Search Results (749)

Background: This study presents an innovative approach to cardiovascular disease (CVD) risk prediction based on a comprehensive analysis of clinical, immunological and biochemical markers using mathematical modelling and machine learning methods. Baseline data include indices of humoral and cellular immunity (CD59, CD16, IL-10, CD14, CD19, CD8, CD4, etc.), cytokines and markers of cardiovascular disease, inflammatory markers (TNF, GM-CSF, CRP), growth and angiogenesis factors (VEGF, PGF), proteins involved in apoptosis and cytotoxicity (perforin, CD95), as well as indices of liver function, kidney function, oxidative stress and heart failure (albumin, cystatin C, N-terminal pro B-type natriuretic peptide (NT-proBNP), superoxide dismutase (SOD), C-reactive protein (CRP), cholinesterase (ChE), cholesterol, and glomerular filtration rate (GFR)). Clinical and behavioural risk factors were also considered: arterial hypertension (AH), previous myocardial infarction (PICS), aortocoronary bypass surgery (CABG) and/or stenting, coronary heart disease (CHD), atrial fibrillation (AF), atrioventricular block (AB block), and diabetes mellitus (DM), as well as lifestyle (smoking, alcohol consumption, physical activity level), education, and body mass index (BMI). Methods: The study included 52 patients aged 65 years and older. Based on the clinical, biochemical and immunological data obtained, a model for predicting the risk of premature cardiovascular aging was developed using mathematical modelling and machine learning methods. The aim of the study was to develop a predictive model allowing for the early detection of predisposition to the development of CVDs and their complications. Numerical methods of mathematical modelling, including Runge–Kutta, Adams–Bashforth and backward-directed Euler methods, were used to solve the prediction problem, which made it possible to describe the dynamics of changes in biomarkers and patients’ condition over time with high accuracy. Results: HLA-DR (50%), CD14 (41%) and CD16 (38%) showed the highest association with aging processes. BMI was correlated with placental growth factor (37%). The glomerular filtration rate was positively associated with physical activity (47%), whereas SOD activity was negatively correlated with it (48%), reflecting a decline in antioxidant defence. Conclusions: The obtained results allow for improving the accuracy of cardiovascular risk prediction, and form personalised recommendations for the prevention and correction of its development. Full article

This paper provides research that shows that the scale and quantification of the degree of fracturing in a rock mass should and can be considered when estimating geological strength index (GSI) ratings for rock mass strength and deformability estimates. In support of this notion, a brief review is provided to demonstrate why it is imperative that scale is considered when using GSI in engineering design. The impact of scale and scale effects on the engineering response of a rock mass typically requires a definition of fracture intensity relative to the volume or size of rock mass under consideration and the relative scale of the project being built. In this research three volume scales are considered: the volume of a structural domain, a representative elemental REV, and unit volume. A theoretical framework is established that links these three volume scales together, how they are estimated, and how they relate to parameters used to estimate engineering behaviour. Analysis of data from several examples and case histories for real rock masses is presented that compares and validates the use of a new and innovative but practical method (a sphere of unit volume) to estimate fracture intensity parameters VFC or P30 (fractures/m³) and P32 (fracture area—m²/m³) that is included on the vertical axis of the volumetric V-GSI chart. The research demonstrates that the unit volume approach to calculating VFC and P32 used in the V-GSI system compares well with other methods of estimating these two parameters (e.g., discrete fracture network (DFN) modelling). The research also demonstrates the reliability of the VFC-correlated rating scale included on the vertical axis of the V-GSI chart for use in estimating first-order strength and deformability estimates for rock masses. This quantification does not negate or detract from geological logic implicit in the original graphical GSI chart. Full article

