Search Results (7,342)

In this work we investigate the integration possibility of a thermistor paste from ESL (ElectroScience Laboratory, now Vibrantz) to see if it is adapted for Vibrantz Low Temperature Cofired Ceramics (LTCC) L8 and A6M-E materials. An alumina-based sample is used as a reference circuit throughout this study. Square, two-squares-in-parallel and two-squares-in-series thermistors are tested, placed internally and externally. Resistive values are measured in a range from 25 °C to 300 °C. The variation in the resistive values among similar thermistors is significant, with a maximum standard deviation of 67%. However, in all cases, there is a positive linear relationship between resistance and temperature. The Temperature Coefficient of Resistance (TCR) value is calculated before and after annealing. In general, the L8 and Al₂O₃ samples exhibit higher TCR values than the A6M-E sample. Additionally, when placed internally, the TCR value decreases approximately 30% for both tested LTCC materials. An Energy-Dispersive X-ray Spectroscopy (EDX) material analysis has also been conducted on the samples, revealing that the main chemical components are oxide, silicon, calcium, and ruthenium but also some barium and titanium, which indicates SiO₂, TiO₂, BaTiO₃ and RuO₂ oxides in the thermistor paste. The possibility to implement thermistors internally and externally on Vibrantz LTCC without delamination problems is endorsed by this study. Full article

Background: This systematic review evaluates the efficacy of rehabilitation-focused exercise interventions for lumbar degenerative disc disease (DDD), a leading cause of chronic low back pain. Methods: Following PRISMA guidelines, a comprehensive search was conducted across international and regional databases (PubMed, Scopus, Web of Science, Magiran, SID, and Noormags) covering the period from January 2010 to January 2025. The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD420251088811. Using keywords such as “lumbar DDD,” “exercise therapy,” and “rehabilitation,” a total of 2495 records were identified. After screening, 20 studies—including clinical trials, quasi-experimental, and experimental designs—met the inclusion criteria and were assessed using the McMaster Critical Review Form for Quantitative Studies. Results: Interventions such as hydrotherapy, core stability training, Pilates, and suspension exercises were found to significantly reduce pain and improve functional outcomes. While multimodal approaches (e.g., aquatic exercise combined with acupuncture) showed positive effects, the comparative studies revealed no significant differences between modalities. Suspension training demonstrated superior efficacy in pain reduction compared to isolated core stability exercises. The methodological quality of included studies ranged from good to excellent, with the majority rated as very good or excellent (McMaster scores: 8 “excellent,” 7 “very good,” and 5 “good”). Common limitations among the studies included methodological heterogeneity, small sample sizes (n = 14–30), and insufficient long-term follow-up. Conclusions: Exercise-based rehabilitation is an effective strategy for managing lumbar DDD. Evidence particularly supports the use of suspension training and aquatic therapy for superior improvements in pain and functional outcomes. Future research should aim to adopt standardized protocols, recruit larger sample sizes, and include extended follow-up periods to produce more robust and generalizable findings. Full article

Background: Medical clearance for competitive sports is vital to safeguarding athletes’ health, particularly in high-intensity disciplines like football. In Italy, fitness assessments follow stringent protocols set by the Commissione di Vigilanza per il controllo dell’Idoneità Sportiva (COCIS), with a strong focus on cardiovascular screening. The primary goal is to prevent sudden cardiac death (SCD), a rare but catastrophic event in athletes. Methods: This paper provides an in-depth narrative review of the 2023 COCIS guidelines, examining the cardiological screening process, required diagnostic tests, management of identified cardiovascular conditions, and the protocols’ role in reducing SCD risk. Results: Comparisons with international standards underscore the effectiveness of the Italian approach. Conclusions: The COCIS 2023 guidelines provide clear, evidence-based protocols for cardiovascular risk assessment, significantly enhancing athlete safety and reducing the incidence of SCD in high-intensity sports. Full article

