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Reanalysis data fusion-based tropical cyclone formation prediction network
Abstract This paper proposes a tropical cyclone formation prediction network based on pyramid attention feature extraction and multi-scale feature fusion, aiming to enhance the prediction of whether tropical cloud cluster (TCC) precursors intensify to tropical storm (TS) strength by integrating multi-source reanalysis data. First, reanalysis data from ERA5 and NCEP/NCAR are represented as images at different scales and labeled according to tropical cyclone (TC) formation events derived from the TCC and IBTrACS datasets. The labels include information on whether TC formation occurred and its location. Then, a feature extraction module based on a Pyramid Attention Mechanism (PAM) is designed to extract features related to TC formation. Next, the features at different scales are input into a PAM-based feature fusion module that dynamically generates weights for different features to perform weighted fusion and unify the feature scales. Finally, a lightweight Convolutional Neural Network (CNN) is designed as the prediction module to predict TC formation occurrence and location. Experimental results over five independent data splits show that at a lead time of 24 hours, the proposed method achieves a Probability of Detection (POD) of $$0.865 \pm 0.012$$ , a False Alarm Ratio (FAR) of $$0.326 \pm 0.016$$ , and a location prediction Root Mean Square Error (RMSE) of $$0.795 \pm 0.033$$ grid units ( $$\approx$$ 437 km), demonstrating competitive performance in balancing POD and FAR. Ablation studies confirm the contribution of each proposed module to overall performance.
Proteomics risk scores and mortality in heart failure: Generalizability across populations
Background Heart failure (HF) is a complex syndrome with high mortality. Proteomics risk scores have shown promise in predicting mortality beyond guideline-recommended clinical tools. It is crucial to understand how risk scores generated by different methods and populations perform, and whether they highlight the same protein targets relevant to outcomes. Methods To examine whether the study design impacts proteomics scores designed to predict mortality in HF, we evaluated three published risk scores that used the SomaScan assay to measure plasma proteins in a community cohort, clinical trial, and registry. Each score was assessed in the aforementioned community cohort and Cox models examined the association of a 1-standard deviation increase in score with mortality, with and without adjustment for clinical covariates. Performance of each risk score to predict 5-year mortality risk was assessed using calibration plots and time-dependent area under the curve and compared with a clinical model. Results Risk scores were similarly distributed and moderately correlated (Pearson correlation coefficient = 0.59–0.76). A 1-standard deviation increase in each risk score was associated with an increased risk of all-cause mortality: community cohort (HR = 2.70, 95% CI: 2.50–2.91); clinical trial (HR = 1.76, 95% CI: 1.65–1.88); registry (HR = 1.70, 95% CI: 1.6–1.81). Risk remained after adjustment for clinical covariates, although slightly attenuated, and similar across different ejection fraction categories. All risk scores showed strong calibration across the risk levels, alone, with an average expected over observed ratio ranging between 0.96–1.56. Seven proteins were included in at least two risk scores, with renin being included in all three. Conclusions All three proteomics risk scores improved risk stratification in HF patients beyond guideline recommended clinical tools, independent of study design and ejection fraction. These results demonstrate that proteomics risk scores can enhance risk stratification across the HF syndrome, even when derived from different methods and populations.
pH-responsive delivery of hydrophobic anticancer drugs using boron and nitrogen Co-doped carbon dots as fluorescent nanocarriers
Learning variable-order time fractional diffusion equations using Physics-Informed Neural Networks
This paper introduces a novel approach using physics-informed neural networks (PINNs) to simultaneously solve variable-order time fractional diffusion equations and infer the time-dependent fractional order from data. By embedding the governing equations into the neural network’s loss function, our method achieves high accuracy and flexibility, even with sparse or noisy data. We present a dual-network architecture where one network approximates the solution u ( x , t ) while another learns the fractional order α ( t ) . Numerical experiments demonstrate the effectiveness of our approach, achieving mean squared errors below 10 −4 for solutions and 10 −3 for fractional orders in smooth cases, while also handling noisy data and non-smooth orders robustly.