The transition to a decarbonised energy system in Ireland presents significant socio-technical challenges. This paper, focused on the work of the SMARTLAB project at the Citizen Innovation Lab in Limerick city, investigated the potential of a localised living lab approach to address these challenges. Engaging across 70 buildings and their inhabitants, the project captured the evolution of attitudes and intentions towards the clean energy transition in ways directly relevant to future policy implementation across grid redevelopment, smart service design, and national retrofit. Project methodology was framed by a living lab approach, with wireless energy and indoor environment sensors installed in participant buildings and participant journeys developed by harnessing the Citizen Innovation Lab ecosystem. The results indicate behaviour changes among participants, particularly focusing on indoor environmental conditions. The study concludes that embedded, localised living labs offer a methodological framework which can capture diverse datasets and encompass complex contemporary contexts towards transition goals. Full article

The increasing complexity of financial reporting has enabled the implementation of innovative accounting practices that often obscure a company’s actual performance. This project seeks to uncover manipulative behaviours by constructing an anomaly detection model that utilises unsupervised machine learning techniques. We examined a dataset of 149,566 Slovak firms from 2016 to 2023, which included 12 financial parameters. Utilising TwoSteps and K-means clustering in IBM SPSS, we discerned patterns of normative financial activity and computed an abnormality index for each firm. Entities with the most significant deviation from cluster centroids were identified as suspicious. The model attained a silhouette score of 1.0, signifying outstanding clustering quality. We discovered a total of 231 anomalous firms, predominantly concentrated in sectors C (32.47%), G (13.42%), and L (7.36%). Our research indicates that anomaly-based models can markedly enhance the precision of fraud detection, especially in scenarios with scarce labelled data. The model integrates intricate data processing and delivers an exhaustive study of the regional and sectoral distribution of anomalies, thereby increasing its relevance in practical applications. Full article

Innovative approaches in hot forging, such as the use of floating dies, which aim to minimise burr formation by controlling material flow, require precise management of die geometry distortions. These distortions, primarily caused by thermal gradients, must be tightly controlled to prevent malfunctions during production. This study introduces a comprehensive thermal analysis framework that captures the complete forging cycle—from billet transfer and die closure to forging, spray-cooling, and lubrication. Two advanced heat transfer models were developed: a pressure- and lubrication-dependent contact heat transfer model and a spray-cooling model that simulates fluid dispersion over die surfaces. These models were implemented within the finite element software FORGE-NxT to evaluate the thermal behaviour of dies under realistic operating conditions. These two new models, contact and spray-cooling, implemented within a full-cycle thermal simulation and validated with industrial thermal imaging data, represent a novel contribution. The simulation results showed an average temperature deviation of just 5.8%, demonstrating the predictive reliability of this approach. This validated framework enables accurate estimation of thermal fields in the dies, and offers a practical tool for optimising process parameters, reducing burr formation, and extending die life. Moreover, its structure and methodology can be adapted to various hot forging applications where thermal control is critical to ensuring part quality and process efficiency. Full article

Background: Borderline personality disorder (BPD) is a severe psychiatric condition characterised by emotional instability, impulsivity, interpersonal dysfunction, and self-injurious behaviours. Despite growing clinical interest, the neuropsychological mechanisms underlying these symptoms are still not fully understood. This review aims to summarise findings from neuroimaging, psychophysiological, and neurodevelopmental studies in order to clarify the neurobiological and physiological basis of BPD, with a particular focus on emotional dysregulation and implications for the treatment of adolescents. Methods: A narrative review was conducted, integrating results from longitudinal neurodevelopmental studies, functional and structural neuroimaging research (e.g. FMRI and PET), and psychophysiological assessments (e.g., heart rate variability and cortisol reactivity). Studies were selected based on their contribution to understanding the neural correlates of BPD symptom dimensions, particularly emotion dysregulation, impulsivity, interpersonal dysfunction, and self-harm. Results: Findings suggest that early reductions in amygdala volume, as early as age 13 predict later BPD symptoms. Hyperactivity of the amygdala, combined with hypoactivity in the prefrontal cortex, underlies deficits in emotion regulation. Orbitofrontal abnormalities correlate with impulsivity, while disruptions in the default mode network and oxytocin signaling are related to interpersonal dysfunction. Self-injurious behaviour appears to serve a neuropsychological function in regulating emotional pain and trauma-related arousal. This is linked to disruption of the hypothalamic-pituitary-adrenal (HPA) axis and structural brain alterations. The Unified Protocol for Adolescents (UP-A) was more effective to Mentalization-Based Therapy for Adolescents (MBT-A) at reducing emotional dysregulation compared, though challenges in treating identity disturbance and relational difficulties remain. Discussion: The reviewed evidence suggests that BPD has its in early neurodevelopmental vulnerability and is sustained by maladaptive neurophysiological processes. Emotional dysregulation emerges as a central transdiagnostic mechanism. Self-harm may serve as a strategy for regulating emotions in response to trauma-related neural dysregulation. These findings advocate for the integration of neuroscience into psychotherapeutic practice, including the application of neuromodulation techniques and psychophysiological monitoring. Conclusions: A comprehensive understanding of BPD requires a neuropsychologically informed framework. Personalised treatment approaches combining pharmacotherapy, brain-based interventions, and developmentally adapted psychotherapies—particularly DBT, psychodynamic therapy, and trauma-informed care—are essential. Future research should prioritise interdisciplinary, longitudinal studies to further bridge the gap between neurobiological findings and clinical innovation. Full article

