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Prenatal cadmium exposure impairs neural tube closure via inducing excessive apoptosis in neuroepithelium

Journal of Environmental Sciences 2024年第4期138卷 572-584页

作者： Shiyong Zhu Xuenan Li xueyan dai Jinlong Li College of Veterinary Medicine Northeast Agricultural UniversityHarbin 150030China Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment Northeast Agricultural UniversityHarbin 150030China Heilongjiang Key Laboratory for Laboratory Animals and Comparative Medicine Northeast Agricultural UniversityHarbin 150030China

Birth defects have become a public health concern.The hazardous environmental factors exposure to embryos could increase the risk of birth defects.Cadmium,a toxic environmental factor,can cross the placental barrier during pregnancy.Pregnant woman may be subjected to cadmium before taking precautionary protective actions.However,the link between birth defects and cadmium remains obscure.Cadmium exposure can induce excessive apoptosis in neuroepithelium during embryonic development progresses.Cadmium exposure activated the p53 via enhancing the adenosine 5‘-monophosphate(AMP)-activated protein kinase(AMPK)and reactive oxygen species'(ROS)level.And cadmium decreases the level of Paired box 3(Pax3)and murine double minute 2(Mdm2),disrupting the process of p53 ubiquitylation.And p53 accumulation induced excessive apoptosis in neuroepithelium during embryonic development progresses.Excessive apoptosis led to the failure of neural tube closure.The study emphasizes that environmental materials may increase the health risk for embryos.Cadmium caused the failure of neural tube closure during early embryotic day.Pregnant women may be exposed by cadmium before taking precautionary protective actions,because of cadmium concentration-containing foods and environmental tobacco smoking.This suggests that prenatal cadmium exposure is a threatening risk factor for birth defects.

关键词： Cadmium Neural tube closure Excessive apoptosis p53 Embryogenesis

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Molybdenum and cadmium co-induce necroptosis through Th1/Th2 imbalance-mediated endoplasmic reticulum stress in duck ovaries

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Journal of Environmental Sciences 2024年第8期142卷 92-102页

作者： Ting Cui xueyan dai Huiling Guo Dianyun Wang Bingyan Huang Wenjing Pu Xuesheng Chu Caiying Zhang Jiangxi Provincial Key Laboratory for Animal Health Institute of Animal Population HealthCollege of Animal Science and TechnologyJiangxi Agricultural UniversityNanchang 330045China

Cadmium(Cd)and excess molybdenum(Mo)pose serious threats to animal health.Our previous study has determined that Cd and/or Mo exposure can cause ovarian damage of ducks,while the specific mechanism is still obscure.To further investigate the toxic mechanism of Cd and Mo co-exposure in the ovary,forty 8-day-old female ducks were randomly allocated into four groups for 16 weeks,and the doses of Cd and Mo in basic diet per kg were as follows:control group,Mo group(100 mg Mo),Cd group(4 mg Cd),and Mo+Cd group(100 mg Mo+4 mg Cd).Cadmium sulfate 8/3-hydrate(CdSO_(4)·8/3H_(2)O)and hexaammonium molybdate((NH_(4))_(6)Mo_(7)O_(24)·4H_(2)O)were the origins of Cd and Mo,respectively.At the 16th week of the experiment,all ovary tissues were collected for the detection of related indexes.The data indicated that Mo and/or Cd induced trace element disorders and Th1/Th2 balance to divert toward Th1 in the ovary,which activated endoplasmic reticulum(ER)stress and then provoked necroptosis through triggering RIPK1/RIPK3/MLKL signaling pathway,and eventually caused ovarian pathological injuries and necroptosis characteristics.The alterations of above indicators were most apparent in the joint group.Above all,this research illustrates that Mo and/or Cd exposure can initiate necroptosis through Th1/Th2 imbalance-modulated ER stress in duck ovaries,and Mo and Cd combined exposure aggravates ovarian injuries.This research explores the molecular mechanism of necroptosis caused by Mo and/or Cd,which reveals that ER stress attenuation may be a therapeutic target to alleviate necroptosis.

关键词： Molybdenum Cadmium Th1/Th2 imbalance Endoplasmic reticulum stress Necroptosis Ovary

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CCF800S/8210双马来酰亚胺树脂基复合材料固化工艺参数与耐热性能的关系

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化工新型材料 2024年第5期52卷 255-257页

作者：许晓洲戴雪岩王天娇汪东柯红军李丽英王国勇航天特种材料及工艺技术研究所北京100074

采用热分析方法研究了CCF800S/8210双马来酰亚胺树脂基复合材料的固化工艺参数与耐热性能的关系。结果表明,在250℃以内,随着固化温度的增加,CCF800S/8210双马来酰亚胺树脂基复合材料的耐热性能提高,玻璃化转变温度从310℃提高到350℃... 详细信息

