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Benchmark Dose Assessment for Coke Oven Emissions-Induced Mitochondrial DNA Copy Number Damage Effects

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Biomedical and Environmental Sciences 2023年第6期36卷 490-500页

作者： yaN Zhao fan GU Zhi Guang fan ya hui LI Xin Ling NIU Ze Ming DUAN Xiao Ran Mallah Ali Manthar ZHANG Qiao yaNG Yong Li yaO Wu WANG Wei Department of Occupational Health and Occupational Diseases College of Public HealthZhengzhou UniversityZhengzhou 450001HenanChina Department of Toxicology College of Public HealthZhengzhou UniversityZhengzhou 450001HenanChina Department of Epidemiology and Biostatistics College of Public HealthZhengzhou UniversityZhengzhou 450001HenanChina

Objective The study aimed to estimate the benchmark dose(BMD)of coke oven emissions(COEs)exposure based on mitochondrial damage with the mitochondrial DNA copy number(mtDNAcn)as a *** A total of 782 subjects were recruited,including 238 controls and 544 exposed *** mtDNAcn of peripheral leukocytes was detected through the real-time fluorescence-based quantitative polymerase chain *** BMD approaches were used to calculate the BMD of COEs exposure based on the mitochondrial damage and its 95%confidence lower limit(BMDL).Results The mtDNAcn of the exposure group was lower than that of the control group(0.60±0.29 vs.1.03±0.31;P<0.001).A dose-response relationship was shown between the mtDNAcn damage and *** the Benchmark Dose Software,the occupational exposure limits(OELs)for COEs exposure in males was 0.00190 mg/m^(3).The OELs for COEs exposure using the BBMD were 0.00170 mg/m^(3)for the total population,0.00158 mg/m^(3)for males,and 0.00174 mg/m^(3)for *** possible risk obtained from animal studies(PROAST),the OELs of the total population,males,and females were 0.00184,0.00178,and 0.00192 mg/m^(3),*** Based on our conservative estimate,the BMDL of mitochondrial damage caused by COEs is0.002 mg/m^(3).This value will provide a benchmark for determining possible OELs.

关键词： Coke oven emissions Mitochondrial DNA copy number Benchmark dose Occupational exposure limits

Association between Polymorphisms in Telomere-Associated Protein Genes and the Cholinesterase Activity of Omethoate-Exposed Workers

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Biomedical and Environmental Sciences 2022年第5期35卷 448-452页

作者： fan ya hui LI Xin Ling LIU Xiao Hua GUO Zhi Feng yaN Meng Qing DUAN Xiao Ran MIAO Wen Bin WANG Wei Department of Occupational Health and Occupational Diseases College of Public HealthZhengzhou UniversityZhengzhou 450001HenanChina Biotherapy Center The First Affiliated Hospital of Zhengzhou UniversityZhengzhou UniversityZhengzhou 450052HenanChina Director of Efficacy and Safety Evaluation Laboratory Pony Testing Group Shanghai Co.Ltd.Shanghai 201600China

Organophosphorus pesticides(OPs)are extensively used for their high efficiency,broad spectrum,and low ***,the health hazards caused by long-term,low-dose exposure to OPs are easily *** is a large class of OPs that is widely used in *** inhibition of the cholinesterase(ChE)activity is the main toxicity mechanism of OPs,and such an activity is used as a biomarker of exposure to OPs.

关键词： pesticides China. residue

Game theory based finite-time formation control using artificial potentials for tethered space net robot

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Chinese Journal of Aeronautics 2024年第8期37卷 358-372页

作者： Yifeng MA Yizhai ZHANG Panfeng HUANG ya LIU fan ZHANG The Research Center for Intelligent Robotics School of AstronauticsNorthwestern Polytechnical UniversityXi’an 710072China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

The Tethered Space Net Robot(TSNR)is an innovative solution for active space debris capture and *** large envelope and simple capture method make it an attractive option for this ***,capturing maneuverable debris with the flexible and elastic underactuated net poses significant *** address this,a novel formation control method for the TSNR is proposed through the integration of differential game theory and robust adaptive control in this ***,the trajectory of the TSNR is obtained through the solution of a real-time feedback pursuit-evasion game with a dynamic target,where the primary condition is to ensure the stability of the ***,to minimize tracking errors and maintain a specific configuration,a robust adaptive formation control scheme with Artificial Potential Field(APF)based on a Finite-Time Convergent Extended State Observer(FTCESO)is *** proposed control method has a key advantage in suppressing complex oscillations by a new adaptive law,thus precisely maintaining the ***,numerical simulations are performed to demonstrate the effectiveness of the proposed scheme.

