Search Results (142,484)

Although existing Chinese word segmentation systems have achieved substantial progress on standard benchmarks, prediction disagreements among heterogeneous models remain prevalent when processing texts containing complex ambiguities and out-of-vocabulary words, and traditional static ensemble methods such as majority voting often fail to make reliable decisions in low-consensus scenarios. To address this issue, this paper proposes SegFusion, a stacked heterogeneous ensemble framework for Chinese word segmentation based on word lattice re-scoring. The framework first constructs a candidate word lattice to consolidate diverse outputs from heterogeneous segmenters into a unified lattice representation, and then incorporates unsupervised statistical features, including mutual information and branching entropy, as external discriminative evidence to perform dynamic arbitration at the word level, followed by global decoding to obtain the optimal segmentation path. Experimental results on multiple standard datasets demonstrate that SegFusion consistently outperforms individual models and mainstream ensemble baselines in terms of overall segmentation performance and out-of-vocabulary (OOV) recall. In particular, on the MSR dataset with severe ambiguity, SegFusion achieves improvements of 3.71% in F1 score and 4.10% in OOV recall. Further fine-grained analysis shows that the introduction of unsupervised statistical features effectively mitigates model consistency bias in low-support scenarios. These results indicate that integrating language statistical priors independent of training data into the ensemble arbitration stage is an effective way to enhance the robustness and consistency of Chinese word segmentation systems. Full article

Evaluating the vertical bearing capacity of offshore wind turbine pile-ring composite foundations under complex marine environmental loads is critical for ensuring engineering safety. This study employs the rigorously validated T-EMSD upper-bound method to conduct a three-dimensional numerical analysis of the vertical bearing capacity of pile-ring composite foundations in saturated clay. It systematically investigates the influence of soil homogeneity ($\eta$, diameter ratio (D/B), embedment ratio (L/B), and external shaft friction coefficient ($\alpha$) on the bearing capacity factor $N_c$, and reveals the associated failure mechanism through velocity field analysis. The results indicate that the bearing capacity factor $N_c$ increases significantly with the diameter ratio D/B. The system exhibits optimal bearing performance when the pile shaft friction is fully mobilized ($\alpha$ = 1) in homogeneous soil ($\eta =1$). Moreover, as the embedment ratio L/B increases, the plastic zone extends downward along the pile shaft, enhancing the deep foundation effect. Based on parametric analysis, a predictive formula for the net bearing capacity factor of the pile-ring composite foundation under homogeneous conditions is established. Verified against existing numerical methods and experimental data, the formula demonstrates an error margin within ±5%, indicating its good suitability for engineering applications. Furthermore, by establishing a ratio relationship, the net bearing capacity factor under heterogeneous conditions is correlated with that under homogeneous conditions. This enables a more in-depth analysis of the influences of soil strength heterogeneity and external shaft friction coefficient on the vertical bearing capacity of the pile-ring composite foundation. The work presented in this paper provides a theoretical basis for the design and bearing capacity assessment of this type of composite foundation. Full article

A/T(U) and G/C nucleobase pair formation in DNA and RNA is crucial to numerous fundamental biological processes, including replication, transcription, and translation. The specificity of A/T(U) and G/C base pairing is used for the recognition of complementary sequences in medical and biotechnological applications, such as PCR, nucleic acid drugs, and CRISPR–Cas9-based gene editing. It is essential to understand and predict fidelity of biological reactions, avoiding off-target binding, in order to improve the accuracy and efficacy of applications. In particular, recognition mechanisms of complementary bases or whole sequences must be understood in detail. Despite the prevailing view that Watson–Crick hydrogen bonding is a primary mechanism for complementary base recognition, several experiments have shown that DNA polymerase does not require hydrogen bonding to select complementary bases. Other factors, such as the shape and geometric fitting of the bases and the base stacking, also appear to be crucially involved in the selection. E.g., artificial bases lacking the ability to form hydrogen bonds can still be recognized by DNA polymerase solely based on base-pair geometry. However, hydrogen bonding also contributes importantly to recognition. The accuracy of selecting a complementary nucleobase or sequence varies depending on reactions, suggesting the co-existence of multiple selection mechanisms. This review provides an overview of biological processes and applications involving base pairing and discusses the molecular mechanism underlying complementary base recognition. Full article