采用热分析方法研究了CCF800S/8210双马来酰亚胺树脂基复合材料的固化工艺参数与耐热性能的关系。结果表明,在250℃以内,随着固化温度的增加,CCF800S/8210双马来酰亚胺树脂基复合材料的耐热性能提高,玻璃化转变温度从310℃提高到350℃。进一步考察了该复合材料在室温和250℃时的力学性能,发现在250℃下力学性能保持率大于51%。因此,该双马来酰亚胺树脂基复合材料体系作为结构材料在航天航空领域有着潜在的应用价值。

关键词：双马来酰亚胺树脂复合材料高温力学性能

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Numerical simulation of flow and heat transfer in a random packed bed

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Particuology 2010年第3期8卷 293-299页

作者： xueyan Guo Ren dai School of Energy and Power Engineering University of Shanghai for Science and Technology S 16Jun Gong Road Shanghai 200093 China

Random packed beds have more complex interior structure than structured beds and are widely used in industry and engineering. CFD simulation was carried out to investigate and analyze the local flow and heat transfer in a 120-sphere random packed bed. 3D Navier-Stokes equation was solved with a finite volume formulation based on the Chimera meshing technique. Investigation was focused on low Reynolds number flow （Re=4.6-56.2）, which typically occurs in packed bed reactors in bio-chemical fields. Detailed temperature field information was obtained. Inhomogeneity of flow and heat transfer due to the non-uniform distribution of void fraction was discussed and analyzed.

关键词： Packed bed Heat transfer Chimera grid Numerical simulation Low Reynolds number

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光热双响应形状记忆聚氨酯/炭黑纳米复合材料的制备及性能研究

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化工新型材料 2024年第5期52卷 229-233页

作者：王天娇汪东李丽英戴雪岩许晓洲李娜柯红军王国勇航天特种材料及工艺技术研究所北京100074

选用聚己内酯为预聚物,炭黑(CB)纳米颗粒作为光响应功能性填料,通过溶液聚合制备了一种光热双响应形状记忆聚氨酯(SMPU)/CB纳米复合材料。利用IR、SEM、DSC和DMA对其结构、形貌、热学性能和形状记忆性能进行表征。研究结果表明,SMPU/CB... 详细信息

选用聚己内酯为预聚物,炭黑(CB)纳米颗粒作为光响应功能性填料,通过溶液聚合制备了一种光热双响应形状记忆聚氨酯(SMPU)/CB纳米复合材料。利用IR、SEM、DSC和DMA对其结构、形貌、热学性能和形状记忆性能进行表征。研究结果表明,SMPU/CB纳米复合材料展示出优异的形状记忆性能,其形状固定率和形状回复率均在97%以上。此外,由于CB的光热效应,SMPU/CB纳米复合材料在红外光的照射下具有快的响应速度及大的弯曲变形角度,在航空航天、智能驱动等领域具有潜在的应用前景。

关键词：形状记忆聚合物复合材料光响应热响应聚氨酯炭黑

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Distributed Fault-Tolerant Control of Uncertain Multi-Agent Systems with Connectivity Maintenance

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Journal of Systems Science & Complexity 2024年第1期37卷 40-62页

作者： XING xueyan HU Guoqiang Continental-NTU Corporate Lab Nanyang Technological UniversitySingapore 639798Singapore Continental-NTU Corporate Lab and the School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore

In this paper,a distributed cooperative control protocol is presented to deal with actuator failures of multi-agent systems in the presence of connectivity preservation.With the developed strategy,each agent can track the reference trajectory of the leader in the presence of actuator failures,disturbances and uncertainties.The connectivity of the multi-agent system can always be ensured during the control process.To achieve the aforementioned control objectives,a potential function is introduced to the distributed adaptive fault-tolerant control algorithm to preserve the initial connected network among the agents.The uncertainty of the multi-agent system,which is allowed to be described by discontinuous functions,is approximated and compensated using the fuzzy logic system.The asymptotic stability of the closed-loop system is demonstrated through the use of Cellina’s approximate selection theorem of nonsmooth analysis.Due to the developed adaptive laws,the upper bound of the disturbance is allowed to be uncertain,which facilitates the implementation of the control scheme.Finally,simulation results are provided to verify the effectiveness of the proposed control scheme.

关键词： Actuator failure connectivity maintenance coordination control uncertainties

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Synergically regulated silver species and surface oxygen on manganese oxide for promoted activity of formaldehyde oxidation

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Journal of Environmental Sciences 2024年第4期138卷 709-718页

作者： Shuo Hu Jianghao Zhang xueyan Chen Xiaoxiao Qin Jinshui Yao Changbin Zhang School of Materials Science&Engineering Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China

Formaldehyde(HCHO)is a common indoor pollutant that is detrimental to human health.Its efficient removal has become an urgent demand to reduce the public health risk.In this work,Ag-MnO_(x)-based catalysts were prepared and activated under different atmosphere(i.e.,air,hydrogen(H_(2))and carbon monoxide(CO))for efficient oxidation of HCHO.The catalyst activated with CO(Ag/Mn-CO)displayed the highest activity among the tested samples with 90% conversion at 100℃ under a gas space velocity of 75,000 mL/(g_(cat)·hr).Complementary characterizations demonstrate that CO reduction treatment resulted in synergically regulated content of surface oxygen on support to adsorb/activate HCHO and size of Ag particle to dissociate oxygen to oxidize the adsorbed HCHO.In contrast,other catalysts lack for either abundant surface oxygen species or metallic silver with the appropriate particle size,so that the integrate activity is limited by one specific reaction step.This study contributes to elucidating the mechanisms regulating the oxidation activity of Ag-based catalysts.

