Search Results (7,076)

Background: Temporomandibular disorders (TMDs) are common musculoskeletal conditions associated with pain, functional limitation, and reduced quality of life (QoL). Despite the widespread use of conservative and minimally invasive treatments, the available evidence remains fragmented across heterogeneous interventions, diagnostic criteria, and outcome measures, limiting comparative interpretation and clinical applicability. Objectives: The primary objective of this systematic review is to evaluate the effectiveness of conservative and minimally invasive interventions for pain reduction in adult patients with temporomandibular disorders. Secondary objectives include assessing effects on mandibular function and QoL and exploring differences across intervention categories, TMD subtypes, diagnostic criteria, and follow-up durations. Methods: This protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251250251) and adheres to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. A systematic search will be conducted in PubMed/MEDLINE, Web of Science, Scopus, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) for randomized controlled trials (RCTs) published from 1 January 2015, up to the date of study initiation, using controlled vocabulary terms and free-text keywords combined with Boolean operators. Eligible studies will include adult patients (≥18 years) diagnosed with temporomandibular disorders using validated diagnostic criteria and treated with conservative or minimally invasive interventions, compared with placebo/sham, no treatment or usual care, or active comparators, in accordance with the PICOS framework. Two reviewers will independently screen studies and extract data, with disagreements resolved by consensus or consultation with a third reviewer; the study selection process will be documented using a PRISMA 2020 flow diagram. Interventions will be synthesized within predefined clusters (e.g., physical and manual therapies, occlusal splint therapy, physical agent modalities, and minimally invasive joint procedures). Risk of bias will be assessed using the revised Cochrane Risk of Bias tool (RoB 2). The primary outcome will be pain intensity, while secondary outcomes will include mandibular function and QoL. Where appropriate, meta-analysis using a random-effects model will be performed; otherwise, a structured narrative synthesis will be provided. Expected Impact: The systematic review is expected to deliver an updated and methodologically rigorous synthesis of evidence on conservative and minimally invasive interventions for TMDs. By addressing existing research gaps such as the fragmentation of evidence across intervention types, heterogeneity in diagnostic criteria, and variability in outcome measures, this review will support evidence-based clinical decision-making and identify priorities for future research. Full article

With renewable integration and zero-carbon microgrids achieving 100% penetration, converter-dominated systems exhibit millisecond-timescale transient synchronization, which challenges existing physical cognitive methods and cognitive methodology with the synchronous generator (SG). In this paper, in order to quantificationally analyze the transient synchronization, a unified framework has been proposed that combines the generalized participation factor (GPF) method and basin of attraction (BOA) boundary analysis using the manifold approach. According to the GPF and BOA analyses, the fourth-order models are essential for accurate stability quantification, with synchronization controls (PLL, VSG, and droop control) contributing greater than 70% to transient dynamics versus about 20% from power-balance interactions. Further, the dynamic security region (DSR) is redefined by two typologies. Type 1 DSR maps stability in active-power injection space, and Type 2 DSR (generalized DSR) delineates limits in the controllable parameter space. The estimation procedures are proposed for these two types of DSRs by the BOA method. Finally, electromagnetic transient simulations and critical clearing time validation are employed for fidelity verification of models and estimation approaches. To sum up, the proposed novel framework enables systematic DSR estimations for renewable-rich power systems, empowering grid operators to optimize converter-controllable parameters and system operation conditions. Full article

