The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through acceler...The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through accelerated life testing.In the absence of lifetime data,the hidden long-term correlation between performance degradation data is challenging to mine effectively,which is the main factor that restricts the prediction precision and engineering application of the residual life prediction method.To address this problem,a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is proposed.Firstly,a nonlinear health indicator(HI)calculation method based on kernel principal component analysis(KPCA)and exponential weighted moving average(EWMA)is designed.Then,using the raw vibration data and HI,a multi-layer perceptron(MLP)neural network is trained to further calculate the HI of the online bearing in real time.Furthermore,The bidirectional long short-term memory model(BiLSTM)optimized by particle swarm optimization(PSO)is used to mine the time series features of HI and predict the remaining service life.Performance verification experiments and comparative experiments are carried out on the XJTU-SY bearing open dataset.The research results indicate that this method has an excellent ability to predict future HI and remaining life.展开更多
BACKGROUND Diabetic retinopathy(DR)is the primary cause of visual problems in patients with diabetes.The Heyingwuzi formulation(HYWZF)is effective against DR.AIM To determine the HYWZF prevention mechanisms,especially...BACKGROUND Diabetic retinopathy(DR)is the primary cause of visual problems in patients with diabetes.The Heyingwuzi formulation(HYWZF)is effective against DR.AIM To determine the HYWZF prevention mechanisms,especially those underlying mitophagy.METHODS Human retinal capillary endothelial cells(HRCECs)were treated with high glucose(hg),HYWZF serum,PX-478,or Mdivi-1 in vitro.Then,cell counting kit-8,transwell,and tube formation assays were used to evaluate HRCEC proliferation,invasion,and tube formation,respectively.Transmission electron microscopy was used to assess mitochondrial morphology,and Western blotting was used to determine the protein levels.Flow cytometry was used to assess cell apoptosis,reactive oxygen species(ROS)production,and mitochondrial membrane potential.Moreover,C57BL/6 mice were established in vivo using streptozotocin and treated with HYWZF for four weeks.Blood glucose levels and body weight were monitored continuously.Changes in retinal characteristics were evaluated using hematoxylin and eosin,tar violet,and periodic acid-Schiff staining.Protein levels in retinal tissues were determined via Western blotting,immunohistochemistry,and immunostaining.RESULTS HYWZF inhibited excessive ROS production,apoptosis,tube formation,and invasion in hg-induced HRCECs via mitochondrial autophagy in vitro.It increased the mRNA expression levels of BCL2-interacting protein 3(BNIP3),FUN14 domain-containing 1,BNIP3-like(BNIP3L,also known as NIX),PARKIN,PTEN-induced kinase 1,and hypoxia-inducible factor(HIF)-1α.Moreover,it downregulated the protein levels of vascular endothelial cell growth factor and increased the light chain 3-II/I ratio.However,PX-478 and Mdivi-1 reversed these effects.Additionally,PX-478 and Mdivi-1 rescued the effects of HYWZF by decreasing oxidative stress and apoptosis and increasing mitophagy.HYWZF intervention improved the symptoms of diabetes,tissue damage,number of acellular capillaries,and oxidative stress in vivo.Furthermore,in vivo experiments confirmed the results of in vitro experiments.CONCLUSION HYWZF alleviated DR and associated damage by promoting mitophagy via the HIF-1α/BNIP3/NIX axis.展开更多
In this paper,we consider the high order method for solving the linear transport equations under diffusive scaling and with random inputs.To tackle the randomness in the problem,the stochastic Galerkin method of the g...In this paper,we consider the high order method for solving the linear transport equations under diffusive scaling and with random inputs.To tackle the randomness in the problem,the stochastic Galerkin method of the generalized polynomial chaos approach has been employed.Besides,the high order implicit-explicit scheme under the micro-macro decomposition framework and the discontinuous Galerkin method have been employed.We provide several numerical experiments to validate the accuracy and the stochastic asymptotic-preserving property.展开更多
