Search Results (2,132)

Writing development in the early grades depends critically on transcription skills, yet little is known about how components of orthographic knowledge support children’s written composition in European Portuguese. This study examined whether lexical and sublexical orthographic knowledge assessed at the beginning of Grade 2 predict written composition at the end of the school year, and whether these effects are direct or mediated by word spelling. Eighty Grade 2 children completed measures of lexical orthographic knowledge (orthographic choice), sublexical orthographic knowledge (orthographic awareness), and word spelling at the beginning of the year, and a written composition task scored for lexical diversity at year’s end. Path analyses with maximum likelihood estimation and bias-corrected bootstrapping showed that orthographic knowledge explained 44% of the variance in word spelling and up to 18% in written composition. Lexical orthographic knowledge was a significant direct predictor of written composition (β = 0.38, p < 0.01), whereas sublexical orthographic knowledge showed a small but significant indirect effect through spelling (β = 0.08, p < 0.05) in the full mediation model. These findings highlight the central role of orthographic knowledge, particularly its lexical component, in supporting early writing in an orthography of intermediate depth. Full article

Liuchun Lake area, located in the high-elevation and topographically complex western region of Zhejiang Province, exhibits temperature variability strongly influenced by terrain-induced dynamics and local microclimates. The Zhejiang Operational Consensus Forecasts (ZJOCF) model shows pronounced systematic biases in this area, making it difficult to meet the demand for short-term, fine-scale forecasts in cultural-tourism applications. Using observational data from four stations at different elevations, this study analyzes how ZJOCF temperature forecast errors vary with altitude, develops a station-level machine-learning temperature bias-correction model, and evaluates its performance in terms of accuracy, mean absolute error (MAE), error distribution, and control of extreme errors. Results show that the accuracy of the raw forecasts decreases significantly with increasing elevation, with high-altitude sites exhibiting distinct warm biases and strong fluctuations. After correction, the 72 h forecast accuracy at the four stations increases to 69–71% (up to 40.8% at the mountaintop station), MAE is reduced by more than 60% on average, extreme-error cases decrease by 40–60%, and the error distribution shifts from a scattered multi-peak pattern to a concentrated single-peak structure. These findings demonstrate that station-level machine-learning correction can effectively mitigate structural errors in ZJOCF temperature forecasts over complex terrain, providing a reliable technical pathway for refined meteorological services in mountainous regions. Full article

Hurricane Florence (2018) proved to be a damaging tropical cyclone that formed off the coast of the Cabo Verde Islands. On 12 UTC 14 September 2018, Florence made landfall as a weakened category 1 Hurricane in Wrightsville Beach, NC. In the midst of landfall, Florence’s ground speed stalled considerably to near zero. Because of this stall, Florence continued to accumulate feet of rain along the coastline, and the inundation of seawater became extreme. Due to the impacts of Florence, the Weather Research and Forecasting Model (WRF-ARW) was used to simulate the tropical cyclone and provide insight into the thermodynamics and dynamics that played a significant role at the time of landfall. After the control case, several sensitivity experiments were conducted. The historical sensitivity experiments utilize the thermodynamic and moisture fields of ERA5 reanalysis data from 1968 and 1998, respectively, to modify the thermodynamic and moisture fields in the initial conditions of the WRF–ARW control case. In addition, to study the potential future climate impacts of Florence, the NCAR CESM Global Bias-Corrected CMIP5 Output to Support WRF/MPAS Research dataset was utilized. The same approach was taken as the historical versions of Florence for sensitivity experiments for future climate, i.e., thermodynamic and moisture fields for both 2038 and 2068 under the RCP6.0 and RCP8.5 climate scenarios, respectively. Results suggest a corresponding intensity shift with minor track deflections. Based on these modifications, synoptic and mesoscale dynamics will be studied to provide insight into how Florence-like hurricanes may change based on certain climate scenarios. Full article

