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Multi boron-doping effects in hard carbon toward enhanced sodium ion storage

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Journal of Energy Chemistry 2025年第1期100卷 730-738页

作者： Peng Zheng Wang Zhou Ying Mo Biao Zheng Miaomiao Han Qin Zhong Wenwen Yang Peng Gao Lezhi Yang Jilei Liu College of Materials Science and Engineering Hunan Joint International Laboratory of Advanced Materials and Technology for Clean Energy Hunan Province Key Laboratory for Advanced Carbon Materials and Applied Technology Hunan University Greater Bay Area institute for Innovation Hunan University Changsha research institute of Mining & Metallurgy Co. LTD.

Hard carbon （HC） has been considered as promising anode material for sodium-ion batteries （SIBs）.The optimization of hard carbon’s microstructure and solid electrolyte interface （SEI） property are demonstrated effective in enhancing the Na+storage capability,however,a one-step regulation strategy to achieve simultaneous multi-scale structures optimization is highly ***,we have systematically investigated the effects of boron doping on hard carbon’s microstructure and interface chemistry.A variety of structure characterizations show that appropriate amount of boron doping can increase the size of closed pores via rearrangement of carbon layers with improved graphitization degree,which provides more Na+storage ***-situ Fourier transform infrared spectroscopy/electrochemical impedance spectroscopy （FTIR/EIS） and X-ray photoelectron spectroscopy （XPS） analysis demonstrate the presence of more BC3and less B–C–O structures that result in enhanced ion diffusion kinetics and the formation of inorganic rich and robust SEI,which leads to facilitated charge transfer and excellent rate *** a result,the hard carbon anode with optimized boron doping content exhibits enhanced rate and cycling *** general,this work unravels the critical role of boron doping in optimizing the pore structure,interface chemistry and diffusion kinetics of hard carbon,which enables rational design of sodium-ion battery anode with enhanced Na+storage performance.

关键词： X ray photoelectron spectroscopy

Depression mechanism of sulfite ions on sphalerite and Pb^(2+)activated sphalerite in the flotation separation of galena from sphalerite

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international Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 335-345页

作者： Feng Zhang Chenyang Zhang Linlin Wu Wei Sun Hongliang Zhang Jianhua Chen Yong Pei Songjiang Li Engineering research center of Ministry of Education for Carbon Emission Reduction in Metal Resource Exploitation and Utilization Hunan International Joint Research Center for Efficient and Clean Utilization of Critical Metal Mineral ResourcesSchool of Minerals Processing and BioengineeringCentral South UniversityChangsha 410083China State Key Laboratory of Mineral Processing Beijing General Research Institute of Mining&MetallurgyBeijing 100160China Hunan Provincial Key Laboratory of Micro&Nano Materials Interfaces Science College of Chemistry and Chemical EngineeringCentral South UniversityChangsha 410083China School of Resources Environment and MaterialsGuangxi UniversityNanning 530004China Department of Chemistry Xiangtan UniversityXiangtan 411105China China Railway Resource Group Co.Ltd Beijing 102300China

The depression mechanism of sulfite ions on sphalerite and Pb^(2+)activated sphalerite in the flotation separation of galena from sphalerite still lacked in-depth ***,the depression mechanism of sulfite ions on sphalerite and Pb^(2+)activated sphalerite in the flotation separation of galena from sphalerite was further systematically investigated with experiments and density functional theory(DFT)*** X-ray photoelectric spectroscopy(XPS)results,DFT calculation results,and frontier molecular orbital analysis indicated that sulfite ions were difficult to be adsorbed on sphalerite surface,suggesting that sulfite ions achieved depression effects on sphalerite through other non-adsorption ***,the oxygen content in the surface of sphalerite treated with sulfite ions in creased,which enhanced the hydrophilicity of the sphalerite and further increased the difference in hydrophilicity between sphalerite and ***,sulfite ions were chelated with lead ions to form PbSO_(3)in *** hydrophilic PbSO_(3)was more easily adsorbed on sphalerite than *** interaction between sulfite ions and lead ions could effectively inhibit the activation of *** addition the UV spectrum showed that after adding sulfite ions,the peak of perxanthate in the sphalerite treated xanthate solution was significantly stronger than that in the galena with xanthate solution,indicating that xanthate interacted more readily with sulfite ions and oxygen mo lecules within the sphalerite system,leading to the formation of ***,sulfite ions hardly depressed the flotation of ga lena and could promote the flotation of galena to some *** study deepened the understanding of the depression mechanism o sulfite ions on sphalerite and Pb^(2+)activated sphalerite.

关键词： sphalerite galena sulfite ion density functional theory depression mechanism

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

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Neural Regeneration research 2025年第1期20卷 93-106页

作者： Yujie Yang Xinyi Li Jiaying Lu Jingjie Ge Mingjia Chen Ruixin Yao Mei Tian Jian Wang Fengtao Liu Chuantao Zuo Key Laboratory of Arrhythmias Ministry of EducationDepartment of Medical GeneticsShanghai East HospitalSchool of MedicineTongji UniversityShanghaiChina Department of Neurology National Research Center for Aging and MedicineNational Center for Neurological Disordersand State Key Laboratory of Medical NeurobiologyHuashan HospitalFudan UniversityShanghaiChina Department of Nuclear Medicine&PET center National Center for Neurological Disordersand National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina international Human Phenome institutes(Shanghai) ShanghaiChina Human Phenome institute Fudan UniversityShanghaiChina