Distributed acoustic sensing shows great potential for pipeline monitoring. However, internally deployed and unfixed sensing cables are highly susceptible to disturbances from water flow noise, severely challenging impact source localization. This study proposes a novel two-step method to address this. The first step employs Variational Mode Decomposition (VMD) combined with Short-Time Energy Entropy (STEE) for the adaptive extraction of impact signal from noisy data. STEE is introduced as a stable metric to quantify signal impulsiveness and guides the selection of the relevant intrinsic mode function. The second step utilizes the Pruned Exact Linear Time (PELT) algorithm for accurate signal segmentation, followed by an unsupervised learning method combining Dynamic Time Warping (DTW) and clustering to identify the impact segment and precisely pick the arrival time based on shape similarity, overcoming the limitations of traditional pickers under conditions of complex noise. Field tests on an operational water pipeline validated the method, demonstrating the consistent localization of manual impacts with standard deviations typically between 1.4 m and 2.0 m, proving its efficacy under realistic noisy conditions. This approach offers a reliable framework for pipeline safety assessments under operational conditions. Full article

The sphingolipidoses Fabry disease, Gaucher disease and Acid sphingomyelinase deficiency (ASMD) are the three most common lysosomal storage diseases for which treatment is currently available. Timely diagnosis with estimation of the disease severity and possibilities of follow-up of patients, whether or not under therapy, is crucial for providing good care and for the prevention of possible lethal complications. With this research we provide an efficient and sensitive detection method; its implementation in clinical practice could optimize the diagnosis and follow-up of patients with Gaucher, Fabry and ASMD. This detection method on dried blood spots (DBS) was validated according to the international Clinical and Laboratory Standards Institute (CLSI) guidelines, looking at reproducibility, linearity, carry-over and lower limit of quantification. Analogously, validation and subsequent comparison of the method validation results using another matrix, the Capitainer blood sampling cards (Capitainers), was fulfilled. The results showed that this detection method is fully applicable clinically when using DBS as well as Capitainers. In addition, even additional improvements of some validation parameters were found when using the Capitainers. Twenty-six patient samples and fifteen healthy samples were analyzed for case finding control. All patient cases were detected without ambiguity. We present a high-resolution mass spectrometry method that provides an accurate analysis for targeted screening, aiming for improved/accelerated diagnosis when added in the diagnostic pathway and monitoring of Fabry, Gaucher and ASMD in DBS as well as in Capitainers, with the main advantages of a small volume of blood samples, guaranteeing stability and easy transportation from the collection site to the laboratory. Full article

Background: The interaction between prosthetic restorations and periodontal health is a critical factor for the long-term success of dental treatments. A biologically compatible prosthetic design supports periodontal stability, whereas neglecting periodontal principles can compromise treatment outcomes. This study aimed to validate a questionnaire designed to assess dentists’ perceptions regarding the influence of prosthetic restorations on the periodontium. Material and Methods: An observational cross-sectional study was conducted using a self-administered questionnaire distributed to licensed dentists across Romania. The questionnaire underwent expert review, pilot testing (n = 50), and statistical validation, including the Content Validity Index (CVI), Cronbach’s alpha for internal consistency, and Exploratory Factor Analysis (EFA) using Principal Component Analysis (PCA) with Varimax rotation. The final sample included 39 respondents. Data was analyzed using SPSS v26.0. Results: The questionnaire demonstrated excellent internal consistency (Cronbach’s alpha = 0.900; standardized alpha = 0.917). Most items had corrected item-total correlations > 0.40. EFA revealed eight coherent factors explaining 81.68% of total variance, with high communalities (0.549–0.966), strong Kaiser–Meyer–Olkin test (KMO) values, and significant Bartlett’s test values, confirming construct validity. Descriptive statistics showed predominantly positive attitudes among dentists regarding the periodontal considerations in prosthetic treatment. The highest-rated items emphasized oral hygiene, periodontal stability, and biological adaptation of restorations. Lower scores were associated with routine use of periodontal indices and recognition of failures due to insufficient evaluation. Conclusions: The validated instrument proved reliable and demonstrated strong psychometric properties in this exploratory validation, supporting its use in research and education. Romanian dentists demonstrated a favorable perception of the role of periodontal health in prosthetic success. This tool can inform curriculum development and interdisciplinary clinical protocols in prosthodontics and periodontology. Full article

