Search Results (3,838)

The exponential increase in electronic waste (e-waste) from end-of-life electrical and electronic equipment presents a growing environmental challenge. E-waste contains high concentrations of rare earth elements (REEs), which are classified as critical raw materials (CRMs). Their removal and recovery from contaminated systems not only mitigate pollution but also support resource sustainability within a circular economy framework. The present study proposed the use of hazelnut shells as a biosorbent to reduce water contamination and recover REEs. The sorption capabilities of this lignocellulosic material were assessed and optimized using the response surface methodology (RSM) combined with a Box–Behnken Design (three factors, three levels). Factors such as pH (4 to 8), salinity (0 to 30), and biosorbent dose (0.25 to 0.75 g/L) were evaluated in a complex mixture containing 9 REEs (Y, La, Ce, Pr, Nd, Eu, Gd, Tb and Dy; equimolar concentration of 1 µmol/L). Salinity was found to be the factor with greater significance for REEs sorption efficiency, followed by water pH and biosorbent dose. At a pH of 7, salinity of 0, biosorbent dose of 0.75 g/L, and a contact time of 48 h, optimal conditions were observed, achieving removals of 100% for Gd and Eu and between 81 and 99% for other REEs. Optimized conditions were also predicted to maximize the REEs concentration in the biosorbent, which allowed us to obtain values (total REEs content of 2.69 mg/g) higher than those in some ores. These results underscore the high potential of this agricultural waste with no relevant commercial value to improve water quality while providing an alternative source of elements of interest for reuse (circular economy). Full article

Background/Objectives: Cardiovascular diseases (CVDs) encompass a wide range of heart and vascular conditions and remain the leading cause of death worldwide. Acceptance and Commitment Therapy (ACT) is a psychotherapeutic approach that integrates acceptance, mindfulness, and commitment to value-based actions. This systematic review aims to explore the current evidence on the potential role of ACT interventions in supporting psychological well-being among individuals with CVDs. Methods: A systematic review was conducted in accordance with PRISMA guidelines. A search of the literature was conducted through Scopus, PubMed, Web of Science, Cochrane, and PsycINFO databases. Six studies met the inclusion criteria. Results: The reviewed studies suggest that ACT may promote psychological flexibility, emotion regulation, and self-care behaviors in patients with CVDs. Reported outcomes include improved mindfulness, reduced distress, and enhanced quality of life. However, the evidence base is limited in both size and methodological rigor, with included studies varying in design and population. Conclusions: While preliminary findings indicate that ACT shows promise in addressing psychological aspects of CVDs, the current evidence remains insufficient to draw definitive conclusions. Further high-quality, large-scale studies are needed to evaluate the effectiveness and clinical applicability of ACT in cardiovascular populations. Full article

As manufacturing demands for challenging-to-machine metallic materials continue to evolve, the performance of cutting tools has emerged as a critical limiting factor. The synergistic application of micro-texture and coating in cutting tools can improve various properties. For the processing of existing micro-texture, because of the fast cooling and heating processing method of laser, there are defects such as remelted layer stacking and micro-cracks on the surface after processing. This study introduces a preheating-assisted technology aimed at optimizing the milling performance of textured coated tools. A milling test platform was established to evaluate the performance of these tools on titanium alloys under thermally assisted conditions. The face-centered cubic response surface methodology, as part of the central composite design (CCD) experimental framework, was employed to investigate the interaction effects of micro-texture preparation parameters and thermal assistance temperature on milling performance. The findings indicate a significant correlation between thermal assistance temperature and tool milling performance, suggesting that an appropriately selected thermal assistance temperature can enhance both the milling efficiency of the tool and the surface quality of the titanium alloy. Utilizing the response surface methodology, a multi-objective optimization of the textured coating tool-preparation process was conducted, resulting in the following optimized parameters: laser power of 45 W, scanning speed of 1576 mm/s, the number of scans was 7, micro-texture spacing of 130 μm, micro-texture diameter of 30 μm, and a heat-assisted temperature of 675.15 K. Finally, the experimental platform of optimization results is built, which proves that the optimization results are accurate and reliable, and provides theoretical basis and technical support for the preparation process of textured coating tools. It is of great significance to realize high-precision and high-quality machining of difficult-to-machine materials such as titanium alloy. Full article

