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Adsorption of copper(II) in biochar-humic acid–water system
Overall Survival with Inavolisib in <i>PIK3CA</i> -Mutated Advanced Breast Cancer
Plastics pollution is surging — the planned UN treaty to curb it must be ambitious
Constructing electrospun 3D liquid metal adhesion channel on stretchable yarns for broad-range strain-insensitivity smart textiles
Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method
Maximum Power Point Tracking (MPPT) is a promising technology for extracting peak power from single or multiple solar modules for improving Photovoltaic (PV) system performance and satisfying economic operation. The tracker should continuously follow the MPP of the PV module at all operating and weather conditions. The Particle Swarm Optimization (PSO) algorithm represents a powerful optimal MPP tracker due to its simplicity and has enhanced greatest exploration characteristics. This article proposes a new technique based on PSO enhanced with Quasi-Newton local search for improving power quality while minimizing oscillation. This tracking process is making the MPPT comparable between high accuracy and fast tracking speed. MPPT proposal algorithm results are compared to the results of the hybrid PSO-P&O algorithm at different operating conditions. The proposed algorithm results show that MPP extraction has been done with a high-speed response and the best efficiency. Moreover, the PSO is enhanced with a Quasi-Newton (QN) local search method for tuning the optimal MPP.
Enhanced spectrum sensing for 5G and LTE signals using advanced deep learning models and hyperparameter tuning
Case 19-2025: A 69-Year-Old Man with Headache and Ataxia
Author Correction: Regulatory genomic circuitry of human disease loci by integrative epigenomics
Author Correction: Caveolae-mediated Tie2 signaling contributes to CCM pathogenesis in a brain endothelial cell-specific Pdcd10-deficient mouse model
Relationship between serum anion gap and mortality in ICU in multiple myeloma patients in the MIMIC database: A retrospective cohort study
Background Serum anion gap has diagnostic value in patients with multiple myeloma, but its association with ICU mortality and threshold value remain unclear. Methods Multiple myeloma patients meeting criteria were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The exposure factor was serum anion gap, and the outcome was ICU in-hospital mortality. Multivariable-adjusted Cox regression, curve fitting, and forest plots were used to evaluate the relationship between anion gap and ICU mortality in multiple myeloma patients. Results A total of 323 eligible subjects were included (206 males [63.8%], 117 females [36.2%]). Multivariable Cox regression showed that each 1-unit increase in AG was associated with a 7% increased mortality risk (HR = 1.07, 95%CI = 1.01–1.14, P = 0.032). Curve fitting revealed a nonlinear relationship between anion gap and ICU mortality (nonlinear P = 0.038), with the lowest risk at 15.29 mmol/L. Incorporating AG into traditional risk factor models improved mortality prediction (P = 0.038). Conclusion Serum anion gap exhibits a nonlinear relationship with ICU mortality in multiple myeloma patients, with the lowest risk observed at approximately 15.29 mmol/L.
NFATc1 facilitates hepatocellular carcinoma progression by regulating the senescence-associated secretory phenotype
Juvenile Idiopathic Arthritis
Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery
Abstract While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence (AI) technologies to explore the predictive value of whole exome sequencing in forecasting clinical outcomes following surgery for congenital heart defects (CHD). We report results for a prospective observational cohort study of 2,253 CHD patients from the Pediatric Cardiac Genomics Consortium with a broad range of complex heart defects, pre- and post-operative clinical variables and exome sequencing. Damaging genotypes in chromatin-modifying and cilia-related genes are associated with an elevated risk of adverse post-operative outcomes, including mortality, cardiac arrest and prolonged mechanical ventilation. The impact of damaging genotypes is further amplified in the context of specific CHD phenotypes, surgical complexity and extra-cardiac anomalies. The absence of a damaging genotype in chromatin-modifying and cilia-related genes is also informative, reducing the risk for some adverse postoperative outcomes. Thus, genome sequencing enriches the ability to forecast outcomes following congenital cardiac surgery.
