Western diet(rich in highly refined sugar and fat)can induce a range of metabolic dysfunctions in animals and humans,including neuroinflammation and cognitive function decline.Neuroinflammation and cognitive impairmen...Western diet(rich in highly refined sugar and fat)can induce a range of metabolic dysfunctions in animals and humans,including neuroinflammation and cognitive function decline.Neuroinflammation and cognitive impairment,two critical pathological characteristics of Alzheimer’s disease,have been closely associated with microbial alteration via the gut-brain axis.Thus,the present study aimed to investigate the influence of 2-O-β-D-glucopyranosyl-L-ascorbic acid(AA-2βG)isolated from the fruits of Lycium barbarum on preventing the high-fructose diet(HFrD)induced neuroinflammation in mice.It was found that AA-2βG prevented HFr D-induced cognitive deficits.AA-2βG also predominantly enhanced the gut barrier integrity,decreased lipopolysaccharide entry into the circulation,which subsequently countered the activation of glial cells and neuroinflammatory response.These beneficial effects were transmissible by horizontal fecal microbiome transplantation,transferring from AA-2βG fed mice to HFr D fed mice.Additionally,AA-2βG exerted neuroprotective effects involving the enrichment of Lactobacillus and Akkermansia,potentially beneficial intestinal bacteria.The present study provided the evidence that AA-2βG could improve indices of cognition and neuroinflammmation via modulating gut dybiosis and preventing leaky gut.As a potential functional food ingredient,AA-2βG may be applied to attenuate neuroinflammation associated with Western-style diets.展开更多
This study aimed to characterize and identify calcium-chelating peptides from rabbit bone collagen and explore the underlying chelating mechanism.Collagen peptides and calcium were extracted from rabbit bone by instan...This study aimed to characterize and identify calcium-chelating peptides from rabbit bone collagen and explore the underlying chelating mechanism.Collagen peptides and calcium were extracted from rabbit bone by instant ejection steam explosion(ICSE)combined with enzymatic hydrolysis,followed by chelation reaction to prepare rabbit bone peptide-calcium chelate(RBCP-Ca).The chelating sites were further analyzed by liquid chromatography-tandem mass(LC-MS/MS)spectrometry while the chelating mechanism and binding modes were investigated.The structural characterization revealed that RBCP successfully chelated with calcium ions.Furthermore,LC-MS/MS analysis indicated that the binding sites included both acidic amino acids(Asp and Glu)and basic amino acids(Lys and Arg),Interestingly,three binding modes,namely Inter-Linking,Loop-Linking and Mono-Linking were for the first time found,while Inter-Linking mode accounted for the highest proportion(75.1%),suggesting that chelation of calcium ions frequently occurred between two peptides.Overall,this study provides a theoretical basis for the elucidation of chelation mechanism of calcium-chelating peptides.展开更多
Transcription Terminators (TTs) play an impor-tant role in bacterial RNA transcription. Some bacteria are known to have Species-Specific Subsequences (SSS) in their TTs, which are be-lieved containing useful clues to ...Transcription Terminators (TTs) play an impor-tant role in bacterial RNA transcription. Some bacteria are known to have Species-Specific Subsequences (SSS) in their TTs, which are be-lieved containing useful clues to bacterial evolu-tion. The SSS can be identified using biological methods which, however, tend to be costly and time-consuming due to the vast number of sub-sequences to experiment on. In this paper, we study the problem from a computational per-spective and propose a computing method to identify the SSS. Given DNA sequences of a tar-get species, some of which are known to contain a TT while others not, our method uses machine learning techniques and is done in three steps. First, we find all frequent subsequences from the given sequences, and show that this can be effi-ciently done using generalized suffix trees. Sec-ond, we use these subsequences as features to characterize the original DNA sequences and train a classification model using Support Vector Machines (SVM), one of the currently most effec-tive machine learning techniques. Using the pa-rameters of the resulting SVM model, we define a measure called subsequence specificity to rank the frequent subsequences, and output the one with the highest rank as the SSS. Our experi-ments show that the SSS found by the proposed method are very close to those determined by biological experiments. This suggests that our method, though purely computational, can help efficiently locate the SSS by effectively narrowing down the search space.展开更多
