Search Results (2,795)

Ambiguity Resolution (AR) is regarded as an effective technique for enhancing positioning accuracy and reducing convergence time in Precise Point Positioning (PPP). However, the Wide-Lane Fractional Cycle Bias (WL FCB) and Narrow-Lane Fractional Cycle Bias (NL FCB) needed for AR are generated from network solutions based on numerous globally distributed stations, leading to considerable computational load and processing time. A prediction model for FCB is proposed using the Genetic Algorithm Optimized Backpropagation Neural Network (GA-BPNN), and high-precision predictions of WL and NL FCB for Day of Year (DOY) 321 in 2023 are successfully achieved. Comparisons with iGMAS products show that predicted WL FCB deviations are within 0.01 cycles, and predicted NL FCB over 12 h deviates within 0.1 cycles (excluding satellite C20). The performance of three PPP schemes, Float, Fixed (based on FCB from iGMAS), and BP-Fixed (based on FCB predicted by GA-BPNN), is compared through experiments. For GPS + BDS-3, the accuracies of the BP-Fixed scheme are 0.0034 m, 0.0039 m, and 0.0100 m in the east, north, and up directions, respectively. The ambiguity fixed rates reach 98.62% for BP-Fixed. These outcomes confirm that the positioning performance using the predicted FCB of GA-BPNN is highly consistent with that using FCB products. Full article

The purpose of this study was to evaluate how a multi-component soil conditioner consisting of zeolite, calcium carbonate, potassium humate, and Ascophyllum nodosum extract affects selected soil properties (physical, chemical, and water-related properties, as well as microbial and enzymatic properties) and the growth and grain yield of spring barley (Hordeum vulgare L.). To achieve the goal, one-year research experiments were conducted at three conventionally tilled sites, which were situated on farms across three geographically separate regions in the Kuyavian–Pomeranian Region of Midwestern Poland. Most of the chemical properties, namely, total organic C, total N, pH in KCl, cation exchangeable capacity (CEC), as well as exchangeable (Mg, Ca, K, and Na) and available (Mg, K, and P) forms of nutrients, were not significantly affected by the conditioner or sampling time. Independent of the study location, the percentage of macropores in total porosity (TP) and dissolved nitrogen content (DNt) determined in July were considerably greater in the soil treated with Solactiv compared to the reference soil. Bulk density (BD), in turn, showed the opposite tendency, also suggesting the positive effect of the studied conditioner. At all study sites, application of the conditioner significantly reduced the percentage of micropores in total porosity (TP) (by 17%), while significantly increasing the content of macropores in TP (15%) and enhancing the percentage of available and readily available water capacity (8.5% and 14%). No clear changes in the results of C and N form and enzymatic activity were noted. The activities of DHA and FDAH behave differently in each study site, making it difficult to draw clear conclusions. The cellulase was the only enzyme that was significantly and positively affected by Solactiv at all study sites and for both sampling times. The values of dry matter of roots and plants, barley root length and surface, and barley grain yield were considerably greater in soil amended with Solactiv compared to the reference soil. Because some important soil and plant properties showed a positive response toward the tested conditioner, despite the low dose used, further studies should be conducted at a larger scale, focusing on different soils and plants. Full article

To address the challenges of small-sample rock fine classification—such as overfitting caused by limited sample size and the increased complexity resulting from high inter-class similarity—this study proposes a Stacking ensemble method tailored for small-sample rock image classification. Using a dataset of seven rock categories provided by the BdRace platform, 38 features were extracted across three dimensions—color, texture, and grain size—through grayscale thresholding, HSV color space analysis, gray-level co-occurrence matrix computation, and morphological analysis. The interrelationships among features were evaluated using Spearman correlation analysis and hierarchical clustering, while a voting-based fusion strategy integrated Lasso regularization, gray correlation analysis, and variance filtering for feature dimensionality reduction. The Whale Optimization Algorithm (WOA) was employed to perform global optimization on the base learners, including Random Forest (RF), K-Nearest Neighbors (KNN), Naive Bayes (NBM), and Support Vector Machine (SVM), with Logistic Regression serving as the meta-classifier to construct the final Stacking ensemble model. Experimental results demonstrate that the Stacking method achieves an average classification accuracy of 85.41%, with the highest accuracy for black coal identification (97.16%). Compared to the single models RF, KNN, NBM, and SVM, it improves accuracy by 7.27%, 8.64%, 6.79%, and 6.94%, respectively. Evidently, the Stacking model integrates the strengths of individual models, significantly enhancing recognition accuracy. This research not only improves rock identification accuracy and reduces exploration costs but also advances the intelligent transformation of geological exploration, demonstrating considerable engineering application value. Full article