Deep learning has achieved remarkable performance in skin lesion classification, but its lack of interpretability often remains a critical barrier to clinical adoption. In this study, we investigate the spatial properties of saliency-based model explanations, focusing on symmetry and other morphometric features. We benchmark five deep learning architectures (ResNet-50, EfficientNetV2-S, ConvNeXt-Tiny, Swin-Tiny, and MaxViT-Tiny) on a nine-class skin lesion dataset from the International Skin Imaging Collaboration (ISIC) archive, generating saliency maps with Grad-CAM++ and LayerCAM. The best-performing model, Swin-Tiny, achieved an accuracy of 78.2% and a macro-F1 score of 71.2%. Our morphometric analysis reveals statistically significant differences in the explanation maps between correct and incorrect predictions. Notably, the transformer-based models exhibit highly significant differences ($p<0.001$) in metrics related to attentional focus (Entropy and Gini), indicating that their correct predictions are associated with more concentrated saliency maps. In contrast, convolutional models show less consistent differences, and only at a standard significance level ($p<0.05$). These findings suggest that the quantitative morphometric properties of saliency maps could serve as valuable indicators of predictive reliability in medical AI. Full article

The integration of virtual and augmented reality is transforming processes in the field of product design. This study evaluates the usability of immersive digital tools applied to industrial design through a combined market research and empirical case study, using the software ‘Gravity Sketch’ and the immersive headset ‘Meta Quest 3’. An embedded single case study was conducted based on the international standard ISO 9241-11, considering the dimensions of effectiveness, efficiency, and satisfaction, analysed through nine indicators: tasks completed, time to complete tasks, dimensional accuracy, interoperability, interactivity, fatigue, human error, learning curve, and perceived creativity. The results show a progressive improvement in user–system interaction across the seven Design Units, as users become more familiar with immersive technologies. Effectiveness improves as users gain experience, though it remains sensitive to design complexity. Efficiency shows favourable values even in early stages, reflecting operational fluency despite learning demands. Satisfaction records the greatest improvement, driven by smoother interaction and greater creative freedom. These findings highlight the potential of immersive tools to support design processes while also underlining the need for future research on sustained usability, interface ergonomics, and collaborative workflows in extended reality environments. Full article

Trace metal pollution in tropical freshwater ecosystems poses growing public health concerns, particularly in regions where fisheries are central to food security; however, little is known about metal exposure risks in the Western Amazon. This study presents the first assessment of trace metal concentrations in fish sold at the main market in El Coca, a rapidly growing city in the Ecuadorian Amazon. We analyzed 11 trace metals in 17 commercially important species and estimated seven health risk indices based on two fish consumption scenarios and international reference dose standards. Our results show that all species exceeded recommended thresholds for arsenic, mercury, and lead, while one species surpassed guidelines for aluminum. Metal concentrations varied by species and river of origin: small catfish from the Payamino River had elevated cadmium, chromium, copper, and manganese levels, potentially linked to upstream gold mining, whereas larger catfish showed higher mercury and arsenic accumulation. Monte Carlo simulations of risk indices suggested overall low disease risk, but the lack of local demographic data limits accurate assessments for vulnerable groups. Despite sampling limitations, our findings offer the first baseline for monitoring trace metal exposure in the northern Ecuadorian Amazon and underscore the need for targeted public health strategies in this understudied region. Full article

