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Migration mechanism and risk assessment of perand polyfluoroalkyl substances in the Ya'Er Lake oxidation pond area,China

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Journal of Environmental Sciences 2024年第2期136卷 301-312页

作者： Chang Li Huifang Zhong Jing wu Lingyi Meng Yingjun Wang Chunyang Liao yawei Wang Yujian He University of Chinese Academy of Sciences Beijing 100049China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China China National Environmental Monitoring Centre Beijing 100012China Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances Institute of Environment and HealthJianghan UniversityWuhan 430056China

The migration mechanisms,sources,and environmental risks of 29 legacy and emerging perfluorinated and polyfluoroalkyl species present in an oxidation pond(Ya'Er Lake)were investigated for treating sewage based on the analysis of their occurrence and distribution.The concentration of per-and polyfluoroalkyl substances(PFAS)in pond area was between0.30 and 63.2 ng/g dw(dry weight),with the overall average concentration of 8.00 ng/g dw.Notably,the PFAS concentrations in the surface sediments near the sewage outlet in Pond-1(50.2 ng/g dw)and Pond-5(average 15.1 ng/g dw)were 1–2 orders of magnitude higher than those in other areas.In general,the legacy PFAS,i.e.,perfluorooctane sulfonic acid was considered to be the major pollutant in the polluted area,on average,accounting for 73.0%of the total concentration of PFAS pollutants.By evaluating the regional distribution of different PFAS homologs,the short-chain PFAS pollutants with lower K_(ow)were found to migrate farther in both horizontal and vertical directions.The sewage outlets in Pond-1 and Pond-5are the main pollution sources in polluted area and the emerging PFAS pollutants in Pond-5have replaced the legacy PFAS pollutants as the main pollutants.Based on positive matrix factorization analysis,three main industrial sources of PFAS pollutants in the study area were identified:protective coating,fire-fighting,and food packaging sources.Moreover,the environmental risk assessment results showed that most study areas exhibited medium environmental risk(0.01≤Risk quotient(RQ)<1),indicating that the ecological environment risks in this area need further attention.

关键词： Perfluoroalkyl substances Distribution Migration mechanism Risk assessment

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Large language model and domain-specific model collaboration for smart education

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Frontiers of Information Technology & Electronic Engineering 2024年第3期25卷 333-341页

作者： yawei LUO Yi YANG School of Software Technology Zhejiang UniversityNingbo 315048China College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China

In this paper,we introduce the large language model and domain-specific model collaboration(LDMC)framework designed to enhance smart education.The LDMC framework leverages the comprehensive and versatile knowledge of large domain-general models,combines it with the specialized and disciplinary knowledge from small domainspecific models(DSMs),and incorporates pedagogy knowledge from learning theory models.This integration yields multiple knowledge representations,fostering personalized and adaptive educational experiences.We explore various applications of the LDMC framework in the context of smart education.

关键词： smart language knowledge

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Lanthanide-based microlasers:Synthesis,structures,and biomedical applications

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Nano Research 2024年第1期17卷 97-111页

作者： Qian Zhang yawei Liu Kai Liu Hongjie Zhang Engineering Research Center of Advanced Rare Earth Materials(Ministry of Education) Department of ChemistryTsinghua UniversityBeijing 100084China State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022China Xiangfu Laboratory Jiaxing 314102China

The large size of lasers limits their applications in confined spaces,such as in biosensing and in vivo brain tissue imaging.In this regard,micron-sized lasers have been developed.They exhibit great potential for biological detecting,remote sensing,and depth tracking due to their small sizes,sensitive properties of their spectral fingerprints,and flexible positional modulation in the microenvironment.Lanthanide-based luminescent materials that possess long excited-state lifetime,narrow emission bandwidth,and upconversion behaviors are promising as gain mediums for novel microlasers.In addition,lanthanide-based microlasers could be generated under natural ambient conditions with pumped or continuous light sources,which significantly promotes the practical applications of microlasers.Recent progress in the design,synthesis,and biomedical applications of lanthanide-based microlasers has been outlined in this review.Lanthanide ions doped and upconverted lanthanide-based microlasers are highlighted,which exhibit advantageous structures,miniaturized dimensions,and high lasing performance.The applications of lanthanide-based microlasers are further discussed,the upconverted microlasers show great advantages for biological applications owing to their tunable excitation and emission characteristics and excellent environmental stability.Moreover,perspectives and challenges in the field of lanthanide-based microlasers are presented.