Background/Objectives: A widespread assumption exists among scientists, health care providers, and the public that later life is a time of inevitable and universal cognitive and physical decline. This assumption is likely due to considering older persons who improve to be exceptions, and the reliance on aging-health measures that do not allow for improvement. In contrast, we utilized a measure that allowed for an upward trajectory to occur. Our objective was to examine whether a meaningful number of older persons improve with this measure and, if so, to examine whether a promising modifiable culture-based variable, positive age beliefs, contributes to this improvement. Methods: Individuals 65 years and older, who participated in a nationally representative longitudinal study, had their physical health assessed by walking speed and their cognitive health assessed by a global performance measure. We calculated the percentage of the sample that showed improvement in each domain from baseline to the last measurement up to 12 years later. We also examined whether a positive-age-belief measure predicted this improvement in regression models. Results: It was found that 45.15% of persons improved in cognitive and/or physical function over this period, and positive age beliefs predicted these two types of improvement, both with and without adjusting for relevant covariates. Conclusions: Our findings underscore the need to instill or magnify the positivity of age beliefs and to redefine aging so that it includes the possibility of improvement. Full article

Background: Individuals with type 2 diabetes mellitus (T2DM) are at markedly increased risk of developing coronary heart disease (CHD); however, the generalizability and transportability of existing prediction models remain uncertain. Objective: To identify and evaluate multivariable prognostic models developed to predict CHD in adults with T2DM. Methods: We conducted a PRISMA-guided systematic review and meta-analysis of multivariable prognostic models predicting CHD in T2DM populations. Model characteristics and performance metrics were extracted following the CHARMS and TRIPOD-SRMA frameworks, and pooled discrimination was estimated on the logit-transformed AUC scale using a random-effects model (REML, Hartung–Knapp adjustment). Between-study heterogeneity and 95% prediction intervals were quantified, while risk of bias and applicability were assessed using the PROBAST tool. Results: Thirteen studies encompassing clinical, imaging-based, and omics-augmented models met the inclusion criteria. The pooled AUC was 0.69 (95% CI: 0.66–0.71), with high heterogeneity (I² = 97.4%; τ² = 0.0979) and a wide 95% prediction interval (0.54–0.81). Classical regression-based models demonstrated modest discrimination, whereas machine learning, imaging, and proteomic approaches achieved higher AUC estimates but were frequently constrained by small sample sizes, internal-only validation, and poor calibration reporting. The analysis domain emerged as the principal source of bias in PROBAST evaluations, and applicability issues were most frequent in models requiring advanced imaging or molecular platforms. Conclusions: Prognostic models for CHD in T2DM demonstrate moderate-to-good discrimination but substantial heterogeneity and frequent miscalibration across studies. Their clinical utility depends on rigorous external validation and local recalibration, particularly when incorporating imaging or molecular predictors. Future research should prioritize standardized CHD outcomes, consistent calibration reporting, decision-analytic assessments, and the development of transportable multimodal prediction models across diverse populations. Full article

Background: The Temporomandibular Joint Ankylosis Quality of Life Questionnaire (TMJAQoL) is a disease-specific instrument designed to assess quality of life in patients with temporomandibular joint (TMJ) ankylosis. No validated Turkish version of this scale existed prior to this study. The aim of this study was to translate, culturally adapt, and evaluate the Turkish version of the TMJAQoL (TMJAQoL-TR) in patients with severe temporomandibular disorders, including a predefined ankylosis subgroup. Materials and Methods: A total of 120 patients with temporomandibular complaints were included. Test–retest reliability was evaluated in a clinically stable subsample of 72 participants with a one-week interval. Following forward–backward translation and cultural adaptation procedures, the TMJAQoL-TR was administered together with the Oral Health Impact Profile Short Form-14 (OHIP-14), the Short Form-36 (SF-36), and Visual Analog Scale (VAS) pain scores. Reliability was assessed using Cronbach’s α, item-level Weighted Cohen’s Kappa, and test–retest Intraclass Correlation Coefficients (ICC), supported by measurement error indices (Standard Error of Measurement [SEM] and Minimal Detectable Change at 95% confidence [MDC₉₅]). Construct validity was examined using Spearman correlation coefficients. Structural validity was investigated through exploratory factor analysis, followed by a confirmatory structural model in AMOS to evaluate preliminary model consistency. Floor and ceiling effects were analyzed using the 15% criterion. Results: The TMJAQoL-TR demonstrated excellent internal consistency (Cronbach’s α = 0.879) and very high test–retest reliability (ICC = 0.995; 95% CI: 0.992–0.997). Strong correlations were observed with OHIP-14 (r = 0.772, p < 0.01), and moderate correlations with VAS pain scores (r = 0.312, p < 0.01). No significant floor or ceiling effects were detected. A weak but significant negative correlation with the SF-36 physical role subscale suggests that TMJ-related quality of life impairment is associated with role limitations in daily activities, although the magnitude of this association was modest. Exploratory factor analysis supported a clinically coherent two-factor structure, and the AMOS structural model demonstrated acceptable consistency with this framework. Conclusions: The TMJAQoL-TR appears to be a valid and reliable instrument for assessing quality of life in patients with severe TMJ-related functional limitations. Findings from the ankylosis subgroup support potential applicability within the instrument’s original target population; however, further validation in larger ankylosis-specific samples is warranted. Full article

