Search Results (21,205)

Background: Lower limb amputation (LLA), due to non-traumatic causes such as vascular diseases and diabetes, significantly impacts patients’ physical, psychological, and social well-being. While multidisciplinary rehabilitation programs commonly address physical and functional recovery, psychological and subjective experiences related to limb loss remain less explored. Thus, this preliminary study aimed to investigate the psychological and behavioral adaptation processes in patients undergoing rehabilitation following lower limb amputation. Methods: A preliminary observational study with a mixed-method approach based on quantitative and qualitative data triangulation was conducted. This approach involves integrating multiple data sources and methodologies—in this case, quantitative psychometric measures and qualitative interviews via the prospective of amputees and those who use prostheses—to enhance the validity and depth of the research findings. Results: Fourteen inpatient amputees and fourteen inpatient prosthesis users (years: 66.6 ± 2.5 for amputee and 61.5 ± 1.9 for prosthesis users, male amputees: 85.7%, male prosthesis users: 100%) of a research hospital in the North of Italy were assessed using validated psychometric tools (GAD-7, PHQ-9, PID-5-BF, BIS, ASonA) alongside semi-structured interviews analyzed through the Interpretive Description approach. Key themes highlighted illness acceptance, prosthesis adaptation, body image, medication and behavioral adherence, anxiety, depression, quality of life, denial, optimism, and social support. Overall, anxiety–depressive symptomatology tended to decrease with the prosthesis, and pharmacological and behavioral adherence improved, as did the disease acceptance. Body image was fairly preserved in all patients despite some fears of others’ judgment with respect to the prosthesis. Interestingly, there was poor agreement between quantitative and qualitative data in both the amputee’ and prosthesis users’ groups: while the former returned a partial and neutral picture, a more multifaceted picture emerged from the interviews collected. Conclusions: These findings underline the importance of integrating quantitative psychometric evaluations with qualitative methods to comprehensively understand patients’ adaptive experiences. Such combined insights are essential to inform tailored psychological interventions throughout the rehabilitation journey. Full article

Lean construction is considered a new methodology for minimizing the causes of waste that hinder the achievement of green building (GB) goals. The main aim of this study is to develop a lean model using fuzzy logic technique to mitigate causes of waste effect in GB projects and to determine the most appropriate lean tools affecting these causes. The inputs of this model include GB waste and four lean tools, comprising Quality Function Deployment (QFD), Last Planner System (LPS), Value Stream Mapping (VSM), and 5S, while the outputs include four improvement level indices based on the lean tools. The model uses various logical rules to achieve several relations among the inputs and outputs, and it is applied and verified using data related to several causes of waste categorized under five groups. The strongest correlation is found between VSM and 5S indices, while an adverse relationship is observed between QFD and 5S indices. The results indicate that a cause of waste that refers to poor assessment of site conditions is considered the most substantial one due to its high improvement level indices across all lean tools. The most significant waste group is related to GB stakeholders, which contains 38% of key causes of waste. The improvement using QFD increases by 10% compared to VSM and 28.20% compared to 5S. QFD and LPS are measured as the most suitable lean tools to mitigate the causes of waste effects due to their high impact and high improvement level indices. Full article

This pilot study uses Raman spectroscopy and SERS to monitor monthly water composition changes in two adjacent hypersaline lakes (L1 and L2) at a balneary resort, during the peak tourist season (May–October 2023). In situ pH and electrical conductivity (EC) measurements, along with evaporite analyses, complemented the spectroscopic data. Although traditionally considered similar, the lakes frequently raise public questions about their relative bathing benefits. While not directly addressing the therapeutic effects, the study reveals distinct physicochemical profiles between the lakes. Raman data showed consistently higher sulfate levels in L2, a trend also observed in winter monitoring. pH levels were higher in L1 (8–9.8) than in L2 (7.2–8), except for one October depth reading. This trend held during winter, except in April. Surface waters showed more variability and slightly higher values than those at 1 m depth. SERS spectra featured β-carotene peaks, linked to cyanobacteria, and Ag–Cl bands, indicating nanoparticle aggregation from inorganic ions. SERS intensity strongly correlated with pH and EC, especially in L2 (r = 0.96), suggesting stable surface–depth chemistry. L1 exhibited more monthly variability, likely due to differing biological activity. Although salinity and EC were not linearly correlated at high salt levels, both reflected seasonal trends. The integration of Raman, SERS, and physicochemical data proves effective for monitoring hypersaline lake dynamics, offering a valuable tool for environmental surveillance and therapeutic water quality assessment, in support of evidence-based water management and therapeutic use of salt lakes, aligning with goals for sustainable medical tourism and environmental stewardship. Full article