Multiaxial low-cycle fatigue (MLCF) behavior of laser powder bed fused (L-PBF) Ti-6Al-4V was systematically investigated with four building direction (BD) in this paper. Proportional and non-proportional strain-controlled MLCF tests characterized cyclic softening and fracture mechanisms. L-PBF Ti-6Al-4V exhibits three-stage cyclic softening with occasional initial hardening, while non-proportional softening predominates, contrasting with conventional titanium alloys. Macro-micro characterization reveals that defect density and cleavage morphology strongly influence fatigue performance across BD. Fatigue life was predicted using analytical models (FS and KBMP) and a hybrid physics- and data-driven VAE-ANN model. While the KBMP model improves predictions over FS, both fail to fully account for BD effects. Incorporating macro-micro features, the VAE-ANN model achieves highly accurate MLCF life predictions within 10% error. These results highlight the critical roles of BD and microstructural characteristics in governing the MLCF behavior of L-PBF Ti-6Al-4V. Full article

Background/Objectives: Late presentations of advanced hepatocellular carcinoma (HCC) indicate a lack of detection of underlying cirrhosis and a need to identify clinical and socioeconomic risk factors contributing to early-stage HCC recognition. This study tested associations between early diagnostics of HCC and demographic, socioeconomic, clinical, and healthcare-related indicators. Methods: A retrospective analysis of clinical data accumulated between February 2018 and February 2024 was completed at a quaternary care centre (South Australia). Results: We identified 388 cases of newly diagnosed HCC during a six-year period. There were 131 (33.7%) patients with early-stage (Barcelona clinic liver cancer (BCLC) stage 0–A) and 257 (66.3%) patients with late-stage (BCLC B–D) HCC. Late-stage HCC was found in 66.3% of patients, with half of the cohort not having a diagnosis of cirrhosis at the time of HCC detection. A retrospectively calculated Fibrosis Index (FIB-4) of >3.25 was present in nearly half of patients with newly diagnosed HCC with no prior diagnosis of cirrhosis. Engagement with healthcare (p < 0.05), a history of liver cirrhosis (p < 0.001), and gastroenterologist-led care with surveillance programmes (p < 0.001) was associated with early-stage presentation and curative treatment. Late-stage HCC was associated with male sex (p = 0.041), failing to attend appointments (p < 0.001), and liver function tests ordered by general physicians (p = 0.002) or non-gastroenterologist specialists (p = 0.023). Logistic regression analysis indicated that engaging in a surveillance programme, assessment by a gastroenterologist, and Model for End-Stage Liver Disease scores were important factors contributing to early detection of HCC; the area under the curve for this model on the ROC analysis was 0.892 (95% CI 0.855–0.929). Conclusions: Better cirrhosis detection is required, given that 60% of patients had a retrospectively calculated FIB-4 > 3.25. Routine use of non-invasive scores by all healthcare providers may increase engagement with surveillance and improve HCC screening. Full article

Zinc (Zn²⁺) is a trace element essential for its catalytic, antioxidant, and immunomodulatory roles extending to synaptic signalling in the central nervous system. In this narrative review, we aim to offer the reader evidence linking perturbations of the Zn²⁺ homeostasis, including deficiency, excess, or transportation anomalies, to neuropsychiatric conditions such as Alzheimer’s disease (AD), Parkinson’s disease (PD), autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD). A targeted, unsystematic PubMed search followed by an extensive pearl-growing strategy was applied to further augment study selection based on the extensive expertise of study authors. Overall, most of the evidence currently available suggests a modest benefit for a Zn²⁺ supplement of around 25–30 mg/day as an augmentation to MDD treatment, with potential benefits of smaller magnitude in paediatric ADHD. Evidence for perturbations of Zn²⁺ as a biomarker of risk for these neuropsychiatric disorders remains unconvincing. The role of Zn²⁺ supplements in the treatment of the selected conditions remains largely unknown due to the lack of specific, randomised controlled trials conducted to explore their efficacy. The long-term safety, optimal doses for specific applications, and the exploration of possible biomarkers to stratify patient selection to identify the optimal candidate for Zn²⁺ supplements remain unanswered questions. Full article