In this paper, we study the cyclicity of binary group codes, identifying them as ideals in a group algebra. We focus on the construction of $\omega |\overline{\omega }$ codes, proving that they are self-dual group codes over the abelian group $C_2\times C_k$. We demonstrate that for even integers $k>2$, if the polynomial $x^k-1$ splits into self-reciprocal irreducible factors, these codes are not permutationally equivalent to any cyclic code. Additionally, we present computational results for binary group codes of length $n<24$ using the MAGMA software (V2.29-4). These results confirm that while all cyclic codes in this range are equivalent to abelian group codes, there exist non-cyclic group codes that cannot be realized as ideals in a cyclic group algebra, highlighting the strictly larger scope of the class of group codes. Full article

This study addresses high water cut and low recovery in bottom-water sandstone reservoirs by optimizing CO₂ and N₂ foam flooding parameters. The key innovation is the pioneering application of fractal dimension to quantitatively characterize water coning morphology during composite gas flooding. A numerical simulation assessed composite gas type, injection gas ratio, sequence, speed, volume, and injection–production ratio. Fractal dimension quantified water coning. Optimal conditions were: 2:1 injection gas ratio (CO₂ then N₂ foam), 140 t/d injection speed, 0.31 PV volume, and 1:3.2 injection–production ratio. This achieved 39.52% recovery over 15 years—a 4.89% increase, adding 3.17 × 10⁴ t of oil. Fractal dimension fell to 1.672. Sensitivity analysis showed the injection gas ratio most affects oil output. The injection volume best suppresses water coning. The injection speed has low sensitivity. Key interactions exist between volume, gas type, and injection–production ratio. Injection gas ratio, volume, and injection–production ratio are crucial for development control. The proposed methodology presents a viable strategy for enhancing oil recovery in similar reservoirs, with broader implications for advancing CO₂ utilization and supporting carbon management objectives in the petroleum industry. Full article

Background/Objectives: Gastrointestinal (GI) manifestations may persist in COVID-19 survivors, potentially worsening pre-existing conditions and increasing the risk of malnutrition. Understanding the long-term association between GI symptoms and nutritional risk is essential. This study aimed to investigate this relationship in COVID-19 survivors, regardless of comorbidities. Methods: A retrospective cohort study with prospective follow-up was conducted among 103 adults (52 males and 51 females) with PCR-confirmed COVID-19 admitted to King Salman Specialist Hospital, Ha’il, Saudi Arabia, between January 2021 and January 2023. Participants were grouped based on the presence of comorbidities, mainly type 2 diabetes mellitus (DM) and hypertension (HTN), and GI symptoms. Demographic characteristics, COVID-19 severity, and clinical data were obtained from medical records and structured interviews. Nutritional risk was assessed using the Malnutrition Screening Tool (MST). Statistical analysis was performed using Chi-Square tests, with p < 0.05 considered significant. Results: Over a mean follow-up of 26.6 months, 40.8% of participants reported at least one persistent GI symptom. Patients with comorbidities were older than those without comorbidities (mean age 58.24 ± 13.23 vs. 48.22 ± 14.83 years), and malnutrition risk was commonly observed in both groups during hospitalization and follow-up. The most frequently reported symptoms were abdominal pain (15.5%), diarrhea (12.6%), appetite loss (9.7%), and vomiting (7.8%), with no significant differences between groups. GI symptoms were significantly associated with reduced food intake, weight loss, and increased malnutrition risk (p < 0.05). Conclusions: Some COVID-19 survivors reported persistent GI symptoms during long-term follow-up, with no significant differences based on comorbidity status. GI symptoms were associated with nutritional risk and lifestyle changes, supporting the need for nutritional screening in post-COVID-19 care. Full article