Corporate tax avoidance has become a major governance and fiscal sustainability concern, particularly in developing economies where corporate tax revenues constitute a critical source of public financing. While prior research suggests that board gender diversity (BGD) enhances ethical oversight and monitoring, its effectiveness in constraining aggressive tax planning may depend on firms’ informational and technological environments. This study examines whether artificial intelligence (AI) capability strengthens the governance role of BGD in reducing corporate tax avoidance. Using a balanced panel of 1586 non-financial firms from developing economies over the period 2009–2023, the analysis employs firm FE models and dynamic two-step System GMM estimations to address unobserved heterogeneity, endogeneity, and the persistence of corporate tax behavior. The results indicate that BGD is positively associated with effective tax rates, implying lower levels of corporate tax avoidance. Furthermore, AI capability—measured using a lagged specification—significantly strengthens this relationship, suggesting that firms with higher AI adoption exhibit a stronger governance effect of gender-diverse boards on tax compliance. Additional robustness tests—including alternative tax avoidance measures, alternative BGD specifications, heterogeneity analysis, and selection-bias corrections using Heckman, propensity score matching (PSM), and instrumental variable (2SLS) approaches—confirm the stability of the findings. Overall, the results highlight the complementary role of technological capability and board diversity in strengthening corporate governance (CG) and fiscal discipline in developing economies. Full article

Background/Objective: Prehabilitation aims to improve physiological reserve before surgery to enhance postoperative outcomes. Multiple systematic reviews have evaluated preoperative interventions in adult cardiac surgery; however, variability in scope, methodological quality, and overlap of primary trials complicates interpretation. The aim of this study is to synthesise and critically appraise evidence from systematic reviews and meta-analyses evaluating prehabilitation interventions in adults undergoing cardiac surgery. No funding was received for this study. Methods: We conducted an umbrella systematic review following a prospectively registered protocol (PROSPERO: CRD420261292354) and PRISMA 2020 guidance. PubMed, Web of Science, and Scopus were searched from inception to 31 December 2025. Eligible reviews included adults (≥18 years) undergoing cardiac surgery, evaluated and compared preoperative inspiratory muscle training (IMT), respiratory muscle training, and exercise-based, educational, or multimodal prehabilitation with usual care or sham intervention. Reviews focused solely on postoperative interventions or non-cardiac surgery were excluded. Methodological quality was assessed using AMSTAR-2. Certainty of evidence was evaluated using GRADE. Overlap of primary studies was quantified using the Corrected Covered Area (CCA). A structured narrative synthesis with a direction-of-effect framework was applied. Results: Eighteen systematic reviews (published 2012–2025) were included, comprising 46 unique primary studies and more than 6674 participants (exact totals unavailable due to incomplete reporting in at least one review). Overall overlap was high (CCA 12.5%). Respiratory-focused prehabilitation, particularly IMT, demonstrated consistent reductions in postoperative pulmonary complications (PPCs) (risk ratios approximately 0.42–0.53), pneumonia (RR ~0.44–0.45), and atelectasis (RR ~0.49–0.59), favouring prehabilitation over usual care. Hospital length of stay was reduced by approximately 1.5–3 days across multiple reviews. Inspiratory muscle strength improved consistently (mean difference ~+12 to +17 cmH₂O). Effects on ICU length of stay and mechanical ventilation duration were inconsistent or non-significant. Exercise-based programmes improved functional capacity (6 min walk distance increase ~50–75 m) and showed modest reductions in hospital stay, but heterogeneity was substantial. No intervention demonstrated a consistent reduction in postoperative mortality. Evidence was limited by clinical heterogeneity, performance bias in primary trials, inconsistent outcome definitions, and high overlap of key IMT trials across reviews. Mortality outcomes were underpowered. Conclusions: Preoperative IMT provides evidence for reducing pulmonary complications and shortening hospital stays in adult cardiac surgery. Exercise-based prehabilitation improves functional capacity but requires further high-quality, standardised trials. Integration of respiratory prehabilitation into cardiac surgical pathways appears supported by the current evidence. Full article

Breast mastitis is a common condition that can be found during clinical practice, challenging the clinician, who must reach the correct diagnosis among the many differentials, to properly treat the underlying pathology. In this review, we aim to provide clinicians and radiologists with an overview of the various forms of mastitis, focusing on clinical presentation, etiological subtypes, imaging appearances across modalities (e.g., ultrasound, mammography/tomosynthesis, contrast enhanced techniques, MRI), related complications, and the typical imaging takeaways. Our goal is also to provide tools for the correct differential diagnosis between various forms of mastitis, breast cancer and other inflammatory breast pathologies. A computerized literature search using PubMed and Google Scholar was performed by authors, entering various keywords (e.g., “mastitis”, “breast infections”, “breast abscess”, “breast cancer mimickers”, “lactational mastitis”, “non lactational mastitis”, “mastitis imaging”, “rare forms of mastitis”). Articles published between 2002 and 2025 were taken into consideration. The authors selected various eligible studies, scientific articles and extracted data to cover the whole spectrum of mastitis clinical presentation and underlying pathology. Authors divided the mastitis spectrum into “lactational” and “non-lactational” forms. Between the second group, periductal mastitis, idiopathic granulomatous mastitis, and rarer forms are taken into consideration. Our review has several limitations: it is a narrative and not systematic review and has limited generalizability of rare subtypes because of the case report driven evidence, heterogeneity of selected studies and potential selection bias. It supplies imaging from various clinical cases, which can be useful to familiarize with the pathology spectrum. In conclusion, breast mastitis is a challenge for breast radiologists and clinicians, familiarity with this condition is crucial to make a correct differential diagnosis. Further studies are needed on rarer subtypes. Full article