Lycopene, a carotenoid found in tomatoes and watermelon, has been investigated for its potential to improve male fertility through its antioxidant and anti-inflammatory mechanisms. However, evidence of its effectiveness remains inconsistent. We conducted a systematic review and meta-analysis of studies published until February 2025 in the PubMed, Scopus, Web of Science, and Medline databases. Clinical studies evaluating lycopene supplementation in relation to male fertility outcomes were included in this review. Standardized mean differences (SMDs) were calculated for the key outcomes. Four clinical studies involving 151 participants were included. Lycopene supplementation significantly improved sperm concentration (SMD 0.33, 95% CI [0.02–0.65], p = 0.037) and nonprogressive motility (SMD 0.45, 95% CI [0.04–0.87], p = 0.032). No statistically significant effects were observed on total motility, progressive motility, normal or abnormal morphology, semen volume, or DNA damage. Sensitivity analyses showed that the findings were generally robust, although publication bias and methodological heterogeneity were noted. Lycopene supplementation may offer modest benefits in improving sperm concentration and nonprogressive motility in men. However, evidence for other fertility-related outcomes is inconclusive. Larger, high-quality randomized trials are needed to confirm these findings and clarify the role of lycopene in male reproductive health. Full article

This research analyzed university students’ perceptions of the use of generative artificial intelligence (hereafter Gen-AI) in a higher education context. Specifically, it addressed the potential benefits and challenges related to the application of these web-based resources. A mixed method was adopted and the sample consisted of 407 teacher training students enrolled in the Early Childhood and Primary Education Degrees in the Region of Murcia in Spain. The results indicated a clear recognition of the relevance of these technological tools for teaching and learning. Respondents highlighted the potential to engage them in academic tasks, increase their motivation, and personalize their learning pathways. However, participants identified some challenges related to technology dependency, ethical issues, and privacy concerns. By understanding learners’ beliefs and assumptions, educators and educational administrations can adapt Gen-AI according to learners’ needs and preferences to improve their academic performance. In learning practice, these adaptations could involve evidence-based interventions, such as AI literacy modules or hybrid assessment frameworks, to translate findings into practice. In addition, it is necessary to adjust materials, methodologies, and the assessment of the academic curriculum to facilitate student learning and ensure that all students have access to quality education and the adequate development of digital skills. Full article

Background: Chronic primary orofacial pain (COFP) affects approximately 7% of the population and often leads to reduced quality of life. Patients frequently undergo multiple assessments and treatments across healthcare disciplines, often without a definitive diagnosis. The 2019 ICD-11 classification of chronic primary pain clusters together COFP subtypes based on chronicity and associated functional and emotional impairment. Objective: This study aimed to evaluate whether these subtypes of COFP share common underlying mechanisms by comparing neuroimaging findings. Methods: A systematic review was conducted in accordance with PRISMA guidelines. Searches were performed using Medline (OVID) and Scopus up to April 2025. Inclusion criteria focused on MRI-based neuroimaging studies of participants diagnosed with COFP subtypes. Data extraction included participant demographics, imaging modality, brain regions affected, and pain assessment tools. Quality assessment used a modified Coleman methodological score. Results: Fourteen studies met the inclusion criteria, all utilising MRI and including two COFP subtypes (temporomandibular disorder and burning mouth syndrome). Resting- and task-state imaging revealed overlapping alterations in several brain regions, including the thalamus, somatosensory cortices (S1, S2), cingulate cortex, insula, prefrontal cortex, basal ganglia, medial temporal lobe, and primary motor area. These changes were consistent across both TMD and BMS populations. Conclusions: The findings suggest that chronic primary orofacial pain conditions (TMD and BMS) may share common central neuroplastic changes, supporting the hypothesis of a unified pathophysiological mechanism. This has implications for improving diagnosis and treatment strategies, potentially leading to more targeted and effective care for these patients. Full article