Stator short-circuit faults (SSCFs) account for a significant portion of induction motor failures, yet their early detection remains a challenge in industrial environments where labeled fault data is scarce and installing additional sensors is often impractical. This paper proposes a novel, data-driven fault detection and diagnosis framework grounded in the Residual Information Value (RIV) principle to overcome reliability limitations of traditional spectral and residual energy methods. By redefining fault detection as a statistical test of independence between control inputs (voltages) and current residuals, the proposed method identifies incipient faults as model drifts without relying on prior knowledge of fault distributions. A key contribution of this work is the seamless integration of the diagnostic scheme into standard Variable Speed Drives (VSDs): the healthy nominal model (a Multilayer Perceptron) is trained exclusively using data from the drive’s existing self-commissioning routine, eliminating the need for manual data collection or complex physical parameter identification. Experimental validation on an industrial test bench demonstrates that the framework achieves superior diagnostic performance compared to traditional baselines, providing higher statistical separability and a reduced false alarm rate. The system can detect 1% incipient faults in approximately 61 ms while accurately identifying the faulty phase. The results confirm that the proposed RIV-based strategy offers a robust, non-intrusive, and industry-ready solution for predictive maintenance that effectively balances high-speed detection with enhanced statistical reliability. Full article

Performance of Osmia bicornis larvae fed on six diets with different pollen species composition (one wild collected by foraging adults), each with known levels of nine essential amino acids (EAA; leucine, lysine, valine, arginine, isoleucine, phenylalanine, threonine, histidine, methionine), was investigated. Four of the pollen diets consisted of individual pollen species and two were mixtures of either four or five species (including one naturally foraged by adult O. bicornis). The diets fell into four statistically distinct groups with different EAA contents (ranked from Group I (highest EAA) to Group IV (lowest EAA; pine pollen). The highest larval survival rate was recorded with the wild-foraged diet (Group III) with no survival in Group IV. Similar survival occurred for all other diets. Where larvae survived (Group I–III), there was no effect of diet on the time to commencement of larval stages, cocoon completion or larval development time (egg hatch to pupation), or on pupal weight. The findings provide corroborative evidence of the existence of amino acid thresholds for larval success, but the need for further work is discussed in relation to their multidimensional nutritional requirements and variation of the nutritional content of pollen. Full article

This paper presents the notion of primal weak structures as a generalized mathematical framework obtained by relaxing the axioms of classical topological spaces. We formally define primal weak structures and provide a detailed investigation of their fundamental properties. Particular attention is given to the operator $c_{\mathit{w}}^{\diamond }$, whose essential characteristics and related properties are analyzed to obtain a comprehensive characterization of primal weak structures. Furthermore, we introduce new constructions denoted by $\sigma (\mathit{w},\mathcal{P})$, $\pi (\mathit{w},\mathcal{P})$, $\beta (\mathit{w},\mathcal{P})$, and $\alpha (\mathit{w},\mathcal{P})$, and demonstrate that they generate generalized primal topological spaces. These results establish a unifying connection between primal weak structures and existing generalized topological frameworks. In addition, several separation axioms are proposed to distinguish between different classes of primal weak structure spaces. Overall, primal weak structures constitute a flexible and robust class of mathematical models with strong connections to classical topology and significant potential for future applications. The operators and constructions developed in this work provide a solid foundation for further research in this area. Full article