This study examines the impact of cost stickiness on research and development (R&D) investment and corporate performance in Japanese firms. Additionally, it investigates the moderating effect of managerial overconfidence and financial slack. To do so, we analysed a sample of 4877 observations from Japanese firms listed on the Tokyo Stock Exchange between 2014 and 2020. The results show that cost stickiness generally promotes R&D investment while negatively affecting corporate performance. Further, although managerial overconfidence does not moderate the relationship between cost stickiness and R&D investment, it weakens the negative effect of cost stickiness on corporate performance. Meanwhile, financial slack strengthens the positive impact of cost stickiness on R&D investment, but it does not moderate the relationship between cost stickiness and corporate performance. These findings provide strategic insights into resource allocation behaviour in driving innovation and influencing corporate outcomes in the Japanese market context. Full article

This study investigates medical students’ intentions to adopt AI-powered Natural Language Processing (NLP) tools (e.g., ChatGPT, Copilot) within educational contexts aligned with the perceived requirements of digital sustainability. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), data were collected from 301 medical students in Saudi Arabia and analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results indicate that Performance Expectancy (PE) (β = 0.65), Effort Expectancy (EE) (β = 0.58), and Social Influence (SI) (β = 0.53) collectively and significantly predict Behavioral Intention (BI), explicating 62% of the variance in BI (R² = 0.62). AI awareness did not significantly influence students’ responses or the relationships among constructs, possibly because practical familiarity and widespread exposure to AI-NLP tools exert a stronger influence than general awareness. Moreover, BI exhibited a strong positive effect on perceptions of digital sustainability (PDS) (β = 0.72, R² = 0.51), highlighting a meaningful link between AI adoption and sustainable digital practices. Consequently, these findings indicate the strategic role of AI-driven NLP tools as both educational innovations and key enablers of digital sustainability, aligning with global frameworks such as the Sustainable Development Goals (SDGs) 4 and 9. The study also concerns AI’s transformative potential in medical education and recommends further research, particularly longitudinal studies, to better understand the evolving impact of AI awareness on students’ adoption behaviours. Full article