As the smart home ecosystem expands with the adoption of Matter, a wide variety of Internet of Things (IoT) devices are entering the market, and these devices are becoming more complex, as they support diverse functionalities. Consequently, smart home forensics often requires data extraction procedures that are specific to each device and platform, which increases the technical burden and time costs for investigators. To address these challenges, this study proposes a method that leverages Matter Multi-Admin support for multiple fabrics to enable efficient data acquisition from Matter-enabled IoT devices, regardless of the underlying smart home platform. This method configures a forensic Matter controller using chip-tool and commissions IoT devices that have already been commissioned to a smart home platform into a secondary fabric via Multi-Admin. The forensic controller then performs data extraction using standardized Matter interfaces. The proposed approach was validated on our smart home testbed by targeting a Matter smart bulb commissioned to the SmartThings platform and successfully extracting data generated by the platform, thereby demonstrating the utility of the method. The results indicate that the method enables nondestructive and efficient evidence acquisition from smart home IoT devices and can support future research and real-world investigations. Full article

Introduction: Rapid and reliable neurovascular imaging is critical for time-sensitive diagnosis in acute cerebrovascular disorders, yet conventional magnetic resonance imaging (MRI) workflows remain constrained by acquisition speed, motion sensitivity, and limited integration of physiological context. We introduce the Intelligent Neurovascular Imaging Engine (INIE), a sensor-informed, topology-aware framework that jointly optimizes accelerated data acquisition, physics-grounded reconstruction, and cross-scale physiological consistency. Methods: INIE combines adaptive sampling, structured low-rank (Hankel) priors, and topology-preserving objectives with multimodal physiological sensors and scanner telemetry, enabling phase-consistent gating and confidence-weighted reconstruction under realistic operating conditions. The framework was evaluated using synthetic phantoms, a translational porcine stroke recanalization model with repeated measures, and retrospective human datasets. Across $N_{\mathrm{runs}}=120$ acquisition–reconstruction runs derived from $N_{\mathrm{animals}}=18$ pigs with animal-level train/validation/test separation, performance was assessed using image quality, topological fidelity, and cross-modal consistency metrics. Multiple-comparison control was performed using Bonferroni/Holm–Bonferroni procedures. Results: INIE achieved acquisition acceleration exceeding 70% while maintaining high reconstruction fidelity (PSNR $\approx 35$–36 dB, SSIM $\approx 0.90$–0.92). Topology-aware analysis showed an approximately twofold reduction in Betti number deviation relative to baseline accelerated methods. Cross-modal validation in a PET subset demonstrated strong agreement between MRI-derived perfusion parameters and metabolic markers (Pearson $r\approx 0.9$). INIE improved large-vessel occlusion detection accuracy to approximately 93% and reduced automated time-to-decision to under three minutes. Conclusions: These results indicate that sensor-informed, topology-aware, closed-loop imaging improves the reliability and physiological consistency of accelerated neurovascular MRI and supports faster, more robust decision-making in acute cerebrovascular imaging workflows. Full article

Critical thinking (CT) is widely recognized as a central goal of science education, yet its mechanisms within specific disciplinary contexts remain underexplored. This study developed a biology-specific theoretical model of CT through qualitative analysis of high school students’ engagement with contradictory evidence. Data included pen-and-paper responses from 196 students and eight classroom dialogue transcripts, analyzed using Corbin and Strauss’s coding procedures, with sequential batching and external validation. Selective coding identified questioning—transforming multiple criteria—as the core category, supported by four major categories: evolving evaluative criteria, various types of reasoning, analysis without judgment, and the application of empirical knowledge across criteria. This model explains how learners shift between confirmation, falsification, and reconstruction when anomalies disrupt initial assumptions. To extend its theoretical reach, the model was placed in heuristic dialogue with Kuhn’s structure of scientific revolutions. The comparison highlights the cyclical nature of CT development: anomalies destabilize prevailing frameworks and trigger reorganization of evaluative criteria, fostering cognitive growth. By explicating how students engage with contradictory evidence and transform evaluative criteria, this study elucidates the emergence of critical thinking in disciplinary practice. The findings also inform the design of biology learning environments that deliberately incorporate anomalies and cognitive conflicts, and justify the integration of history and philosophy of science (HPS) perspectives to support students’ questioning, analysis, and criteria revision in authentic scientific contexts. Full article