The Wushan Loess, situated in the Yangtze Three Gorges region of China, represents the southernmost aeolian loess deposit in China and provides critical insights into Late Pleistocene paleoenvironmental conditions and East Asian monsoon dynamics. Despite its significance, the genesis and provenance of this unique loess deposit remain controversial. This study employs an integrated multi-proxy approach combining detrital zircon U-Pb geochronology, optically stimulated luminescence (OSL) dating, and detailed grain size analysis to systematically investigate the provenance and depositional mechanisms of the Wushan Loess. Three representative loess–paleosol profiles (Gaotang-GT, Badong-BD, and Zigui-ZG) were analyzed, yielding 17 OSL ages, 729 grain size measurements, and approximately 420 analyses per profile were conducted, yielding 1189 valid ages (GT 406, BD 391, ZG 402). OSL chronology constrains the deposition period to 18–103 ka (Marine Isotope Stages 2–5), coinciding with enhanced East Asian winter monsoon activity during the Last Glacial period. Grain size analysis reveals a dominant silt fraction (modal size: 20–25 μm) characteristic of aeolian transport, with coarse silt (20–63 μm) averaging 47.1% and fine silt (<20 μm) averaging 44.2% of the sediments. Detrital zircon U-Pb age spectra exhibit consistent major peaks at 200–220 Ma, 450–500 Ma, 720–780 Ma, and 1800–1850 Ma across all profiles. Kernel Density Estimation (KDE) and Multi-Dimensional Scaling (MDS) analyses indicate a mixed provenance model. Non-negative least squares (NNLS) unmixing confirms this quantitative source apportionment., dominated by proximal contributions from the upper Yangtze River basin (including the Three Gorges area and Sichuan Basin, ~65%–70%), supplemented by distal dust input from the Loess Plateau and northern Chinese deserts (~30%–35%). This study establishes for the first time a proximal-dominated provenance model for the Wushan Loess, providing new evidence for understanding southern Chinese loess formation mechanisms and Late Pleistocene East Asian monsoon evolution. Full article

Background/Objectives: Proficiency in moral reasoning is essential for healthcare providers to successfully navigate ethically challenging decision-making. It is critical that student dentists about to enter practice have well-developed moral reasoning skills to ensure optimal patient care. The aim of the present study was to investigate the moral reasoning ability of students undertaking their final year of the undergraduate Bachelor of Dental Surgery (BDS) programme at the University of Adelaide (UofA) in Australia. Methods: Sixty-six final-year BDS students were invited to participate in an e-survey which included the Defined Issues Test 2 (DIT-2), a validated instrument for measuring moral reasoning. Calculated DIT-2 scores incorporatedthe postconventional (P) score and N2 score. Data analysis of demographic details and scores related to the DIT-2 included the use of t-tests, Mann–Whitney and the Spearman rank correlation coefficient tests. Results: A response rate of 45.5% (n = 30) was recorded. The mean (95% CI) P and N2 scores were 37.80 (32.04, 43.56) and 42.12 (37.72, 46.53), respectively. Scores for females and for those who had undertaken the majority of their pre-BDS studies outside of Australia and New Zealand were higher, but the differences were not statistically significant (p > 0.05). A Spearman Correlation Coefficient test indicated that age was moderately associated (r = 0.41; 95% CI: 0.01, 0.65; p = 0.04) with N2 scores. Conclusions: Moral reasoning scores were comparable to studies among similar cohorts conducted in other countries but were less than the scores considered optimal for a healthcare provider to proficiently manage challenges to ethical decision-making. Consideration should be given to the introduction of appropriate formal training in ethics to better manage these challenges. Full article

Timely detection of the spatial distribution of building damage in the immediate aftermath of a disaster is essential for guiding emergency response and recovery strategies. In January 2025, a large-scale wildfire struck the Los Angeles metropolitan area, with Altadena as one of the most severely affected regions. A timely and comprehensive understanding of the spatial distribution of building damage is essential for guiding rescue and resource allocation. In this study, we adopted the MambaBDA framework, which is built upon Mamba, a recently proposed state space architecture in the computer vision domain, and tailored it for spatio-temporal modeling of disaster impacts. The model was trained on the publicly available xBD dataset and subsequently applied to evaluate wildfire-induced building damage in Altadena, with pre- and post-disaster data acquired from WorldView-3 imagery captured during the 2025 Los Angeles wildfire. The workflow consisted of building localization and damage grading, followed by optimization to improve boundary accuracy and conversion to individual building-level assessments. Results show that about 28% of the buildings in Altadena suffered Major or Destroyed levels of damage. Population impact analysis, based on GHSL data, estimated approximately 3241 residents living in Major damage zones and 31,975 in Destroyed zones. These findings highlight the applicability of MambaBDA to wildfire scenarios, demonstrating its capability for efficient and transferable building damage assessment. The proposed approach provides timely information to support post-disaster rescue and recovery decision-making. Full article

