Search Results (584)

Background/Objectives: Emergency arterial embolization is a life-saving procedure typically performed via femoral access. This study evaluated the safety and efficacy of immediate femoral sheath removal following emergency embolization. Methods: A retrospective cohort study was conducted at a Level 1 trauma center (January 2022–May 2025). Adult patients undergoing emergency embolization with immediate sheath removal were included. Endpoints were reintervention (repeat embolization within 7 days) and access site complications. Multivariate logistic regression identified independent predictors of outcomes. Results: A total of 322 emergency embolization procedures in 299 patients were included. The most common indication was gastrointestinal hemorrhage (45.7%). Vascular closure devices (VCDs) were used in 92.5% of cases. The re-intervention rate was 4.0% (13/322). The overall access site complication rate was 6.2% (20/322), with a major complication rate of 0.9% (3/322). On univariate analysis, pre-procedural platelet level ≤ 80 × 10⁹/L (p = 0.034) and INR > 1.5 (p = 0.034) were significantly associated with an increased risk of complications. On multivariate analysis, pre-procedural platelets ≤ 80 × 10⁹/L was the strongest independent predictor of access site complications (OR 7.28, 95% CI 1.51–35.12; p = 0.013). Choice of vascular closure device was an independent predictor for both reintervention and complications (p < 0.05), likely reflecting bias. Conclusions: Immediate femoral sheath removal following emergency embolization is safe for most patients. However, thrombocytopenia is a significant risk factor for access site complications. A risk-stratified approach with consideration for delayed sheath removal is warranted for patients with platelet counts ≤ 80 × 10⁹/L. Full article

Background: The present study aimed to identify the differences between experiences, in terms of oral health-related quality of life, pain, side effects and/or other complications, of adults undergoing orthodontic treatment using removable aligners and fixed labial or lingual appliances. Methods: The review was registered with PROSPERO, and a comprehensive electronic search was undertaken without language or date restrictions. Randomised and non-randomised trials and prospective cohort and cross-sectional studies along with case series were included. The Cochrane Collaboration’s Risk of Bias 2 Tool, Newcastle–Ottawa Scale and The Risk Of Bias In Non-Randomized Studies—of Interventions tools were used to assess quality. Data were grouped in terms of oral health-related quality of life, pain side effects and/or other complications. Results: Data from 35 studies were included; 9 were eligible for meta-analysis. Thus 2611 participants were included related to removable aligners (n = 513), fixed labial (n = 1816) and lingual (n = 218) appliances or a combination (n = 64) of appliances. The standardised mean differences in visual analogue scale pain reports between 24 h and 7 days were −10.02 (95% CI: −11.13, −8.91) for aligners and −6.40 (95%CI: −10.42, −2.38) for labial appliances (p = 0.09). There was a significant improvement in dental self-confidence following fixed labial appliance treatment (p = 0.001). Conclusions: No difference was detected in short-term pain with aligners and labial appliances. Aligners may have less impact on oral health-related quality of life measures compared to labial appliances. Lingual appliances have a persistent impact on speech, despite some adaptability. Any deterioration in oral health-related quality of life measures during treatment appears temporary. Further randomised trials using validated assessment tools and comparing aligners and labial and lingual appliances are required. Full article

Obtaining accurate estimates of the true probabilities of sporting events remains a long-standing problem in sports analytics. In this paper we propose a new domain-driven approach that infers true probabilities from betting odds. This task is not trivial, as betting odds are noisy because of bookmaker margins (vig), insider bets, and model imperfections. In this study, we present a novel approach that integrates estimates across multiple groups of betting markets to obtain more robust estimates of true probability. Our method takes market structure into account and constructs a constrained optimisation problem that is solved using the Dixon–Coles model of a football match. We compare our approach with a wide range of existing methods, using a large dataset of 359035 matches from more than 6000 leagues. The proposed method achieves the lowest log-loss and the best probability calibration among all tested approaches. It also performs the best in terms of expected profit convergence in Monte Carlo simulations, outperforming its competitors in terms of MSE and bias. This study contributes both to a new margin-removal (devig) method and provides a comprehensive comparative analysis of other known methods. Beyond football, this approach has potential applications in other sports with discrete scoring systems and potentially in other areas involving stochastic processes and market inference, such as prediction markets, finance, reliability engineering, and social prediction systems. Full article