Background/Objectives: Deep neck space abscesses (DNSAs), representing severe suppurative infections, continue to pose a significant global health challenge due to their morbidity, mortality, and evolving epidemiology. This review synthesizes existing knowledge regarding DNSA definitions, anatomic basis, epidemiological trends, microbiology, clinical presentation, diagnostic strategies, treatment paradigms, outcomes, health system challenges, and disparities to guide global efforts in DNSA prevention, management, and research. Methods: A structured narrative review was performed following SANRA guidelines. PubMed/MEDLINE and the Cochrane Library were searched from January 2000 to May 2025, retrieving 1102 records. After screening, 49 studies met the inclusion criteria. Data were extracted using standardized templates and synthesized thematically. Results: During the period 2004–2015, annual case increases were reported in a Finnish population-based retrospective cohort (n = 277), going from 14 to 24 subjects, and for a UK tertiary center retrospective series, going from 1 to 15 cases annually (2006–2015) (Pearson’s correlation, r = 0.9; p = 0.00019). The microbiological environment is mostly polymicrobial, composed of group streptococci and staphylococcus strains and anaerobes. Factors associated with poor outcomes include diabetes mellitus (adjusted hazard ratio of 10.7 [95% CI 6.0–19.1] in a retrospective, population-based cohort of 12,738 diabetic patients compared to 50,952 individuals without diabetes), immunosuppressed state, elderly age, and multispace involvement. Diagnosis relies on contrast-enhanced CT imaging (sensitivity > 90%), and treatment consists of early multidisciplinary intervention combining empiric broad-spectrum antibiotics with surgical drainage in 60–97% of cases. Mortality ranges from 1.6% to 7.6%, with higher rates in cases complicated by mediastinitis (up to 40%). Conclusions: DNSAs demonstrate a clear upward incidence trend across high-income and resource-limited settings. Establishing standardized DNSA registries, validating risk-stratification tools, reinforcing antimicrobial stewardship to address rising resistance, and implementing early detection protocols in primary care remain critical priorities. While emerging technologies, including rapid molecular diagnostics and AI-based decision support, represent promising research directions, current DNSA management relies fundamentally on conventional clinical assessment, prompt imaging, and coordinated multidisciplinary care. Full article

Accurate determination of the physico-mechanical parameters of rock and soil masses is fundamental to the quantitative stability analysis and engineering mitigation of open-pit mine slopes. However, existing studies often rely on generalized parameters and lack systematic empirical data based on full-hole in situ core sampling to quantitatively verify the link between microscopic mineralogy and macroscopic instability. To address this gap, this study investigates the mineral composition, microstructure, and hydro-mechanical behavior of geotechnical materials, using the XG Open-pit Coal Mine in Inner Mongolia as a case study. Field drilling and sampling with a cumulative depth of 1500.7 m were conducted, combined with systematic laboratory tests. The results reveal significant lithological heterogeneity within the mining area. Specifically, hard rocks (e.g., fine sandstone) constitute the stable framework of the slope, whereas mudstones rich in hydrophilic clay minerals, along with low-strength coal seams, form potential weak sliding interfaces. Quantitative X-ray Diffraction (XRD) analysis reveals that the weak mudstone layers contain up to 32.4% hydrophilic expansive minerals (montmorillonite and illite/smectite). Scanning Electron Microscopy (SEM) and slake durability tests demonstrate that the mudstone is characterized by well-developed micropores (1–2 μm) and loose cementation. Theoretical analysis indicates that upon saturation, the strength of these weak layers is reduced by over 40%, causing the factor of safety (FoS) to drop from a stable 1.48 to a critical 0.89. Based on these findings, the slope instability mechanism driven by “Stiffness Mismatch and Hydro-Weakening” is elucidated. Consequently, targeted reinforcement and drainage measures are proposed to provide a scientific basis for safe mining operations. Full article

This study proposes a real-time chiller capacity control strategy based on marginal Coefficient of Performance (COP) analysis to improve the energy efficiency of air-conditioning systems. The research focuses on the air-conditioning system (ACS) of an office building. Operational data, including chiller capacity and the corresponding COP, were collected to derive the chiller’s operating characteristic curve. The Optimal Capacity Control (OCC) strategy aims to maximize the total COP of all chillers, and the initial capacity allocation is determined using the Lagrange multiplier method. To further refine performance, a fine-tuning mechanism is introduced, calculating the ratio of COP variation to capacity variation (RC ratio) for each chiller to identify which unit should be loaded or unloaded. Based on the fine-tuning mechanism, a comprehensive OCC model is established to ensure that the chiller’s cooling output precisely matches the load demand, thereby maximizing system efficiency and reducing energy consumption. To validate the effectiveness of the proposed OCC strategy, a numerical analysis was implemented using real operational data from the existing ACS. Comparative simulations between the OCC and a Traditional Capacity Control (TCC) strategy were conducted. On a representative summer day, total power consumption decreased from 1534.0 kWh (TCC) to 1527.2 kWh (OCC), while total system COP increased from 113.9 to 114.8. Seasonal analysis further confirms consistent energy savings under varying load conditions. The results indicate that the OCC strategy significantly enhances system performance and reduces energy consumption under varying load conditions. Overall, the proposed method achieves a higher system COP, leading to notable electricity savings and improved operational efficiency of the air-conditioning system. Full article