检索结果-南通市图书馆

Developmental toxicity assessment of neonicotinoids and organophosphate esters with a human embryonic stem cell-and metabolism-based fast-screening model

在线全文

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2024年第3期137卷 370-381页

作者： Shuxian zhang Miaomiao zhao Shichang Li Renjun yang Nuoya Yin Francesco Faiola State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

In recent years,neonicotinoids(NEOs)and organophosphate esters(OPEs)have been widely used as substitutes for traditional pesticides and brominated fame-retardants,respectively.Previous studies have shown that those compounds can be frequently detected in environmental and human samples,are able to penetrate the placental barrier,and are toxic to animals.Thus,it is reasonable to speculate that NEOs and OPEs may have potential adverse effects in humans,especially during development.We employed a human embryonic stem cell differentiation-and liver S9 fraction metabolism-based fast screening model to assess the potential embryonic toxicity of those two types of chemicals.We show that four NEO and five OPE prototypes targeted mostly ectoderm specification,as neural ectoderm and neural crest genes were down-regulated,and surface ectoderm and placode markers up-regulated.Human liver S9 fraction's treatment could generally reduce the effects of the chemicals,except in a few specific instances,indicating the liver may detoxify NEOs and OPEs.Our findings suggest that NEOs and OPEs interfere with human early embryonic development.

关键词： Neonicotinoids Organophosphate esters Human embryonic stem cells Fast screening model Developmental toxicity

Improved direct current electrical properties of XLPE modified by graftable antioxidant and crosslinking coagent at a wide temperature range

在线全文

学校读者我要写书评

暂无评论

High Voltage 2024年第1期9卷 94-104页

作者： Xu yang Hong zhao Chengcheng zhang Chunyang Li Xindong zhao Jiaming yang Xuan Wang Key Laboratory of Engineering Dielectrics and Its Application Harbin University of Science and TechnologyHarbinChina

To enhance the DC electrical performance of cross-linked polyethylene(XLPE),the graftable antioxidant methacrylic acid 2-hydroxy-3-(4-anilinoanilino)propyl ester(GA),which contains carbonyl and amino groups,and the crosslinking coagent trimethylolpropane trimethacrylate(TMPTMA),which contains carbonyl groups,are individually or co-grafted onto XLPE.The slightly higher deep trap density introduced by higher grafting concentration of TMPTMA results in more significant suppression effect of conductance current and enhanced breakdown strength at a lower temperature,while the suppression effect for the conductance current at 90°C becomes weakened due to limited trap energy.Meanwhile,the deeper energy level introduced by GA suppresses the conductance current and improves the electrical strength of XLPE at 90°C more significantly.By co-grafting,the conductance current of XLPE in a wide range temperature can be significantly reduced,especially for the temperature dependence of conductance current,which is beneficial to suppress the field strength reversal.The results of thermally stimulated current and molecular simulation show that the polar groups of two monomers introduce deep charge traps in XLPE.The co-grafting system ensures the rationality of the crosslinking reaction kinetics and does not affect the cable manufacturing.

关键词： crosslinking electrical grafting

Causal reasoning in typical computer vision tasks

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2024年第1期67卷 105-120页

作者： zhang KeXuan SUN QiYu zhao ChaoQiang TANG yang Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China National Key Laboratory of Air based Information Perception and Fusion Luoyang 471000China Luoyang Institute of Electro Optical Equipment of Avic Luoyang 471000China

Deep learning has revolutionized the field of artificial intelligence.Based on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing rapidly.Despite being the basis of deep learning,such correlation strongly depends on the distribution of the original data and is susceptible to uncontrolled factors.Without the guidance of prior knowledge,statistical correlations alone cannot correctly reflect the essential causal relations and may even introduce spurious correlations.As a result,researchers are now trying to enhance deep learningbased methods with causal theory.Causal theory can model the intrinsic causal structure unaffected by data bias and effectively avoids spurious correlations.This paper aims to comprehensively review the existing causal methods in typical vision and visionlanguage tasks such as semantic segmentation,object detection,and image captioning.The advantages of causality and the approaches for building causal paradigms will be summarized.Future roadmaps are also proposed,including facilitating the development of causal theory and its application in other complex scenarios and systems.