According to the EFSA Report on Zoonoses (2024), yersiniosis was classified as the fourth most commonly reported zoonosis in humans in 2023, with a 13.5% increase in yersiniosis infections compared to 2022. In 2024, the findings were consistent with the 2020–2023 trend. Isolation and identification of enteropathogenic Yersinia is difficult and time consuming, especially when examining food and environmental samples. Among them, Y. pseudoturbeculosis poses a challenge due to the lack of a single selective medium for all bioserotypes. Therefore, faster methods for the detection of Yersinia spp. need to be implemented into the praxis. Rapid identification of pathogens in food or at the time and location of the epidemiological outbreak (point-of-care testing) enables either prevention of the outbreak or early stage diagnosis and prompt decisions. The loop-mediated isothermal amplification (LAMP) is increasingly coming to scientists’ attention as a robust and rapid methodology for pathogen detection in laboratories with limited resources and equipment. The aim of current study is to evaluate, for the first time, the sensitivity of the LAMP protocol based on colorimetric detection in the visible spectrum in comparison with that of the digital droplet PCR (ddPCR). For this aim, a series of decimal logarithmic dilutions of the pathogen Y. pseudotuberculosis in artificially contaminated raw goat milk was used. One commercial LAMP kit with two different dyes (one dsDNA-binding and one Mg²⁺-sensitive) was compared to the sensitivity of the detection to ddPCR. The results obtained revealed a high sensitivity of the kit for detection of DNA isolated from artificially contaminated milk samples in the following range: visible detection based on visible color change—3.1 × 10⁴ mL (violet dye) and 3.4 × 10³/mL (blue dye); detection with gel electrophoresis—2.0 × 10¹/mL (violet dye) and 3.4 × 10²/mL (blue dye). The enumeration of the DNA copies in the same samples was performed with ddPCR, with a detection limit of 2.0 × 10¹/mL. Our results indicate the potential and the possible applicability of the LAMP method for rapid and sensitive visual detection of Y. pseudotuberculosis in raw goat milk. The presented ddPCR protocol can be used for highly sensitive identification and enumeration of Y. pseudtuberculosis in raw goat milk. In conclusion, the conducted comparison is of importance for future implementation of LAMP protocols for on-field analysis near the sampling site and point-of-care or laboratory diagnostics of Y. pseudtuberculosis after the successful validation procedure of an appropriate LAMP protocol. Full article

Introduction: Distal intracapsular minimally invasive osteotomies (DICMOs) for central metatarsals are described as intracapsular procedures; however, neither their intracapsular location throughout the entire cut nor the optimal anatomical position for their execution have been fully validated. The aim of this study was to assess the geometric position of the DICMO osteotomy in the central metatarsals (third and fourth) and quantify associated anatomical damage when performed under three different guidance modalities: anatomical palpation, fluoroscopic control, and ultrasound guidance. Material and methods: An experimental cadaveric study was conducted using 29 fresh specimens (11 males, 18 females), contributing a total of 58 central metatarsals (third and fourth). All specimens underwent a DICMO-type metatarsal osteotomy. Osteotomies were randomly allocated to three intervention groups: (1) ultrasound (n = 20), (2) fluoroscopy (n = 19), and (3) anatomical guidance (n = 19). Metatarsal length, the distance between the osteotomy line and the articular surface, and post-dissection soft-tissue damage were recorded. Results: After dissection, all osteotomies were confirmed to be intracapsular. A constant proportional relationship was identified between osteotomy location and metatarsal length: distance to the joint line = 0.239 × metatarsal length. This relationship was independent of the guidance technique used. Only one iatrogenic lesion was observed: an articular cartilage injury of a third metatarsal in the anatomical-guidance group. Conclusions: The optimal position for DICMO osteotomy placement is approximately 24% of the total distal metatarsal length. This ensures an intracapsular trajectory and may contribute to intrinsic osteotomy stability. Image guidance—either fluoroscopy or ultrasound—appears essential to optimize outcomes and prevent avoidable anatomical damage. Full article

