68 research outputs found

    Leveraging SOLOv2 model to detect heat stress of poultry in complex environments

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    Heat stress is one of the most important environmental stressors facing poultry production. The presence of heat stress will reduce the antioxidant capacity and immunity of poultry, thereby seriously affecting the health and performance of poultry. The paper proposes an improved FPN-DenseNet-SOLO model for poultry heat stress state detection. The model uses Efficient Channel Attention (ECA) and DropBlock regularization to optimize the DenseNet-169 network to enhance the extraction of poultry heat stress features and suppress the extraction of invalid background features. The model takes the SOLOv2 model as the main frame, and uses the optimized DenseNet-169 as the backbone network to integrate the Feature Pyramid Network to detect and segment instances on the semantic branch and mask branch. In the validation phase, the performance of FPN-DenseNet-SOLO was tested with a test set consisting of 12,740 images of poultry heat stress and normal state, and it was compared with commonly used object detection models (Mask R CNN, Faster RCNN and SOLOv2 model). The results showed that when the DenseNet-169 network lacked the ECA module and the DropBlock regularization module, the original model recognition accuracy was 0.884; when the ECA module was introduced, the model's recognition accuracy improved to 0.919. Not only that, the recall, AP0.5, AP0.75 and mean average precision of the FPN-DenseNet-SOLO model on the test set were all higher than other networks. The recall is 0.954, which is 15, 8.8, and 4.2% higher than the recall of Mask R CNN, Faster R CNN and SOLOv2, respectively. Therefore, the study can achieve accurate segmentation of poultry under normal and heat stress conditions, and provide technical support for the precise breeding of poultry

    Multifunctional Ag@Fe(2)O(3) yolk-shell nanoparticles for simultaneous capture, kill, and removal of pathogen

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    We combined silver and iron oxide nanoparticles to make unique Ag@Fe(2)O(3) yolk-shell multifunctional nanoparticles by the Kirkendall effect. After the surface functionalization using glucose, the Ag@Fe(2)O(3)-Glu conjugates exhibited both high capture efficiency of bacteria and potent antibacterial activity. The Ag@Fe(2)O(3) yolk-shell nanostructures may offer a unique multifunctional platform for simultaneous rapid detection and capture of bacteria and safe detoxification treatment.National Science Foundation of China[21021061, 81000662]; Fundamental Research Funds for the Central Universities[2010121012]; Program for New Century Excellent Talents in University[NCET-10-0709

    Study on rheological, adsorption and hydration properties of cement slurries incorporated with EPEG-based polycarboxylate superplasticizers

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    A series of polycarboxylate superplasticizers (PCEs) with different side-chain densities, main chain polymerization degrees, and side-chain lengths were designed and synthesized using a novel highly active ethylene glycol mono vinyl ether polyethylene glycol as the ether monomer. The influence of polycarboxylate ether on the rheological properties, interface adsorption, and hydration characteristics in cement paste was investigated through characterization of charge density, rheological properties, adsorption behavior, and hydration heat. The results indicate that the adsorption process of PCE on cement particles is spontaneous physical adsorption, and the hydration kinetics fitting reveals that the geometric crystal growth exponent n is in the range of 1–2, with needle-like and lamellar hydration products formed. With a decrease in side-chain density, the broadening of molecular weight distribution and the increase of charge density accelerate the flow of slurry, reduces saturation adsorption, and delays cement hydration. A decrease in main chain polymerization degree results in a downward trend in molecular weight and charge density, leading to larger molecular conformations, reduced slurry flow, decreased saturation adsorption, and delayed cement hydration. As the side-chain length of PCE (molecular weight) increases, the charge density decreases, and the molecular conformation exhibits a compact structure with reduced slurry flow, decreased saturation adsorption, and delayed cement hydration. In cases of low side-chain density, short side chains, and low molecular weight, enhanced adsorption capacity and faster adsorption rates are observed, resulting in the lower viscosity and a delay in the cement hydration process

    Research on Basic Characteristics and Bidding Strategy of Thermal Power Units in Fujian Spot Market