Recommender systems are widely deployed across digital platforms, yet their opacity raises concerns about auditability, fairness, and user trust. To address the gap between predictive accuracy and model interpretability, this study proposes a glass-box architecture for trustworthy recommendation, designed to reconcile predictive performance with interpretability. The framework integrates interpretable tree ensemble model (Random Forest, XGBoost), an NLP sub-model for tag sentiment, prioritising transparency from feature engineering through to explanation. Additionally, a Reality Check mechanism enforces strict temporal separation and removes already-popular items, compelling the model to forecast latent growth signals rather than mimic popularity thresholds. Evaluated on the MovieLens dataset, the glass-box architectures demonstrated superior discrimination capabilities, with the Random Forest and XGBoost models achieving ROC-AUC scores of 0.92 and 0.91, respectively. These tree ensembles notably outperformed the standard Logistic Regression (0.89) and the neural baseline (MLP model with 0.86). Beyond accuracy, the design implements governance through a multi-layered Governance Stack: (i) attribution and traceability via exact TreeSHAP values, (ii) stability verification using ICE plots and sensitivity analysis across policy configurations, and (iii) fairness audits detecting genre and temporal bias. Dynamic threshold optimisation further improves recall for emerging items under severe class imbalance. Cross-domain validation on Amazon Electronics test dataset confirmed architectural generalisability (AUC = 0.89), demonstrating robustness in sparse, high-friction environments. These findings challenge the perceived trade-off between accuracy and interpretability, offering a practical blueprint for Safe-by-Design recommender systems that embed fairness, accountability, and auditability as intrinsic properties rather than post hoc add-ons. Full article

This article presents a comprehensive and intuitive analysis of the impact of packaging on diode performance and a two-step method for packaging parameter extraction. This is performed using a single forward bias point, one-port measurements and probe tips on a conventional printed circuit board (PCB). A PIN diode was used to validate the method, biased from reverse (−5 V) to forward (1.22 V) bias. Measurements were performed up to 27 gigahertz (GHz). The complete diode characterization process—from the design and the electrical modeling of the test fixture to the extraction of the unpackaged diode measurements—is detailed. The parameters of the package model were extracted, its effects were removed from the measurement, and the behavior of the unpackaged diode was determined. Three operating regions based on their radiofrequency and direct current (RF-DC) behavior were proposed, and an electrical model of the unpackaged diode was derived for each region. The results showed that the influence of the package caused the diode to remain in an unchanged behavior under different biases, indicating that it no longer rectified. The results presented herein are validated by the excellent correlation between the diode’s measured S-parameters, impedance, and admittance and their corresponding models. Full article

Background/Objective: To outline strategies for the safe clinical use of orthodontic temporary anchorage devices (TADs) by analyzing papers that examine associated risks, complications, and approaches for their prevention and resolution. Methods: The research protocol used PubMed, Medline, and Scopus up to May 2024, focusing on controlled and randomized clinical trials aligned with the review objective. Fourteen studies were included; bias risk was assessed, key data extracted, and a descriptive analysis performed. Study quality and evidence strength were also evaluated. Results: TADs optimize anchorage control without relying on patient compliance. However, they carry risks and complications. TAD contact with the periodontal ligament or root without pulp involvement requires removal for spontaneous healing. If pulp is involved, the TAD should be removed and endodontic therapy performed. If anatomical structures are violated, TAD should be removed. If transient, spontaneous recovery occurs, but sometimes pharmacological treatment may be needed. A 2 mm gap between the TAD and surrounding structures can prevent damage. In the maxillary sinus, a less than 2 mm perforation of the Schneiderian membrane recovers spontaneously; wider perforations require TAD removal. Good oral hygiene and TAD abutments prevent soft tissue inflammation, which resolves with 0.2% chlorhexidine for 14 days. Unwanted forces can cause TAD fractures, requiring removal. Minor TAD mobility due to loss of primary stability can be maintained; significant instability requires repositioning. Conclusions: The use of TADs requires meticulous planning, radiological guidance, and monitoring to minimize risks and manage complications. With proper care, TADs improve orthodontic outcomes and patient satisfaction. Full article

