Search Results (6,785)

This study develops a machine learning-based predictive model for identifying high-level clouds (HLCs). The model uses meteorological parameters as input features and is trained against human-recorded meteorological observations. A statistical analysis of the relationship between two independent methods of registering HLCs—lidar and meteorological observations—has been performed. Optimal thresholds for the total amount of cloud cover, at which meteorological data are consistent with lidar data, have been determined. The results demonstrate the promising performance of ML models in identifying the links between weather conditions and the probability of HLC detection, which is confirmed by ROC AUC (Area Under the Curve of the Receiver Operating Characteristic) values in the range of 0.87–0.88 for the presence and 0.77–0.78 for the absence of clouds, as well as balanced metrics Precision, Recall, and F1. The XGBoost (eXtreme Gradient Boosting) model proved to be the most robust, demonstrating the ability to effectively integrate data of various types for reliable prediction in various conditions. Full article

Background: The optimal sequencing of regorafenib and trifluridine/tipiracil (FTD/TPI) in refractory metastatic colorectal cancer (mCRC) remains uncertain, particularly in Asian populations. Methods: We retrospectively analyzed 110 patients with mCRC who sequentially received both agents between 2011 and 2025. Patients were categorized into regorafenib followed by FTD/TPI (Rego → FTD/TPI, n = 88) and FTD/TPI followed by regorafenib (FTD/TPI → Rego, n = 22). Co-primary endpoints were time to treatment discontinuation (TTD) and overall survival (OS). Propensity score-based weighting methods, including stabilized inverse probability of treatment weighting (primary analysis), were used to adjust for baseline imbalances. Multivariable Cox regression was performed as a sensitivity analysis. Results: No statistically significant differences were observed between treatment sequences. In the primary analysis, the hazard ratio (HR) for TTD was 1.01 (95% CI 0.71–1.43), and for OS was 1.19 (95% CI 0.67–2.12), with FTD/TPI → Rego as reference. Median TTD was 6.8 versus 8.9 months, and median OS was 14.6 versus 20.2 months, respectively. Conclusions: Clinical outcomes were comparable regardless of treatment order, supporting individualized sequencing decisions in refractory mCRC. Full article

In this work, the so-called characteristic function method is proposed as a new approach to describe and interpret the diffusion process with interacting adsorbates in terms of surface coverage. In this context, the intermediate scattering function is identified as a characteristic function that is very well defined in probability theory. From this function, the generating functions of the moments and cumulants of the jump probability distribution are straightforwardly obtained at any order. This analysis is carried out in two stages. First, the dilute limit, corresponding to non-interacting adsorbates or very low surface coverage, is briefly reviewed. Second, the method is extended to low and intermediate coverages, where adsorbate-adsorbate interactions become relevant. A further consequence of the present analysis is that the static structure factor is also a characteristic function of the adsorbate separation distance distribution. This method thus provides a compact and physically transparent route for connecting scattering observables, diffusion coefficients, and coverage-dependent structural correlations. Full article

In this study, a post-processing algorithm was developed to mitigate the over-detection tendency of the Geo-KOMPSAT-2A fog detection algorithm (GK2A_FDA) by integrating surface observations, facilitated by the recent availability of high-resolution gridded surface analysis data. The method was optimized for six sub-algorithms (inland/coastal × daytime/nighttime/twilight) using an interpretable decision tree model with data from 2021 to 2023. The $RH$ (relative humidity) and $\mathsf{\Delta }FTs$ (clear-sky background minus fog-top brightness temperature) step defines detection boundaries in a two-dimensional decision space using joint false alarm-to-hit ratio and hit count distributions to effectively remove false-alarm-dominated regions with minimal impact on the probability of detection (POD). The post-processing steps were sequenced according to independently quantified accuracy gains ($RH$ and $\mathsf{\Delta }FTs$ >> $T_a$ > wind speed > solar zenith angle), with thresholds conservatively derived and seasonally optimized for South Korea. Following post-processing, the POD decreased only slightly (0.08–0.27%), while the false alarm ratio (FAR) and bias were reduced by 5.13–13.68% and 16.13–52.61%, respectively. Improvements were more pronounced during drier seasons than wet seasons; however, the residual high daytime bias (3.348–5.319) indicated the need for further GK2A_FDA refinement. This study demonstrated that integrating satellite and surface observations could effectively address the limitations of satellite-based fog detection. Full article