关键词： microlasers lanthanide-based luminescent materials upconversion nanoparticles biological applications

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Extensive prediction of drug response in mutation-subtype-specific LUAD with machine learning approach

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Oncology Research 2024年第2期32卷 409-419页

作者： KEGANG JIA yawei WANG QI CAO YOUYU WANG Department of Thoracic Surgery Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduChina School of Medicine University of Electronic Science and Technology of ChinaChengduChina Department of Assisted Reproductive Medicine Sichuan Provincial Academy of Medical Sciences&Sichuan Provincial People’s HospitalChengduChina

Lung cancer is the most prevalent cancer diagnosis and the leading cause of cancer death worldwide.Therapeutic failure in lung cancer(LUAD)is heavily influenced by drug resistance.This challenge stems from the diverse cell populations within the tumor,each having unique genetic,epigenetic,and phenotypic profiles.Such variations lead to varied therapeutic responses,thereby contributing to tumor relapse and disease progression.Methods:The Genomics of Drug Sensitivity in Cancer(GDSC)database was used in this investigation to obtain the mRNA expression dataset,genomic mutation profile,and drug sensitivity information of NSCLS.Machine Learning(ML)methods,including Random Forest(RF),Artificial Neurol Network(ANN),and Support Vector Machine(SVM),were used to predict the response status of each compound based on the mRNA and mutation characteristics determined using statistical methods.The most suitable method for each drug was proposed by comparing the prediction accuracy of different ML methods,and the selected mRNA and mutation characteristics were identified as molecular features for the drug-responsive cancer subtype.Finally,the prognostic influence of molecular features on the mutational subtype of LUAD in publicly available datasets.Results:Our analyses yielded 1,564 gene features and 45 mutational features for 46 drugs.Applying the ML approach to predict the drug response for each medication revealed an upstanding performance for SVM in predicting Afuresertib drug response(area under the curve[AUC]0.875)using CIT,GAS2L3,STAG3L3,ATP2B4-mut,and IL15RA-mut as molecular features.Furthermore,the ANN algorithm using 9 mRNA characteristics demonstrated the highest prediction performance(AUC 0.780)in Gefitinib with CCL23-mut.Conclusion:This work extensively investigated the mRNA and mutation signatures associated with drug response in LUAD using a machine-learning approach and proposed a priority algorithm to predict drug response for different drugs.

关键词： Lung adenocarcinoma Drug resistance Machine learning Molecular features Personalized treatment

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An Innovation of Evaluation and Design of Vehicle Acceleration Sound Based on EEG Signals

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Journal of Bionic Engineering 2024年第1期21卷 344-361页

作者： Liping Xie XinYou Lin Wan Chen Zhien Liu yawei Zhu College of Mechanical Engineering&Automation Fuzhou UniversityFuzhou 350108China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of TechnologyWuhan 430070China

There is a bottleneck in the design of vehicle sound that the subjective perception of sound quality that combines multiple psychological factors fails to be accurately and objectively quantified.Therefore,EEG signals are introduced in this paper to investigate the evaluation and design method of vehicle acceleration sound with powerful sound quality.Firstly,the experiment of EEG acquisition and subjective evaluation under the stimulation of powerful vehicle sounds is conducted,respectively,then three physiological EEG features of PSD_β,PSD_γand DE are constructed to evaluate the vehicle sounds based on the correlation analysis algorithms.Subsequently,the Adaptive Genetic Algorithm(AGA)is proposed to optimize the Elman model,where an intelligent model(AGA–Elman)is constructed to objectively predicate the perception of subjects for the vehicle sounds with powerful sound quality.The results demonstrate that the error of the constructed AGA–Elman model is only 2.88%,which outperforms than the traditional BP and Elman model;Finally,two vehicle acceleration sounds(Design1 and Design2)are designed based on the constructed AGA–Elman model from the perspective of order modulation and frequency modulation,which provide the acoustic theoretical guidance for the design of vehicle sound incorporating the EEG signals.