Cable versus cerclage wire in weber tension band fixation for transverse olecranon fractures: a biomechanical study in a synthetic ulna model
Single-cell transcriptomics identifies ergothioneine as a mitochondrial protector to prevent AKI-to-CKD progression
This study investigates the role and mechanism of ergothioneine (EGT) in mitigating the progression of acute kidney injury (AKI) to chronic kidney disease (CKD). Using a cisplatin-induced mouse model of the AKI-to-CKD transition with EGT intervention, we combined histopathological examination, biochemical assays, and single-cell RNA sequencing (scRNA-seq) to provide evidence that EGT may improve renal function parameters and attenuate renal injury and fibrosis. scRNA-seq analysis revealed that EGT was associated with partial normalization of mitochondria-related gene expression in renal tubular epithelial cells, accompanied by enrichment of oxidative phosphorylation and electron transport chain pathways. Furthermore, our in vitro experiments supported a protective association of EGT with mitochondrial injury-related phenotypes in injured renal tubular epithelial cells, as indicated by reduced reactive oxygen species generation, partial preservation of mitochondrial membrane potential, and increased cellular ATP levels. These findings suggest that EGT may attenuate AKI-to-CKD progression in association with improved mitochondrial homeostasis, offering a potential therapeutic strategy for kidney diseases.
Understanding internet gaming disorder in Mexican university students: prevalence and associated factors
Exploring perceptions towards health and child nutrition: A qualitative study among tribal mothers in Southern Karnataka
Background Malnutrition accounts for nearly one-third of child deaths globally and continues to be a major concern in India. Despite economic progress, undernutrition remains prevalent, with one-third of children underweight and over two-thirds anemic. Within India, marginalized groups such as the Koraga tribe face greater risks due to poverty, limited healthcare access and cultural barriers that compound child health challenges. Understanding maternal perceptions is crucial to effectively address these challenges. Methods In-depth interviews were conducted with Koraga tribal mothers of children aged 5–10 years. Participants were selected using criterion-based purposive sampling to ensure representation across different age groups and household contexts. Interviews were audio-recorded in local languages (Tulu and Kannada), transcribed verbatim, translated into English and analysed inductively using thematic analysis with NVivo software (version 14). Results Twenty Koraga tribal mothers were interviewed between October 2023- March 2024. Thematic analysis revealed five major themes: evolving perceptions of health and wellbeing; nutrition beliefs and practices; hygiene and health promotion; traditional healing with modern care and barriers and community solutions. These findings highlighted key challenges such as limited healthcare access, poverty and educational constraints, while also capturing community-driven strategies including reliance on health workers and government food-schemes. Conclusion Maternal perceptions, shaped by cultural norms and socioeconomic constraints, play a critical role in influencing health and child nutrition in the Koraga community. The findings highlight the need for policy measures that integrate culturally informed nutrition education with strengthened frontline health services, alongside community-based programs involving women’s self-help groups to improve health outcomes in marginalised tribal populations.