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    In the electricity market environment, thermal power units have changed from the executors of power production under the monopoly mechanism to the decision-makers of production and operation under the competitive environment. The merits and demerits of bidding schemes for thermal power units are directly related to self-interest of themselves. The bidding decisions of power plants are not only affected by economic factors, but also by technical factors peculiar to the power system and the electric generator. In recent years, research on bidding strategies of thermal power units based on the power market environment has been paid more and more attention in the field of electric market. This paper first introduces the basic peak regulation and frequency modulation technical characteristics of thermal power units and cost calculation. Then, from the angle of quotation, paper analyzes characteristics of quotation mechanism of units in Fujian Electric Power day-ahead, real-time and peak regulation auxiliary service market. Furthermore, the research status of bidding strategies of thermal power units participating in electricity market at home and abroad in cost analysis, market clearing price prediction, game theory and so on are summarized. Finally, the bidding strategy for units in Fujian Spot Market is put forward

    Unveiling Two Electron-Transport Modes in Oxygen-Deficient TiO2 Nanowires and Their Influence on Photoelectrochemical Operation

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    Introducing oxygen vacancies (V-O) into TiO2 materials is one of the most promising ways to significantly enhance light-harvesting and photocatalytic efficiencies of photoelectrochemical (PEC) cells for water splitting among others. However, the nature of electron transport in V-O-TiO2 nanostructures is not well understood, especially in an operating device. In this work, we use the intensity-modulated photocurrent spectroscopy technique to study the electron-transport property of V-O-TiO2 nanowires (NWs). It is found that the electron transport in pristine TiO2 NWs displays a single trap-limited mode, whereas two electron-transport modes were detected in V-O-TiO2 NWs, a trap-free transport mode at the core, and a trap-limited transport mode near the surface. The considerably higher diffusion coefficient (D-n) of the trap-free transport mode grants a more rapid electron flow in V-O-TiO2 NWs than that in pristine TiO2 NWs. This electron-transport feature is expected to be common in other oxygen-deficient metal oxides, lending a general strategy for promoting the PEC device performance

    Gradual Machine Learning for Entity Resolution

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    A Comprehensive Network Pharmacology-Based Strategy to Investigate Multiple Mechanisms of HeChan Tablet on Lung Cancer

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    Background. HeChan tablet (HCT) is a traditional Chinese medicine preparation extensively prescribed to treat lung cancer in China. However, the pharmacological mechanisms of HCT on lung cancer remain to be elucidated. Methods. A comprehensive network pharmacology-based strategy was conducted to explore underlying mechanisms of HCT on lung cancer. Putative targets and compounds of HCT were retrieved from TCMSP and BATMAN-TCM databases; related genes of lung cancer were retrieved from OMIM and DisGeNET databases; known therapeutic target genes of lung cancer were retrieved from TTD and DrugBank databases; PPI networks among target genes were constructed to filter hub genes by STRING. Furthermore, the pathway and GO enrichment analysis of hub genes was performed by clusterProfiler, and the clinical significance of hub genes was identified by The Cancer Genome Atlas. Result. A total of 206 compounds and 2,433 target genes of HCT were obtained. 5,317 related genes of lung cancer and 77 known therapeutic target genes of lung cancer were identified. 507 unique target genes were identified among HCT-related genes of lung cancer and 34 unique target genes were identified among HCT-known therapeutic target genes of lung cancer. By PPI networks, 11 target genes AKT1, TP53, MAPK8, JUN, EGFR, TNF, INS, IL-6, MYC, VEGFA, and MAPK1 were identified as major hub genes. IL-6, JUN, EGFR, and MYC were shown to associate with the survival of lung cancer patients. Five compounds of HCT, quercetin, luteolin, kaempferol, beta-sitosterol, and baicalein were recognized as key compounds of HCT on lung cancer. The gene enrichment analysis implied that HCT probably benefitted patients with lung cancer by modulating the MAPK and PI3K-Akt pathways. Conclusion. This study predicted pharmacological and molecular mechanisms of HCT against lung cancer and could pave the way for further experimental research and clinical application of HCT

    Joint Inference for Aspect-level Sentiment Analysis by Deep Neural Networks and Linguistic Hints

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