We propose a monolithically integrated optical frequency comb (OFC) generation platform on thin-film lithium niobate (TFLN), featuring cascaded dual-drive Mach–Zehnder modulators (DDMZM) and a ${\mathrm{S}\mathrm{i}}_3{\mathrm{N}}_4$-assisted spot size converter (SSC). To capture microscopic mode mismatches and spatial phase accumulation often overlooked in idealized scalar simulations, we establish a multi-physics co-simulation framework integrating finite-difference time-domain (FDTD) analysis with macroscopic transmission modeling. Based on this framework, the cascaded modulator architecture generates 25 highly stable comb lines with a dense 2 GHz spacing and an envelope flatness within 2 dB. Tolerance analysis indicates that the comb generation is highly resilient to typical manufacturing and environmental variations, including thermal bias drift, RF phase mismatch, and half-wave voltage ($V_{\pi }$) dispersion. Furthermore, physical-layer modeling shows that the integrated SSC reduces fiber-to-chip coupling loss to 0.55 dB per facet, preserving the necessary optical power budget. To validate the platform’s viability as a multi-wavelength continuous-wave source for spatial-division multiplexed (SDM) interconnects, a parallel transmission over a 20 km standard single-mode fiber is modeled. Using a digital signal processing (DSP)-free 10 Gb/s non-return-to-zero (NRZ) scheme, the 25-channel system maintains a worst-case bit error rate strictly below the forward error correction (FEC) threshold. This work offers a practical, physics-based evaluation framework for high-density co-packaged optics (CPO). Full article

Background: Nutrition and sleep are critical determinants of athletic performance and recovery. Direct comparative research between endurance and strength–power athletes remains limited. This study aimed to evaluate and compare nutritional knowledge, dietary habits, sleep quality, and Body Mass Index between ultramarathon runners and American football players, as well as to explore independent predictors of sleep quality. Methods: A cross-sectional study was conducted among 231 male athletes. To address group size disparity and mitigate statistical bias, a random undersampling technique was applied to create a balanced cohort of 86 athletes comprising 43 ultramarathon runners and 43 American football players. Nutritional parameters were assessed using the Kom-PAN questionnaire. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index. Between-group comparisons were performed using the Mann–Whitney U test with False Discovery Rate correction. An integrated multiple regression model was constructed to identify predictors of global sleep quality. Results: Ultramarathon runners demonstrated significantly better overall sleep quality (p = 0.026) and higher nutritional knowledge (p < 0.001) compared to American football players. Differences in adherence to pro-healthy and non-healthy dietary patterns were not statistically significant after False Discovery Rate correction. The integrated multiple regression model revealed that the athletic discipline was the primary independent predictor of global sleep quality (p = 0.001), while dietary variables did not exhibit a significant independent effect. Furthermore, higher Body Mass Index was independently associated with better sleep scores within the multivariate model (p = 0.008). Conclusions: Significant sport-specific differences exist in BMI, nutritional knowledge, and sleep quality. Global sleep quality appears to be primarily associated with the specific physiological and environmental demands of the athletic discipline rather than individual dietary factors, which were not independently significant in the multivariable model. These findings suggest that recovery strategies in strength–power athletes may require a broader, multifactorial approach beyond nutritional education alone. Full article

