Search Results (732)

Background/Objectives: The training of diagnostic pancreatic pathologists is largely limited by the diversity of available pathology images, especially those of rare diseases or conditions. Methods: Using a cohort of seven pancreatic neoplasms, we developed an iterative, pathologist-in-the-loop workflow integrating scalable tile pruning, generative-model optimization, and postprocessing truncation. Two pathologists evaluated synthetic-image quality and subtype representation on a 0–3 scale; the independent pathologist was blinded to image source and truncation condition and also rated curated real training tiles. Results: Untruncated images had lower class-balanced FID than per-class-truncated images (6.64 versus 29.08) and higher recall and coverage, whereas truncation increased precision. The independent pathologist rated per-class-truncated images higher than matched non-truncated images (mean difference 0.80, bootstrap 95% CI 0.57–1.03). Quadratic-weighted Cohen’s κ was 0.599 (95% CI 0.489–0.691); after grouping ratings as 0–1 versus 2–3, raw agreement was 80.7% (95% CI 75.0–86.4%). Conclusions: Per-class truncation improved independently rated image quality and subtype representation. Successful synthetic histology generation requires careful data curation, domain-specific oversight, and independent validation; clinical utility requires separate task-based evaluation. Full article

This paper presents an analytical—mechanistic model for determining local friction and normal force components acting on the rake and flank surfaces during oblique cutting. The proposed formulation integrates the tool geometry by considering both the constructive angles of the cutting tool and the functional angles resulting from the cutting conditions, including cutting speed, feed rate, and depth of cut. The transformation from the oblique cutting coordinate system to the dynamometer reference system is performed using successive rotation matrices based on Euler angles. The model is formulated as a system of three equations with four unknown local force components $\left(F,F_N,F_{\alpha },F_{N\alpha }\right)$, which is analytically resolved by combining the measured cutting force components $\left(F_x,F_y,F_z\right)$ with an experimentally determined friction coefficient. The geometric direction parameters derived from the Euler angles enable the decomposition of the measured global forces into local friction and normal force components acting on the active tool surfaces. The model is further extended to functional geometry by accounting for changes in the effective tool orientation under actual cutting conditions. The internal consistency of the proposed formulation is supported through several particular cases, including orthogonal cutting and zero-angle geometry. Experimental validation was carried out using P20 carbide inserts and AISI 1045 steel. The obtained results showed good agreement between the analytically reconstructed force components, the measured cutting forces, and the friction coefficient values identified experimentally, supporting the applicability of the proposed model for local force evaluation in oblique cutting. Full article

Malachite green (MG), a triarylmethane dye extensively used in the textile and aquaculture industries, is a persistent aquatic contaminant with documented carcinogenic, mutagenic, and teratogenic effects even at trace concentrations. In the present work, a natural, low-cost Serpentine clay was surface-modified with copper oxide nanoparticles generated in situ through a green, lemon-extract-mediated reduction of copper nitrate, yielding a novel SER/CuO nanocomposite. The as-prepared adsorbent was characterized by FTIR, XRD, BET, and SEM to confirm the successful anchoring of CuO nanoparticles onto the Serpentine lattice. Batch adsorption experiments demonstrated that the removal of MG was governed by solution pH, adsorbent dose, contact time, and initial dye concentration, with maximum uptake obtained close to neutral pH, consistent with the point of zero charge (pH_pzc = 7.6) of the composite relative to the pKa (6.9) of the dye. Equilibrium data were described comparably well by the Langmuir and Freundlich isotherms at 25 and 55 °C, with a maximum monolayer capacity of 279.06 mg g⁻¹ at 25 °C, while kinetic analysis showed the closest statistical agreement with the Elovich model, pointing to an energetically heterogeneous, chemisorption-assisted process supported by a three-stage intraparticle-diffusion profile. The individual and combined effects of solution pH, adsorbent dose, and contact time on removal efficiency were systematically evaluated using a one-factor-at-a-time approach. Thermodynamic estimation from the two-temperature Langmuir constants indicated a spontaneous and exothermic, and entropy-favored adsorption process. The spent adsorbent was regenerated using dilute hydrochloric acid and retained appreciable efficiency over successive cycles. Comparison to previously reported adsorbents supported the competitiveness of SER/CuO in terms of capacity, cost, and simplicity of preparation, and a techno-economic appraisal supported the feasibility of scale-up. As a waste-valorization step, both the bare SER/CuO adsorbent and its MG-loaded form were evaluated as electrode materials for the urea oxidation reaction: MG loading raised the anodic current density from 143.10 to 176.46 mA cm⁻² at 1.0 M urea, nearly doubled the electrochemically active surface area (7.34 to 14.41 cm²), and lowered the charge-transfer resistance, while sustaining a higher stable current density (111 vs. 81 mA cm⁻²) over 3600 s of continuous operation demonstrating a promising route for coupling water remediation with energy recovery. Full article