Climate concerns are driving the automotive industry to adopt advanced manufacturing technologies that aim to improve energy efficiency and reduce vehicle weight. In this context, lightweight structural materials such as aluminium alloys have gained significant attention due to their favorable strength-to-weight ratio. Laser welding plays a crucial role in assembling such materials, offering high flexibility and fast joining capabilities for thin aluminium sheets. However, welding these materials presents specific challenges, particularly in controlling heat input to minimize distortions and ensure consistent weld quality. As a result, numerical simulations based on the Finite Element Method (FEM) are essential for predicting weld-induced phenomena and optimizing process performance. This study investigates welding-induced distortions in laser butt welding of 1.5 mm-thick Al 6061 samples through FEM simulations performed in the SYSWELD 2024.0 environment. The methodology provided by the software is based on the Moving Heat Source (MHS) model, which simulates the physical movement of the heat source and typically requires extensive calibration through destructive metallographic testing. This transient approach enables the detailed prediction of thermal, metallurgical, and mechanical behavior, but it is computationally demanding. To improve efficiency, the Imposed Thermal Cycle (ITC) model is often used. In this technique, a thermal cycle, extracted from an MHS simulation or experimental data, is imposed on predefined subregions of the model, allowing only mechanical behavior to be simulated while reducing computation time. To avoid MHS-based calibration, this work proposes using thermal cycles acquired in-line during welding via infrared thermography as direct input for the ITC model. The method was validated experimentally and numerically, showing good agreement in the prediction of distortions and a significant reduction in workflow time. The distortion values from simulations differ from the real experiment by less than 0.3%. Our method exhibits a slight decrease in performance, resulting in an increase in estimation error of 0.03% compared to classic approaches, but more than 85% saving in computation time. The integration of real process data into the simulation enables a virtual representation of the process, supporting future developments toward Digital Twin applications. Full article

Optical networks serve as the backbone of modern communication, requiring statistical analysis and modeling to optimize performance, reliability, and scalability. This review paper explores statistical methodologies for analyzing network characteristics, dimensioning, parameter estimation, and cost prediction of optical networks, and provides a generalized framework based on the idea of convex areas, and link length and shortest path length distributions. Accurate dimensioning and cost estimation are crucial for optical network planning, especially during early-stage design, network upgrades, and optimization. However, detailed information is often unavailable or too complex to compute. Basic parameters like coverage area and node count, along with statistical insights such as distribution patterns and moments, aid in determining the appropriate modulation schemes, compensation techniques, repeater placement, and in estimating the fiber length. Statistical models also help predict link lengths and shortest path lengths, ensuring efficiency in design. Probability distributions, stochastic processes, and machine learning improve network optimization and fault prediction. Metrics like bit error rate, quality of service, and spectral efficiency can be statistically assessed to enhance data transmission. This paper provides a review on statistical analysis and modeling of optical networks, which supports intelligent optical network management, dimensioning of optical networks, performance prediction, and estimation of important optical network parameters with partial information. Full article

Background/Objectives: The inferior thyroid artery (ITA) is an essential component of the thyroid gland’s vasculature, with significant clinical and surgical implications due to its anatomical variability. This systematic review aimed to describe the prevalence of ITA anatomical variants and their association with clinical conditions or surgical implications. Methods: A comprehensive search was conducted in MEDLINE, Web of Science, Google Scholar, CINAHL, Scopus, and EMBASE on 20 November 2025. Eligibility criteria included studies reporting on the presence of ITA variants and their correlation with pathologies. Two authors independently screened the literature, extracted data, and assessed methodological quality using the AQUA and JBI tools. Results: Of the 2647 articles identified, 19 studies involving 1118 subjects/cadavers were included. Variations in ITA origin, absence, and additional arteries were reported, with the most common variant being direct origin from the subclavian artery. Clinically, these variations were associated with increased risk of intraoperative hemorrhage, potential nerve damage, and challenges in preoperative planning, particularly during thyroidectomy and other neck procedures. Conclusions: Understanding the anatomical diversity of the ITA is crucial for reducing surgical risks and improving patient outcomes. The review highlighted the need for more standardized research protocols and comprehensive data reporting to enhance the quality of evidence in this domain. Preoperative imaging and thorough anatomical assessments tailored to individual patient profiles, considering ethnic and gender-related differences, are essential for safe surgical interventions in the thyroid region. Full article