Light hydrocarbons in shale oil readily volatilize during conventional coring, surface handling, storage, and laboratory preparation. The resulting evaporative loss causes systematic underestimation of Rock-Eval S₁ peak (free hydrocarbons measured by programmed pyrolysis), which can bias oil-bearing evaluation, sweet-spot delineation, and resource assessment. Here we investigate Chang 7₃ lacustrine shale oil in the Ordos Basin (China) using frozen cores recovered by pressure-retained coring from four wells. Time-series Rock-Eval pyrolysis and thermal desorption–gas chromatography (TD–GC) were used to quantify the magnitude, temporal evolution, and practical equilibrium time of light-hydrocarbon loss and to establish a practical restoration model. S₁ decreases with storage time and exhibits a clear two-stage behavior. Shale shows a rapid-loss stage during 0–90 days, followed by a practical equilibrium stage after 90 days (S₁ change less than 5%). Sandstone interbeds lose light hydrocarbons faster and more completely, reaching practical equilibrium after 60 days. TD–GC indicates that the lost fraction is dominated by n-alkane components lighter than C₁₃, with gaseous hydrocarbons showing the greatest depletion; medium and heavy fractions decrease modestly. Loss is coupled with progressive desorption from kerogen and clays, leading to enrichment of heavier components in the residual free hydrocarbons and a shift of the modal carbon number toward higher values. At the shale equilibrium time, total organic carbon (TOC) and vitrinite reflectance (R_o) jointly control the restoration factor K. We propose a two-parameter restoration model: K = (0.4024·ln (TOC) + 0.821)·(0.652·R_o + 0.4292). Applying the model to more than 50 conventionally cored wells reveals that the Qingyang–Zhengning area in the southwestern basin is the principal enrichment zone of original free hydrocarbons, followed by the Jiyuan area in the north and the Huachi area in the central basin, whereas the eastern basin is relatively depleted. The workflow provides a robust and transferable approach for correcting S₁ and improving shale-oil evaluation in lacustrine systems. Full article

Kang Youwei (1858–1927) reimagined Confucius as the founding religious leader of Confucianism, a conceptual framework underpinning his entire ideological system of Confucian thought. Yet existing scholarship has largely overlooked systematic analysis of this theoretical reconstruction. Influenced by the impact–response paradigm, many studies have also neglected Kang’s core intention to pursue cross-civilizational dialogue and establish a universalist Confucianism through such interpretive innovation. Faced with the late-Qing predicament of the imbalance between a dominant Western world and a weakened China, Kang thoroughly redefined Confucius by shifting his image from a sage who transmitted rather than created ancient wisdom to a religious authority who reformed institutions through classical precedents. This paper argues that Kang’s reinterpretation was neither a simplistic religious adaptation nor a conservative defence of traditional culture. His fundamental aim was to correct Western-centric bias, facilitate equal Sino-Western civilizational dialogue, critique inherent structural dilemmas of modern Western civilization, and propose the Confucian Way as a viable solution to these deep-rooted crises. Full article

In sandstorm environments, a large number of suspended particles in the air absorb and scatter light, causing strong color bias, low contrast, and blurred details in images. These degradations reduce the reliability of computer vision applications in surveillance systems, intelligent transportation systems, unmanned aerial vehicle monitoring, and outdoor autonomous driving systems. A complete sandstorm image enhancement method was developed in this study by combining sky detection, color correction, contrast enhancement, and adaptive dark channel prior (ADCP) dehazing. The Lab color space was used to correct the color bias. The L channel was enhanced using normalized gamma correction and contrast-limited adaptive histogram equalization to improve brightness and contrast. Then, the sky region is detected to avoid over-processing, preserving the natural appearance of the sky region. Finally, ADCP is applied to non-sky regions for further dehazing. Experiments show that the proposed method provides better subjective and objective performance compared to other algorithms. Full article

Impacted mandibular third-molar surgery commonly causes early postoperative pain, swelling, and trismus. This randomized, controlled, three-arm parallel trial evaluated whether intra-alveolar corticosteroid delivery via an absorbable gelatin sponge improves postoperative recovery compared with a saline control. Fifty-five patients were assessed for eligibility; 37 healthy adults (18–35 years) undergoing standardized mandibular third-molar extraction were randomized to dexamethasone 8 mg (Decort^®), methylprednisolone 40 mg (Prednol^®), or control (saline), all applied intra-alveolarly using a gelatin sponge carrier. Doses were selected using standard systemic glucocorticoid equivalence tables as a pragmatic potency reference, acknowledging unknown intra-alveolar pharmacokinetics/bioavailability. The prespecified primary endpoint (used for sample size planning) was postoperative Day 1 VAS pain; key secondary endpoints were Day 1 analgesic consumption and Day 3 facial swelling. Pain (VAS), analgesic use, trismus, and facial swelling (tragus–pogonion, tragus–labial commissure, and angulus–canthus distances) were assessed on postoperative Days 1, 2, 3, and 7 by a blinded evaluator. Two participants in the methylprednisolone group did not attend postoperative visits. To address potential attrition bias, an Intention-to-Treat (ITT) sensitivity analysis using conservative control-median imputation was performed alongside the available-case analyses. A global False Discovery Rate (FDR) correction was also applied to control for multiplicity. In both analyses, the steroid groups showed lower Day 1 pain scores than the control group. Methylprednisolone was associated with lower Day 3 swelling values than control for the tragus–pogonion and angulus–canthus measurements. These findings should be interpreted as preliminary, given the small sample size, linear swelling measurements, and lack of blinding verification. Full article