University geospatial hubs support research dissemination, teaching, public data access, and community engagement, but their value depends on whether resources can be found, accessed, interpreted, integrated, and reused. This study evaluates 747 publicly listed items in North Carolina Central University’s CoDE Open Data Hub using FAIR principles as an interpretive framework and the Federal Geographic Data Committee Content Standard for Digital Geospatial Metadata (FGDC CSDGM) as the domain-specific measurement basis. Nineteen criteria were scored on explicit criterion-specific 0–2 rules using live ArcGIS item properties, formal metadata XML, and available layer properties. Discoverability was evaluated for a proportionally stratified sample of 153 items through exact-title, keyword, location, item-type, category-browsing, and click-depth tests. The equal-criterion benchmark averaged 28.57 of 38 (75.19%); equal FAIR-dimension weighting produced a mean of 73.26%, and 95.85% of items retained the same descriptive performance band. Independent rescoring of 50 stratified items produced 76.74% exact criterion-level agreement, a linear weighted Cohen’s kappa of 0.587, and an absolute-agreement ICC of 0.715 for total scores. FAIR-aligned scores were highest for Findability (87.25%) and Accessibility (85.96%), followed by Reusability (67.26%) and Interoperability (52.59%). Exact-title and item-type searches retrieved all sampled items, while keyword search was successful for 88.24%. The results distinguish public availability from technical reuse readiness and identify spatial reference, attribute definitions, lineage, limitations, category structure, and navigation depth as priorities. The performance bands are study-specific descriptive summaries rather than FGDC compliance levels or FAIR certification. The study provides an evidence-preserving, type-aware method for applying FAIR principles alongside geospatial metadata standards in heterogeneous ArcGIS Hub catalogs. Full article

Long-term GEO satellite operation requires reliability models that distinguish full mission capability from degraded but still functional states and from critical functional loss. This study develops a five-state Markov reliability model in which states S0–S4 represent successive levels of mission capability. The model integrates sequential degradation, a direct S0 → S4 transition representing sudden critical events, and functional restoration associated with redundancy, FDIR, reconfiguration, and software-supported recovery. Four computational variants were analysed over a segmented 15-year mission horizon to separate the influence of these mechanisms. The transition intensities were specified for a reference scenario rather than estimated for a specific GEO mission. Full and retained mission capability were evaluated using R_full = P₀ and R_partial = 1 − P₄. For the complete model, these measures reached 0.6926 and 0.9633 after 15 years, respectively. Calculations performed in MATLAB 2025 using the matrix exponential method were independently verified by numerical integration, with agreement within approximately 10⁻¹⁴. The framework provides a reproducible basis for analysing long-term GEO satellite functional reliability under different degradation and restoration scenarios. Full article

