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Assessment of hydrological loading displacement from GNSS and GRACE data using deep learning algorithms

Ion Irradiation-Induced Coordinatively Unsaturated Zn Sites for Enhanced CO Hydrogenation

AI-enabled diagnosis and localization of myocardial ischemia and coronary artery stenosis from magnetocardiographic recordings

Vibrationally Assisted Tunneling through the Bread of a Proton Sandwich─Connections to Dynamic Matching

Metformin inhibits the growth of SCLC cells by inducing autophagy and apoptosis via the suppression of EGFR and AKT signalling

High-Pressure Effects on an Octa-Hydrated Curium Complex: An Experimental and Theoretical Investigation

Advancing triple-negative breast cancer treatment through peptide decorated solid lipid nanoparticles for paclitaxel delivery

Comparison of a Nonheme Iron Cyclopropanase with a Homologous Hydroxylase Reveals Mechanistic Features Associated with Distinct Reaction Outcomes

GPU-accelerated simulated annealing based on p-bits with real-world device-variability modeling

Cathode Design Based on Nitrogen Redox and Linear Coordination of Cu Center for All-Solid-State Fluoride-Ion Batteries

LSTM and ResNet18 for optimized ambulance routing and traffic signal control in emergency situations

Total Synthesis of DMOA-Derived Meroterpenoids: Achieving Selectivity in the Synthesis of (+)-Berkeleyacetal D and (+)-Peniciacetal I

The correlation between the atherogenic index of plasma and the severity of coronary artery disease in acute myocardial infarction patients under different glucose metabolic states

A new method for evaluating the coordinated relationship between vegetation greenness and urbanization

Viologen-Radical-Driven Hydrogen Evolution from Water Catalyzed by Co-NHC Catalysts: Radical Scavenging by Nitrate and Volmer-Heyrovsky-like CPET Pathway

Durability and microstructure of polymer-based cement joint sealant

Abstract To promote the engineering application of polymer-based cement joint sealant (PCJS), the durability of PCJS was studied by testing the bonding, tensile and shear properties of PCJS under different service conditions. The results show that PCJS has excellent water resistance, acid/alkali corrosions resistance, UV aging resistance and low temperature resistance. The retention rate of bonding property of PCJS can achieve 85%. After water soaking, dry–wet cycle, acid/alkali corrosion, the retention rates of tensile and shear properties of PCJS can achieve 80%. After UV aging and low temperature treatment, the tensile and shear properties of PCJS are improved. After gasoline corrosion and high temperature treatment, the retention rates of tensile and shear properties of PCJS exhibit larger than 60%. The durability indexes of PCJS fulfill the technical requirements, and PCJS exhibits even more superior properties. Consequently, PCJS can be applied to joint engineering of cement concrete pavement.

Ensemble fuzzy deep learning for brain tumor detection

Abstract This research presents a novel ensemble fuzzy deep learning approach for brain Magnetic Resonance Imaging (MRI) analysis, aiming to improve the segmentation of brain tissues and abnormalities. The method integrates multiple components, including diverse deep learning architectures enhanced with volumetric fuzzy pooling, a model fusion strategy, and an attention mechanism to focus on the most relevant regions of the input data. The process begins by collecting medical data using sensors to acquire MRI images. These data are then used to train several deep learning models that are specifically designed to handle various aspects of brain MRI segmentation. To enhance the model’s performance, an efficient ensemble learning method is employed to combine the predictions of multiple models, ensuring that the final decision accounts for different strengths of each individual model. A key feature of the approach is the construction of a knowledge base that stores data from training images and associates it with the most suitable model for each specific sample. During the inference phase, this knowledge base is consulted to quickly identify and select the best model for processing new test images, based on the similarity between the test data and previously encountered samples. The proposed method is rigorously tested on real-world brain MRI segmentation benchmarks, demonstrating superior performance in comparison to existing techniques. Our proposed method achieves an Intersection over Union (IoU) of 95% on the complete Brain MRI Segmentation dataset, demonstrating a 10% improvement over baseline solutions.

Long term outcomes of patients with chronic kidney disease after COVID-19 in an urban population in the Bronx

Abstract We investigated the long-term kidney and cardiovascular outcomes of patients with chronic kidney disease (CKD) after COVID-19. Our retrospective cohort consisted of 834 CKD patients with COVID-19 and 6,167 CKD patients without COVID-19 between 3/11/2020 to 7/1/2023. Multivariate competing risk regression models were used to estimate risk (as adjusted hazard ratios (aHR) with 95% confidence intervals (CI)) of CKD progression to a more advanced stage (Stage 4 or 5) and major adverse kidney events (MAKE), and risk of major adverse cardiovascular events (MACE) at 6-, 12-, and 24-month follow up. Hospitalized COVID-19 patients at 12 and 24 months (aHR 1.62 95% CI[1.24,2.13] and 1.76 [1.30, 2.40], respectively), but not non-hospitalized COVID-19 patients, were at higher risk of CKD progression compared to those without COVID-19. Both hospitalized and non-hospitalized COVID-19 patients were at higher risk of MAKE at 6-, 12- and 24-months compared to those without COVID-19. Hospitalized COVID-19 patients at 6-, 12- and 24-months (aHR 1.73 [1.21, 2.50], 1.77 [1.34, 2.33], and 1.31 [1.05, 1.64], respectively), but not non-hospitalized COVID-19 patients, were at higher risk of MACE compared to those without COVID-19. COVID-19 increases the risk of long-term CKD progression and cardiovascular events in patients with CKD. These findings highlight the need for close follow up care and therapies that slow CKD progression in this high-risk subgroup.

Suture versus stapler in distal pancreatectomy and its impact on postoperative pancreatic fistula

Exercise reduces the risk of falls in women with polypharmacy: secondary analysis of a randomized controlled trial

Abstract Polypharmacy has previously been found to increase and exercise interventions to reduce the risk of falls and fall-related injuries. In this study, women who had four or more regular medications benefitted the most from the exercise intervention and had the lowest fall risk compared to the reference group. Fall injuries among older people cause significant health problems with high societal costs. Previously, some exercise interventions have been found to reduce the number of falls and related injuries. We studied how different levels of medication use affect the outcome of an exercise intervention in terms of preventing falls. This exercise RCT involved 914 women born in 1932–1945 and randomly assigned to the intervention (n = 457) and control (n = 457) groups. Both groups participated in functional tests three times during the study. Baseline self-reported prescription drug use was trichotomized: 0–1, 2–3, and ≥ 4 drugs/day (i.e. polypharmacy group). We used Poisson regression for follow-up fall risk and Kaplan-Meier survival analysis for fractures. During follow-up, 1380 falls were reported, 739 (53.6%) resulting in an injury and pain and 63 (4.6%) in a fracture. Women with polypharmacy in the intervention group had the lowest fall risk (IRR 0.713, 95% CI 0.586–0.866, p = 0.001) compared to the reference group that used 0–1 medications and did not receive the intervention. Overall, the number of medications associated with the fall incidence was only seen in the intervention group. However, the number of medications was not associated with fractures in either of the groups. Weaker functional test results were associated with polypharmacy in the control group. The most prominent decrease in fall risk with exercise intervention was seen among women with polypharmacy. Targeting these women might enhance fall prevention efficacy among the aging population. Trial Registration: The study has been registered in ClinicalTrials.gov. Trial registration number NCT02665169. Register date 27/01/2016.