Background: B-cell maturation antigen (BCMA) directed therapies have transformed the treatment landscape for relapsed or refractory multiple myeloma (RRMM). Soluble BCMA (sBCMA), a circulating product of the membrane-bound BCMA shedding, has emerged as a potential biomarker reflecting tumor burden and disease biology. This systematic review and meta-analysis aimed to evaluate the prognostic value of baseline circulating sBCMA in patients with multiple myeloma receiving BCMA-directed therapies, with progression-free survival (PFS) as the primary endpoint. Methods: A systematic literature search of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases was conducted in accordance with PRISMA guidelines. Studies enrolling patients with multiple myeloma treated with BCMA-directed therapies and reporting baseline circulating sBCMA measured in serum or plasma in relation to survival outcomes were included. Hazard ratios (HRs) for PFS and overall survival (OS) were pooled using random-effects models. Risk of bias was assessed using the QUIPS tool. Results: Four independent RRMM cohorts fulfilled the eligibility criteria and were included in the quantitative PFS meta-analysis. Elevated baseline circulating sBCMA was significantly associated with inferior PFS (pooled HR = 2.64, p < 0.05), with a consistent adverse prognostic direction across all studies. Moderate to substantial heterogeneity was observed (I² = 63.2%), potentially reflecting differences in BCMA-directed therapy modalities across cohorts and methodological variability, including study-specific sBCMA cut-off definitions, assay procedures and sampling timepoints. Exploratory subgroup analysis suggested that the prognostic impact of baseline sBCMA on PFS may differ according to BCMA-directed therapy class. Overall risk of bias was judged as low to moderate. Conclusions: Elevated baseline circulating sBCMA is associated with inferior progression-free survival in patients with multiple myeloma treated with BCMA-directed therapies. These findings support the prognostic relevance of sBCMA as a risk stratification marker, although harmonization of assays and cut-offs and prospective validation are required before clinical implementation. Full article

Exporting food products from the European Union (EU) to the United States of America (USA) involves navigating complex regulations and procedural barriers that hinder market access. Italian food businesses (FBs), particularly small and medium-sized enterprises (SMEs), often face difficulties accessing clear guidance, as national procedures are scattered across multiple sources. This paper proposes a structured three-step analytical framework to support EU FBs: product-specific analysis, identification of relevant EU and USA legislation, comparative legislative analysis via concordance tables, and identification of procedures to integrate into the Food Safety Management System. The framework was applied to an Italian medium-sized FB exporting pork-based pasta sauce to the USA. Beyond the specific case study, the proposed analytical framework was designed to be transferable and adaptable to other food categories and destination markets, providing a structured methodological tool to support regulatory alignment. In this sense, the framework can be considered product-independent but process-specific. As such, it can support both FBs and Competent Authorities in conducting risk-based assessments of regulatory equivalence and export compliance. Results indicated the need for Sanitation Standard Operating Procedures (SSOPs), thermal process validation, direct verification activities, and pre-shipment review. Findings emphasize that operational and procedural barriers disproportionately affect SMEs, highlighting the importance of targeted support to facilitate market access and strengthen certification systems. Full article