Aircraft stands impose asymmetric spatial and procedural constraints that cannot be represented by geometric free space alone. This study proposes a Structured Operation Corridor for unmanned ground support equipment (SOC-UGSE), which converts existing stand markings, aircraft-side boundaries, and operating rules into machine-interpretable corridor constraints and corridor-specific actions. The framework distinguishes a detour-permitted Longitudinal Transfer Corridor (LTC-UGSE) from a no-detour Lateral Service-Approach Corridor (LSAC-UGSE), and maps object class, motion state, distance, corridor occupancy, and available clearance to Normal, Warning, or Stop responses. Standard vision, ranging, LiDAR, and temporal-processing modules are used only to instantiate these decision variables. On a controlled 1:10-scale platform, the implemented perception chain achieved an overall corridor-perception success of 83.9%, while frame-level agreement with rule-derived reference states reached 90.95%. Across 63 independent interaction sequences, sequence-level success was 95.2%, with no complete missed-stop event or prohibited boundary crossing. In a separate balanced comparison of 150 sequences, SOC-UGSE achieved the highest overall scenario-response compliance of 94.7%, outperforming distance-only stopping and corridor-free obstacle avoidance by reducing unnecessary stops and prohibited actions, respectively. These results support the structured-corridor rule-execution concept under controlled scaled-platform conditions, rather than full-scale operational safety or deployment readiness. Full article

Background/Objectives: Scabies, caused by Sarcoptes scabiei, is a recognised neglected disease of rising global burden, and increasing resistance to first-line scabicides is making treatment failure more frequent. No dermoscopic marker of cure has been validated for monitoring treatment response, so a reliable marker of active infestation is crucial. The tunnel window sign (TWS)—rounded perforations along the burrow, visible under polarised dermoscopy and ultraviolet-induced fluorescence dermoscopy (UVFD)—is a recently introduced candidate. We aimed to determine whether TWS represents a dermoscopic marker of active scabies infestation by evaluating its specificity, treatment dynamics and diagnostic performance under polarised dermoscopy and UVFD. Methods: In this single-centre observational study conducted in 2026, 33 patients with active scabies (Cohort 1; 106 burrows in 30 permethrin–ivermectin-adherent and 11 in 3 non-adherent) and 30 controls with excoriated pruritic dermatoses (Cohort 2; 150 lesions) were examined. All Cohort 1 patients were re-evaluated every 4 weeks until resolution. Paired polarised/UVFD images were re-scored by four raters (three blinded). Results: TWS was undetectable in all 30 controls with pruritic dermatoses and in all 30 post-treatment adherent patients (0/30 and 0/30, respectively). It resolved with effective treatment (undetectable from week 4; McNemar p < 0.0001), preceding pruritus resolution, and persisted in non-adherent patients until retreatment. At the burrow level, UVFD detected TWS more sensitively than polarised dermoscopy (68/106 vs. 60/106; p = 0.0078; adjusted OR 1.38, 95% CI 1.07–1.79). Inter-rater agreement was almost-perfect (Fleiss’ κ = 0.872). Conclusions: TWS behaves as a dermoscopic marker of active scabies infestation: it disappears after successful treatment, persists following treatment failure, and distinguishes active infestation from both post-treatment skin and non-scabietic pruritic dermatoses. UVFD improves its detection compared with polarised dermoscopy. Full article

Background/Objectives: Accurate selection of stainless steel crown (SSC) size is essential for successful restoration of primary molars. Conventional crown selection relies on a trial-and-error approach, which may increase chair time and reduce clinical efficiency. Preoperative digital radiographic measurements may provide an objective adjunct for predicting SSC size; however, evidence supporting their agreement with clinically selected crown sizes remains limited. This study aimed to evaluate the agreement between preoperative digital radiographic measurements and clinically fitted SSC size in primary molars, and to assess whether this agreement is influenced by dental arch or tooth type. Methods: This retrospective cross-sectional study analyzed archived patient records and preoperative digital radiographs of pediatric patients who received SSCs on primary molars. Mesiodistal tooth dimensions were measured and converted to SSC sizes according to manufacturer guidelines. The clinically fitted and cemented crown size, as recorded in the patient chart, served as the reference standard against which radiographically predicted size was compared. Intra-examiner reliability was assessed using the intraclass correlation coefficient. Associations were analyzed using chi-square tests and binomial logistic regression (p ≤ 0.05). Given repeated teeth within patients, the primary logistic regression model was additionally re-fit using generalized estimating equations (GEEs) with an exchangeable working correlation structure and robust standard errors, and prediction error was further characterized using near-miss accuracy, direction of bias, weighted kappa, and Bland–Altman analysis. Results: A total of 152 primary molars from 71 patients were included. Intra-examiner reliability was excellent (ICC = 0.99). Radiographic prediction agreed with the clinically fitted crown size in 33.6% of cases, and 69.7% of predictions fell within one crown size of the cemented crown. Agreement was significantly higher for mandibular molars than maxillary molars (p = 0.010) and varied by tooth type (p < 0.001). Mandibular molars were more likely to show accurate prediction (OR = 2.52; 95% CI: 1.23–5.17); this association remained statistically significant after accounting for within-patient clustering using GEEs with an exchangeable correlation structure (OR = 2.46; 95% CI: 1.10–5.49; p = 0.029). Maxillary first molars showed a systematic under-prediction of exactly two crown sizes in 97% of cases (mean bias −2.00), identifying a specific, correctable calibration problem. Conclusions: Preoperative digital radiographic measurements show moderate agreement with clinically fitted crown size and may serve as a useful adjunct to clinical judgment for SSC size selection, particularly for mandibular molars. Because the reference standard reflects clinical judgment itself rather than an independent anatomical gold standard, these findings should be interpreted as a concordance analysis, and further prospective work is needed before efficiency benefits can be confirmed. Full article