The dynamic control of vibrations in skyscrapers is a critical consideration in sustainable building design, particularly in response to environmental excitations such as wind impact or seismic activity. Effective vibration neutralisation plays a crucial role in providing the safety of high-rise buildings. This research introduces an innovative concept for an active vibration damper that operates based on fluid dynamic transport to adaptively alter a skyscraper’s natural frequency, thereby counteracting resonant vibrations. A distinctive feature of this system is an adjustable-length cable mechanism, allowing for the dynamic modification of the pendulum’s effective length in real time. The structure, based on cable length adjustment, enables the PTMD to precisely tune its natural frequency to variable excitation conditions, thereby improving damping during transient or resonance phenomena of the building’s dynamic behaviour. A comprehensive mathematical model based on Lagrangian mechanics outlines the governing equations for this system, capturing the interactions between pendulum motion, fluid flow, and the damping forces necessary to maintain stability. Simulation analyses examine the role of initial excitation frequency and variable damping coefficients, revealing critical insights into optimal damper performance under varied structural conditions. The findings indicate that the proposed pendulum damper effectively mitigates resonance risks, paving the way for sustainable skyscraper design through enhanced structural adaptability and resilience. This adaptive PTMD, featuring an adjustable-length cable, provides a solution for creating safe and energy-efficient skyscraper designs, aligning with sustainable architectural practices and advancing future trends in vibration management technology. The study presented in this article supports the development of modern skyscraper design, with a focus on dynamic vibration control for sustainability and structural safety. It combines advanced numerical modelling, data-driven control algorithms, and experimental validation. From a sustainability perspective, the proposed PTMD system reduces the need for oversized structural components by providing adaptive, efficient damping, thereby lowering material consumption and embedded carbon. Through dynamically retuning structural stiffness and mass, the proposed PTMD enhances resilience and energy efficiency in skyscrapers, lowers lifetime energy use associated with passive damping devices, and enhances occupant comfort. This aligns with global sustainability objectives and new-generation building standards. Full article

As climate change concerns, urban congestion, and environmental degradation intensify, cities prioritise cycling as a sustainable transport option to reduce CO₂ emissions and improve quality of life. However, rampant bicycle theft and poor security infrastructure often deter daily commuters and tourists from cycling. This study explores how advanced security measures can bolster sustainable urban mobility and tourism by addressing these challenges. A mixed-methods approach is utilised, incorporating primary survey data from Slovenia and secondary data on bicycle sales, imports and thefts from 2015 to 2024. Findings indicate that access to secure parking substantially enhances users’ sense of safety when commuting by bike. Regression analysis shows that for every 1000 additional bicycles sold, approximately 280 more thefts occur—equivalent to a 0.28 rise in reported thefts—highlighting a systemic vulnerability associated with sustainability-oriented behaviour. To bridge this gap, the study advocates for an innovative security framework that combines blockchain technology and Non-Fungible Tokens (NFTs) with encrypted Quick Response (QR) codes. Each bicycle would receive a tamper-proof QR code connected to a blockchain-verified NFT documenting ownership and usage data. This system facilitates real-time authentication, enhances traceability, deters theft, and builds trust in cycling as a dependable transport alternative. The proposed solution merges sustainable transport, digital identity, and urban security, presenting a scalable model for individual users and shared mobility systems. Full article

Green Human Resource Management (GHRM) has garnered widespread international attention, yet the GHRM practices implementation and the challenges they face in African organisations remain underexplored. Given that the majority of GHRM studies in the African context have been published over the past four years, there is a clear need for a systematic review of the literature on GHRM in this region. This review examines 23 studies to identify which GHRM topics have been explored in the African context and what theories and methodologies have been adopted in these studies. Drawing from the selected literature, a conceptual framework is established to facilitate a more structured understanding of GHRM practices within the African context, which finds that GHRM works as an organisational subsystem embedded within broader institutional, environmental, and socio-economic systems. In the concluding section, this review paper further highlights the key gaps in the existing research and offers recommendations for future studies related to GHRM implementation in African organisations. This review paper contributes to the growing body of knowledge in both the theoretical and practical areas of GHRM, while also contributing to the broader goal of sustainable development in Africa. Full article

Steak tartare is a ready-to-eat (RTE) meat product, prepared with finely chopped or ground raw beef, with a rich culinary history and increasing consumption trend in the last years. Yet, its microbiological safety and technological challenges remain largely under-investigated. This review analyses the regulations, the safety, and technological advances in steak tartare manufacturing, focusing on microbiological risks due to potential contamination by pathogens like Salmonella spp., Listeria monocytogenes, and Escherichia coli O157:H7. From this perspective, the outbreaks associated with the consumption of raw meat products have confirmed the importance of good hygiene practice and process control, currently based on the presence of nitrite in the formulation and accurate cold chain management. Recently, the EU regulations have set stricter limits for the use of nitrites and nitrates in meat products, and this evolution has increased the interest in natural alternatives. The scientific literature indicates that plant-based antimicrobials, high-pressure processing (HPP), and novel starter cultures can be promising tools to improve raw meat safety and shelf life. This review analyses the possible options for nitrite replacement, which might involve combined interventions with natural antimicrobials, starter cultures, and packaging solutions. Future studies need to address the microbial behaviour and dynamics in nitrite-free formulations, including safety validation by challenge testing with foodborne pathogens. In this respect, steak tartare could be a model for innovation in the meat industry. However, considering the challenges that must be faced, collaboration across disciplines will be essential to meet regulatory constraints and consumer expectations while ensuring product quality and safety. Full article