Discovery of potential AXL inhibitors using virtual screening, molecular docking, molecular dynamics, molecular mechanics, and in vitro validation
The Andean-Amazonian and Mesoamerican Bioeconomy: A new paradigm for productivity and well-being
Traditional Total Factor Productivity (TFP) metrics often overlook biophysical limits and the depletion of natural capital. This study proposes an alternative paradigm: the Andean-Amazonian Bioeconomy (AAB), which integrates Georgescu-Roegen’s Law of Entropy and ancestral knowledge into an expanded production function. By applying the Malmquist Productivity Index and a Fixed Effects (FE) panel data model, we analyzed a dataset (1995–2024) from six Latin American countries. This approach utilizes the Human Development Index (HDI) as the primary proxy for social welfare. The methodology addresses country heterogeneity and multicollinearity, significantly enhancing the model’s explanatory power to an Adjusted R 2 of 0.695. Our findings reveal a ‘Biocultural Paradox’: where conservation, often viewed as a cost by traditional income-based metric, emerges as vital investment. Our model demonstrate that the preservation of the biocultural fund- represented here as Biocultural Savings [S]- is a positive and highly significant predictor of social well-being ( β = 0.685, p < 0.01), alongside a positive impact from the indigenous population index ( β = 0.015, p < 0.1), suggesting that cultural identity plays a foundational role in regional resilience. We conclude that achieving ‘Vivir Bien’ (Living Well) requires a shift toward indicators that prioritize the biocultural fund -the stock of ancestral knowledge and biodiversity- over mere resource flow. This study provides a scientifically rigorous framework for sustainability policies across the Global South.
Biochar as an enabler for microwave-induced crack healing in asphalt mixtures
Abstract Biochar has attracted increasing attention as a carbon-negative material, including asphalt applications. On the one hand, its impact on the mechanical performance limits its application and might reduce pavement durability. On the other hand, biochar’s microwave-absorbing properties can be used to enable crack healing. In this study, mineral aggregates in an asphalt concrete mixture were partially replaced with biochar at substitution levels of 0%, 2%, 4% and 8% by mass of aggregates. The microwave-induced heating behaviour, fracture resistance and healing performance under repeated damage-healing cycles were systematically investigated. Surface temperature measurements revealed that biochar enhanced microwave energy conversion into heat, although heating rates decreased slightly after repeated damage-healing cycles. Healing efficiency depended on biochar, binder, and air void content, which are closely interlinked. Mixtures containing 2% and 4% biochar by aggregate mass exhibited the highest healing ratios, whereas excessive biochar substitution (8%) resulted in a low and progressively declining healing performance. Notably, the reduction in heating rate under repeated treatment cycles did not affect healing efficiency. These results demonstrate that moderate biochar incorporation into asphalt can enhance microwave-induced healing without compromising cracking resistance, supporting its use in preventive maintenance strategies for asphalt pavements.
Correction: Interpretable machine learning-based real-time sepsis diagnosis
Microbially induced calcite precipitation by a novel alkaliphilic Bacillus albus strain for sustainable self-healing bio-mortar with enhanced mechanical performance and durability
Abstract Micro-crack formation is a major factor limiting the durability of concrete structures. This study investigates a sustainable self-healing approach based on microbially induced calcium carbonate precipitation (MICP). Fifty bacterial isolates were obtained from alkaline soils in Wadi El-Natrun, Egypt, and screened for their ability to precipitate calcium carbonate. Isolate code W39 exhibited the highest activity, producing 0.453 g/100 mL of CaCO₃. Molecular identification by 16 S rRNA sequencing confirmed the strain as Bacillus albus (Accession number: PQ288981). Optimal precipitation occurred at pH 8, with 25 mM CaCl₂ and 20 g/L urea, after seven days of incubation at 30 °C. Instrumental analyses, including scanning electron microscopy (SEM) coupled with an energy-dispersive X-ray (EDX) analyzer, high-resolution transmission electron microscopy (TEM), Fourier-transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), and the N₂ desorption/adsorption isotherm (BET) method, verified that the biogenic CaCO₃ consisted of nanoscale, high-purity calcite. The self-healing potential was evaluated by embedding viable Bacillus albus cells in cement mortar at optical densities (OD₆₀₀) of 0.5, 1.0, and 1.5, and curing in urea-enriched media with varying CaCl₂ concentrations (25–100 mM). Bacterial incorporation significantly enhanced mechanical performance over a 90-day curing period. The optimal dosage depended on Ca²⁺ availability: OD₆₀₀ 1.5 provided the greatest improvement at 25 mM CaCl₂, whereas OD₆₀₀ 0.5 was more effective at 50–100 mM. Microstructural analyses, comprising x-ray diffraction (XRD), differential thermal/thermogravimetric analysis (DTG/TGA), and scanning electron microscopy (SEM), confirmed the formation of additional C–S–H and calcite, resulting in reduced porosity and a denser matrix. The bio-mortar also demonstrated increased durability, including resistance to exposure to MgSO₄ and MgCl₂, as well as thermal stability up to 1000 °C. These findings demonstrate that the indigenous Bacillus albus strain is a promising agent for durable, self-healing bio-concrete. Overall, these results show that microbial incorporation improves the pore system, encourages the formation of more hydrates and CaCO 3 , and creates a more resilient mortar that can withstand extreme thermal exposure.
