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Motor cortical circuit adaptations in parkinsonism

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Neural Regeneration Research 2024年第10期19卷 2107-2108页

作者： Hong-yuan Chu Department of Neurodegenerative Science Van Andel Research InstituteGrand RapidsMIUSA Aligning Science Across Parkinson’s(ASAP)Collaborative Research Network

Parkinson's disease is a chronic and progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta,which leads to the featured motor impairment of parki... 详细信息

关键词： parkin impairment rigidity

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

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Geodesy and Geodynamics 2024年第1期15卷 100-105页

作者： Fei Ye Yunbin yuan State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China Hunan Continuously Operating Reference Stations(HNCORS)Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame ***,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM ***,the weighted LS+AR hybrid method performs well for PM short-term ***,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR *** this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid *** using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid *** to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,***,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

关键词： Stochastic model LS+AR Short-term prediction The earth rotation parameter(ERP) Observation model

MOF glass foam: a blueprint to porous membrane scaling-up

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Science China Chemistry 2024年第3期67卷 746-748页

作者： yuan Peng Weishen Yang State Key Laboratory of Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China

In comparison with conventional energy-intensive separation technologies, such as distillation and crystallization,membrane separation is labelled as an advanced technology with low energy consumption, a small carbon footprint,continuous operation, etc. Metal-organic frameworks(MOFs) are a burgeoning category of crystalline materials consisting of metal ions/clusters coordinated with organic ligands.

关键词： separation porous distillation

Improved LS+MAR hybrid method to UT1-UTC ultra-short-term prediction by using first-order-difference UT1-UTC

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Geodesy and Geodynamics 2024年第4期15卷 379-385页

作者： Fei Ye Yunbin yuan BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha410007China State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan430077China HNCORS Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Accurate ultra-short-term prediction of the Earth rotation parameters(ERP)holds paramount impor-tance for real-time applications,particularly in reference frame *** them,diurnal rota-tion(UT1-UTC)which cannot be directly estimated through Global Navigation Satellite System(GNSS)techniques,significantly affects the rapid and ultra-rapid orbit determination of GNsS ***-ently,the traditional LS(least squares)+AR(autoregressive)and LS+MAR(multivariate autoregressive)hybrid methods stand as primary approaches for UT1-UTC ultra-short-term predictions(1-10 days).The LS+MAR hybrid method relies on the UT1-UTC and LOD(length of day)***,the correlation between LOD and first-order-difference UT1-UTC is stronger than that between LOD and *** light of this,and with the aid of the first-order-difference UT1-UTC,we propose an enhanced LS+MAR hybrid method to UT1-UTC ultra-short-term *** using the UT1-UTC and LOD data series of the IERS(International Earth Rotation and Reference Systems Service)EOP 14 C04 product,we conducted a thorough analysis and evaluation of the improved method's prediction performance compared to the traditional LS+AR and LS+MAR hybrid *** to the numerical results over more than 210 days,they demonstrate that,when considering the correlation information between the LoD and the first-order-difference UT1-UTC,the mean absolute errors(MAEs)of the improved LS+MAR hybrid method range from 21 to 934μs in 1-10 days *** comparison to the traditional LS+AR hybrid method,the MAEs show a reduction of 7-53μs in 1-10 days predictions,with corresponding improvement percentages ranging from 1 to 28%.Similarly,when compared to the traditional LS+MAR hybrid method,the MAEs have a reduction of 5-42μs in 1-10 days predictions,with corresponding improvement percentages ranging from 4-20%.Additionally,when aided by GNSS-derived LOD data series,the MAEs of improved LS+MAR hybrid method experience further

关键词： UT1-UTCultra-short-termprediction Rapidandultra-rapidproducts LS+AR and LS+MAR Correlation First-order-differenceUT1-UTC

A regression approach for seismic first-break picking

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Petroleum Science 2024年第3期21卷 1584-1596页