This study explores whether sustainability achievements—proxied through ESG (environmental, social, and governance) reporting—are associated with superior financial performance in Latvia’s manufacturing sector, where ESG maturity remains low and institutional readiness is still emerging. Building on stakeholder, legitimacy, signal, slack resources, and agency theories, this study applies a mixed-method approach (that consists of two analytical stages) suited to the limited availability and reliability of ESG-related data in the Latvian manufacturing sector. Financial indicators from three large firms—AS MADARA COSMETICS, AS Latvijas Finieris, and AS Valmiera Glass Grupa—are compared with industry averages over the 2019–2023 period using independent sample T-tests. ESG integration is evaluated through a six-stage conceptual schema ranging from symbolic compliance to performance-driven sustainability. The results show that AS MADARA COSMETICS, which demonstrates advanced ESG integration aligned with international standards, significantly outperforms its industry in all profitability metrics. In contrast, the other two companies remain at earlier ESG maturity stages and show weaker financial performance, with sustainability disclosures limited to general statements and outdated indicators. These findings support the synergy hypothesis in contexts where sustainability is internalized and operationalized, while also highlighting structural constraints—such as resource scarcity and fragmented data—that may limit ESG-financial alignment in post-transition economies. This study offers practical guidance for firms seeking competitive advantage through strategic ESG integration and recommends policy actions to enhance ESG transparency and performance in Latvia, including performance-based reporting mandates, ESG data infrastructure, and regulatory alignment with EU directives. These insights contribute to the growing empirical literature on ESG effectiveness under constrained institutional and economic conditions. Full article

This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and Eastern European (CEE) countries, over the period 2019–2023, were evaluated to determine the degree of convergence of the following four measurable qualitative characteristics: relevance, exact representation, comparability and understandability. The main objective is to identify consistency in the quality of accounting information based on the application of an international financial reporting framework. The applied methodology eliminates subjective variability by implementing a standardized scoring system, aligned with the criteria developed by NiCE, using libraries such as spaCy and NLTK for term extraction, respective sentiment analysis and word frequency evaluation. The results reveal significant heterogeneity in all characteristics examined, with statistical tests confirming substantial differences between countries. The investigation of relevance revealed partial convergence, with three dimensions achieving complete uniformity, while the exact representation showed the highest variability. The assessment of comparability showed a significant difference between countries’ extreme values, and in terms of comprehensibility a formalistic approach was evident, with technical dimensions outweighing user-oriented aspects. The overall quality index varied significantly across countries, with a notable average deterioration in 2023, indicating structural vulnerabilities in financial reporting systems. These findings support initial hypotheses on the lack of homogeneity in the quality of financial reporting in the selected region, despite the implementation of international standards. Full article

When there is an absence of disaster prevention measures, natural hazards can lead to disasters. An essential part of disaster risk management is the geospatial modeling of devastating hazards, where data sharing is of paramount importance in the context of early-warning systems. This research points out the usefulness of Spatial Data Infrastructures (SDIs) for disaster risk reduction through a literature review, focusing on the necessity of data unification and disposal. Initially, the principles of SDIs are presented, given the fact that this framework contributes significantly to the fulfilment of specific targets and priorities of the Sendai Framework for Disaster Risk Reduction 2015–2030. Thereafter, the challenges of SDIs are investigated in order to underline the main drawbacks stakeholders in emergency management have to come up against, namely the semantic misalignment that impedes efficient data retrieval, malfunctions in the interoperability of datasets and web services, the non-availability of the data in spite of their existence, and a lack of quality data, while also highlighting the obstacles of real case studies on national NSDIs. Thus, diachronic observations on disasters will not be made, despite these comprising a meaningful dataset in disaster mitigation. Consequently, the harmonization of national SDIs with international schemes, such as the Group on Earth Observations (GEO) and European Union’s space program Copernicus, and the usefulness of Artificial Intelligence (AI) and Machine Learning (ML) for disaster mitigation through the prediction of natural hazards are demonstrated. In this paper, for the purpose of disaster preparedness, real-world implementation barriers that preclude SDIs to be completed or deter their functionality are presented, culminating in the proposed future research directions and topics for the SDIs that need further investigation. SDIs constitute an ongoing collaborative effort intending to offer valuable operational tools for decision-making under the threat of a devastating event. Despite the operational potential of SDIs, the complexity of data standardization and coordination remains a core challenge. Full article