Objective: Accurate knowledge of apical morphology is crucial for determining the correct working length and achieving an optimal seal, both of which are vital for long-term endodontic success. This review summarizes and evaluates the current literature on the physiological foramen, focusing on its diameter and the distance between the anatomical apex and the physiological foramen. Materials and Methods: A systematic literature search was conducted using the databases PubMed (via Medline), Embase, LILACS, and Scopus. Studies addressing the anatomy of the physiological foramen were selected based on predefined inclusion criteria. A total of 743 records were identified. After removing 103 duplicates, the titles and abstract of 640 records were screened, with 625 being excluded as irrelevant. Fifteen full texts were assessed and six excluded for not meeting inclusion criteria. Five additional articles were found through manual search. In total, 14 studies were included in the review. The risk of bias was assessed using the AQUA tool. Results: Considerable variation in the diameter of the physiological foramen was observed across the included studies, ranging from 0.15 mm to 0.43 mm depending on tooth type and location. Additionally, the distance between the anatomical apex and the physiological foramen varied from 0.1 mm to 1.2 mm. Conclusions: The results demonstrate considerable heterogeneity in the dimensions and position of the physiological foramen, with oval shapes occurring more frequently than round or irregular ones. Standardized definitions and consistent terminology are essential to improve comparability across studies and to enhance the clinical applicability of research findings. Recognizing these anatomical variations optimizes endodontic treatment outcomes and minimizes procedural errors. Full article

Background/Objectives: Clear aligners (CAs) are a popular alternative to classical fixed appliances (FAs) for orthodontic treatment. This systematic review aimed to compare the external apical root resorption (EARR) in patients undergoing orthodontic therapy with either FAs or removable CAs. Methods: An electronic search was conducted to identify comparative studies. Risk of bias was assessed using the Cochrane RoB 2.0 tool for randomized controlled trials (RCTs) and the ROBINS-I tool for non-RCTs. EARR at the following incisors was considered: maxillary central (MxC), maxillary lateral (MxL), mandibular central (MdC), and mandibular lateral (MdL). A random-effects meta-analysis was performed, and mean differences were estimated. Results: Ten studies (one RCT, two prospective, and seven retrospective studies) were included. Four had a low risk of bias, four had a moderate risk, and two had a serious concern. In total, 286 patients (1476 incisors) and 289 patients (1487 incisors) in the CA and FA groups were considered, respectively. The mean follow-up was 22.7 ± 9.9 (standard deviation) in the CA group and 22.5 ± 8.2 months in the FA group. The meta-analysis found that CAs caused significantly less EARR than FAs for all tooth types except for MdL. On a patient basis, the mean difference (MD) in favour of CAs ranged from −0.64 mm (95% CI (confidence interval): −0.90, −0.38 mm) for MxC to −0.26 mm (95% CI: −0.43, −0.09 mm) in MdC. Heterogeneity across studies was generally high, except for MdC cases. Conclusions: EARR at incisor teeth is generally lower using CAs compared to FAs. Further evidence-based studies are needed to confirm these results and understand the clinical relevance of such a difference. Full article

