, to the wider financial system. Full article

Fungal keratitis is a severe infection that often requires surgical intervention and is associated with poor outcomes. Penetrating keratoplasty allows for the complete removal of the fungal infiltrate and thus can be a turning point in therapy. The depth of pathogen invasion, which cannot always be reliably assessed by slit lamp examination, can be accurately determined through histological analysis of the corneal trephinate. In this study, we histologically analyzed two corneal trephinates obtained during an emergency keratoplasty performed for uncontrollable mycotic infections. In case 1, caused by Candida albicans, the infiltrate remained localized at the site of pathogen entry. In contrast, in case 2, Fusarium falciforme demonstrated extensive tissue invasion, spreading destructively throughout the cornea. This invasion pattern suggests that Fusarium keratitis is difficult to control due to its aggressive spreading behavior within the tissue. This explains the high rate of penetrating keratoplasty required in such cases. Full article

This study focuses on improving the efficiency of interior permanent magnet synchronous motors (IPMSMs) for electric vehicle (EV) compressors. Seven rotor topologies (B, dB, V, dV, D, U, and UV) were first compared, among which the U-type rotor demonstrated the highest efficiency and the lowest total loss. Subsequently, the influence of the turn number and rotor outer diameter (ROD) on the shift of the high-efficiency region was analyzed, and six key design variables were identified through Pearson correlation-based sensitivity analysis. Using these variables, a multi-objective optimization was performed in Ansys OptiSLang, which improved the integrated part load value (IPLV)-weighted efficiency from 91.05% to 92.29% and shifted the high-efficiency region closer to the main operating point. Experimental validation of the reference model confirmed the reliability of the FEM analysis, and the proposed optimal design is expected to enhance low-speed efficiency and reduce battery energy consumption in EV compressor applications. Full article

This study investigates the evolution of online public opinion during the COVID-19 pandemic by integrating topic mining with sentiment analysis. To overcome the limitations of traditional short-text models and improve the accuracy of sentiment detection, we propose a novel hybrid framework that combines a GloVe-enhanced Biterm Topic Model (BTM) for semantic-aware topic clustering with a RoBERTa-TextCNN architecture for deep, context-rich sentiment classification. The framework is specifically designed to capture both the global semantic relationships of words and the dynamic contextual nuances of social media discourse. Using a large-scale corpus of more than 550,000 Weibo posts, we conducted comprehensive experiments to evaluate the model’s effectiveness. The proposed approach achieved an accuracy of 92.45%, significantly outperforming baseline transformer-based baseline representative of advanced contextual embedding models across multiple evaluation metrics, including precision, recall, F1-score, and AUC. These results confirm the robustness and stability of the hybrid design and demonstrate its advantages in balancing precision and recall. Beyond methodological validation, the empirical analysis provides important insights into the dynamics of online public discourse. User engagement is found to be highest for the topics directly tied to daily life, with discussions about quarantine conditions alone accounting for 42.6% of total discourse. Moreover, public sentiment proves to be highly volatile and event-driven; for example, the announcement of Wuhan’s reopening produced an 11% surge in positive sentiment, reflecting a collective emotional uplift at a major turning point of the pandemic. Taken together, these findings demonstrate that online discourse evolves in close connection with both societal conditions and government interventions. The proposed topic–sentiment analysis framework not only advances methodological research in text mining and sentiment analysis, but also has the potential to serve as a practical tool for real-time monitoring online opinion. By capturing the fluctuations of public sentiment and identifying emerging themes, this study aims to provide insights that could inform policymaking by suggesting strategies to guide emotional contagion, strengthen crisis communication, and promote constructive public debate during health emergencies. Full article

The potential of thin-section petrography for the analysis of ancient ceramic materials, such as pottery vessels, figurative objects and building materials made of fired clay, was already recognized during the 19th century, but its use has become more intensive during the past 80 years. Since pottery is the most common and typologically datable artifact in archaeological excavations from the pottery Neolithic period onwards (some 7000–8000 years ago), the analysis of pottery, including its composition, is a central component of archaeological research. As ceramic materials are made of fired clay, which in turn is procured from soils, weathered rocks and geological formations, the mineralogical composition of the ceramic artifacts represents the clay sources. The study of the mineralogical and rock fragment composition of thin sections of ancient ceramic artifacts can yield the characterization of the clay and soil type and thus the geographic location or area of the clay source. Since in antiquity we assume clay was not precured from a distance of more than one day’s walk from the production site (‘site catchment area’), the production location can be detected as well. Thus, petrographic analysis can identify the trade of artifacts and commodities (if the ceramics are containers) in antiquity, which can shed light on political and cultural links and trade between ancient societies and their economic and social structure. In addition, since clay was often treated by ancient potters to improve its quality (levigation, clay mixing, addition of temper), technological aspects of the production sequence (chaîne opératoire) can also be acquired by petrographic analysis. Today, petrographic analysis is part of many standard studies of ancient pottery. While it is an old and relatively ‘low tech’ method, the accessibility of the equipment needed and its high analytic potential maintains its important and common position in archaeological research. This article describes the method and its analytical potential from the archaeological point of view and briefly mentions several archaeological case studies exemplifying its wide and diversified potential in the study of ancient ceramics in past decades. Full article