Artificial intelligence(AI)models are promising to improve the accuracy of wireless positioning systems,particularly in indoor environments where unpredictable radio propagation channel is a great challenge.Although g...Artificial intelligence(AI)models are promising to improve the accuracy of wireless positioning systems,particularly in indoor environments where unpredictable radio propagation channel is a great challenge.Although great efforts have been made to explore the effectiveness of different AI models,it is still an open problem whether these models,trained with the data collected from all base stations(BSs),could work when some BSs are unavailable.In this paper,we make the first effort to enhance the generalization ability of AI wireless positioning model to adapt to the scenario where only partial BSs work.Particularly,a Siamese Network based Wireless Positioning Model(SNWPM)is proposed to predict the location of mobile user equipment from channel state information(CSI)collected from 5G BSs.Furthermore,a Feature Aware Attention Module(FAAM)is introduced to reinforce the capability of feature extraction from CSI data.Experiments are conducted on the 2022 Wireless Communication AI Competition(WAIC)dataset.The proposed SNWPM achieves decimeter-level positioning accuracy even if the data of partial BSs are unavailable.Compared with other AI models,the proposed SNWPM can reduce the positioning error by nearly 50%to more than 60%while using less parameters and lower computation resources.展开更多
Memristor-based neuromorphic computing shows great potential for high-speed and high-throughput signal processing applications,such as electroencephalogram(EEG)signal processing.Nonetheless,the size of one-transistor ...Memristor-based neuromorphic computing shows great potential for high-speed and high-throughput signal processing applications,such as electroencephalogram(EEG)signal processing.Nonetheless,the size of one-transistor one-resistor(1T1R)memristor arrays is limited by the non-ideality of the devices,which prevents the hardware implementation of large and complex networks.In this work,we propose the depthwise separable convolution and bidirectional gate recurrent unit(DSC-BiGRU)network,a lightweight and highly robust hybrid neural network based on 1T1R arrays that enables efficient processing of EEG signals in the temporal,frequency and spatial domains by hybridizing DSC and BiGRU blocks.The network size is reduced and the network robustness is improved while ensuring the network classification accuracy.In the simulation,the measured non-idealities of the 1T1R array are brought into the network through statistical analysis.Compared with traditional convolutional networks,the network parameters are reduced by 95%and the network classification accuracy is improved by 21%at a 95%array yield rate and 5%tolerable error.This work demonstrates that lightweight and highly robust networks based on memristor arrays hold great promise for applications that rely on low consumption and high efficiency.展开更多
Taxonomic sufficiency(TS)refers to identifying taxa to a taxonomic level sufficient to detect community changes in stressed environments and may provide a cost-effective approach in routine monitoring programs.However...Taxonomic sufficiency(TS)refers to identifying taxa to a taxonomic level sufficient to detect community changes in stressed environments and may provide a cost-effective approach in routine monitoring programs.However,there is still limited information regarding the seasonal impact of applying TS and its implications for the ecological quality evaluation in the estuarine ecosystem.This study investigated the relationship between the multivariate-AZTI’s Marine Biotic Index(M-AMBI)and environmental variables in three seasons(i.e.,spring,summer,and autumn)in the Liaohe River Estuary.We tested the reliability of TS for simplifying the M-AMBI methodology.The results showed that family and genus level data could reproduce the spatial-temporal patterns of community structure at the species level.The M-AMBI values showed a consistent spatial distribution pattern in all sampling seasons,with a decreasing trend with the increasing distance from the estuary mouth.Both genus and family level data performed nearly as well as species level in detecting the seasonal variations of pollutants(i.e.,nutrients and total organic content).The family level M-AMBI was feasible to discern stress in the Liaohe River Estuary because of the high aggregation ratios at different taxonomic levels in all sampling seasons.These findings suggest that applying taxonomic sufficiency based on the M-AMBI provides an efficient approach for evaluating ecological quality in the Liaohe River Estuary.展开更多