锌空气电池具有能量密度高、成本低等优点,是最具前途的绿色储能技术之一,开发用于空气阴极氧还原反应(ORR)和析氧反应(OER)的非贵金属催化剂至关重要。本文提出了一种新型高效的制备方法,通过热处理与电沉积技术,以不锈钢网为基底原位...锌空气电池具有能量密度高、成本低等优点,是最具前途的绿色储能技术之一,开发用于空气阴极氧还原反应(ORR)和析氧反应(OER)的非贵金属催化剂至关重要。本文提出了一种新型高效的制备方法,通过热处理与电沉积技术,以不锈钢网为基底原位生长NiO包裹的氮掺杂碳纳米管三维网络(NiO-CNT/SS)。得益于碳纳米管的独特三维结构,使其可以暴露出更多的活性位点,所制备催化剂OER性能优良,在100 mA cm−2电流密度下过电位仅为374 mV。此外,NiO-CNT/SS材料所组装的锌空气电池具有1.44 V开路电压以及优异的循环稳定性,在5 mA cm−2电流密度下可以稳定循环145 h而无明显衰减。展开更多
Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often comple...Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.展开更多
Moisture contribution and transport pathways for Central Asia(CA)are quantitatively examined using the Lagrangian water cycle model based on reanalysis and observational data to explain the precipitation seasonality a...Moisture contribution and transport pathways for Central Asia(CA)are quantitatively examined using the Lagrangian water cycle model based on reanalysis and observational data to explain the precipitation seasonality and the moisture transport variation during 1979-2015.Westerly-related(northwesterly and westerly)transport explains 42%of CA precipitation and dominates in southwest CA,where precipitation is greatest in the cold season.Southeast CA,including part of Northwest China,experiences its maximum precipitation in the warm season and is solely dominated by southerly transport,which explains about 48%of CA precipitation.The remaining 10%of CA precipitation is explained by northerly transport,which steadily impacts north CA and causes a maximum in precipitation in the warm season.Most CA areas are exposed to seasonally varying moisture transport,except for southeast and north CA,which are impacted by southerly and northerly transport year-round.In general,the midlatitude westerlies-driven transport and the Indian monsoon-driven southerly-related transport explain most of the spatial differences in precipitation seasonality over CA.Moreover,the contribution ratio of local evaporation in CA to precipitation exhibits significant interdecadal variability and a meridionally oriented tripole of moisture transport anomalies.Since the early 2000s,CA has experienced a decade of anomalously low local moisture contribution,which seems jointly determined by the weakened moisture contribution from midlatitudes(the Atlantic,Europe,and CA itself)and the enhanced contribution from high latitudes(West Siberia and the Arctic)and tropical areas(South Asia and the Indian Ocean).展开更多
基金supported by the National Key Research and Development Project(Grant Number 2023YFB3709601)the National Natural Science Foundation of China(Grant Numbers 62373215,62373219,62073193)+2 种基金the Key Research and Development Plan of Shandong Province(Grant Numbers 2021CXGC010204,2022CXGC020902)the Fundamental Research Funds of Shandong University(Grant Number 2021JCG008)the Natural Science Foundation of Shandong Province(Grant Number ZR2023MF100).
文摘The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through accelerated life testing.In the absence of lifetime data,the hidden long-term correlation between performance degradation data is challenging to mine effectively,which is the main factor that restricts the prediction precision and engineering application of the residual life prediction method.To address this problem,a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is proposed.Firstly,a nonlinear health indicator(HI)calculation method based on kernel principal component analysis(KPCA)and exponential weighted moving average(EWMA)is designed.Then,using the raw vibration data and HI,a multi-layer perceptron(MLP)neural network is trained to further calculate the HI of the online bearing in real time.Furthermore,The bidirectional long short-term memory model(BiLSTM)optimized by particle swarm optimization(PSO)is used to mine the time series features of HI and predict the remaining service life.Performance verification experiments and comparative experiments are carried out on the XJTU-SY bearing open dataset.The research results indicate that this method has an excellent ability to predict future HI and remaining life.
基金Supported by the National Key Research and Development Project of China,No.2019YFC1711605National Natural Science Foundation of China,No.81904257Medical Innovation Research Project of Science and Technology Commission of Shanghai Municipality,No.21Y11923100.