关键词： Game theory Formation control Artificial potential field Relative distance constraint Tethered space net robot(TSNR)

Height and body mass index trajectories from 1975 to 2015 and prevalence of stunting,underweight and obesity in 2016 among children in Chinese cities:findings from five rounds of a national survey

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World Journal of Pediatrics 2024年第4期20卷 404-412页

作者： Xin‑Nan Zong hui Li ya‑Qin Zhang Department of Growth and Development Capital Institute of PediatricsBeijing 100020China

Background A more comprehensive assessment of growth and nutrition in children is required in China due to rapid socioeconomic *** aimed to investigate height and body mass index(BMI)trajectories from 1975 to 2015 and the prevalence of stunting and obesity in 2016 among children in Chinese *** A total of 904,263 children from birth to 6.9 years were collected from a series of nationally representative surveys in *** and BMI trajectories and prevalence of stunting,underweight,overweight and obesity were *** The average height level of Chinese urban children under 7 years presented a positive secular trend from 1975 to 2015;however,a slowing tendency occurred in 2005‒*** apparent increase was observed at the 5th,50th and 95th percentiles of BMI in urban children aged 3 years and older,with a more prominent increase at the 95th *** total prevalence of stunting and underweight under 7 years was 1.4%and 2.0%,*** total prevalence of overweight and obesity under 7 years was 12.6%and 4.3%,respectively,with 12.7%and 4.9%for boys,12.6%and 3.6%for girls,12.1%and 4.0%in urban areas and 13.1%and 4.5%in suburban rural *** The average height level of Chinese urban children has reached World Health Organization child growth standards since 2005 and presented a slowing tendency in secular trend in 2005‒*** attention and efforts and public health interventions should be urgently made to combat overweight and obesity among preschool children.

关键词： Body mass index Children Height Obesity Stunting

Tumor microenvironment reprogramming by nanomedicine to enhance the effect of tumor immunotherapy

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Asian Journal of Pharmaceutical Sciences 2024年第2期19卷 1-37页

作者： Yu Huang hui fan huihui Ti School of Chinese Materia Medica Guangdong Pharmaceutical UniversityGuangzhou 510006China Guangdong Province Precise Medicine Big Date of Traditional Chinese Medicine Engineering Technology Research Center Guangdong Pharmaceutical UniversityGuangzhou 510006China School of Pharmacy Guangdong Pharmaceutical UniversityGuangzhou 510006China

With the rapid development of the fields of tumor biology and immunology, tumor immunotherapy has been used in clinical practice and has demonstrated significant therapeutic potential, particularly for treating tumors that do not respond to standard treatment options. Despite its advances, immunotherapy still has limitations, such as poor clinical response rates and differences in individual patient responses, largely because tumor tissues have strong immunosuppressive microenvironments. Many tumors have a tumor microenvironment (TME) that is characterized by hypoxia, low pH, and substantial numbers of immunosuppressive cells, and these are the main factors limiting the efficacy of antitumor immunotherapy. The TME is crucial to the occurrence, growth, and metastasis of tumors. Therefore, numerous studies have been devoted to improving the effects of immunotherapy by remodeling the TME. Effective regulation of the TME and reversal of immunosuppressive conditions are effective strategies for improving tumor immunotherapy. The use of multidrug combinations to improve the TME is an efficient way to enhance antitumor immune efficacy. However, the inability to effectively target drugs decreases therapeutic effects and causes toxic side effects. Nanodrug delivery carriers have the advantageous ability to enhance drug bioavailability and improve drug targeting. Importantly, they can also regulate the TME and deliver large or small therapeutic molecules to decrease the inhibitory effect of the TME on immune cells. Therefore, nanomedicine has great potential for reprogramming immunosuppressive microenvironments and represents a new immunotherapeutic strategy. Therefore, this article reviews strategies for improving the TME and summarizes research on synergistic nanomedicine approaches that enhance the efficacy of tumor immunotherapy.