作者： Huan yuan San-Yi yuan Jie Wu Wen-Jing Sang Yu-He Zhao CNPC Key Laboratory of Geophysical Exploration China University of Petroleum(Beijing)Beijing 102249China Research Institute of Petroleum Exploration&Development—Northwest(NWGI) Key Laboratory of reservoir characterization of CNPCPetroChinaLanzhou 730020GansuChina

The picking efficiency of seismic first breaks(FBs)has been greatly accelerated by deep learning(DL)***,the picking accuracy and efficiency of DL methods still face huge challenges in low signal-to-noise ratio(SNR)*** address this issue,we propose a regression approach to pick FBs based on bidirectional long short-term memory(Bi LSTM)neural network by learning the implicit Eikonal equation of 3D inhomogeneous media with rugged topography in the target *** employ a regressive model that represents the relationships among the elevation of shots,offset and the elevation of receivers with their seismic traveltime to predict the unknown FBs,from common-shot gathers with sparsely distributed *** from image segmentation methods which automatically extract image features and classify FBs from seismic data,the proposed method can learn the inner relationship between field geometry and *** addition,the predicted results by the regressive model are continuous values of FBs rather than the discrete ones of the binary *** picking results of synthetic data shows that the proposed method has low dependence on label data,and can obtain reliable and similar predicted results using two types of label data with large *** picking results of9380 shots for 3D seismic data generated by vibroseis indicate that the proposed method can still accurately predict FBs in low SNR *** subsequent stacked profiles further illustrate the reliability and effectiveness of the proposed *** results of model data and field seismic data demonstrate that the proposed regression method is a robust first-break picker with high potential for field application.

关键词： First-break picking Low signal-to-noiseratio Regression BiLSTM Traveltime Geometry Noisy seismic data

Outlier item detection in bundle recommendation via the attention mechanism

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High-Confidence Computing

High-Confidence Computing 2024年第3期4卷 51-57页

作者： yuan Liang School of Information Engineering Suqian UniversitySuqian 223800China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China

Bundle recommendation offers users more holistic insights by recommending multiple compatible items at ***,the intricate correlations between items,varied user preferences,and the pronounced data sparsity in combinations present significant challenges for bundle recommendation ***,current bundle recommendation methods fail to identify mismatched items within a given set,a process termed as‘‘outlier item detection’’.These outlier items are those with the weakest correlations within a *** them can aid users in refining their item *** the correlation among items can predict the detection of such outliers,the adaptability of combinations might not be adequately responsive to shifts in individual items during the learning *** limitation can hinder the algorithm’s *** tackle these challenges,we introduce an encoder–decoder architecture tailored for outlier item *** encoder learns potential item correlations through a self-attention ***,the decoder garners efficient inference frameworks by directly assessing item *** have validated the efficacy and efficiency of our proposed algorithm using real-world datasets.

关键词： Bundle recommendation Outlier item detection Attention mechanism Decoder encoder

Numerical investigation of the photo-thermal characteristics of a direct absorption solar collector using Monte Carlo and finite volume methods

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Science China(Technological Sciences) 2024年第8期67卷 2436-2448页

作者： ZHU YanLong LI SuNing FAN JianHua KONG WeiQiang yuan yuan TAN HePing School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China Department of Civil Engineering and Mechanical Engineering Technical University of DenmarkKoppels AlléBuilding 4042800 Kgs.LyngbyDenmark School of Vehicle and Energy Yanshan UniversityQinhuangdao 066004China

In this study, a novel model of photothermal conversion in a direct absorption solar collector based on the Monte Carlo and finite volume methods was built and validated and the temperatures of the novel and traditional solar collectors were compared. The sensitivity of the parameters to the radiative heat loss was investigated. Finally, the radiative heat transfer characteristics were discussed using the radiative exchange factor. The results of this study validated the advantages of the novel solar collector at both the surface and fluid temperatures. Under the conditions used in this study, the maximum temperature difference of the novel solar collector was 30 K, compared with 193 K for the traditional solar collector. Furthermore, the collector was divided into several units along the flow direction. The radiative exchange factor indicated that with an increase in the attenuation coefficient, the percentage of radiation intensity in the total solar radiation absorbed by the corresponding unit ***, it decreased with an increase in the incident angle and scattering albedo. These results provide a reference for addressing the low efficiency and thermal damage caused by traditional solar collectors at high temperatures.