Large Language Models (LLMs) are increasingly used for rubric-based assessment, yet reliability is limited by instability, bias, and weak diagnostics. We present EvalCouncil, a committee-and-chief framework for rubric-guided grading with auditable traces and a human adjudication baseline. Our objectives are to (i) characterize domain structure in Human–LLM alignment, (ii) assess robustness to concordance tolerance and panel composition, and (iii) derive a domain-adaptive audit policy grounded in dispersion and chief–panel differences. Authentic student responses from two domains–Computer Networks (CNs) and Machine Learning (ML)–are graded by multiple heterogeneous LLM evaluators using identical rubric prompts. A designated chief arbitrator operates within a tolerance band and issues the final grade. We quantify within-panel dispersion via MPAD (mean pairwise absolute deviation), measure chief–panel concordance (e.g., absolute error and bias), and compute Human–LLM deviation. Robustness is examined by sweeping the tolerance and performing leave-one-out perturbations of panel composition. All outputs and reasoning traces are stored in a graph database for full provenance. Human–LLM alignment exhibits systematic domain dependence: ML shows tighter central tendency and shorter upper tails, whereas CN displays broader dispersion with heavier upper tails and larger extreme spreads. Disagreement increases with item difficulty as captured by MPAD, concentrating misalignment on a relatively small subset of items. These patterns are stable to tolerance variation and single-grader removals. The signals support a practical triage policy: accept low-dispersion, small-gap items; apply a brief check to borderline cases; and adjudicate high-dispersion or large-gap items with targeted rubric clarification. EvalCouncil instantiates a committee-and-chief, rubric-guided grading workflow with committee arbitration, a human adjudication baseline, and graph-based auditability in a real classroom deployment. By linking domain-aware dispersion (MPAD), a policy tolerance dial, and chief–panel discrepancy, the study shows how these elements can be combined into a replicable, auditable, and capacity-aware approach for organizing LLM-assisted grading and identifying instability and systematic misalignment, while maintaining pedagogical interpretability. Full article

The development of AI systems and benchmarks has been rapidly increasing, yet there has been a disproportionately small amount of examination into the domains used to evaluate these systems. Most benchmarks introduce bias by focusing on a particular type of domain or combine different domains without consideration of their relative complexity or similarity. We propose the Artificial Intelligence Quotient (AIQ) framework as a means for measuring the similarity and complexity of domains in order to remove these biases and assess the scope of intelligent capabilities evaluated by a benchmark composed of multiple domains. These measures are evaluated with several intuitive experiments using simple domains with known complexities and similarities. We construct test suites using the AIQ framework and evaluate them using known AI systems to validate that AIQ-based benchmarks capture an agent’s intelligence. Full article

Modern electronic devices, such as smartphones and drones, integrate various sensors to enable diverse sensor-based applications. Yet, sensor measurements exhibit significant variations across different device models, even under the same environment. These variations arise from sensor biases, which occur in three different types: offset bias (additive constant errors), scale bias (multiplicative proportional errors), and drift bias (time-dependent or temperature-dependent errors). Among the biases, in this paper we specifically target offset bias, which has the greatest impact in typical smartphone usage scenarios. This generally leads to performance degradation in sensor-based applications across various device models and instances. To understand the characteristics of the offset bias, we categorize sensors into sensors with and without absolute reference values. Sensors with absolute references enable direct calibration using theoretical true values, while sensors with relative references require different approaches depending on how sensor applications process the data. For scalar-based applications that determine the current state by comparing a sensor measurement against a pre-defined reference, the offset biases can be removed by the existing procedures using reference devices. However, for sequence-based applications that determine the current state by analyzing relative changes in a sequence, the offset bias issue has not been addressed yet. We propose initial value removal and mean removal algorithms that statically and dynamically remove the offset biases from the sensor data sequences for these sequence-based applications. We evaluate our bias normalization algorithms for two different use cases in a geomagnetic-based indoor positioning system (IPS). First, we evaluate the impact of our bias normalization algorithms on the positioning performance of our LSTM-based IPS. Without bias normalization, although the reference device (Galaxy S23 Plus) showed an average positioning error of 0.6 m, the other three smartphone models (Galaxy S22 Plus, iPhone 15, and iPhone 16 Pro) exhibited much worse positioning performance, with errors of 2.48 m, 18.21 m, and 13.13 m. However, after applying our bias normalization, the average positioning errors of all models dropped below 0.68 m. Second, we also evaluate the impact of the bias normalization on detecting whether the position of a smartphone is in a pocket or in a hand-held state. For this, we analyze the sequence of light sensor measurements. We improved the detection accuracy from 42.3% to 97.6% with bias normalization across all device models without requiring individual threshold settings. Full article