One of the limiting factors in the implementation of water resource management is the absence of tools that help water programs evaluate processes and progress. This is because, until now, the indicators that have been developed have not addressed specific local characteristics and issues. Therefore, in this research, a set of indicators has been proposed, with the purpose of developing a management index for urban public water supply, which will consider the Drinking Water and Sewer System of León (SAPAL), in the Mexican state of Guanajuato, as case study. This index will be useful to measure progress toward sustainable development, monitor the impact of public policies, and foster citizen participation. In order to propose a methodology that aligns with the changing environments, where proper decision-making is key to the current water management requirements, the combination of the Analytic Hierarchy Process (AHP) and Fuzzy Logic (FL) methodologies will be helpful for proper decision-making. All this will foster a paradigm shift towards appropriate water management actions that allow for the conditions and availability of human and natural resources, which the municipality has control of, for a long-term improvement that guarantees the well-being of the population. Full article

Background/Objectives: Hearing loss is a disorder that develops because of being exposed to high noise levels affecting the quality of life among affected individuals. A review of the literature was conducted to explore the prevalence of hearing loss and its associated factors among workers in the metal industry. Methods: The literature search was conducted on ScienceDirect, Google Scholar, Pub Med, ResearchGate and African Journals Online databases to identify articles according to the Preferred Reporting Items for Systematic Reviews and Meta analyses (PRISMA) guidelines. The studies published in scientific journals between January 2014 and December 2024 describing hearing loss and its associated factors among workers in the metal industry were considered for inclusion in the review. The articles were screened by the author. The Critical Appraisal Skills Programme (CASP) quality assessment tool with modified checklist questions was used to evaluate the quality of studies. Results: Following the literature search and using the relevant inclusion criteria, a total of 127 articles were identified, and 8 articles with a total of 2605 participants were included in the review. The sample sizes ranged from 93 to 606. The participants’ age ranged from 19 to 65 years. A review of studies showed varying prevalence of hearing loss ranging from 13.8% to 59%. Furthermore, the studies have found working experience, advanced age, cigarette smoking, tinnitus, working in areas of high noise levels and not using hearing protective devices to be associated with a risk of developing hearing loss. Conclusions: The review found that workers in the metal industry are at risk of developing hearing loss and, therefore, implementation of control measures to prevent the occurrence of hearing loss is necessary. Full article

Background: The hyoid bone is a key anatomical structure involved in the functional coordination of the stomatognathic system. Although its position may vary in response to masticatory patterns, its relationship with functional occlusion remains insufficiently studied in orthodontics. Objective: This pilot study aimed to explore the association between masticatory type and hyoid bone position and to assess the clinical utility of the Functional Masticatory Angle of Planas (AFMP) in classifying masticatory patterns. Materials and Methods: A descriptive, observational, cross-sectional study was conducted with 18 patients. Right and left AFMPs were measured using standardized intraoral photographs, and hyoid bone position was assessed via panoramic radiographs, classified as either aligned or displaced. Measurements were repeated to assess intraobserver reliability. Results: In most cases, hyoid bone elevation occurred on the same side as the smaller AFMP, suggesting a possible adaptive response to unilateral masticatory dominance. High intraobserver agreement was confirmed for both AFMP and hyoid measurements. Conclusions: The findings suggest a potential relationship between functional masticatory asymmetry and hyoid bone position. While further studies with larger samples are needed, the AFMP appears to be a promising tool for evaluating functional occlusion in relation to craniofacial dynamics. Full article

Soil electrical conductivity (EC) and water content are key indicators of soil health, influencing nutrient availability, salinity stress, and crop productivity. Monitoring these parameters is critical for precision agriculture. However, most existing measurement systems are costly, which restricts their use in practical field conditions. The aim of this study was to develop and validate a low-cost, portable system for simultaneous measurement of soil EC, water content, and temperature, while maintaining accuracy comparable to laboratory-grade instruments. The system was designed with four electrodes arranged in two pairs and employed an AC bipolar pulse method with a constant-current circuit, precision rectifier, and peak detector to minimize electrode polarization. Experiments were carried out in sandy loam soil at water contents of 13%, 18%, and 22% and KNO₃ concentrations of 0, 0.1, 0.2, and 0.4 M. Measurements from the developed system were benchmarked against a professional impedance analyzer (E4990A). The findings demonstrated that EC increased with both frequency and water content. At 100 Hz, the mean error compared with the analyzer was 8.95%, rising slightly to 9.98% at 10 kHz. A strong linear relationship was observed between EC and KNO₃ concentration at 100 Hz (R² = 0.9898), and for the same salt concentration (0.1 M KNO₃) at 100 Hz, EC increased from ~0.26 mS/cm at 13% water content to ~0.43 mS/cm at 22%. In conclusion, the developed system consistently achieved <10% error while maintaining a cost of ~€55, significantly lower than commercial devices. These results confirm its potential as an affordable and reliable tool for soil salinity and water content monitoring in precision agriculture. Full article