关键词： Tumor immunotherapy Tumor micr oenvir onment Nanomedicine Tumor repr ogramming

Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

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China Communications 2024年第4期21卷 38-52页

作者： Jiang fan Qin Junwei Liu Lei Tian hui School of Communications and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy co

关键词： associative tasks cache-aided procedure double deep Q-network Internet of Medical Things(IoMT) multi-access edge computing(MEC)

Type Synthesis of Self-Alignment Parallel Ankle Rehabilitation Robot with Suitable Passive Degrees of Freedom

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 160-175页

作者： ya Liu Wenjuan Lu Dabao fan Weijian Tan Bo Hu Daxing Zeng School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004China School of Mechanical Engineering Dongguan University of TechnologyDongguan 523808China Dongguan Engineering Technology Research Center for Parallel Robot Dongguan 523808China The DGUT Innovation Center of Robotics and Intelligent Equipment Dongguan 523808China

The current parallel ankle rehabilitation robot(ARR)suffers from the problem of difficult real-time alignment of the human-robot joint center of rotation,which may lead to secondary injuries to the *** study investigates type synthesis of a parallel self-alignment ankle rehabilitation robot(PSAARR)based on the kinematic characteristics of ankle joint rotation center drift from the perspective of introducing"suitable passive degrees of freedom(DOF)"with a suitable number and ***,the self-alignment principle of parallel ARR was proposed by deriving conditions for transforming a human-robot closed chain(HRCC)formed by an ARR and human body into a kinematic suitable constrained system and introducing conditions of"decoupled"and"less limb".Second,the relationship between the self-alignment principle and actuation wrenches(twists)of PSAARR was analyzed with the velocity Jacobian matrix as a"bridge".Subsequently,the type synthesis conditions of PSAARR were ***,a PSAARR synthesis method was proposed based on the screw theory and type of PSAARR synthesis ***,an HRCC kinematic model was established to verify the self-alignment capability of the *** this study,93 types of PSAARR limb structures were synthesized and the self-alignment capability of a human-robot joint axis was verified through kinematic analysis,which provides a theoretical basis for the design of such an ARR.

关键词： Ankle rehabilitation robot Self-alignment Parallel mechanism Type synthesis Screw theory

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu Qi Zhang Yufan Hu hui Zeng Bin fan the School of Intelligence Science and Technology and the Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

Data complexity-based batch sanitization method against poison in distributed learning

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Digital Communications and Networks 2024年第2期10卷 416-428页

作者： Silv Wang Kai fan Kuan Zhang hui Li Yintang yang State Key Laboratory of Integrated Service Networks Xidian UniversityXi'an710126China Department of Electrical and Computer Engineering University of Nebraska-LincolnLincolnNE68588USA Key Lab.of the Minist.of Educ.for Wide Bandgap Semiconductor Materials and Devices Xidian UniversityXi'an710071China

The security of Federated Learning(FL)/Distributed Machine Learning(DML)is gravely threatened by data poisoning attacks,which destroy the usability of the model by contaminating training samples,so such attacks are called causative availability indiscriminate *** the problem that existing data sanitization methods are hard to apply to real-time applications due to their tedious process and heavy computations,we propose a new supervised batch detection method for poison,which can fleetly sanitize the training dataset before the local model *** design a training dataset generation method that helps to enhance accuracy and uses data complexity features to train a detection model,which will be used in an efficient batch hierarchical detection *** model stockpiles knowledge about poison,which can be expanded by retraining to adapt to new *** neither attack-specific nor scenario-specific,our method is applicable to FL/DML or other online or offline scenarios.

关键词： Distributed machine learning security Federated learning Data poisoning attacks Data sanitization Batch detection Data complexity