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Analyzing the neural wave structures in the field of neuroscience
Optimized design and sizing of wireless magnetic coupling stage for electric vehicle to grid V2G charging station
Fast and efficient method for parallel construction of targeted exome and methylome single-stranded DNA sequencing libraries
An accurate DNA and RNA based targeted sequencing assay for clinical detection of gene fusions in solid tumors
Dapagliflozin inhibits ferroptosis and ameliorates renal fibrosis in diabetic C57BL/6J mice
Smooth endoplasmic reticulum aggregates in human oocytes are related to female infertility etiology and diminished reproductive outcomes
Isotopes (δ2H) in wings and stored lipids of fall migratory monarch butterflies (Danaus plexippus) provide insights into population structure and nectaring origins
Enhanced Mamba model with multi-head attention mechanism and learnable scaling parameters for remaining useful life prediction
Research on the optimal scheduling of a multi-storage combined integrated energy system based on an energy supply grading strategy
Fabrication of biosynthesized nickel ferrites nanoparticles and evaluation of their insecticidal efficacy on beetles (Blaps polychresta) testicular integrity
Abstract Green synthesis of nanoparticles has emerged as a significant strategy to develop effective and eco-friendly insecticide agents to combat insecticide resistance and preserve environmental integrity and biodiversity. This study was thus designed to fabricate novel green synthesized NiFe2O4 nanoparticles (NiFe NPs) and investigate their potential insecticidal effects for the first time using Blaps polychresta beetle as an agricultural coleopteran pest model. Therefore, we prepared NiFe NPs following the hydrothermal synthesis procedure in the presence of lemon juice. The physiochemical characteristics of NiFe NPs were investigated employing SEM, TEM, FT-IR, XRD, TGA, VSM, and UV-Vis analysis. The lowest and most effective dose of NiFe NPs against male beetles was ascertained at a concentration of 0.03 mg/g body weight, reporting 67% mortality after 48 h. To study the insecticidal impact of NiFe NPs, EDX analysis demonstrated the bioaccumulation of NiFe NPs in testicular tissues of beetles, leading to pathophysiological consequences. Precisely, the oxidative stress incited by NiFe NPs led to disturbance of the antioxidant defense system, which was defined by augmentation of lipid peroxidation and suppression of antioxidant enzymes. Furthermore, the comet assay exhibited remarkable DNA impairment, while flow cytometry analysis showed substantial cellular necrosis and apoptosis in NiFe NPs-treated beetles compared to control insects. In correlation with these findings, several aberrations in the histological and ultrastructure attributes of testicular tissues were perceived, including impaired follicular and cyst walls, deteriorated parietal cells, necrosis, and vacuolations. These results implied that NiFe NPs triggered oxidative injury in the testes, resulting in male reproductive system dysfunction. Altogether, our findings accentuate the potential application of NiFe NPs as nanopesticides, paving the way for the sustainable and cost-effective management of insect pests in agriculture.
OVision A raspberry Pi powered portable low cost medical device framework for cancer diagnosis
Smart distributed data factory volunteer computing platform for active learning-driven molecular data acquisition
Abstract This paper presents the smart distributed data factory (SDDF), an AI-driven distributed computing platform designed to address challenges in drug discovery by creating comprehensive datasets of molecular conformations and their properties. SDDF uses volunteer computing, leveraging the processing power of personal computers worldwide to accelerate quantum chemistry (DFT) calculations. To tackle the vast chemical space and limited high-quality data, SDDF employs an ensemble of machine learning (ML) models to predict molecular properties and selectively choose the most challenging data points for further DFT calculations. The platform also generates new molecular conformations using molecular dynamics with the forces derived from these models. SDDF makes several contributions: the volunteer computing platform for DFT calculations; an active learning framework for constructing a dataset of molecular conformations; a large public dataset of diverse ENAMINE molecules with calculated energies; an ensemble of ML models for accurate energy prediction. The energy dataset was generated to validate the SDDF approach of reducing the need for extensive calculations. With its strict scaffold split, the dataset can be used for training and benchmarking energy models. By combining active learning, distributed computing, and quantum chemistry, SDDF offers a scalable, cost-effective solution for developing accurate molecular models and ultimately accelerating drug discovery.
Hepatitis A epidemics in Japan, France, and Thailand from 2007 to 2021, highlighting a post-COVID-19 decline
Response of wheat crop to water-logged conditions under different land configurations and nutrient management
Semantic structure preservation for accurate multi-modal glioma diagnosis
A novel voice in head actor critic reinforcement learning with human feedback framework for enhanced robot navigation
Abstract This work presents a novel Voice in Head (ViH) framework, that integrates Large Language Models (LLMs) and the power of semantic understanding to enhance robotic navigation and interaction within complex environments. Our system strategically combines GPT and Gemini powered LLMs as Actor and Critic components within a reinforcement learning (RL) loop for continuous learning and adaptation. ViH employs a sophisticated semantic search mechanism powered by Azure AI Search, allowing users to interact with the system through natural language queries. To ensure safety and address potential LLM limitations, the system incorporates a Reinforcement Learning with Human Feedback (RLHF) component, triggered only when necessary. This hybrid approach delivers impressive results, achieving success rates of up to 94.54%, surpassing established benchmarks. Most importantly, the ViH framework offers a modular and scalable architecture. By simply modifying the environment, the system demonstrates the potential to adapt to diverse application domains. This research provides a significant advancement in the field of cognitive robotics, paving the way for intelligent autonomous systems capable of sophisticated reasoning and decision-making in real-world scenarios bringing us one step closer to achieving Artificial General Intelligence.
Carbon dioxide removal from triethanolamine solution using living microalgae-loofah biocomposites
Abstract Nowadays, the climate change crisis is an urgent matter in which carbon dioxide (CO2) is a major greenhouse gas contributing to global warming. Amine solvents are commonly used for CO2 capture with high efficiency and absorption rates. However, solvent regeneration consumes an extensive amount of energy. One of alternative approaches is amine regeneration through microalgae. Recently, living biocomposites, intensifying traditional suspended cultivation, have been developed. With this technology, immobilizing microalgae on biocompatible materials with binder outperformed the suspended system in terms of CO2 capture rates. In this study, living microalgae-loofah biocomposites with immobilized Scenedesmus acuminatus TISTR 8457 using 5%v/v acrylic medium were tested to remove CO2 from CO2-rich triethanolamine (TEA) solutions. The test using 1 M TEA at various CO2 loading ratios (0.2, 0.4, 0.6, and 0.8 mol CO2/mol TEA) demonstrated that the biocomposites achieved CO2 removal rates 3 to 5 times higher than the suspended cell system over 28 days, with the highest removal observed at the 1 M with 0.4 mol CO2/mol TEA (4.34 ± 0.20 gCO2/gbiomass). This study triggers a new exploration of integration between biological and chemical processes that could elevate the traditional amine-based CO2 capture capabilities. Nevertheless, pilot-scale investigations are necessary to confirm the biocomposites’s efficiency.