Rural property rights reform is considered paramount for mobilizing land resources and promoting rural entrepreneurship. However, the outcomes of tenure clarification depend on the role of the land in household livelihoods. The study focuses on China’s homestead rights confirmation and examines its effects on farmer entrepreneurship. The analysis is based on data from 2337 households in Jiangsu Province from the 2020 China Land Economic Survey. The application of Probit and endogenous switching Probit models yielded the following finding: confirming homestead rights reduces the probability of farmer entrepreneurship by approximately 11.4 percentage points. This decline can be attributed to several factors, including a decrease in homestead utilization, a shift towards lower-investment-risk preferences, an increase in entrepreneurial risk perception, and a contraction in entrepreneurial social networks. Collectively, these factors contribute to a reshaping of households’ risk evaluation and asset allocation. The negative impact is primarily observed among households with higher dependency ratios, poorer housing conditions, older heads of household, and those residing in less developed areas. The findings indicate that the consequences of property rights confirmation are characterized by institutional and functional specificity, thereby underscoring the necessity for measures that promote land transfer, exit, and risk-sharing to harmonize tenure reform with entrepreneurship. Full article

This study examines the propagation from meteorological to hydrological drought across representative river basins in Bulgaria, focusing on temporal and spatial characteristics of the process. Monthly precipitation and streamflow data for 1964–2023 were used to calculate the Standardized Precipitation Index (SPI-1 to SPI-12) and the Streamflow Drought Index (SDI-1). The results indicate an increase in drought frequency and severity during 1994–2023 compared to 1964–1993, particularly at longer accumulation scales (SPI-6 to SPI-12). The strongest relationships between meteorological and hydrological drought are observed at multi-seasonal scales (SPI-3 to SPI-6), while clear seasonal differences are identified between the cold (November–April) and warm (May–October) half-years. Conditional probability analysis shows a common propagation lag of 7–9 months across the studied basins. At the same time, once critical precipitation deficits are reached, hydrological drought may develop at short lags of 0–1 month, indicating a rapid system response under severe conditions. Marked regional differences are observed. The middle and lower Struma basin shows the highest drought-transition probabilities (>50%), whereas the Tundzha basin appears more buffered due to reservoir regulation and hydrogeological conditions. The results highlight that drought propagation depends on accumulation time, seasonal regime, and basin characteristics, and they support the need for basin-specific and proactive water management under changing climate conditions. Full article

Offshore pipeline systems associated with floating platforms operate under complex environmental and operational conditions that significantly influence their structural integrity and inspection requirements. Limited accessibility, harsh marine environments, and time-dependent degradation mechanisms require inspection planning to be supported by structured decision-making frameworks capable of explicitly accounting for both degradation processes and failure consequences. In this study, a Risk-Based Inspection (RBI)-driven integrity assessment is applied to three carbon steel pipeline systems associated with a SPAR offshore platform. The analysis integrates system description, identification of dominant damage mechanisms, and RBI quantification to evaluate probability of failure and consequence-related risk under offshore operating conditions. Internal corrosion is identified as the dominant long-term degradation mechanism for all analyzed pipelines, while external corrosion governs short-term inspection interval definition due to its higher growth rate and sensitivity to insulation characteristics and environmental exposure. Although all pipelines are classified within the same overall qualitative risk category, significant differences in failure probability, risk intensity, and consequence-driven risk behavior are observed, reflecting variations in system configuration, insulation systems, length, and functional role within the offshore production infrastructure. To enable meaningful comparison between pipeline systems of significantly different total lengths, normalized risk indicators per unit length are introduced. These indicators provide additional insight into local risk intensity and spatial risk distribution that are not evident from absolute risk values alone. The results highlight the importance of treating risk as a dynamic quantity rather than a static classification and demonstrate that RBI-based assessment supported by normalized risk metrics can enhance inspection prioritization and maintenance decision-making for SPAR-associated offshore pipeline systems. Full article

In this paper, we propose a novel method which utilizes samples of measured product quality characteristics to efficiently estimate the probabilities of those quality characteristics being within the desired specifications and, consequently, the process yield. Specifically, when dealing with 1D Gaussian distributions, we formally prove that the proposed yield estimator asymptotically gives a lower Mean Squared Error compared to the best unbiased estimator. In order to enable maximization of yield, this novel estimator is incorporated into the framework of Bayesian Optimization which iteratively seeks controllable tool parameters under which the outgoing product yield is maximized. The newly proposed yield maximization method is demonstrated in an application involving high-fidelity simulations of a reactive ion etch chamber, a tool component commonly used in semiconductor manufacturing. The aim of these simulations was to rapidly and reliably determine tool parameters that maximize the probability of delivering desired plasma density characteristics under stochastic variations in chamber conditions. The novel yield estimation and optimization methods show superiority when the number of experimental observations is limited and the distributions of outgoing product characteristics can be approximated well by a Gaussian distribution. Full article