This study proposes the first ground motion prediction equation (GMPE) for the parameter I_Np, an intensity measure based on the spectral shape. A Machine Learning Algorithm based on Support Vector Machines (SVMs) was employed due to its robustness towards outliers, which is a key advantage over ordinary linear regression. I_Np also offers a more robust measure of the ground motion intensity than the traditionally used spectral acceleration at the first mode of vibration of the structure Sa(T₁). The SVM algorithm, configured for regression (SVR), was applied to derive the prediction coefficients of I_Np for diverse vibration periods. Furthermore, the complete dataset was analyzed to develop a unified, generalized expression applicable across all the periods considered. To validate the model’s reliability and its ability to generalize, a cross-validation analysis was performed. The results from this rigorous validation confirm the model’s robustness and demonstrate that its predictive accuracy is not dependent on a specific data split. The numerical results show that the newly developed GMPE reveals high predictive accuracy for periods shorter than 3 s and acceptable accuracy for longer periods. The generalized equation exhibits an acceptable coefficient of determination and Mean Squared Error (MSE) for periods from 0.1 to 5 s. This work not only highlights the powerful potential of machine learning in seismic engineering but also introduces a more sophisticated and effective tool for predicting ground motion intensity. Full article

Background: Coronary collateral circulation (CCC) plays a crucial protective role in patients with chronic total occlusion (CTO), mitigating ischemia and improving long-term outcomes. However, the degree of collateral vessel development varies substantially among individuals. Systemic inflammatory and nutritional status may influence this variability. The Naples Prognostic Score (NPS) is a composite index reflecting these parameters, yet its relationship with CCC remains incompletely defined. Methods: We retrospectively analyzed 324 patients with angiographically confirmed CTO at Selçuk University Faculty of Medicine between 2014 and 2025. Coronary collaterals were graded using the Rentrop classification, and patients were categorized as having poor (grades 0–1) or good (grades 2–3) collaterals. The NPS was calculated using serum albumin, cholesterol, neutrophil-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio. Baseline clinical and laboratory data were compared between groups. Univariate and multiple binary logistic regression analyses were performed to identify independent predictors of collateral development. Results: Of the 324 patients, 208 (64.2%) had poor and 116 (35.8%) had good collateral circulation. Patients with good collaterals had higher body mass index, HDL Cholesterol (HDL-C), and triglyceride levels, and significantly lower NPS values compared with those with poor collaterals (p < 0.05 for all). In multiple binary logistic regression analysis, HDL-C (OR 1.035; 95% CI 1.008–1.063; p = 0.011) and NPS (OR 0.226; 95% CI 0.130–0.393; p < 0.001) emerged as independent predictors of well-developed collaterals. Conclusions: Both NPS and HDL-C are independently associated with the degree of coronary collateral circulation in CTO patients. These findings highlight the interplay between systemic inflammation, nutritional status, lipid metabolism, and vascular adaptation. As simple and routinely available measures, NPS and HDL-C may serve as practical tools for risk stratification and identifying patients at risk of inadequate collateral formation. Prospective studies with functional assessments of collateral flow are warranted to confirm these associations and explore potential therapeutic interventions. Full article