关键词： EEG signal Brain activity analysis Vehicle sound design Adaptive genetic algorithm-Elman model

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Experimental Investigation and X-Ray Computed Microtomography Simulation on Thermal Physical Properties of Foundation Materials after Molten Salt Leakage in the Storage Tank

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Journal of Thermal Science 2024年第2期33卷 591-601页

作者： WANG Zhaowen ZHOU Hao LUO Jiawei LI yawei FANG Hao LIU Tianxiao State Key Laboratory of Clean Energy Utilization Institute for Thermal Power EngineeringZhejiang UniversityHangzhou310027China

This paper studied the thermal physical properties of foundation materials in the molten salt tank of thermal energy storage system after molten salt leakage by Transient plane source experiment and X-ray computed microtomography simulation methods.The microstructure,thermal properties and pressure resistance with different particle diameters were addressed.The measured heat conductivities from Transient plane source experiment for three cases are 0.49 W/(m·K),0.48 W/(m·K),and 0.51 W/(m·K),and the porosity is 30.1%,30.7%,and 31.2% respectively.The heat conductivity simulating results of three cases are 0.471 W/(m·K),0.482W/(m·K),and 0.513 W/(m·K).The ratio of difference between the results of simulation and Transient plane source measurement is as low as 1.2%,verifying the reliability of experimental and simulation results to a certain degree.Compared with the heat conductivity of 0.097-0.129 W/(m·K) and porosity of 71.6%-78.9% without leaking salt,the porosity is reduced by more than 50% while the heat conductivity increased by 4 to 5 times after molten salt leakage.This significant increase in heat conductivity has a great impact on security operation,structure design,and modeling of the tank foundation for solar power plants.

关键词： heat conductivity X-ray computed microtomography foundation materials three-phase threshold algorithm molten salt leakage

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Rbm8a regulates neurogenesis and reduces Alzheimer's disease-associated pathology in the dentate gyrus of 5×FAD mice

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Neural Regeneration Research 2024年第4期19卷 863-871页

作者： Chenlu Zhu Xiao Ren Chen Liu yawei Liu Yonggang Wang Department of Neurology Lanzhou University Second Hospital Department of Neurology The First Affiliated Hospital of Nanchang University Department of Neurology Xiaogan City Central Hospital Health Service Department of the Guard Bureau of the General Office of the Central Committee of the Communist Party of China Headache Center Department of NeurologyBeijing Tiantan HospitalCapital Medical University

Alzheimer’s disease is a prevalent and debilitating neurodegenerative condition that profoundly affects a patient’s daily functioning with progressive cognitive decline,which can be partly attributed to impaired hippocampal neurogenesis.Neurogenesis in the hippocampal dentate gyrus is likely to persist throughout life but declines with aging,especially in Alzheimer’s disease.Recent evidence indicated that RNA-binding protein 8A(Rbm8a)promotes the proliferation of neural progenitor cells,with lower expression levels observed in Alzheimer’s disease patients compared with healthy people.This study investigated the hypothesis that Rbm8a overexpression may enhance neurogenesis by promoting the proliferation of neural progenitor cells to improve memory impairment in Alzheimer’s disease.Therefore,Rbm8a overexpression was induced in the dentate gyrus of 5×FAD mice to validate this hypothesis.Elevated Rbm8a levels in the dentate gyrus triggered neurogenesis and abated pathological phenotypes(such as plaque formation,gliosis reaction,and dystrophic neurites),leading to ameliorated memory performance in 5×FAD mice.RNA sequencing data further substantiated these findings,showing the enrichment of differentially expressed genes involved in biological processes including neurogenesis,cell proliferation,and amyloid protein formation.In conclusion,overexpressing Rbm8a in the dentate gyrus of 5×FAD mouse brains improved cognitive function by ameliorating amyloid-beta-associated pathological phenotypes and enhancing neurogenesis.

关键词： Adora2a Alzheimer’s disease astrocyte cAMP signaling pathway dentate gyrus dystrophic neurites microglia neurogenesis plaque Rbm8a

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Audio-visual keyword transformer for unconstrained sentence-level keyword spotting

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 142-152页

作者： Yidi Li Jiale Ren yawei Wang Guoquan Wang Xia Li Hong Liu Key Laboratory of Machine Perception Peking UniversityShenzhen Graduate SchoolShenzhenChina College of Electronics and Information Engineering Sichuan UniversityChengduChina Department of Computer Science ETH ZurichZurichSwitzerland