关键词： causal reasoning computer vision tasks vision-language tasks semantic segmentation object detection

Clarification of the dispersion mechanism of cathode slurry of lithium-ion battery under effects of both poly vinylidene fluoride/carbon black ratio and mixing time

在线全文

学校读者我要写书评

暂无评论

Particuology 2024年第5期88卷 116-127页

作者： Zhilong Wang Zhenzhen zhao Ye yang An zhang Xiayi Liu Tong zhao Yahui Cui School of Mechanical and Precision Instrument Engineering Xi'an University of TechnologyXi'an 710048China

This paper presents the effects of both poly vinylidene fluoride(PVDF)/carbon black(CB)ratio(m PVDF:m CB)and mixing time t on the dispersion mechanism of the cathode slurry of lithium-ion battery(LIB).The dispersion mechanism is deduced from the electrochemical,morphological and rheological properties of the cathode slurry by using electrical impedance spectroscopy(EIS),scanning electron microscopy and rheology methods,respectively.From the perspective of EIS method,static simulation models are established in the COMSOL Multiphysics software;meanwhile,the simulated results are used to verify the correctness of the electrochemical properties of the cathode slurry.As a result,the following conclusions are able to be obtained.Firstly,in the case of the mass ratio m PVDF:m CB=5:10,LiCoO2 particles are completely coated by the mixture of CB and PVDF to form a stable polymer gel structure.Higher or lower m PVDF:m CB leads to the larger impedance and worse dispersion status for the cathode slurry.Secondly,when t=6 min,a good gel-like conductive network structure is formed by coating the thinner evenly dispersed CB–PVDF double layer around LiCoO2 particles.Finally,a strategy regarding to both m PVDF:m CB and t in experimental scale is proposed,which has the capability of improving the performance of LIB.

关键词： Cathode slurry Dispersion mechanism Lithium-ion battery(LIB)

Adverse effects of exposure to fine particles and ultrafine particles in the environment on different organs of organisms

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2024年第1期135卷 449-473页

作者： Jianwei zhang zhao Chen Dan Shan yang Wu Yue zhao Chen Li Yue Shu Xiaoyu Linghu Baiqi Wang Department of Occupational and Environmental Health School of Public HealthTianjin Medical UniversityTianjin 300070China Department of Medical Tianjin Stomatological HospitalSchool of MedicineNankai UniversityTianjin 300041China Tianjin Key Laboratory of Environment Nutrition and Public HealthTianjin 300070China National Demonstration Center for Experimental Preventive Medicine Education(Tianjin Medical University) Tianjin 300070China

Particulate pollution is a global risk factor that seriously threatens human health.Fine particles(FPs)and ultrafine particles(UFPs)have small particle diameters and large specific surface areas,which can easily adsorb metals,microorganisms and other pollutants.FPs and UFPs can enter the human body in multiple ways and can be easily and quickly absorbed by the cells,tissues and organs.In the body,the particles can induce oxidative stress,inflammatory response and apoptosis,furthermore causing great adverse effects.Epidemiological studies mainly take the population as the research object to study the distribution of diseases and health conditions in a specific population and to focus on the identification of influencing factors.However,the mechanism by which a substance harms the health of organisms is mainly demonstrated through toxicological studies.Combining epidemiological studies with toxicological studies will provide a more systematic and comprehensive understanding of the impact of PM on the health of organisms.In this review,the sources,compositions,and morphologies of FPs and UFPs are briefly introduced in the first part.The effects and action mechanisms of exposure to FPs and UFPs on the heart,lungs,brain,liver,spleen,kidneys,pancreas,gastrointestinal tract,joints and reproductive system are systematically summarized.In addition,challenges are further pointed out at the end of the paper.This work provides useful theoretical guidance and a strong experimental foundation for investigating and preventing the adverse effects of FPs and UFPs on human health.

关键词： Fine particles Ultrafine particles Organs Adverse effect

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

在线全文

学校读者我要写书评

暂无评论

China Communications 2024年第5期21卷 113-122页

作者： Qiu Wanqing zhang Qingmiao zhao Junhui yang Lihua School of Information Engineering East China Jiaotong UniversityNanchang 330013China School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related features.The basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location distance.Therefore,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy localization.In this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting localization.Firstly,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it receives.Secondly,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are obtained.Finally,extensive simulation results are presented.It is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

关键词： extreme learning machine fingerprinting localization indoor localization machine learning particle swarm optimization

Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

在线全文

学校读者我要写书评

暂无评论

Neural Regeneration Research 2024年第3期19卷 663-670页

作者： yang Guo Liying Sun Wenyao Zhong Nan zhang Zongxuan zhao Wen Tian Department of Hand Surgery Beijing Jishuitan HospitalBeijingChina