Background/Objectives: Evidence on the use of biologics in severe eosinophilic asthma (SEA) associated with persistent airflow obstruction (PAO) status and smoking habits is scarce. As these factors could potentially impact real-world benralizumab clinical effects, this study was conceived to provide a deeper understanding of these specific patient subgroups. Methods: This observational, retrospective ORBE II study (NCT04648839) involved 204 adults with uncontrolled SEA treated with benralizumab in Spain. In this analysis, patients were categorized by baseline PAO status (PAO− or PAO+) and smoking habit (SMK− or SMK+) to assess baseline characteristics and clinical outcomes after one year of follow-up. The impact of smoking on PAO+ patients was also analyzed. Results: This analysis showed that 75.6% of patients had PAO and 36.9% were former/current smokers. After benralizumab, both PAO subgroups showed substantial improvement, with higher proportions of PAO+ patients achieving prespecified clinical objectives. Benralizumab benefited patients regardless of their smoking habit, though patients who had never smoked exhibited slightly fewer exacerbations, greater improvements in ACT scores, and a higher proportion achieved a ≥100 mL increase in pre-BD FEV₁. An analysis of the impact of smoking on the PAO+ subgroup showed that while a similar proportion of patients were able to eliminate exacerbations and discontinue OCS use, higher percentages of PAO+SMK− patients achieved an ACT score ≥ 20 and a ≥100 mL increase in pre-BD FEV₁. Conclusions: PAO is common among patients included in ORBE II, and a considerable proportion are former/current smokers. This study showed that clinical outcomes improved after benralizumab initiation regardless of these factors, highlighting its potential as a valuable therapeutic option for managing SEA. These findings also emphasize the need for further real-world evidence to optimize treatment strategies for diverse patient subgroups. Full article

Background/Objectives: We aimed to determine the prevalence of bipolar disorder (BD) in a Spanish disabled adult population (DAP), the differences in sociodemographic and clinical variables in the DAP with and without BD, and the factors associated with self-reported health status in the DAP with BD. Methods: This is a population-based cross-sectional study including N = 11,130 adults from the “Disability, Personal Autonomy and Dependency Situations Survey 2020” carried out in Spain by the Spanish National Institute of Statistics (INE). We used secondary data with self-reported information on sociodemographic, mental and physical health status (HS), difficulties in daily living, and use of health services. We estimated the prevalence of BD in the DAP. Bivariate analyses were carried out to compare the DAP with/without BD and multinomial logistic regression was performed to analyse factors associated with self-reported HS in the DAP with BD. Results: The prevalence of BD in the DAP is 2.42%. People with BD were younger, showed more anxiety and musculoskeletal diseases, reported worse HS, performed less physical and social activities, had more social difficulties and less contact with other people, used more health services, and reported discrimination due to their disability. Older age (OR = 1.030) and the presence of anxiety (OR = 4.479) were related to worse self-reported HS. Conclusions: BD is present in 2.42% of the Spanish DAP with significant consequences for their HS. Our findings summarise some of the main factors that characterise the BD population with disability versus those without BD and show that anxiety is an important factor affecting the perception of HS. Full article

Napping is recognized as a strategy to enhance athletic performance. However, the optimal timing and duration for maximizing its benefits remain unclear. This study investigated the effects of a 90 min nap at different times on physical performance, psycho-cognitive responses, and perceived recovery in trained youth male athletes. Fourteen athletes (18 ± 1 years) completed four conditions in a randomized crossover design: (1) No-nap-13h, (2) No-nap-15h, (3) Nap-13h, and (4) Nap-15h. After each condition, athletes performed a 5 m shuttle run test (5mSRT) and were assessed on best distance (BD), total distance (TD), and fatigue index (FI). Ratings of perceived exertion (RPE) were recorded after each 5mSRT repetition, whereas muscle soreness (DOMS) and recovery (PRS) were assessed post-test and 24 h later. The digit cancelation test (DCT), feeling scale (FS), Stanford Sleepiness Scale (SSS), and Hooper Questionnaire evaluated sleep quality and psycho-cognitive state. Results showed that the athletes felt greater sleepiness before Nap-15h and after Nap-13h versus the no-nap conditions. TD was higher in Nap-13h than Nap-15h (p = 0.001) and No-nap-15h (p = 0.0009). BD was higher in Nap-13h versus No-nap-15h and No-nap-13h, while RPE was higher in Nap-13h versus No-nap-13 h, Nap-15h, and No-nap-15h (all, p < 0.05). DCT scores were also higher in Nap-13h. No significant effects were found for FI, FS, or Hooper. In conclusion, a 90 min nap at 13:00 was more effective than a later nap or no nap in improving performance and recovery, suggesting benefits for afternoon training or competitions. Full article