Background: Micronutrient deficiencies (MD) are highly prevalent among candidates for bariatric surgery (BS) and are associated with adverse perioperative and postoperative outcomes. Although guidelines recommend systematic preoperative screening and correction, conventional targeted supplementation (CTS) often requires multiple products, potentially limiting adherence and delaying surgical readiness. Bariatric-specific multivitamins (BSM) may simplify nutritional management, but their real-world effectiveness for preoperative correction of multiple MD remains insufficiently investigated. Objective: To compare the effectiveness, efficiency, and adherence of a BSM versus CTS for preoperative correction of multiple MD in BS candidates. Methods: This retrospective multicenter cohort study included 1560 adults with obesity evaluated for BS between 2020 and 2024 across three Italian bariatric centers. The primary efficacy analysis was restricted to patients presenting with ≥3 laboratory-confirmed MD at baseline. Patients treated between 2020 and 2022 received individualized CTS using multiple products, whereas those treated between 2023 and 2024 received a single BSM. Biochemical follow-up was scheduled at 4 and 8 weeks. The primary outcome was the achievement of complete biochemical correction of all baseline deficiencies at the predefined 4-week follow-up assessment (composite endpoint). Secondary outcomes included supplementation burden and self-reported adherence. Early correction rates were compared using absolute risk differences and risk ratios; adjusted associations were evaluated using multivariable regression models including center and baseline deficiency burden. As a supplementary analysis, the patient-level proportion of baseline deficiencies corrected at 4 weeks was also evaluated. Results: Among patients with ≥3 baseline deficiencies (n = 216), complete biochemical correction at 4 weeks was achieved in 55/134 patients (41.0%) in the BSM group and in 13/82 patients (15.9%) in the CTS group, corresponding to an absolute risk difference of 25.2 percentage points (95% CI 7.8–40.0) and a risk ratio of 2.59 (95% CI 1.51–4.44). In adjusted analyses accounting for center and baseline deficiency pattern, BSM use remained independently associated with early complete correction (adjusted absolute risk difference 26.3 percentage points; adjusted risk ratio 2.69). Sensitivity analyses restricting follow-up timing and excluding early calendar periods yielded consistent results. The mean proportion of baseline deficiencies corrected per patient at 4 weeks was higher in the BSM group compared with CTS (0.74 ± 0.25 vs. 0.54 ± 0.30). Compared with CTS, BSM was associated with lower supplementation burden (1 vs. 3.5 supplements on average) and higher adherence (92% vs. 70%). Conclusions: In a real-world multicenter cohort of BS candidates with ≥3 baseline MD, a simplified preoperative supplementation strategy based on a BSM was associated with a significantly higher probability of complete biochemical correction at 4 weeks, lower supplementation burden, and higher reported adherence compared with CTS. Although complete correction was not universal at 4 weeks, BSM significantly increased the likelihood of achieving early multi-deficiency normalization. Given the non-concurrent observational design, these findings should be interpreted as hypothesis-generating and warrant confirmation in prospective studies with concurrent cohorts. Full article

Urban sustainability depends on rural hinterlands, yet national-scale evaluation and AI screening often rely on urban-centric proxies, which can under-recognize remote villages where the evidence base is sparse. Using China’s national honored-village programme (N = 24,450) as a case, we examine how recognition patterns change when data availability and observability are unequal across regions, with a focus on the Qinghai–Tibetan Plateau (QTP), where 923 honored villages account for only 3.78% of the national total. We interpret urban-centric proxy reliance as the tendency for recognition patterns to correlate with urban-linked observability signals (e.g., nighttime lights). In this study, discovery lag refers to situations where villages exhibit characteristics similar to historically recognized villages but remain unrecognized under the current honor regime due to uneven data availability and observability. Methodologically, we build a scene-aware predictive framework that integrates multi-source geospatial indicators and explicitly handles extreme imbalance and environmental heterogeneity to estimate recognition likelihood under the current honor regime, treating national honor lists as administratively produced recognition outcomes rather than objective measures of village value. The model highlights four high-probability nomination belts on the QTP and reveals a pronounced DEM–NTL decoupling: the median NTL of currently honored QTP villages is 0, suggesting that NTL-based urban proxies can fail in high-altitude, data-scarce contexts. Overall, the observed under-representation is consistent with uneven observability and institutional constraints within the current honor system, and the proposed framework provides a scalable diagnostic and screening tool for identifying villages with high predicted recognition likelihood and supporting more evidence-aware rural data collection. Full article