Background: Delayed onset of lactogenesis II or delayed secretory activation, defined as milk onset > 72 h postpartum, is a recognized barrier to successful breastfeeding initiation and duration. Prenatal identification and screening for risk factors associated with delayed secretory activation remains underutilized in maternal–child health services. This project aimed to develop and validate content for the Prenatal Evaluation and Referral for Lactation (PEARL) tool, a prenatal screening and referral instrument designed to identify lactation risk factors and guide anticipatory counseling and early referral to an International Board Certified Lactation Consultant (IBCLC) or breastfeeding medicine physician. Methods: Tool development was informed by a structured literature review conducted on 2 October 2024, across four databases (CINAHL, PubMed, Scopus, and Embase), identifying clinical and other health factors associated with delayed lactogenesis II. A three-round Delphi process was used to establish content validity through multidisciplinary expert consensus. Item-level content validity (ICV) was evaluated using a predefined consensus threshold (≥0.80), while average-measures Intraclass Correlation Coefficients (ICC) were calculated as a complementary assessment of interrater consistency. Following tool refinement, a pilot implementation training was conducted to obtain preliminary feedback regarding clarity, usability, and implementation. Results: Twelve lactation experts were selected from 59 eligible respondents to participate in the Delphi process. Most of the proposed items achieved the predefined content validity threshold (ICV ≥ 0.80) across the first two Delphi rounds, resulting in refinement and consensus on the final PEARL instrument. Interrater reliability improved from moderate agreement in Round 1 (ICC = 0.769; 95% CI 0.425–0.953) to excellent agreement following refinement in Round 2 (ICC = 0.911; 95% CI 0.787–0.979). Qualitative feedback informed revisions to item wording, organization, and content. A pilot implementation training indicated that the tool was perceived as understandable, usable, and appropriate for prenatal practice. Conclusions: The PEARL demonstrated strong evidence of content validity and preliminary implementation feasibility as a standardized prenatal lactation screening tool. Future research should evaluate additional psychometric properties, implementation outcomes, and prospective clinical performance to determine its effectiveness in improving referral practices and breastfeeding outcomes. Full article