The increasing demand for sustainable energy and clean water has prompted the exploration of alternative solutions to reduce reliance on fossil fuels. In this context, hydrogen production through water electrolysis powered by solar energy presents a promising pathway toward a zero-carbon footprint. This study investigates the potential of copper slag, an abundant industrial waste, as a low-cost electrocatalyst for the hydrogen evolution reaction (HER) in contact with saline water such as 0.5 M NaCl and seawater, comparing the electrochemical response when in contact with geothermal water from El Tatio (Atacama Desert). The physicochemical characterisation of copper slag was performed using XRD, Raman, and SEM-EDS to determine its surface properties. Electrochemical evaluations were conducted in 0.5 M NaCl and natural seawater using polarisation techniques to assess the corrosion behaviour and catalytic efficiency of the copper slag electrodes. The results indicate that copper slag exhibits high stability and promising HER kinetics, particularly in seawater, where its mesoporous structure facilitates efficient charge transfer processes. The key novelty of this manuscript lies in the direct revalorisation of untreated copper slag as a functional electrode for HER in real seawater and geothermal water, avoiding the use of expensive noble metals and aligning with circular economy principles. This innovative combination of recycled material and natural saline electrolyte enhances both the technical and economic viability of electrolysis, while reducing environmental impact and promoting green hydrogen production in coastal regions with high solar potential. This research contributes to the value of industrial waste, offering a viable pathway for advancing sustainable hydrogen technologies in real-world environments. Full article

Soil literacy, defined as the combination of attitudes, behaviours, and competencies necessary to make informed decisions that promote soil health, is increasingly recognised as a crucial element for sustainable development. This article presents the outcomes of the Soil Literacy Think Tank established under the Soils for Europe (SOLO) project, which aims to identify research and innovation knowledge gaps to strengthen soil literacy in Europe. Drawing on literature reviews, stakeholder engagement, and interdisciplinary dialogue, the paper highlights 18 prioritised knowledge gaps across different topics. These include a lack of integrated pedagogical strategies, limited outreach to specific social groups, and underdeveloped communication methods linking soil knowledge to stewardship actions. The article proposes adaptive and inclusive approaches to soil education that respect multiple knowledge systems and values and emphasises the importance of embedding soil literacy into sustainability agendas and governance processes. By addressing these challenges, the paper contributes to broader efforts supporting the EU Soil Mission and the goals of World Soil Day by promoting public awareness, citizen engagement, and responsible soil care. Full article

This study presents a phenomenological model for predicting the thermomechanical behaviour of spring-type actuators made of shape memory alloys (SMAs). The model incorporates the kinetics of martensite–austenite phase transitions as a function of temperature and applied stress. The primary innovation is the inclusion of a scalar internal variable that represents the evolution of the phase transformation within a phenomenological macroscopic model. This approach enables the deformation–force–temperature behaviour of SMA-based spring elements under cyclic loading to be accurately described. A set of constitutive equations was derived to describe reversible and residual strains, along with transformation start and finish conditions. Model parameters were calibrated using experimental data from VSP-1 and TN-1K SMA springs that were subjected to thermal cycling. The validation results show a high correlation between the theoretical predictions and the experimental data, with deviation margins of less than 6.5%. The model was then applied to designing and analysing thermosensitive actuator mechanisms for temperature control systems. This yielded accurate deformation–force characteristics, demonstrating low inertia and high repeatability. This approach enables the efficient prediction and improvement of the performance of SMA-based spring elements in actuators, making it relevant for adaptive systems in marine and aerospace applications. Full article