Background/Objectives: Acquired sensorineural hearing loss (SNHL) can result from a wide range of insults, including ototoxic drugs, Meniere’s disease, noise-induced ototoxicity, and aging. The underlying pathophysiological mechanism arises through damage to the inner ear via oxidative stress and inflammation. Recent research suggests that natural antioxidants are promising solutions to prevent SNHL. Nigella sativa (NS), through its active compound thymoquinone (TQ), is a potent antioxidant that has shown promising results. The aim of this systematic review is to examine whether NS can offer protection against acquired SNHL. Methods: This study reviewed the literature on the protective effects of Nigella sativa oil (NSO) or TQ against acquired SNHL. We followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A comprehensive literature search was conducted across multiple databases using keywords related to NS and hearing loss. Meta-analyses were performed on eligible studies. Risk of bias was assessed using the Systematic Review Center for Laboratory Animal Experiments (SYRCLE) tool for animal studies. Results: Out of a total of 76 records, 38 duplicates were removed. From the remaining 38, 13 studies met the inclusion criteria. Multiple studies reported a significant protective effect of NS, especially against ototoxicity. The risk of bias across the studies was moderate. Conclusions: Preclinical evidence indicates that NS provides significant protection against acquired SNHL. These protective effects are attributed to their antioxidant, anti-apoptotic, and anti-inflammatory properties. Overall, our systematic review highlights NS as a promising candidate for preventing SNHL. Full article

This study investigates the impact of high-resolution spatiotemporal profiles of road transport emissions on urban air quality simulations for Thessaloniki, Greece. Dynamic spatiotemporal emission profiles were developed based on real vehicle speed data and implemented in an integrated air quality modeling system to improve the representation of temporal and spatial traffic activity patterns. The new profiles captured the variability of emissions across hours, days, and months, reflecting differences in congestion intensity and seasonal mobility behavior. Zero-out air quality simulations, in which road transport emissions were entirely removed from the model domain, revealed that road transport is a dominant source of urban air pollution, contributing by up to 47 μg/m³ to daily NO₂ and up to 15 μg/m³ to daily PM_2.5 concentrations during winter, while remaining significant in summer. The speed-based spatiotemporal profiles affected NO and NO₂ concentrations by up to +20 μg/m³ and +3.8 μg/m³, respectively, during the rush hours in winter. The use of dynamic spatiotemporal profiles improved model performance with a maximum daily BIAS reduction of –5 μg/m³ for NO and an increase in the index of agreement of up to 0.13 during the warm period, demonstrating a more accurate representation of traffic-related air pollution dynamics. Improvements for PM_2.5 were smaller but consistent across most monitoring sites. Overall, the study demonstrated that incorporating detailed traffic-derived spatiotemporal profiles enhances the accuracy of urban air quality simulations. The proposed approach provides valuable input for municipal action plans, supporting the design of effective traffic management and emission reduction strategies tailored to local conditions. Full article