Modern out-of-order processors depend critically on TAGE family branch predictors, which often struggle with context-fragile branches whose outcomes are highly sensitive to slight perturbations in the most recent global history. Existing predictors are confined to single-path factual reasoning and lack any mechanism to explicitly probe the local stability of a prediction. We formalise this limitation from an information entropy perspective: a context-fragile branch corresponds to a high conditional entropy region in the joint space of recent history bits and branch outcomes, where a single bit flip in the youngest history can shift the posterior branch probability across the decision boundary. To address this, we propose Mirror-TAGE, a lightweight microarchitectural framework that integrates counterfactual stability modeling with replay-guided selective overrides. Building on a TAGE-SC-L baseline following Seznec, Mirror-TAGE injects controlled bit-level perturbations into the youngest global history bits to construct two mirrored views, screened by an entropy-based reliability filter. We define a local prediction entropy, derive an information-theoretic characterisation of override correctness via DRT-filtered agreement, and decompose uncertainty into aleatoric and epistemic components. Under a paired causally consistent learning framework on synthetic workloads isolating the context-fragile regime, Mirror-TAGE achieves a 0.82 pp gain (66% override correctness, 7.5% overhead). Of successful overrides, 78% occur at entropy > 0.85 bits, consistent with the entropy-guided criterion, though partly driven by the entry gate design. Six SPEC CPU 2017 traces confirm no accuracy degradation, with gains of up to 0.38 pp. These results support entropy-guided counterfactual stability modelling as a promising branch prediction paradigm. Full article

Compliant muscle–tendon mechanics can improve terrain adaptation in musculoskeletal robots, but heterogeneous terrains impose competing requirements on compliance, propulsion, foot clearance, and support transfer. This paper proposes Value-Gradient Generalist Design (VGGD), a framework for selecting one fixed physiological muscle–tendon parameterization for cross-terrain locomotion while preserving skeletal topology and muscle routing. VGGD searches a compact PCA-based manifold that coordinates bounded scale factors for muscle strength, contraction-velocity capacity, and passive elastic response. A design- and terrain-conditioned value proxy is learned from sampled latent designs and then optimized by proximity-regularized projected value-gradient ascent under a soft-worst objective. Independent proxy validation uses 50 random designs solely for calibration and 100 separately sampled test designs excluded from fitting and Stage-B optimization. On the 100-design test set, the proxy shows positive agreement with mean cross-terrain return (Pearson $r=0.580$, Spearman $\rho =0.565$) and worst-terrain return ($r=0.583$, $\rho =0.551$), with all bootstrap intervals above zero and Holm-adjusted permutation $p=0.0006$. A separate paired local-direction test uses 60 previously unused evaluation seeds and equal feasible-space perturbation radii; at the nominal, midpoint, and selected designs, the proxy-gradient direction agrees with improvements in mean and seed-wise worst-terrain rollout return. After design selection, the muscle–tendon parameters are fixed, and a terrain-aware controller is trained with variational information-bottleneck regularization and auxiliary expert distillation. Checkpoint-resolved evaluation records identify 216/300 successes and an overall mean distance of 12.14 m for the complete pipeline, compared with 57/300 and 6.20 m for nominal-body PPO. The three checkpoint success rates are 84%, 78%, and 54% for Proposed and 49%, 0%, and 8% for PPO; exact two-sided policy-level permutation tests yield $p=0.10$ for success rate and $p=0.20$ for mean distance. All methods receive the same nominal 100-million-step final-controller budget per training run, while the 10 M Stage-A budget and expert-pretraining costs are reported separately. Full article

Objectives: To evaluate the inter- and intra-observer reliability of three methods for measuring root canal curvature and the reliability of canal visibility ratings on periapical radiographs over repeated calibration rounds. Materials and Methods: A total of 360 clinical periapical radiographs were divided into six batches and independently evaluated by three observers. Root canal curvature was measured using the Schneider, Weine, and a novel tangency-based method, while canal visibility was classified on a three-category scale. Inter- and intra-observer reliability were assessed using intraclass correlation coefficients (ICC). Agreement between observers was evaluated using Bland–Altman analysis, and differences between measurement methods were compared using repeated-measures analysis. The association between canal visibility and inter-observer measurement differences was assessed using Spearman rank correlation. Results: Inter-observer reliability for curvature measurements was predominantly good to excellent across all methods, with no consistent improvement over successive calibration rounds. Intra-observer reliability, assessed in one observer, was excellent (ICC 0.90–0.97). Measurement method significantly influenced angle values, with the Weine method producing larger angles than the Schneider and tangency-based methods, whereas the latter two showed comparable results. Agreement on canal visibility remained fair to moderate, and reduced canal visibility showed a weak but significant association with greater inter-observer differences in curvature measurements. Conclusions: All three methods demonstrated comparable inter-observer reliability, although the Weine method yielded systematically larger curvature angles. Agreement did not consistently improve over repeated calibration rounds. Reduced canal visibility may increase measurement variability and should be considered when interpreting root canal curvature on periapical radiographs. Full article