Sewage sludge (SS) is commonly applied as a soil amendment. This practice has raised concern about the dissemination of emerging pollutants (EPs). EPs include compounds such as flame retardants, plasticizers, pharmaceuticals, and personal care products, among others, which may pose risks to human health and ecosystems. The complexity of the SS matrix, combined to the absence of an international legislation framework, makes it necessary to evaluate the techniques available for detecting these contaminants. Detection is typically performed using sensitive analytical techniques; however, the extraction strategy selected remains a crucial step. This review aims to compile different methodologies for the determination of EPs in SS, focusing on extraction strategies reported between 2010 and 2025. Ultrasound-assisted extraction (UAE), pressurized liquid extraction (PLE), and microwave-assisted extraction (MAE) are the most widely used strategies for EPs. UAE is considered the most preferable option, as it enables the extraction of a wide range of compounds without the need for expensive equipment. Among novel techniques, the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method is especially promising, as it is applicable to multiple target compounds. This review provides up-to-date information that can support the development of routine and standardized methodologies for the characterization of EPs in SS. Full article

Rapid pavement repair demands materials that combine accelerated strength gains, dimensional stability, long-term durability, and sustainability. However, finding materials or formulations that offer these balances remains a critical challenge. This study systematically evaluates two polymer-modified belitic calcium sulfoaluminate (CSA) concretes—CSAP (powdered polymer) and CSA-LLP (liquid polymer admixture)—against a traditional Type III Portland cement (OPC) control under both laboratory and realistic outdoor conditions. Laboratory specimens were tested for fresh properties, early-age and later-age compressive, flexural, and splitting tensile strengths, as well as drying shrinkage according to ASTM standards. Outdoor 5 × 4 × 12-inch slabs mimicking typical jointed plain concrete panels (JPCPs), instrumented with vibrating wire strain gauges and thermocouples, recorded the strain and temperature at 5 min intervals over 16 weeks, with 24 h wet-burlap curing to replicate field practices. Laboratory findings show that CSA mixes exceeded 3200 psi of compressive strength at 4 h, but cold outdoor casting (~48 °F) delayed the early-age strength development. The CSA-LLP exhibited the lowest drying shrinkage (0.036% at 16 weeks), and outdoor CSA slabs captured the initial ettringite-driven expansion, resulting in a net expansion (+200 µε) rather than contraction. Approximately 80% of the total strain evolved within the first 48 h, driven by autogenous and plastic effects. CSA mixes generated lower peak internal temperatures and reduced thermal strain amplitudes compared to the OPC, improving dimensional stability and mitigating restraint-induced cracking. These results underscore the necessity of field validation for shrinkage compensation mechanisms and highlight the critical roles of the polymer type and curing protocol in optimizing CSA-based repairs for durable, low-carbon pavement rehabilitation. Full article

An important task for the European Union is to transpose agreements and international standards in regulation and directives that are binding on member states. The resultant European action plans and directives identify priority areas in the building and energy sectors where circular economy principles can be applied. Italy records a general circular materials rate of 20.8%, surpassing the mean European value. But low recycling rates are still registered in the construction sector. This paper aims to assess the position of Italy with respect to the European regulatory framework on circularity in the energy transition of buildings. Firstly, the government’s initiatives and technical standards are introduced and commented upon. Secondly, the study illustrates the current Italian platforms, networks, and public and private initiatives highlighting opportunities and obstacles that the energy sector has to overcome in the area of circularity. It emerges that Italian policies still use voluntary tools that are not sufficiently in line with an effective circular economy model. Moreover, data collection plays a crucial role in accelerating the implementation of future actions. Italy should consider the foundation of a National Observatory for the Circular Economy to elaborate European directives, harmonize regional policies, and promote the implementation of effective practices. Full article