The accurate inference of hidden states from non-stationary physiological signals remains a significant challenge in stochastic process modeling. This paper proposes an Adaptive Sticky Hidden Markov Model (Sticky-HMM) framework designed to enhance the robustness of state decoding in noisy environments. To address the “state-flickering” issue inherent in traditional HMMs, we incorporate a “Sticky” parameter into the transition matrix, imposing a temporal penalty on spurious state switching to maintain continuity. Furthermore, we introduce a Dynamic Prior Strategy that adaptively calibrates self-transition probabilities by mapping frequency-domain features of the observed sequence to the model’s parameter space. The proposed decoding process employs a two-pass refinement strategy and the Viterbi algorithm in the logarithmic domain to ensure numerical stability. The model’s efficacy was validated using a high-fidelity dataset of simulated apnea events. This work provides a computationally efficient and mathematically rigorous approach that demonstrates strong potential for long-term respiratory health monitoring. Full article

Background/Objectives: The aim of the study was to evaluate the diagnostic accuracy of a commercial artificial intelligence (AI) algorithm originally developed for screening mammography when applied to symptomatic women presenting to a tertiary outpatient clinic. Methods: This single-center, retrospective diagnostic accuracy study included women who presented with breast symptoms to a tertiary outpatient clinic between January and June 2013 and underwent digital mammography. An AI algorithm cleared by the U.S. Food and Drug Administration (FDA)-cleared AI algorithm was applied to all mammograms and generated continuous malignancy scores ranging from 1 to 100. Mammographic breast density was classified according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) by two experienced radiologists. Histopathology, when available, or otherwise a minimum of 2 years of clinical and imaging follow-up served as the reference standard. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis with calculation of the area under the curve (AUC) and 95% confidence intervals (CI) derived by patient level bootstrap resampling (n = 2000). Analyses were performed for the overall cohort and stratified by breast density (non-dense [BI-RADS A–B] vs. dense [BI-RADS C–D]). Results: A total of 78 women (mean age, 55 ± 11 years) were included, of whom 16 had histopathological verification of suspicious lesions with proven breast cancer in 14 patients and 62 were classified based on follow-up alone. In the overall cohort (156 breasts, including 15 breasts with malignancies), the AI algorithm achieved an AUC of 0.96 (95% CI: 0.86–1.00). Performance remained high in non-dense breasts (AUC = 0.96; 95% CI: 0.88–1.00) and dense breasts (AUC = 0.99; 95% CI: 0.93–1.00), with no statistically significant difference observed between density subgroups (DeLong test, p = 0.36), although subgroup comparisons were underpowered. Decision curve analysis suggested a consistent positive net benefit across a wide range of threshold probabilities in both density groups. Conclusions: In this preliminary, single-center retrospective cohort, a screening-trained AI algorithm showed promising diagnostic accuracy when applied to symptomatic mammograms. These findings require validation in larger, contemporary, multicenter cohorts before clinical implementation. Full article

The strategic choice of training system is essential for adapting viticulture to current climate change, ensuring a balance of physiological efficiency and the sustainability of productivity and oenological quality. This study evaluated the effects of vertical shoot positioning and foldable lyre systems (set at angles of 20°, 30° and 40°) on the physiological performance and yield of ‘Merlot’ grapevines. The experiment was conducted in a humid temperate region in Brazil over two consecutive seasons. The experiment followed a randomized block design. The variables evaluated included: the number of clusters per shoot, cluster weight, pruning weight, Ravaz Index, leaf area and yield; gas exchange parameters such as net CO₂ assimilation rate, stomatal conductance, transpiration rate, rubisco carboxylation efficiency, intercellular CO₂ concentration and photosynthetic photon flux density; and chemical composition of berries such as pH, Total Soluble Solids and Titratable Acidity. The data were subjected to an analysis of variance, and the means were compared using Tukey’s test at a 5% probability level. The results indicated that canopy architecture significantly influenced solar radiation interception, with the 30° and 40° foldable lyre systems achieving the highest mean daily radiation levels, exceeding the vertical positioning system by 73.7% and 76.6%, respectively. Although gas exchange at the leaf level remained comparable across all systems, agronomic performance varied considerably. The 40° foldable lyre system achieved the highest yield (22.99 t ha⁻¹), representing a 63.1% increase over the vertical positioning system (14.10 t ha⁻¹). The number of buds in the foldable lyre systems increased by around 70%, which is closely in line with the observed increase in yield. In addition, the foldable lyre systems provided about 40% more leaf area than the vertical positioning system. These findings suggest that divided canopy systems, such as foldable lyre systems, particularly at 30° and 40°, optimize bud load, fruitfulness per shoot, light interception and significantly increase yield without compromising individual physiological efficiency and berry chemical composition, with a balance between vegetation and fruit load preserved and with positive effects on the ripeness and quality of the grapes. Full article