Non-pharmacological interventions, such as physical activity and exercise, are essential in managing type 1 diabetes mellitus by improving glycemic control, cardiovascular health and autonomic function. Given the chronic nature and long-term complications associated with type 1 diabetes, strategies beyond pharmacotherapy are essential. This review examines the effects of exercise on heart rate variability, a key indicator of autonomic nervous system activity. A systematic search was conducted in March 2024 across PubMed, Embase, Cochrane and CINAHL databases. Studies evaluating the retrospective or prospective impact of exercise or physical activity on heart rate variability parameters were included. Utilizing best evidence synthesis, the methodological quality of the included studies was evaluated. Seven studies met the inclusion criteria, all of which were rated as methodologically weak. Moderate evidence suggests that exercise may enhance heart rate variability, particularly by increasing parasympathetic activity and improving sympathovagal balance. However, evidence remains limited regarding the optimal type, frequency and intensity of exercise. Exercise appears to support autonomic function in individuals with type 1 diabetes mellitus. Nonetheless, further high-quality research is needed to determine the most effective exercise modalities and to inform evidence-based clinical guidelines. Full article

Background: The emergency department (ED) often represents the entry point to care for patients that require urgent medical attention or have no alternative for medical treatment. This has implications on scope of practice and how quality of care is measured. A diverse array of methodologies has been developed to evaluate the quality of clinical care and broadly includes quality improvement (QI), quality assurance (QA), observational research (OR) and clinical quality registries (CQRs). Considering the overlap between QI, QA, OR and CQRs, we conceptualized a modular framework for TECOR to effectively and efficiently streamline clinical quality evaluations. Streamlining is both appropriate and justified as it reduces redundancy, enhances clarity and optimizes resource utilization, thereby allowing clinicians to focus on delivering high-quality patient care without being overwhelmed by excessive data and procedural complexities. The objective of this study is to describe the process for designing a modular framework for ED CQRs using TECOR as a case study. Methods: We performed a scoping audit of all quality projects performed in our ED over a 1-year period (1 January 2021 to 31 December 2021) as well as data mapping and categorical formulation of key themes from the TECOR dataset with clinical data sources. Both these processes then informed the design of TECOR. Results: For the audit of quality projects, we identified 29 projects. The quality evaluation methodologies for these projects included 12 QI projects, 5 CQRs and 12 OR projects. Data mapping identified that clinical information was fragmented across 11 distinct data sources. Through thematic analysis during data mapping, we identified three extraction techniques: self-extractable, manual entry and on request. Conclusions: The modular framework for TECOR aims to enable an efficient streamlined approach that caters to all aspects of clinical quality evaluation to enable higher throughput of clinician-led quality evaluations and improvements. TECOR is also an essential component in the development of a learning health system to drive evidence-based practice and the subject of future research. Full article

Crop disease identification is a pivotal research area in smart agriculture, forming the foundation for disease mapping and targeted prevention strategies. Among the most prevalent global wheat diseases, powdery mildew—caused by fungal infection—poses a significant threat to crop yield and quality, making early and accurate detection crucial for effective management. In this study, we present QY-SE-MResNet34, a deep learning-based classification model that builds upon ResNet34 to perform multi-class classification of wheat leaf images and assess powdery mildew severity at the single-leaf level. The proposed methodology begins with dataset construction following the GBT 17980.22-2000 national standard for powdery mildew severity grading, resulting in a curated collection of 4248 wheat leaf images at the grain-filling stage across six severity levels. To enhance model performance, we integrated transfer learning with ResNet34, leveraging pretrained weights to improve feature extraction and accelerate convergence. Further refinements included embedding a Squeeze-and-Excitation (SE) block to strengthen feature representation while maintaining computational efficiency. The model architecture was also optimized by modifying the first convolutional layer (conv1)—replacing the original 7 × 7 kernel with a 3 × 3 kernel, adjusting the stride to 1, and setting padding to 1—to better capture fine-grained leaf textures and edge features. Subsequently, the optimal training strategy was determined through hyperparameter tuning experiments, and GrabCut-based background processing along with data augmentation were introduced to enhance model robustness. In addition, interpretability techniques such as channel masking and Grad-CAM were employed to visualize the model’s decision-making process. Experimental validation demonstrated that QY-SE-MResNet34 achieved an 89% classification accuracy, outperforming established models such as ResNet50, VGG16, and MobileNetV2 and surpassing the original ResNet34 by 11%. This study delivers a high-performance solution for single-leaf wheat powdery mildew severity assessment, offering practical value for intelligent disease monitoring and early warning systems in precision agriculture. Full article