To address the urgent demand for high-precision positioning in power industry operations within sparse reference station areas, this paper proposes a real-time kinematic positioning method integrating BeiDou multi-antenna Precise Point Positioning–Real-Time Kinematic (PPP-RTK) with inertial measurement unit (IMU) assistance. By combining the strengths of Precise Point Positioning (PPP) and Real-Time Kinematic (RTK) technologies, we establish a multi-antenna observation model based on State Space Representation (SSR), incorporating satellite-based augmentation signals and atmospheric correction information from sparse reference station networks. Lie group theory is employed to enhance the Extended Kalman Filter (EKF) for simultaneous estimation of position, attitude, and ambiguity parameters. The integration of IMU measurements significantly improves robustness against environmental interference in dynamic scenarios. Experimental results demonstrate average positioning errors of 3.12 cm, 3.71 cm, and 6.23 cm in the East, North, and Up (ENU) directions, respectively, with an average convergence time of 1.62 min. Compared with non-IMU-augmented single-antenna PPP-RTK solutions, the proposed method achieves accuracy improvements up to 59.6% while maintaining stability in signal-occluded environments. This approach provides centimeter-level real-time positioning support for critical power grid operations in remote areas such as desert and Gobi regions, including infrastructure inspection and precise tower assembly, thereby significantly improving the efficiency of intelligent grid operation and maintenance. Full article

The undifferenced and uncombined (UDUC) model preserves raw code and carrier-phase observations for each frequency, avoiding differencing or ionosphere-free combinations. This approach enables the direct estimation of atmospheric parameters. However, the stochastic characteristics of these parameters, particularly ionospheric delay, are often oversimplified or based on empirical assumptions, limiting the accuracy and convergence speed of Precise Point Positioning (PPP). To address this issue, this study introduces a stochastic constraint model based on the power spectral density (PSD) of ionospheric variations. The PSD describes the distribution of ionospheric delay variance across temporal frequencies, thereby providing a physically meaningful constraint for modeling their temporal correlations. Integrating this PSD-derived stochastic model into the UDUC framework improves both ionospheric delay estimation and PPP performance, especially under disturbed ionospheric conditions. This paper presents a BDS PPP/PPP-AR method that estimates the ionospheric power spectral density (IPSD) in real time. Vondrak smoothing is applied to suppress noise in ionospheric observations before IPSD estimation. Experimental results demonstrate that the proposed approach significantly improves convergence time and positioning accuracy. Compared to the empirical IPSD model, the PPP mode using the estimated IPSD reduced horizontal and vertical convergence times by 11.1% and 13.2%, and improved the corresponding accuracies by 15.7% and 12.6%, respectively. These results confirm that real-time IPSD estimation, coupled with Vondrak smoothing, establishes an adaptive and robust ionospheric modeling framework that enhances BDS PPP and PPP-AR performance under varying ionospheric conditions. Full article

Binge drinking (BD) is defined as a pattern of alcohol consumption that results in a blood alcohol concentration of 0.08 g/dL or higher, typically achieved after consuming approximately 70 g of pure alcohol (about five drinks for men) or 56 g (about four drinks for women) within roughly two hours. It is highly prevalent among adolescents and young adults and has significant physical, psychological, and social consequences. Despite numerous interventions to reduce BD, there is limited systematic evidence on their effectiveness. This study presents a systematic review of randomized controlled trials (RCTs) evaluating interventions to reduce BD, focusing on their impact on frequency, intensity, and associated physical, psychological, or social outcomes. The review followed PRISMA 2020, and the protocol was registered with PROSPERO (CRD42024623481). A comprehensive search was conducted in multidisciplinary and specialized databases. Included studies were RCTs targeting BD in clinical or community populations of any age. Non-empirical and observational studies, or studies not specifically focused on BD were excluded. The risk of bias was assessed using RoB 2, and a total of 21 studies (N = 14,754 participants) were included, showing high variability in design, format, and theoretical basis. Brief, individual digital interventions predominated, although face-to-face group and multimodal interventions proved more effective. Eleven studies reported significant reductions in BD frequency or prevalence; fewer addressed intensity. Interventions based on motivational and cognitive behavioral approaches, especially in structured programmes with prolonged follow-up, were the most effective. Improvements were observed in psychosocial variables (e.g., negative consequences, self-efficacy, expectations, social norms, and intention to consume), but not in physical health or consumption of other substances. Most studies had a moderate risk of bias, and few demonstrated long-term effects. More robust, comparative, and longitudinal studies are needed. Full article