Background: Clinical remission has become a realistic treatment goal in severe asthma, but current evidence mostly reports global remission rates without accounting for baseline disease burden. No simple tool exists to quantify baseline severity and estimate an individual patient’s probability of achieving remission under biologic therapy. Methods: This prospective observational study included 93 adults with severe asthma initiating tezepelumab across 14 specialised severe asthma units in Spain. Four baseline domains—poor symptom control (ACT < 20), ≥1 severe exacerbation in the previous 12 months, maintenance oral corticosteroid (OCS) use, and FEV₁ < 80% predicted—were used to construct an empirically weighted composite score (Base4Score) based on the inverse probability of correcting each abnormal domain at 12 months. Strict clinical remission at 12 months was defined as ACT ≥ 20, no severe exacerbations, no maintenance OCS, and FEV₁ ≥ 80%. Logistic regression was used to assess the association between the score and non-remission, adjusting for age, sex, smoking status, T2 phenotype, and biologic-naive status. Results: Of 93 treated patients, 81 had complete baseline data for Base4Score derivation and 77 had complete 12-month data for strict clinical remission analysis. Strict clinical remission was achieved in 16/77 patients (20.8%). Remission rates decreased across increasing baseline score strata: 40.0% for scores < 5, 17.6% for scores 5 to <9, and 12.5% for scores ≥ 9 (linear p-trend = 0.022). Each 1-point increase in the continuous Base4Score was associated with higher adjusted odds of non-remission (OR 1.22; 95% CI 1.00–1.49; p = 0.047), and patients with scores ≥ 9 had approximately sevenfold higher adjusted odds of non-remission than those with scores < 5 (OR 6.77; 95% CI 1.40–32.84; p = 0.018). Conclusions: The Base4Score is a simple, empirically derived baseline severity index that predicts 12-month strict clinical remission in severe asthma treated with tezepelumab. If externally validated, it could help personalise expectations, optimise timing of biologic initiation and guide treat-to-target strategies in severe asthma. Full article

Background: Although HPV vaccination is highly effective in the primary prevention of cervical cancer, its potential role in women already diagnosed with HPV-associated cervical dysplasia remains uncertain. This study aimed to evaluate the association between post-diagnosis HPV vaccination and short-term clinical outcomes in HPV-positive women with cervical dysplasia. Methods: Women aged ≥18 years with abnormal cervical screening results suggestive of squamous intraepithelial lesions and high-risk HPV positivity were retrospectively evaluated. High-grade disease was defined as histologically confirmed CIN2/3. HPV vaccination (9-valent) was recommended to all eligible patients at the time of diagnosis. Vaccination status was primarily analyzed as vaccinated (≥1 dose) versus unvaccinated; additionally, dose-stratified analyses (0, 1–2, and 3 doses) were performed to explore potential dose–response relationships. Results: A total of 392 women were included (173 unvaccinated and 219 vaccinated). At 12 months, regression occurred in 51.1% of vaccinated patients compared with 41.0% of unvaccinated women (OR 1.50, 95% CI 1.02–2.20, p = 0.04). A dose–response pattern was observed, with regression rates of 41.0% in unvaccinated patients, 46.1% in partially vaccinated patients, and 54.6% in fully vaccinated patients (p for trend = 0.012). In the HSIL subgroup, regression occurred in 49.0% of vaccinated women versus 33.8% of unvaccinated patients (OR 1.88, 95% CI 1.01–3.52, p = 0.047). When stratified by treatment modality, vaccination was significantly associated with higher regression in the non-LEEP cohort (OR 1.67, p = 0.04) but not in the LEEP cohort (p = 0.22). In multivariable analysis adjusting for age, smoking, HPV genotype, baseline histopathologic grade (CIN1 vs. CIN2/3), and treatment modality, HPV vaccination remained independently associated with regression (aOR 1.55, 95% CI 1.05–2.30, p = 0.028). Conclusions: Post-diagnosis HPV vaccination was associated with a higher probability of cervical dysplasia regression at 12 months, particularly among women with baseline HSIL. These findings suggest that HPV vaccination may provide a beneficial adjunct effect in the clinical management of HPV-associated cervical dysplasia. Prospective studies are required to confirm these observations and clarify the mechanisms underlying this association. Full article