As one of the most effective methods to improve the accuracy and robustness of speech tasks,the audio-visual fusion approach has recently been introduced into the field of Keyword Spotting(KWS).However,existing audio-visual keyword spotting models are limited to detecting isolated words,while keyword spotting for unconstrained speech is still a challenging problem.To this end,an Audio-Visual Keyword Transformer(AVKT)network is proposed to spot keywords in unconstrained video clips.The authors present a transformer classifier with learnable CLS tokens to extract distinctive keyword features from the variable-length audio and visual inputs.The outputs of audio and visual branches are combined in a decision fusion module.As humans can easily notice whether a keyword appears in a sentence or not,our AVKT network can detect whether a video clip with a spoken sentence contains a pre-specified keyword.Moreover,the position of the keyword is localised in the attention map without additional position labels.Exper-imental results on the LRS2-KWS dataset and our newly collected PKU-KWS dataset show that the accuracy of AVKT exceeded 99%in clean scenes and 85%in extremely noisy conditions.The code is available at https://***/jialeren/AVKT.

关键词： artificial intelligence multimodal approaches natural language processing neural network speech processing

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Tailored boron phosphate monolithic foam with multimodal hierarchically porous structure and its applications

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Nano Research 2022年第7期15卷 6695-6704页

作者： Qiuwen Liu Qiang Liu Yawei Wu Renyou Zeng Fangshu Xing ChuChu Cheng Huibin Qiu Caijin Huang State Key Laboratory of Photocatalysis on Energy and Environment College of ChemistryFuzhou UniversityFuzhou 350116China School of Chemistry and Chemical Engineering Frontiers Science Center for Transformative MoleculesState Key Laboratory of Metal Matrix CompositesShanghai Jiao Tong UniversityShanghai 200240China Ganjiang Innovation Academy Chinese Academy of SciencesGanzhou 341000China

The synthesis of multimodal hierarchically porous materials is of great challenge by facile approach.Herein,we assemble BPO_(4) hollow spheres into macroscopic foam materials with multimodal hierarchically porous structure by combining down-to-up process and Ostwald ripening effect.Tailored monolithic B_(2)O_(3)@BPO_(4) foams were obtained from a sticky hydrogel precursor by a one-step annealing process.The foam has the self-supporting frame of BPO_(4) hollow spheres with covering B_(2)O_(3) nanowires and shows excellent permeability and relatively high surface area due to hierarchical structure.The formation mechanism of monolithic B_(2)O_(3)@BPO_(4) foams mainly undergoes inflation,particle aggregation,and Ostwald ripening process.Monolithic foams exhibit superior catalytic activity in oxidation dehydrogenation of alkanes due to the sufficient exposure of active sites over the special frame structure.Furthermore,various monolithic functionalized BPO_(4) foam composites can be easily synthesized and exhibit superior performance in different applications including the oxidation of carbon monoxide,and the self-driven removal of organic pollutants.More interestingly,we also found the sticky hydrogel precursor possesses good heat shielding effect.This work provides a new insight for constructing multimodal hierarchically porous materials with the remaining superior property of nanoscale to cope with various challenges.

关键词： multimodal hierarchically porous materials tailored monolithic foam sticky hydrogel self-supporting hollow spheres

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An Asymmetric Galactic Stellar Disk Traced by OB-type Stars from LAMOST DR7

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Research in Astronomy and Astrophysics 2024年第6期24卷 40-53页

作者： Xiaopeng Liu Hao Tian Wenyuan Cui Linlin Li Jiaming Liu Zhenyan Huo yawei Gao Department of Physics Hebei Normal University Guo Shoujing Institute for Astronomy Hebei Normal University Key Laboratory of Space Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University

Using 9943 OB-type stars from LAMOST DR7 in the solar neighborhood,we fit the vertical stellar density profile with the model including a single exponential distribution at different positions (R,Φ).The distributions of the scale heights and scale length show that the young disk traced by the OB-type stars is not axisymmetric.The scale length decreases versus the azimuthal angle Φ,i.e.,from.■kpc withΦ=-3°to■kpc withΦ=9°.Meanwhile we find signal of non-symmetry in the distribution of the scale height of the north and south of the disk plane.The scale height in the north side shows signal of flaring of the disk,while that of the south disk stays almost constant around hs=130 pc.The distribution of the displaceeent of the disk plane Z0also shows variance versus the azimuthal angleΦ,which displays significant differences with the warp model constrained by the Cepheid stars.We also test different values for the position of the Sun,and the distance between the Sun and the Galactic center affects the scale heights and the displacement of the disk significantly,but that does not change our conclusion that the disk is not axisymmetric.

关键词： galaxies: spiral Galaxy: disk stars: early-type stars: massive

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