The COVID-19 pandemic necessitated rigorous infection control protocols across hospital environments, particularly in nutrition services. UV-C light emerged as a viable option due to its shortest wavelength, conferring the greatest capacity for nucleic acid (DNA/RNA) penetration in both microorganisms and human cells. We aim to develop and validate an alternative method for decontaminating food carts using UV-C light. A prototype box was created to cover the meal transport carts, with UV-C lamps strategically positioned for irradiation and decontamination. To validate this technology, four different hygiene protocols were compared: Group 1, positive control, with no sanitization procedure; Group 2, cleaned using the standard protocol of the University Hospital of UFS (HU/UFS) with 70% ethanol solution; Group 3, negative control, cleaned using the standard HU/UFS protocol with 70% ethanol and neutral detergent; and Group 4, exposed to UV-C light irradiation for 10 min after food transport. Microbiological samples were collected from 15 distinct points on the carts. Samples were collected using sterile swabs moistened with 0.85% saline solution and incubated in BHI broth at 37 °C for 24 h for presence/absence testing. Positive samples were plated on selective media (CLED, SS, MacConkey and Blood agar), incubated at 37 °C for 24–48 h, and evaluated for colony-forming unit (CFU) count. A statistically significant association was found between the hygiene method and the presence of microbial contamination (p < 0.001), based on both bacterial plate counts and BHI broth growth. Carts sanitized with 70% alcohol showed a lower probability of contamination compared to the control group (alcohol + detergent), while unsanitized carts showed a higher risk. UV-C light treatment resulted in complete absence of bacterial growth. UV-C disinfection demonstrated superior effectiveness in eliminating microorganisms, indicating a promising alternative to traditional methods. Full article

Accurate quantification of surface runoff is required for the appropriate design of storage structures, irrigation patterns, waterways, erosion control structures, water harvesting projects, and groundwater development schemes. However, the paucity of runoff data in Iraq and Iran is a serious obstacle. The soil conservation service–curve number (SCS–CN) method is applied in conjunction with remote sensing (RS) and geographic information system (GIS) to predict the surface runoff in the Shatt Al-Arab Region. In the present study, the Shatt Al-Arab Region is defined as the drainage areas and lateral sub-basins that contribute direct surface runoff to the main channel between Qurna city and the Arabian Gulf. Rainfall, land use/land cover (LULC), hydrologic soil group (HSG), and slope maps are developed in a GIS platform and processed to produce surface runoff for 35 years (1979–2013). The surface runoff ranges between 163 mm (2008) and 300 mm (1982) with an average of 233 mm yr⁻¹. The average annual surface runoff in the study area is 33.657 km³. A scatter plot constructed to visualize the connection between annual rainfall and annual runoff reveals a significant positive relation (coefficient of determination (r²) = 0.67, probability value (p) < 0.05). The runoff potential is low in the southern parts of the study area and gradually rises towards the northern parts. Cross-validation of the modeled annual runoff with the annual runoff data shows reasonably close matches (r² = 0.73, p < 0.001) demonstrating the procedure’s suitability. Full article

Strategic evaluation is essential for decision-making under uncertainty. Yet existing qualitative and quantitative methods—including chat-oriented large language model (LLM) evaluations—are difficult to deploy in complex, dynamic environments. They often fail to represent nonlinear causal dependencies among indicators, account for temporal lags, or support scalable reasoning. To address these limitations, we propose an LLM-driven strategic evaluation framework with three innovations. First, the framework integrates LLMs across the evaluation lifecycle and couples their qualitative reasoning with quantitative model computation, improving both efficiency and deployability. Second, we introduce a Time-Series Directed Acyclic Graph (TS-DAG) indicator system that explicitly encodes causal structure and time-lagged interdependencies. Third, we develop an LLM-driven procedure that automatically derives the TS-DAG architecture and instantiates its computational parameters, reducing reliance on expert-only construction. We validate the framework through an empirical study of the new energy vehicle market, complemented by baseline algorithm comparisons and sensitivity analyses. The results show that the proposed framework can uncover core indicators, capture competitive dynamics, and explain long-term strategic outcomes across varying environmental conditions. Overall, the framework provides a robust solution for strategic evaluation in complex settings, bridging qualitative strategic reasoning and quantitative, data-driven analysis. Full article