关键词： HCHO oxidation Ag-MnO_(x)-based catalyst Activation condition Synergic regulation Surface oxygen Oxidized Ag

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Data error propagation in stacked bioclimatic envelope models

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Integrative Zoology 2024年第2期19卷 262-276页

作者： xueyan LI Babak NAIMI Peng GONG Miguel B.ARAÚJO Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of ScienceGuangzhouChina ‘Rui Nabeiro’Biodiversity Chair CHANGE-MED InstituteUniversity ofÉvoraÉvoraPortugal Department of Geography and Department of Earth Sciences University of Hong KongHong KongChina Department of Biogeography and Global Change National Museum of Natural SciencesCSICMadridSpain

Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models(BEMs).The approach can be used to investigate patterns and processes of species richness.If data limitations on individual species distributions are inevitable,but how do they affect inferences of patterns and processes of species richness?We investigate the influence of different data sources on estimated species richness gradients in China.We fitted BEMs using species distributions data for 334 bird species obtained from(1)global range maps,(2)regional checklists,(3)museum records and surveys,and(4)citizen science data using presence-only(Mahalanobis distance),presence-background(MAXENT),and presence–absence(GAM and BRT)BEMs.Individual species predictions were stacked to generate species richness gradients.Here,we show that different data sources and BEMs can generate spatially varying gradients of species richness.The environmental predictors that best explained species distributions also differed between data sources.Models using citizen-based data had the highest accuracy,whereas those using range data had the lowest accuracy.Potential richness patterns estimated by GAM and BRT models were robust to data uncertainty.When multiple data sets exist for the same region and taxa,we advise that explicit treatments of uncertainty,such as sensitivity analyses of the input data,should be conducted during the process of modeling.

关键词： richness patterns species distribution stacked bioclimatic envelope models uncertainty

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A novel graph oversampling framework for node classification in class-imbalanced graphs

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Science China(Information Sciences) 2024年第6期67卷 214-229页

作者： Riting XIA Chunxu ZHANG Yan ZHANG xueyan LIU Bo YANG Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University College of Artificial Intelligence Jilin University College of Computer Science and Technology Jilin University College of Communication Engineering Jilin University

Graph neural network(GNN) is a promising method to analyze graphs. Most existing GNNs adopt the class-balanced assumption, which cannot deal with class-imbalanced graphs well. The oversampling technique is effective in alleviating class-imbalanced problems. However, most graph oversampling methods generate synthetic minority nodes and their edges after applying GNNs. They ignore the problem that the representations of the original and synthetic minority nodes are dominated by majority nodes caused by aggregating neighbor information through GNN before oversampling. In this paper, we propose a novel graph oversampling framework, termed distribution alignment-based oversampling for node classification in classimbalanced graphs(named Graph-DAO). Our framework generates synthetic minority nodes before GNN to avoid the dominance of majority nodes caused by message passing in GNNs. Additionally, we introduce a distribution alignment method based on the sum-product network to learn more information about minority nodes. To our best knowledge, it is the first to use the sum-product network to solve the class-imbalanced problem in node classification. A large number of experiments on four real datasets show that our method achieves the optimal results on the node classification task for class-imbalanced graphs.

关键词： graph neural network class-imbalanced graphs sum-product network oversampling node classification

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A Method for Detecting and Recognizing Yi Character Based on Deep Learning

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Computers, Materials & Continua 2024年第2期78卷 2721-2739页

作者： Haipeng Sun xueyan Ding Jian Sun HuaYu Jianxin Zhang School of Computer Science and Engineering Dalian Minzu UniversityDalian116600China Institute of Machine Intelligence and Bio-Computing Dalian Minzu UniversityDalian116600China 3Yi Language Research RoomChina Ethnic Languages Translation Centre Beijing100080China

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and recognition.In the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character detection.Then,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different scales.Further,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original map.These maps are then subjected to a differentiable binarization process,resulting in an approximate binarization map.This map helps to identify the boundaries of the text boxes.Finally,the text detection box is generated after the post-processing stage.In the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters recognition.Meanwhile,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text recognition.The experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,respectively.And also,we have compared the detection and recognition algorithms proposed in this paper with

关键词： Yi characters text detection text recognition attention mechanism deep neural network

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