文摘BACKGROUND Diabetic retinopathy(DR)is the primary cause of visual problems in patients with diabetes.The Heyingwuzi formulation(HYWZF)is effective against DR.AIM To determine the HYWZF prevention mechanisms,especially those underlying mitophagy.METHODS Human retinal capillary endothelial cells(HRCECs)were treated with high glucose(hg),HYWZF serum,PX-478,or Mdivi-1 in vitro.Then,cell counting kit-8,transwell,and tube formation assays were used to evaluate HRCEC proliferation,invasion,and tube formation,respectively.Transmission electron microscopy was used to assess mitochondrial morphology,and Western blotting was used to determine the protein levels.Flow cytometry was used to assess cell apoptosis,reactive oxygen species(ROS)production,and mitochondrial membrane potential.Moreover,C57BL/6 mice were established in vivo using streptozotocin and treated with HYWZF for four weeks.Blood glucose levels and body weight were monitored continuously.Changes in retinal characteristics were evaluated using hematoxylin and eosin,tar violet,and periodic acid-Schiff staining.Protein levels in retinal tissues were determined via Western blotting,immunohistochemistry,and immunostaining.RESULTS HYWZF inhibited excessive ROS production,apoptosis,tube formation,and invasion in hg-induced HRCECs via mitochondrial autophagy in vitro.It increased the mRNA expression levels of BCL2-interacting protein 3(BNIP3),FUN14 domain-containing 1,BNIP3-like(BNIP3L,also known as NIX),PARKIN,PTEN-induced kinase 1,and hypoxia-inducible factor(HIF)-1α.Moreover,it downregulated the protein levels of vascular endothelial cell growth factor and increased the light chain 3-II/I ratio.However,PX-478 and Mdivi-1 reversed these effects.Additionally,PX-478 and Mdivi-1 rescued the effects of HYWZF by decreasing oxidative stress and apoptosis and increasing mitophagy.HYWZF intervention improved the symptoms of diabetes,tissue damage,number of acellular capillaries,and oxidative stress in vivo.Furthermore,in vivo experiments confirmed the results of in vitro experiments.CONCLUSION HYWZF alleviated DR and associated damage by promoting mitophagy via the HIF-1α/BNIP3/NIX axis.
基金supported by the Simons Foundation:Collaboration Grantssupported by the AFOSR grant FA9550-18-1-0383.
文摘In this paper,we consider the high order method for solving the linear transport equations under diffusive scaling and with random inputs.To tackle the randomness in the problem,the stochastic Galerkin method of the generalized polynomial chaos approach has been employed.Besides,the high order implicit-explicit scheme under the micro-macro decomposition framework and the discontinuous Galerkin method have been employed.We provide several numerical experiments to validate the accuracy and the stochastic asymptotic-preserving property.
文摘锌空气电池具有能量密度高、成本低等优点,是最具前途的绿色储能技术之一,开发用于空气阴极氧还原反应(ORR)和析氧反应(OER)的非贵金属催化剂至关重要。本文提出了一种新型高效的制备方法,通过热处理与电沉积技术,以不锈钢网为基底原位生长NiO包裹的氮掺杂碳纳米管三维网络(NiO-CNT/SS)。得益于碳纳米管的独特三维结构,使其可以暴露出更多的活性位点,所制备催化剂OER性能优良,在100 mA cm−2电流密度下过电位仅为374 mV。此外,NiO-CNT/SS材料所组装的锌空气电池具有1.44 V开路电压以及优异的循环稳定性,在5 mA cm−2电流密度下可以稳定循环145 h而无明显衰减。
基金supported by the National Natural Science Foundation of China(72101263).
文摘Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences Sci-ences under Grant No.XDA20020201the National Natural Sci-ence Foundation of China(NSFC)under Grant Nos.41975099,U2006210,and 41475072.
文摘Moisture contribution and transport pathways for Central Asia(CA)are quantitatively examined using the Lagrangian water cycle model based on reanalysis and observational data to explain the precipitation seasonality and the moisture transport variation during 1979-2015.Westerly-related(northwesterly and westerly)transport explains 42%of CA precipitation and dominates in southwest CA,where precipitation is greatest in the cold season.Southeast CA,including part of Northwest China,experiences its maximum precipitation in the warm season and is solely dominated by southerly transport,which explains about 48%of CA precipitation.The remaining 10%of CA precipitation is explained by northerly transport,which steadily impacts north CA and causes a maximum in precipitation in the warm season.Most CA areas are exposed to seasonally varying moisture transport,except for southeast and north CA,which are impacted by southerly and northerly transport year-round.In general,the midlatitude westerlies-driven transport and the Indian monsoon-driven southerly-related transport explain most of the spatial differences in precipitation seasonality over CA.Moreover,the contribution ratio of local evaporation in CA to precipitation exhibits significant interdecadal variability and a meridionally oriented tripole of moisture transport anomalies.Since the early 2000s,CA has experienced a decade of anomalously low local moisture contribution,which seems jointly determined by the weakened moisture contribution from midlatitudes(the Atlantic,Europe,and CA itself)and the enhanced contribution from high latitudes(West Siberia and the Arctic)and tropical areas(South Asia and the Indian Ocean).