In the process of evaluating the quality of a company’s development, the issues related to production capacity and environmental pollution have emerged as significant concerns. Drawing on the methodologies employed in previous related research, this study utilizes the Data Envelopment Analysis with relaxation variables and the Global Malmquist–Luenberger index to measure the green total factor productivity of Chinese heavy-polluting enterprises. The main findings of this study are as follows: (1) It is clearly demonstrated that higher managerial effectiveness has a substantial positive impact on the improvement of a company’s green total factor productivity; (2) the digitalization progress within enterprises serves as a moderating factor in the relationship between managerial effectiveness and green total factor productivity; (3) the extent of financial constraints acts as a mediating variable, intervening in the relationship between managerial efficiency and green total factor productivity; and (4) a threshold effect is detected between managerial effectiveness and the debt repayment pressure faced by enterprises. When the threshold values of managerial effectiveness or the quick ratio are surpassed, the influence of managerial effectiveness on the green total factor productivity of enterprises will undergo a change. Full article

Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare, progressive form of pre-capillary pulmonary hypertension characterized by persistent, organized thromboemboli in the pulmonary vasculature, leading to vascular remodeling, elevated pulmonary artery pressures, right heart failure, and significant morbidity and mortality if untreated. Despite advances, CTEPH remains underdiagnosed due to nonspecific symptoms and overlapping features with other forms of pulmonary hypertension. Basic Methodology: This review synthesizes data from large international registries, epidemiologic studies, translational research, and multicenter clinical trials. Key methodologies include analysis of registry data to assess incidence and risk factors, histopathological examination of lung specimens, and molecular studies investigating endothelial dysfunction and inflammatory pathways. Diagnostic modalities and treatment outcomes are evaluated through observational studies and randomized controlled trials. Recent Advances and Affected Population: Research has elucidated that CTEPH arises from incomplete resolution of pulmonary emboli, with subsequent fibrotic transformation mediated by dysregulated TGF-β/TGFBI signaling, endothelial dysfunction, and chronic inflammation. Affected populations are typically older adults, often with prior venous thromboembolism, splenectomy, or prothrombotic conditions, though up to 25% have no history of acute PE. The disease burden is substantial, with delayed diagnosis contributing to worse outcomes and higher societal costs. Microvascular arteriopathy and PAH-like lesions in non-occluded vessels further complicate the clinical picture. Conclusions: CTEPH is now recognized as a treatable disease, with multimodal therapies—surgical endarterectomy, balloon pulmonary angioplasty, and targeted pharmacotherapy—significantly improving survival and quality of life. Ongoing research into molecular mechanisms and biomarker-driven diagnostics promises earlier identification and more personalized management. Multidisciplinary care and continued translational investigation are essential to further reduce mortality and optimize outcomes for this complex patient population. Full article

Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European water management, drawing on a structured synthesis of empirical evidence from regional case studies and policy frameworks. The analysis found that while NbS are effective in reducing surface runoff, mitigating floods, and improving water quality under low- to moderate-intensity events, their performance remains uncertain under extreme climate scenarios. Key gaps identified include the lack of long-term monitoring data, limited assessment of NbS under future climate conditions, and weak integration into mainstream planning and financing systems. Existing evaluation frameworks are critiqued for treating NbS as static interventions, overlooking their ecological dynamics and temporal variability. In response, a dynamic, climate-resilient assessment model is proposed—grounded in systems thinking, backcasting, and participatory scenario planning—to evaluate NbS adaptively. Emerging innovations, such as hybrid green–grey infrastructure, adaptive governance models, and novel financing mechanisms, are highlighted as key enablers for scaling NbS. The article contributes to the scientific literature by bridging theoretical and empirical insights, offering region-specific findings and recommendations based on a comparative analysis across diverse European contexts. These findings provide conceptual and methodological tools to better design, evaluate, and scale NbS for transformative, equitable, and climate-resilient water governance. Full article