East Africa is highly vulnerable to climate change due to limited adaptive capacity and strong reliance on rain-fed agriculture. Ethiopia, in particular, experiences recurrent socio-economic losses from droughts and floods. This study presents a national-scale assessment of observed (1981–2010) and projected (2041–2100) changes in extreme seasonal precipitation across Ethiopia using ten ETCCDIs. High-resolution Enhancing National Climate Services (ENACTS) observations and bias-corrected outputs from a selected ensemble of CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios are used to assess historically trends and future extreme precipitation, respectively. Historical trends show increases in extreme precipitation during the Kiremt (JJAS) season, particularly over the northwestern, western, and southwestern highlands; however, most of these increases are not statistically significant. In contrast, the Belg (FMAM) season exhibits widespread declines, which are also largely not statistically significant. Future projections suggest increases in total precipitation (PRCPTOT), heavy (R10) and very heavy rainfall days (R20), very wet days (R95p) and extremely wet days (R95p), and rainfall intensity (SDII) over northwestern, western, southwestern, and parts of northeastern Ethiopia during JJAS. During FMAM, PRCPTOT is projected to increase in the northern and northwestern regions, while decreases are expected in the northeastern and southeastern regions. The Awash and Tekeze basins emerge as key hotspots of change, indicating potential seasonal shifts and an increased likelihood of extreme weather in these regions. Despite inter-model uncertainty, the results highlight the need for flexible, uncertainty-informed adaptation strategies to enhance climate resilience in Ethiopia. Full article

Infrared focal plane arrays (IRFPAs) often suffer from spatiotemporal nonuniformity that persists after conventional two-point nonuniformity correction (NUC), especially under temperature drift and time-varying readout conditions. These residuals are typically structured, including column-group striping caused by shared column-end circuits and row-wise baseline/common-mode drift induced by row-scanning paths. We propose a structured, digital-twin-inspired detector-side refinement of two-point NUC that augments the bias term with interpretable low-dimensional components: a static column bias vector capturing group-correlated residuals and a row-related structured term consisting of a static row baseline and a frame-synchronous common-mode component with row-dependent sensitivity, while keeping the two-point gain/offset backbone unchanged. Rather than representing a full system-level digital twin of the infrared payload, the proposed framework serves as a detector-side virtual representation of dominant readout-induced structured residual states that can be estimated and updated from calibration data. Experiments on blackbody calibration data across multiple temperature points demonstrate that the column-related structured component significantly reduces group-wise column residuals, the row-related structured component suppresses time-varying row striping, and the combined method improves both column- and row-direction metrics consistently across temperatures. Full article

Multi-campus AI data centers procure identical hardware and service SKUs across geographically heterogeneous locations, yet finance and operations require a single system-level benchmark (“world price”) per SKU for budgeting, chargeback, and capacity planning. Naive deployment-weighted aggregation preserves total cost but can induce Simpson-type aggregation bias, where heterogeneous location mixes reverse global SKU rankings and weaken managerial decision signals. This study formalizes the problem of location-robust, cost-preserving aggregation and develops two mathematically structured operators for production cost pipelines. The first operator applies a two-way fixed-effects decomposition to separate global SKU effects from campus-specific premia, followed by normalization to guarantee exact cost preservation. This yields an interpretable benchmark that performs well when campus coverage is sufficiently broad and location effects remain approximately additive. The second operator solves a constrained convex common-weight optimization, producing a unified set of non-negative campus weights that preserves total cost while providing the strongest protection against dominance reversals in the ordered setting. Simulation experiments and a semi-real calibrated AI datacenter OPEX illustration show that both operators substantially improve ranking stability relative to naive blending, while the convex operator serves as the more conservative safeguard under adverse heterogeneity. The resulting detect–correct–validate workflow provides a scalable decision-support framework for robust cost aggregation in distributed AI infrastructure and illustrates how symmetry-preserving aggregation operators can stabilize benchmarking in large heterogeneous systems. Full article