Background: Whether nanoengineered titanium surfaces confer superior implant stability beyond modern microrough controls remains uncertain. Methods: This systematic review followed PRISMA 2020 guidance: comprehensive multi-database searching with de-duplication; dual independent screening, full-text assessment, and standardized data extraction for predefined outcomes (implant stability quotient [ISQ], mechanical anchorage by removal/push-out/pull-out torque, and histologic bone-to-implant contact). Risk of bias was appraised with RoB 2 for randomized trials, ROBINS-I for non-randomized clinical studies, and CAMARADES (animal experimentation). The certainty of clinical evidence was summarized using GRADE. Results: Across animal models, nanoengineered surfaces consistently improved early osseointegration indices (higher removal torque and bone-to-implant contact at initial healing). In clinical comparative studies, nanoengineered implants showed modest, time-limited gains in early stability (ISQ) versus microrough titanium. By 3–6 months, between-group differences typically diminished, and no consistent advantages were demonstrated for survival or marginal bone outcomes at later follow-up. Methodologic heterogeneity (surface chemistries, timepoints, outcome definitions) and small clinical samples limited quantitative synthesis. Overall, risk-of-bias concerns ranged from some concerns to high in non-randomized studies; the certainty of clinical evidence was low. Conclusions: Nanofeatured titanium surfaces improve early osseointegration but do not demonstrate a consistent long-term advantage over modern microrough implants. Current evidence supports an early osseointegration benefit without clear long-term clinical advantage over contemporary microrough implants. Adequately powered, head-to-head trials with standardized stability endpoints and ≥12-month follow-up are needed to determine whether early gains translate into patient-important outcomes. Full article

Background: The relative merits of the Henderson–Hasselbalch (HH) versus Stewart frameworks for interpreting dialysis-associated acid–base shifts remain debated. Dialysis alters systemic pH through exogenous bicarbonate delivery, chloride displacement, and removal of organic anions. We compared these approaches across hemodialysis (HD) and peritoneal dialysis (PD). Methods: We studied 53 HD patients with paired pre/post-HD blood gas and chemistry (106 observations) and 41 PD patients cross-sectionally, totaling 147 datasets. Derived variables followed the Figge/Stewart implementation [apparent SID (SIDa), effective SID (SIDe), strong ion gap (SIG), albumin-corrected anion gap (AGc)]. For HD, changes in pH (ΔpH) were modeled using HH predictors (ΔHCO₃⁻, ΔPCO₂) and Stewart predictors (ΔSIDa, ΔATOT, ΔPCO₂). For cross-sectional data (pre-HD, post-HD, and PD), HH- and Stewart-based level models were fitted. Stewart-predicted pH was also computed using the Figge and the simplified Constable electroneutrality equation. Results: HD increased pH by 0.11, driven by ΔHCO₃⁻ = +5.7 mΕq/L, ΔCl⁻ = −2.3 mEq/L, and declines in unmeasured anions (ΔSIG = −3.9; ΔAGc = −3.3). SIDa increased only marginally (+1.3 mEq/L), whereas SIDe rose by +5.3 mEq/L and fully tracked the alkalinization. In Δ-models, HH explained 90% of variance in ΔpH (R² = 0.903) compared with 51% for Stewart (R² = 0.514). In level models, HH explained 96% of pH variance versus 36% for Stewart. Bland–Altman analysis showed systematic overestimation of pH by the Figge and Constable approach (bias + 0.111), most pronounced pre-HD. PD patients had consistently higher AGc and SIG values than HD patients, indicating a greater burden of unmeasured anions. Conclusions: Alkalinization during HD is primarily attributable to bicarbonate gain, chloride displacement, and organic-anion clearance. The HH framework provides superior predictive performance for ΔpH, while closed-system Stewart formulations based on SIDa underestimate alkalinization. However, a broader physicochemical interpretation using SIDe and SIG, which incorporate bicarbonate and unmeasured anions, coherently describes the observed physiology. Future applications of the Stewart approach in dialysis should emphasize SIDe and SIG to better reflect the open-system physiology of both HD and PD. Our findings suggest that the HH model remains more predictive of alkalinization, while SIDe and SIG refine the physicochemical understanding. Full article