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future re

关键词： artificial intelligence artificial prosthesis medical-industrial integration brain-machine interface deep learning machine learning networked hand prosthesis neural interface neural network neural regeneration peripheral nerve

Twisted Integration of Complex Oxide Magnetoelectric Heterostructures via Water‑Etching and Transfer Process

在线全文

学校读者我要写书评

暂无评论

Nano-Micro Letters 2024年第1期16卷 360-369页

作者： Guannan yang Guohua Dong Butong zhang Xu Xu Yanan zhao Zhongqiang Hu Ming Liu State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research LaboratoryKey Laboratory of the Ministry of EducationEngineering Research Center of Spin Quantum Sensor ChipsUniversities of Shaanxi ProvinceSchool of Electronic Science and EngineeringXi’an Jiaotong UniversityXi’an 710049People’s Republic of China

Manipulating strain mode and degree that can be applied to epitaxial complex oxide thin films have been a cornerstone of strain engineering.In recent years,lift-off and transfer technology of the epitaxial oxide thin films have been developed that enabled the integration of heterostructures without the limitation of material types and crystal orientations.Moreover,twisted integration would provide a more interesting strategy in artificial magnetoelectric heterostructures.A specific twist angle between the ferroelectric and ferromagnetic oxide layers corresponds to the distinct strain regulation modes in the magnetoelectric coupling process,which could provide some insight in to the physical phenomena.In this work,the La_(0.67)Sr_(0.33)MnO_(3)(001)/0.7Pb(Mg_(1/3)Nb_(2/3))O_(3)-0.3PbTiO_(3)(011)(LSMO/PMN-PT)heterostructures with 45.and 0.twist angles were assembled via water-etching and transfer process.The transferred LSMO films exhibit a fourfold magnetic anisotropy with easy axis along LSMO.A coexistence of uniaxial and fourfold magnetic anisotropy with LSMO[110]easy axis is observed for the 45°Sample by applying a 7.2 kV cm^(−1)electrical field,significantly different from a uniaxial anisotropy with LSMO[100]easy axis for the 0°Sample.The fitting of the ferromagnetic resonance field reveals that the strain coupling generated by the 45°twist angle causes different lattice distortion of LSMO,thereby enhancing both the fourfold and uniaxial anisotropy.This work confirms the twisting degrees of freedom for magnetoelectric coupling and opens opportunities for fabricating artificial magnetoelectric heterostructures.

关键词： Magnetoelectric heterostructures Twist angle Epitaxial lift-off Magnetic anisotropy Ferromagnetic resonance

Generative pre-trained transformers(GPT)-based automated data mining for building energy management:Advantages,limitations and the future

在线全文

学校读者我要写书评

暂无评论

Energy and Built Environment

Energy and Built Environment 2024年第1期5卷 143-169页

作者： Chaobo zhang Jie Lu yang zhao Institute of Refrigeration and Cryogenics Zhejiang UniversityHangzhouChina Department of the Built Environment Eindhoven University of TechnologyEindhovenThe Netherlands Key Laboratory of Clean Energy and Carbon Neutrality of Zhejiang Province Jiaxing Research InstituteZhejiang UniversityJiaxingChina

Advanced data mining methods have shown a promising capacity in building energy management.However,in the past decade,such methods are rarely applied in practice,since they highly rely on users to customize solutions according to the characteristics of target building energy systems.Hence,the major barrier is that the practical applications of such methods remain laborious.It is necessary to enable computers to have the human-like ability to solve data mining tasks.Generative pre-trained transformers(GPT)might be capable of addressing this issue,as some GPT models such as GPT-3.5 and GPT-4 have shown powerful abilities on interaction with humans,code generation,and inference with common sense and domain knowledge.This study explores the potential of the most advanced GPT model(GPT-4)in three data mining scenarios of building energy management,i.e.,energy load prediction,fault diagnosis,and anomaly detection.A performance evaluation framework is proposed to verify the capabilities of GPT-4 on generating energy load prediction codes,diagnosing device faults,and detecting abnormal system operation patterns.It is demonstrated that GPT-4 can automatically solve most of the data mining tasks in this domain,which overcomes the barrier of practical applications of data mining methods in this domain.In the exploration of GPT-4,its advantages and limitations are also discussed comprehensively for revealing future research directions in this domain.

关键词： ChatGPT GPT-4 Artificial general intelligence Data mining Building energy management