Large language models are increasingly used for automated grading, but final-score agreement does not reveal whether credit is assigned to the rubric element affected by a response change. This study introduces CreditTrace-LLM, a controlled framework for auditing directional responsiveness, credit locality, paraphrase stability, and correspondence with expert evaluations in rubric-guided grading. The evaluation used 500 response families across ten questions, equally divided between technical and argumentative tasks. Each family included a baseline response (C0), a positive intervention adding rubric-relevant evidence (C+), a negative intervention removing or weakening such evidence (C−), and a placebo paraphrase (CP) constructed through lexical or syntactic reformulation with the intention of preserving rubric-relevant meaning. Eight local open-weight LLM graders produced 15,999 structurally valid Gold-point-level outputs from 16,000 expected evaluations. Targeted Gold-point scores changed in the expected direction in 75.7% of C+ comparisons and 50.2% of C− comparisons. Localized directional success was lower under C+ and C−, at 31.5% and 21.3%, respectively, indicating frequent non-target score changes. Under CP, total-score stability was 75.4%, while complete-profile stability was 73.6%. Direction concordance with the mean expert score change was 69.8% for C+, 47.4% for C−, and 18.2% for CP. The CP condition also showed substantial variability in expert scoring, particularly for argumentative responses, indicating that intended rubric-relevant meaning preservation did not guarantee score invariance. Final-score behavior alone is insufficient for validating rubric-guided LLM grading. CreditTrace-LLM therefore evaluates target responsiveness, credit locality, paraphrase stability, and traceable Gold-point-level outputs as complementary diagnostic dimensions rather than as predefined criteria for acceptable grading performance. Full article

This article presents analytical approaches for determining the stress state in hypotrochoidal profiles (H-profiles) under torsional, bending, and shear loading. The focus lies on shear loading. Using conformal mapping, a formulation of elasticity theory is first adapted to H-profile cross-sections. Closed-form solutions for the respective stress components are then derived by solving a reformulated surface integral. Suitable conformal mappings for hypotrochoidal contours are obtained through a successive method applied to their parametric description. These mappings are essential for the elasticity-theoretical formulation used to determine the stress state in the profile bar. Building on this, the transverse shear stresses for H-profile cross-sections are determined for the first time. The influence of shear stresses on the overall stress state is discussed in detail. These stresses generally act in a rotational manner and superimpose on the torsional stresses. This effect proves more pronounced here than in circular cross-sections. Accompanying finite element analyses (FEA), carried out for several examples, showed very good agreement with the analytical solutions. From the resulting maximum stress values and stress gradients, form and notch factors are calculated. The proposed procedure also applies to combined loading cases. It is intended for use in the new standard covering hypotrochoidal profile contours. Full article

Robotic bin-picking of disordered, randomly stacked workpieces remains challenging because reliable grasping depends on an accurate estimate of object pose, yet many established solutions require high-precision 3D sensing, detailed object models, or large annotated datasets that raise the cost and effort of deployment on a new production line. This work presents a complete binocular vision framework that estimates workpiece pose by image matching and executes vision-guided grasping on a 6-DOF manipulator. A pose-annotated multi-view template library is constructed automatically through robot-driven image acquisition and compressed by a coarse-to-fine clustering scheme, and object pose is estimated by discriminative template matching with rigid refinement. To characterize the geometric reliability of the matched poses, an offline cross-modal analysis relates the 2D templates to a 3D reference model of the object and measures their agreement through region and contour reprojection metrics. Grasp configurations are then generated under orientation and collision constraints and corrected online by closed-loop visual feedback. Experiments on two representative workpieces show template-matching accuracy of 89–90% against classical and learned similarity measures, and grasp success between 81 and 87% across single-object and mixed scenes, outperforming the GraspNet baseline under the tested conditions. The framework offers an accurate and deployment-friendly route to robotic bin-picking. Full article