关键词： direct absorption solar collector radiative heat transfer Monte Carlo

Tribological evaluation of thermoplastic polyurethane-based bearing materials under water lubrication:Effect of load,sliding speed,and temperature

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Friction 2024年第8期12卷 1801-1815页

作者： Shaoli JIANG Janet SSWONG Debashis PUHAN Tian yuan Xiuqin BAI Chengqing yuan State Key Laboratory of Maritime Technology and Safety Wuhan University of TechnologyWuhan 430063China Department of Mechanical Engineering Imperial College LondonLondon SW72AZUK Yusuf Hamied Department of Chemistry University of CambridgeLensfield RoadCambridge CB21EWUK

Polymers are widely used in bearing *** the case of water-lubricated stern tube bearings,thermoplastic polyurethane(TPU)-based composites are used due to their excellent wear resistance,corrosion resistance,and tunable mechanical *** tribological performance,however,depends on operating *** this work,TPU was blended with carbon fiber,graphene platelet,and ultra-high molecular weight polyethylene(UHMWPE).Friction tests of TPU based-composites against copper countersurface were carried out in water to mimic the actual operating conditions of the *** of the resulting contacts were in the boundary lubrication regime,in which friction was attributed to both contact mechanics of asperities as well as water *** results show that the viscoelasticity of TPU has a considerable impact on its tribological *** lubrication at 50°C promotes the softening of polymer surface material during sliding,resulting in higher fluctuation in the coefficient of friction and wear *** is attributed to the reduced thermomechanical *** addition,Schallamach waviness is observed on worn *** tribological properties of TPU are significantly improved by the inclusion of carbon fiber,graphene platelet,and *** formation of graphene transfer-layers and UHMWPE transfer film reduces friction and wear loss,while the inclusion of carbon fiber enhances wear resistance due to improved mechanical properties and load bearing capacity.

关键词： friction thermoplastic polyurethane(TPU) water-lubricated bearings graphene platelet carbon fibers ultra-high molecular weight polyethylene(UHMWPE)

Single-atom Ag-loaded carbon nitride photocatalysts for efficient degradation of acetaminophen:The role of Ag-atom and O_(2)

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Journal of Environmental Sciences 2024年第5期139卷 12-22页

作者： Yi yuan Wen-Long Wang Zhi-Wei Wang Jin Wang Qian-yuan Wu Key Laboratory of Microorganism Application and Risk Control of Shenzhen Guangdong Provincial Engineering Research Center for Urban Water Recycling and Environmental SafetyInstitute of Environment and EcologyShenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Shenzhen Environmental Science and New Energy Technology Engineering Laboratory Tsinghua-Berkeley Shenzhen InstituteShenzhen 518055China College of Materials Science and Engineering Shenzhen UniversityShenzhen 518071China

Carbon nitride has been extensively used as a visible-light photocatalyst,but it has the disadvantages of a low specific surface area,rapid electron-hole recombination,and relatively low light *** this study,single-atom Ag was successfully anchored on ultrathin carbon nitride(UTCN)via thermal polymerization,the catalyst obtained is called *** Ag hardly changed the carbon nitride's layered and porous physical *** exhibited efficient visible-light photocatalytic performances in the degradation of various recalcitrant pollutants,eliminations of 85% were achieved by visible-light irradiation for *** with Ag improved the photocatalytic performance of UTCN by narrowing the forbidden band gap from 2.49 to 2.36 e V and suppressing electron-hole pair *** addition,Ag doping facilitated O_(2) adsorption on UTCN by decreasing the adsorption energy from -0.2 to -2.22 e V and favored the formation of O_(2)^(·-).Electron spin resonance and radical-quenching experiments showed that O_(2)^(·-)was the major reactive species in the degradation of Acetaminophen(paracetamol,APAP).

关键词： Ag single atom Carbon nitride Photocatalysis Visible light Adsorption energy Reactive species