This paper defines the term “graffiti” and outlines the origins of this concept. The terminological arrangement allowed for the subject of this research, i.e., illegal graffiti, to be situated in reality, i.e., an urban space. It was assumed that the existence of the tag was associated with a disturbance of spatial order and had an impact on safety in a space. This, in turn, is related to whether the principles of sustainable development in the social dimension are applied. This paper makes reference to theories of security in a space (the “broken windows” theory and the strategy of Crime Prevention Through Environmental Design, CPTED) and shows the problem of illegal graffiti against the background of these theories. A new research aspect of the occurrence of illegal graffiti (scribbles and tags) within urban space is the features that determine its emergence in a spatial dimension. The aim of the analyses in this paper is to obtain information on which geospatial features are generators of illegal graffiti. The research field was limited to the space of one city—Olsztyn—with the assumption that the proposed research methodology would be useful for the spaces of other cities. The research methodology consists of several steps: firstly, we determined a list of features in the surroundings of illegal graffiti using direct interviews, and secondly, we analyzed the frequency of occurrence of these features in the researched locations in space. The next step was to standardize the obtained results using the quotient transformation method with respect to a reference point, where the reference point is the sum of all observations. After that, we assigned ranks for standardized results. The last stage involved an analysis using the GRA type of grey systems to obtain a sequence of strengths of relationships. This sequence allowed us to determine which of the features adopted for analysis have the greatest impact on the creation of illegal graffiti in a space. As indicated by the strength of the relationship, in the analyses conducted, geospatial features such as poor sidewalk condition and neglected greenery have the greatest impact on the occurrence of illegal graffiti. Other features that influence the occurrence of illegal graffiti in a given space include a lack of visibility from neighboring windows and the proximity of a two-way street. It can be assumed that these features are generators of illegal graffiti in the studied area and space. The poor condition of the facade has the least impact on the possibility of illegal graffiti occurring in a given space. Full article

Performance analysis in elite football still faces significant challenges: traditional descriptive statistics often fail to capture tactical adaptability, and African teams remain underrepresented in the scientific literature despite achieving historic breakthroughs. The FIFA World Cup Qatar 2022 marked a turning point, with Morocco becoming the first African nation to reach the semi-finals. This study systematically analyzed the tactical, physical, and structural performance of the Moroccan national team across seven matches using official FIFA post-match reports. A three-level methodological framework was adopted: (i) descriptive analysis of key performance indicators (KPIs); (ii) visual profiling through radar charts, heatmaps, and passing networks; and (iii) exploratory modelling using principal component analysis (PCA) and clustering. Results revealed consistent defensive organization, low ball possession (<40% in five matches), and effective counter-attacking transitions, with pressing peaks against Spain (288 actions) and France (299 actions). PCA explained 76% of the variance, identifying two principal axes (physical intensity vs. technical mastery; verticality vs. build-up play) and clustering distinguished three match types: low-block defensive games, transition-oriented games, and open matches. These findings highlight Morocco’s tactical adaptability and sustained physical commitment. The study demonstrates how AI-enhanced analytics and multidimensional data visualization can uncover latent performance patterns and support evidence-based decision-making. Practical implications include actionable insights for performance analysts and coaching staff, particularly as Morocco prepares for the 2025 Africa Cup of Nations and the FIFA World Cups in 2026 and 2030. This integrative approach can serve as a model for federations seeking data-driven performance optimization in elite football. Full article

The study investigates the interaction of humic acids (HAs) with road petroleum bitumen to enhance its performance and resistance to technological aging. It addresses a critical gap in understanding the modification mechanisms. The research is motivated by the need for sustainable and effective bitumen modifiers to improve the durability of asphalt pavements. The primary objective was to characterize the interaction between HA and bitumen using advanced analytical techniques, including complex thermal analysis (DTA/DTG), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The results demonstrated that adding two wt.% HA to bitumen BND 70/100 increased its thermal stability, raising the onset temperature of thermo-oxidative processes from 214 to 237 °C and reducing the mass loss rate during heating from 2.5 to 1.9%·min⁻¹. FTIR analysis revealed chemical interactions between polar groups of humic acids (e.g., –COOH, –OH) and bitumen components, forming a denser structure. SEM images confirmed a more homogeneous microstructure with fewer microcracks in the modified bitumen. Practical improvements included a higher softening point (52.6 to 54 °C) and enhanced elastic recovery (17.5 to 28.7%). However, the study noted limitations such as reduced ductility (from 58 to 15 cm) and penetration (from 78 to 72 dmm), indicating increased stiffness. The findings highlight the potential of humic acids as eco-friendly modifiers to improve bitumen’s aging resistance and thermal performance, offering practical value for extending pavement lifespan. The effective use of HA will, in turn, allow the use of Ukrainian lignite, the balance reserves of which are estimated at 2.0–2.9 billion tons, in non-fuel technologies. Full article

It is of great significance to analyze the molecular mechanism of rice response to heavy ion irradiation and to mine its key response genes for food security. In this study, the regression equation for the dose survival rate was constructed using heavy ion irradiation on rice pollen. Through an immunofluorescence experiment, it was found that DSBs induced by irradiation could be repaired quickly, but the repair of complex damage required more time. RNA-seq of irradiated pollen showed that the gene expression patterns at different time points were significantly different. A total of 5556 differentially expressed genes (DEGs) were screened out, and the number of DEGs decreased with time. DEGs were mainly involved in stress response, protein folding, DNA repair, and other damage response processes at 0–1 h. At 6 h, the cells turned to normal metabolism functions, such as organic synthesis and protein activity. Combined with weighted gene co-expression network analysis (WGCNA) and trend analysis, the key transcription factor OsERF110 was identified in response to heavy ion irradiation, which acts on the nucleus and cell membrane. A total of 45,680 OsERF110 binding peaks were identified by DNA affinity purification sequencing (DAP-seq) in the whole genome. When this method was combined with RNA sequencing (RNA-seq), 62 OsERF110 target genes were further screened. These target genes were involved in DNA repair, stress response, redox, metabolic regulation, and other processes, forming the OsERF110 mediated radiation response regulatory network. The results of this study provide a new target for rice mutation breeding and lay a theoretical foundation for radiation biology research. Full article