Losartan shows limited benefit in preclinical models of Geleophysic dysplasia
ViewAdapt-Det: view-adaptive detection for soccer broadcasting videos
Risk of new-onset obstructive sleep apnea up to 4.5 years after COVID-19 in the urban population
Elucidation of physical, structural, optical and luminescence properties of Cr2O3-doped B2O3-TeO2-Li2O-SrO glasses for deep red-light and NIR luminescence applications
Abstract The standard melt quenching technique was used to prepare samples with nominal composition (50-x)B 2 O 3 -15TeO 2 -20Li 2 O-15SrO-xCr 2 O 3 , where 0 < x < 0.5. XRD validates the non-crystalline nature of BTLSC glass. Density and molar volume exhibited an inverse trend, and other physical parameters were calculated. SEM and EDS determined the morphological and elemental composition of the BTLSC samples. The FTIR and Raman spectra explain reduced pentaborate units and caused the production of ortho and pyroborate units, including tetrahedral [CrO 4 ] and octahedral [CrO 6 ] units in the glasses with Cr 2 O 3 incorporation. The UV-Vis absorption band showed redshift from 351 nm to 461 nm, with three major bands at 626 nm, 663 nm, and 701 nm of Cr 3+ (octahedral sites) in the BTLSC glasses. The direct bandgap and indirect bandgap were reduced from 3.44 eV to 2.58 eV and from 3.01 eV to 2.08 eV, respectively. The observed Urbach energy increases from 0.216 eV to 0.266 eV, confirming the distortion in the BTLSC glasses. Furthermore, optical properties were calculated from refractive index and bandgap values. The photoluminescence spectra showed a small narrow band emission at ~ 690 nm and a broad band ~ 750 nm with two excitation wavelengths, ~ 420 nm and ~ 580 nm. The CIE coordinates and CCT values indicate that BTLSC-3 glass is ideal for deep red-light solid-state lighting and NIR luminescence material applications.
Cortical activation during auditory working memory varies with hearing aid use status in age-related hearing loss
Abstract Age-related hearing loss (ARHL) is associated with increased listening effort due to greater cognitive demands needed for supporting effective communication. Verbal working memory (WM) is an important mechanism supporting speech understanding in adults with ARHL. Using functional near-infrared spectroscopy and an auditory N-back task (0-, 1-, 2-back load), we examined whether hearing aid status was associated with cortical activation in adults with ARHL. Three groups were compared: typical-hearing adults, experienced hearing aid users, and newly fitted users. Linear mixed-effects models revealed significant Group × Load interactions across the left superior temporal gyrus (STG), left inferior parietal lobule (IPL), and left dorsolateral prefrontal cortex (DLPFC). Experienced users exhibited accuracy comparable to the typical-hearing adults and showed STG and IPL activation patterns more similar to the typical-hearing group, whereas newly fitted users showed reduced activation under higher WM load. These findings indicate that cortical activity during an auditory N-back task engaging verbal WM differs as a function of hearing aid status and is not explained by aided audibility alone. Overall, experienced users exhibited load-dependent cortical activation patterns that more closely resembled those of typical-hearing adults than newly fitted users during an auditory N-back task.