Background: Diabetic eye surface disease, including dry eye syndrome, corneal neuropathy, and diabetic retinopathy, is a common complication of diabetes. Tear fluid biomarkers may aid in early diagnosis and disease monitoring. The objective of this systematic review was to identify and evaluate tear fluid biomarkers in diabetic ocular surface disease according to PRISMA guidelines. Methods: PubMed, Scopus, and Embase databases were searched through June 2025. Eligible studies included clinical and observational studies measuring proteins, lipids, cytokines, trace elements, or nucleic acids in tear fluids in patients with diabetes. Results: The search identified 198 studies, and of those, 30 studies were included, comprising 14 original investigations with 871 participants (133 with type 1 diabetes, 453 with type 2 diabetes, 16 with pre-diabetes, and 269 healthy controls). The main biomarker categories were cytokines (IL-6, IL-8, TNF-α, and MMP-9), neuropeptides (substance P, NPY), proteins (IGFBP-3, progranulin), lipids, glycans, microRNAs, circRNAs, and trace elements. Conclusions: More than a dozen biomarkers in the tear fluid have been identified that may reflect diabetes-related changes in the ocular surface. Tear fluid analysis may be a valuable tool in personalizing the diagnosis and treatment of diabetic ocular surface diseases, but further studies are needed to confirm its clinical significance. Full article

Continuous technological, ecological, and digital transformations reshape urban mobility systems. While sustainable mobility has become a dominant keyword, there are many different approaches and policies to help achieve lasting and properly functioning change. This study applies a comprehensive qualitative policy analysis to influential and leading sustainable mobility approaches (i.a. Mobility Justice, Avoid–Shift–Improve, spatial models like the 15-Minute City and Superblocks, governance frameworks such as SUMPs, and tools ranging from economic incentives to service architectures like MaaS and others). Each was assessed across structural barriers, psychological resistance, governance constraints, and affective dimensions. The results show that, although these approaches provide clear normative direction, measurable impacts, and scalable applicability, their implementation is often undermined by fragmentation, Policy Layering, limited intermodality, weak Future-Readiness, and insufficient participatory engagement. Particularly, the lack of sequencing and pacing mechanisms leads to policy silos and societal resistance. The analysis highlights that the main challenge is not the absence of solutions but the absence of a unifying paradigm. To address this gap, the paper introduces CalmMobility, a conceptual framework that integrates existing strengths while emphasizing comprehensiveness, pacing–sequencing–inclusion, and Future-Readiness. CalmMobility offers adaptive and co-created pathways for mobility transitions, grounded in education, open innovation, and a calm, deliberate approach. Rather than being driven by hasty or disruptive change, it seeks to align technological and spatial innovations with societal expectations, building trust, legitimacy, and long-term resilience of sustainable mobility. Full article

Recent advances in cardiovascular imaging have revolutionized the assessment and management of abdominal aortic aneurysm (AAA) through the integration of sophisticated haemodynamic biomarkers. This comprehensive review evaluates the clinical utility and mechanistic significance of multiple biomarkers in AAA pathogenesis, progression, and treatment outcomes. Advanced cardiac imaging modalities, including four-dimensional magnetic resonance imaging (4D MRI), computational fluid dynamics (CFD), and specialized echocardiography, enable precise quantification of critical haemodynamic parameters. Wall shear stress (WSS) emerges as a fundamental biomarker, with values below 0.4 Pa indicating pathological conditions and increased risk for aneurysm progression. Time-averaged wall shear stress (TAWSS), typically maintaining values above 1.5 Pa in healthy arterial segments, provides crucial information about sustained haemodynamic forces affecting the vessel wall. The oscillatory shear index (OSI), ranging from 0 (unidirectional flow) to 0.5 (purely oscillatory flow), quantifies directional changes in WSS during cardiac cycles. In AAA, elevated OSI values between 0.3 and 0.4 correlate with disturbed flow patterns and accelerated disease progression. The relative residence time (RRT), combining TAWSS and OSI, identifies regions prone to thrombosis, with values exceeding 2–3 Pa⁻¹ indicating increased risk. The endothelial cell activation potential (ECAP), calculated as OSI/TAWSS, serves as an integrated metric for endothelial dysfunction risk, with values above 0.2–0.3 Pa⁻¹ suggesting increased inflammatory activity. Additional biomarkers include the volumetric perivascular characterization index (VPCI), which assesses vessel wall inflammation through perivascular tissue analysis, and pulse wave velocity (PWV), measuring arterial stiffness. Central aortic systolic pressure and the aortic augmentation index provide essential information about cardiovascular load and arterial compliance. Novel parameters such as particle residence time, flow stagnation, and recirculation zones offer detailed insights into local haemodynamics and potential complications. Implementation challenges include the need for specialized equipment, standardized protocols, and expertise in data interpretation. However, the potential for improved patient outcomes through more precise risk stratification and personalized treatment planning justifies continued development and validation of these advanced assessment tools. Full article