Increase trajectories of tendon micro vibration intensity during ankle plantar flexion: A longitudinal data analysis using latent curve models
We focus on fine vibrations originating from tendons (Mechanotendography: MTG) as a novel method for quantifying muscle activity. Quantifying muscle activity using MTG can enable daily and long-term continuous measurements, which have been challenging for electromyography (EMG) and mechanomyography (MMG). However, the detailed trajectory of MTG increase relative to exerted muscle strength has not been clarified, nor has the mechanism of MTG generation. Our research has two objectives. The first is to clarify the detailed relationship between exerted muscle strength levels and MTG through statistical modeling. The second is to establish a highly accurate hypothesis concerning the mechanism of MTG generation based on the modeling results and physiological knowledge. We focused on the Achilles tendon to study these two objectives. Experiments were conducted on 62 participants, and MTG data were obtained at various levels of exerted muscle strength. The obtained data were structured into a longitudinal data format representing the trajectory of MTG increase with increasing exerted muscle strength. We used latent curve models (LCM) to identify this structure. By applying various LCMs to explore an optimal model, we found that the quadratic LCM received the best fit for females, while the piecewise linear LCM with a breakpoint at 50% exerted muscle strength received the best fit for males. Notably, a significant sex difference was observed in the rate of increase in MTG at low levels of exerted muscle strength. These results suggest that MTG is caused by fine vibrations generated by muscle fiber contractions, and these fine vibrations are transmitted to the tendons connected to the muscles, where they are observed. Future research will focus on verifying this hypothesis through increased time points and physiological experiments.
Study of payload calculation and motion prediction for unpowered diving and floating of deep-sea manned submersible
Transforming Health Care — Shared Commitments for a Learning Health System
Nonlocal electrical detection of reciprocal orbital Edelstein effect
Abstract The orbital Edelstein effect and orbital Hall effect, where a charge current induces a nonequilibrium orbital angular momentum, offer a promising method for efficiently manipulating nanomagnets using light elements. Despite extensive research, understanding the Onsager’s reciprocity of orbital transport remains elusive. In this study, we experimentally demonstrate the Onsager’s reciprocity of orbital transport in an orbital Edelstein system by utilizing nonlocal measurements. This method enables the precise identification of the chemical potential generated by orbital accumulation, avoiding the limitations associated with local measurements. We observe that the direct and inverse orbital-charge conversion processes produce identical electric voltages, confirming Onsager’s reciprocity in orbital transport. Additionally, we find that the orbital decay length, approximately 100 nm at room temperature, is independent of the Cu thickness and decreases with decreasing temperature, revealing a distinct contrast to the spin transport behavior. Our findings provide valuable insights into both the reciprocity of the charge-orbital interconversion and the nonlocal correlation of orbital degree of freedom, laying the ground for orbitronics devices with long-range interconnections.
Influence of dietary composition on the nutritional profile and feed conversion efficiency of Tenebrio molitor
Insects, such as mealworm larvae, are promising sustainable protein sources due to their high reproductive ability, nutritional value, efficient organic matter conversion, cost-effective rearing, and minimal environmental impact. This study evaluates the nutritional composition and feed conversion efficiency of mealworm larvae reared on seven diets: W (100% wheat bran) as a control, A (50% wheat bran + 50% barley bran), B (75% wheat bran + 25% barley bran), C (50% wheat bran + 50% chickpea bran), D (75% wheat bran + 25% chickpea bran), E (50% wheat bran + 50% corn bran), and F (75% wheat bran + 25% corn bran). Results showed that diet C yielded the highest protein content and feed conversion efficiency, while diet B had the lowest. Fat content peaked in diets B and F. Variations in fiber, carbohydrates, ash, moisture, and minerals were also observed. Factors such as food intake, digestibility, and conversion ratios varied significantly among diets. The study highlights the critical role of dietary composition in optimizing mealworm larvae’s nutritional profile and feed efficiency, offering a sustainable, cost-effective protein source for poultry and broilers. These findings support the strategic use of cereal brans to enhance feed quality, reduce costs, and improve scalability in insect farming, contributing to the sustainable production of animal protein.