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of *** review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest *** conducted a thorough literature search using reputable databases such as PubMed and Web of *** criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical *** findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting ***,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo *** validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic *** summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

关键词： aromatic amino acid decarboxylase brain imaging dopamine transporter Parkinson’s disease parkinsonism positron emission tomography presynaptic dopaminergic function vesicle monoamine transporter type 2

Unraveling brain aging through the lens of oral microbiota

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Neural Regeneration research 2025年第7期20卷 1930-1943页

作者： Qinchao Hu Si Wang Weiqi Zhang Jing Qu Guang-Hui Liu State Key Laboratory of Membrane Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Hospital of Stomatology Guanghua School of StomatologyGuangdong Provincial Key Laboratory of StomatologySun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Advanced Innovation center for Human Brain Protection and National Clinical research center for Geriatric Disorders Xuanwu HospitalCapital Medical UniversityBeijingChina Aging Translational Medicine center International Center for Aging and CancerBeijing Municipal Geriatric Medical Research CenterXuanwu HospitalCapital Medical UniversityBeijingChina CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijingChina University of Chinese Academy of Sciences BeijingChina institute for Stem Cell and Regeneration Chinese Academy of SciencesBeijingChina Aging Biomarker Consortium BeijingChina State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Beijing institute for Stem Cell and Regenerative Medicine BeijingChina

The oral cavity is a complex physiological community encompassing a wide range of *** of oral microbiota can lead to various oral infectious diseases,such as periodontitis and tooth decay,and even affect systemic health,including brain aging and neurodegenerative *** studies have highlighted how oral microbes might be involved in brain aging and neurodegeneration,indicating potential avenues for intervention *** this review,we summarize clinical evidence demonstrating a link between oral microbes/oral infectious diseases and brain aging/neurodegenerative diseases,and dissect potential mechanisms by which oral microbes contribute to brain aging and *** also highlight advances in therapeutic development grounded in the realm of oral microbes,with the goal of advancing brain health and promoting healthy aging.

关键词： Alzheimer's disease brain aging multiple sclerosis neurodegeneration neurodegenerative diseases oral microbiota Parkinson's disease periodontitis bacteria Porphyromonas gingivalis

Optimizing the key parameter to accelerate the recovery of AMOC under a rapid increase of greenhouse gas forcing

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 39-45页

作者： Haolan Ren Fei Zheng Tingwei Cao Qiang Wang international center for Climate and Environment Science(ICCES) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina College of Oceanography Hohai UniversityNanjingChina CAS Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of Sciences and Pilot National Laboratory for Marine Science and Technology(Qingdao)QingdaoChina

Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate *** studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC *** this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its *** a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s *** traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of *** results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter ***,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.

关键词： Recovery of AMOC 4×CO_(2)forcing Key parameter Parameter estimation Data assimilation Machine learning

Toward understanding the role of genomic repeat elements in neurodegenerative diseases

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Neural Regeneration research 2025年第3期20卷 646-659页

作者： Zhengyu An Aidi Jiang Jingqi Chen institute of Science and Technology for Brain-Inspired Intelligence Fudan UniversityShanghaiChina MOE Frontiers center for Brain Science Fudan UniversityShanghaiChina MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan UniversityShanghaiChina Zhangjiang Fudan international Innovation center ShanghaiChina

Neurodegenerative diseases cause great medical and economic burdens for both patients and society;however, the complex molecular mechanisms thereof are not yet well understood. With the development of high-coverage sequencing technology, researchers have started to notice that genomic repeat regions, previously neglected in search of disease culprits, are active contributors to multiple neurodegenerative diseases. In this review, we describe the association between repeat element variants and multiple degenerative diseases through genome-wide association studies and targeted sequencing. We discuss the identification of disease-relevant repeat element variants, further powered by the advancement of long-read sequencing technologies and their related tools, and summarize recent findings in the molecular mechanisms of repeat element variants in brain degeneration, such as those causing transcriptional silencing or RNA-mediated gain of toxic function. Furthermore, we describe how in silico predictions using innovative computational models, such as deep learning language models, could enhance and accelerate our understanding of the functional impact of repeat element variants. Finally, we discuss future directions to advance current findings for a better understanding of neurodegenerative diseases and the clinical applications of genomic repeat elements.

关键词： Alzheimer's disease ataxia deep learning long-read sequencing neurodegeneration neurodegenerative diseases Parkinson's disease repeat element structural variant

A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of research and Innovation Insights2TechinfoJaipur302001India University Centre for research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India center for Interdisciplinary research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun Wen-Biao Han Yi-Yang Guo He Wang Minghui Du Hangzhou institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space Science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou) University of Chinese Academy of Sciences Lanzhou center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University institute of Theoretical Physics & research center of Gravitation Lanzhou University international Centre for Theoretical Physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

Multi-layer multi-pass friction rolling additive manufacturing of Al alloy:Toward complex large-scale high-performance components

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international Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 425-438页

作者： Haibin Liu Run Hou Chenghao Wu Ruishan Xie Shujun Chen College of Mechanical&Energy Engineering Beijing University of TechnologyBeijing 100124China Chongqing research institute of Beijing University of Technology Chongqing 401121China

At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass *** this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool *** material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum *** results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center *** friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped *** tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition *** is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping *** multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.

关键词： aluminum alloy additive manufacturing solid-state friction stir welding multi-layer multi-pass