Excessive energy consumption of communication protocols in IoT/IIoT systems constitutes one of the key constraints for the operational longevity of remote sensor nodes, where radio transmission often incurs higher energy costs than data acquisition or local computation. Previous studies have remained fragmented, typically focusing on selected technologies or specific layers of the communication stack, which has hindered the development of comparable quantitative metrics across protocols. The aim of this study is to design and validate a unified evaluation framework enabling consistent assessment of both wired and wireless protocols in terms of energy efficiency, reliability, and maintenance costs. The proposed approach employs three complementary research methods: laboratory measurements on physical hardware, profiling of SBC devices, and simulations conducted in the COOJA/Powertrace environment. A Unified Comparative Method was developed, incorporating bilinear interpolation and weighted normalization, with its robustness confirmed by a Spearman rank correlation coefficient exceeding 0.9. The analysis demonstrates that MQTT-SN and CoAP (non-confirmable mode) exhibit the highest energy efficiency, whereas HTTP/3 and AMQP incur the greatest energy overhead. Results are consolidated in the ICoPEP matrix, which links protocol characteristics to four representative RS-IoT scenarios: unmanned aerial vehicles (UAVs), ocean buoys, meteorological stations, and urban sensor networks. The framework provides well-grounded engineering guidelines that may extend node lifetime by up to 35% through the adoption of lightweight protocol stacks and optimized sampling intervals. The principal contribution of this work is the development of a reproducible, technology-agnostic tool for comparative assessment of IoT/IIoT communication protocols. The proposed framework addresses a significant research gap in the literature and establishes a foundation for further research into the design of highly energy-efficient and reliable IoT/IIoT infrastructures, supporting scalable and long-term deployments in diverse application environments. Full article

Background and Objectives: The objectives of this review were as follows: to measure changes in renal biomarker levels before, immediately after, and 24 h post-marathon; to identify promising biomarkers for the diagnosis of acute kidney injury; and to describe the temporal patterns of biomarker dynamics in relation to the marathon. Materials and Methods: Studies of marathon runners reporting AKI-related biomarkers were included. Four databases (PubMed, EMBASE, Web of Science, and LILACS) were searched. Data on study design, participant characteristics, and biomarker values (pre-, post-, and 24 h post-race) were extracted, and a random effects meta-analysis was performed. Risk of bias was assessed with the National Heart, Lung, and Blood Institute pre–post tool. Results: The study showed significant increases in most biomarkers immediately after the marathon compared to baseline values. The largest increases were observed in Tissue Inhibitor of Metalloproteinases-2* Insulin-like Growth Factor Binding Protein-7 (TIMP-2*IGFBP), copeptin, urinary Liver-type Fatty Acid Binding Protein (L-FABP), urinary Monocyte Chemoattractant Protein-1 (MCP-1), IGFBP-7, urinary Chitinase 3-like Protein 1 (YKL-40), and TIMP-2, suggesting that these biomarkers are promising candidates for future research. Several patterns of biomarker evolution were observed: some increased without decreasing even at 24 h after the marathon; others increased post-marathon and decreased at 24 h while remaining above baseline; some increased after the marathon and then fell below baseline at 24 h. Conclusions: Marathon running causes significant increases in kidney injury biomarkers, with different patterns of evolution. Full article

Accurate prediction of soil–structure interface shear strength (τ_max) is critical for reliable geotechnical design. This study combines experimental testing with interpretable machine learning to overcome the limitations of traditional empirical models and black-box approaches. Ninety large-displacement ring shear tests were performed on five sands and three interface materials (steel, PVC, and stone) under normal stresses of 25–100 kPa. The results showed that particle morphology, quantified by the regularity index (RI), and surface roughness (R_t) are dominant factors. Irregular grains and rougher interfaces mobilised higher τ_max through enhanced interlocking, while smoother particles reduced this benefit. Harder surfaces resisted asperity crushing and maintained higher shear strength, whereas softer materials such as PVC showed localised deformation and lower resistance. These experimental findings formed the basis for a hybrid symbolic regression framework integrating Genetic Programming (GP) with Shapley Additive Explanations (SHAP), Fourier feature augmentation, and physics-informed constraints. Compared with multiple linear regression and other hybrid GP variants, the Physics-Informed Neural Fourier GP (PIN-FGP) model achieved the best performance (R² = 0.9866, RMSE = 2.0 kPa). The outcome is a set of five interpretable and physics-consistent formulas linking measurable soil and interface properties to τ_max. The study provides both new experimental insights and transparent predictive tools, supporting safer and more defensible geotechnical design and analysis. Full article