Background/Objectives: The classification of adhesive systems has historically relied on the type of etching agent and the sequence of application steps, distinguishing etch-and-rinse and self-etch categories. However, these models do not encompass the versatility introduced by universal adhesives or other emerging polymeric materials. This review aimed to integrate etching technique as a defining parameter within adhesive classification, linking material composition, bonding strategy, and clinical execution into a coherent functional framework. Methods: A structured narrative review of experimental, translational, and clinical studies published between 2010 and 2025 was conducted using PubMed and Scopus. Literature addressing adhesive categories, etching strategies, etching techniques, and smear layer characteristics was critically synthesized to identify functional relationships relevant to bonding performance and clinical decision-making. Results: The proposed taxonomy classifies materials as conventional, universal, touch-cure primers, self-adhesive/universal, and glass ionomer cements. Bonding strategies are organized as etch-and-rinse, self-etch, pre-etched, and unassisted, while etching techniques are defined as selective or nonselective families encompassing five clinically defined techniques. Incorporating etching technique clarifies the role of smear layer density, the acidity of adhesive materials, and functional monomer reactivity in demineralization and bonding. This structure enhances the understanding and teaching of adhesive concepts and supports evidence-based clinical selection of materials and techniques. Conclusions: Integrating etching technique into adhesive classification provides a functional and dynamic framework that unifies material, strategy, and technique. This taxonomy facilitates clinical decision-making and can evolve with future adhesive formulations. Further independent, long-term studies are warranted to validate the proposed combinations of materials and etching procedures. Full article

In this work, thermal imaging is employed to study the opto-thermal response of apples (Malus domestica Borkh.), assessing their post-harvest evolution through the estimation of thermal diffusivity. A non-destructive experimental procedure based on mid-wave infrared (MWIR) thermal camera (3–5 µm) and localized heating with a visible laser is developed, enabling spatially and temporally resolved surface temperature measurements. Temperature fields are recorded at different time points and radial distances from the heated spot. A theoretical model based on Fourier thermal diffusion equation is formulated to describe the spatio-temporal evolution of surface temperature. After validation on a reference sample, the method is applied to Golden and Red Delicious apples over a 28-day storage period at room temperature. Red Delicious apple exhibits higher mean diffusivity values without significant temporal changes, whereas a progressive increase in diffusivity is observed for Golden Delicious apples. These results show that thermal diffusivity is sensitive to post-harvest physiological changes in apple tissue and may be associated with intrinsic properties such as tissue density and water content. By relating laser-induced temperature fields to the estimation of thermal diffusivity, this approach enables the non-destructive, quantitative assessment of thermal diffusivity, showing potential for fruit maturity and quality assessment, which are of high importance in agri-food monitoring applications. Full article

This study presents U-Net deep learning of total electron content (TEC) obtained from Global Ionosphere Maps (GIMs) to forecast ionospheric TEC over the African 0–40° N latitude sector during geomagnetic storms which have occurred between 2011 and 2024. Before being utilized in the deep learning procedure, the GIM-TEC data were improved by assimilating ground-based vertical TEC (VTEC) observations from available Global Navigation Satellite System (GNSS) receiver stations. The U-Net one-hour-ahead prediction of TEC was examined during the intense geomagnetic storm of May 2024. Additionally, the model’s accuracy and reliability were evaluated through quantitative comparison with established climatological models, including IRI-2020 and AfriTEC storm time models. The results indicate that the integration of data assimilation with the deep learning framework yields TEC estimates that closely agree with observations, achieving a RMSE of approximately 5 TECU. On the other hand, the IRI-2020 model exhibits substantially larger errors, with RMSE ~10–17 TECU, while the AfriTEC model shows the poorest performance, with RMSE reaching approximately 15–22 TECU. Further, the U-Net was validated using two equatorial and mid-latitude GNSS stations whose data were excluded from the assimilation process, achieving RMSE values of 4.44 and 6.75 TECU and correlation coefficients of 0.93 and 0.97, confirming the model forecasting capability for reproducing ionospheric TEC variability. These results establish the model as a precise, robust tool for TEC prediction in regions with sparse GPS coverage that is crucial for ionospheric monitoring and space weather applications. Full article