Although the relationship between anesthesia and consciousness has been investigated for decades, our understanding of the underlying neural mechanisms of anesthesia and consciousness remains rudimentary, which limits...Although the relationship between anesthesia and consciousness has been investigated for decades, our understanding of the underlying neural mechanisms of anesthesia and consciousness remains rudimentary, which limits the development of systems for anesthesia monitoring and consciousness evaluation. Moreover, the current practices for anesthesia monitoring are mainly based on methods that do not provide adequate information and may present obstacles to the precise application of anesthesia. Most recently, there has been a growing trend to utilize brain network analysis to reveal the mechanisms of anesthesia, with the aim of providing novel insights to promote practical application. This review summarizes recent research on brain network studies of anesthesia, and compares the underlying neural mechanisms of consciousness and anesthesia along with the neural signs and measures of the distinct aspects of neural activity. Using the theory of cortical fragmentation as a starting point, we introduce important methods and research involving connectivity and network analysis. We demonstrate that whole-brain multimodal network data can provide important supplementary clinical information. More importantly, this review posits that brain network methods, if simplified, will likely play an important role in improving the current clinical anesthesia monitoring systems.展开更多
Electrosynthesis of ammonia from the reduction of nitrogen is still confronted with the limited supply of gas reactant in dynamics as well as high activation barrier in thermodynamics.Unfortunately,despite tremendous ...Electrosynthesis of ammonia from the reduction of nitrogen is still confronted with the limited supply of gas reactant in dynamics as well as high activation barrier in thermodynamics.Unfortunately,despite tremendous efforts devoted to electrocatalysts themselves,they still fail to tackle the above two challenges simultaneously.Herein,we employ a heterogeneous catalyst adlayer-composed of crown ethers associated with Li^(+)ions-to achieve the dual promotion of dynamics and thermodynamics for ambient ammonia synthesis.Dynamically,the bound Li^(+)ions interact with the strong quadrupole moment of nitrogen,and trigger considerable reactant flux toward the catalyst.Thermodynamically,Li^(+)associated with the oxygen of crown ether achieves a higher density of states at the Fermi level for the catalyst,enabling effortless electron transfer from the catalysts to nitrogen and thus greatly reducing the activation barrier.As expected,the proof-of-concept system achieves an ammonia yield rate of 168.5μg h^(-1)mg^(-1)and a Faradaic efficiency of 75.3%at-0.3 V vs.RHE.This system-level approach opens up pathways for tackling the two key challenges that have limited the field of ammonia synthesis.展开更多
Marine spatial planning(MSP)is designed to divide the sea area into different types of functional zones,to implement corresponding development activities.However,the long-term impacts of anthropogenic activities assoc...Marine spatial planning(MSP)is designed to divide the sea area into different types of functional zones,to implement corresponding development activities.However,the long-term impacts of anthropogenic activities associated with MSP practice on the marine microbial biosphere are still unclear.Yalu River Estuary,a coastal region in northeast of China,has been divided into fishery&agricultural(F&A)zone,shipping&port(S&P)zone and marine protected area(MPA)zone by a local MSP guideline that has been run for decades.To examine the effects of long-term executed MSP,benthic bacterial communities from different MSP zones were obtained and compared in this study.The results revealed significant differences in the bacterial community structure and predict functions among different zones.Bacterial genera enriched in different zones were identified,including SBR1031 in MPA,Woeseia and Sva0996 in S&P,and Halioglobus in F&A.In addition,correlations between some bacterial genera and sediment pollutants were uncovered.Furthermore,bacteria related to sulphide production were more abundant in the F&A zone,which was according to the accumulation of sulphides in this area.Moreover,bacteria associated with chemoheterotrophy and fermentation were more predominant in the S&P zone,consistent with high levels of organic matter and petroleum caused by shipping.Our findings indicated benthic bacterial communities could bring to light the anthropogenic activity footprints by different activities induced by long-term MSP practice.展开更多
In automotive industries,panel acoustic contribution analysis(PACA)is used to investigate the contributions of the body panels to the acoustic pressure at a certain point of interest.Currently,PACA is implementedmostl...In automotive industries,panel acoustic contribution analysis(PACA)is used to investigate the contributions of the body panels to the acoustic pressure at a certain point of interest.Currently,PACA is implementedmostly by either experiment-based methods or traditional numerical methods.However,these schemes are effort-consuming and inefficient in solving engineering problems,thereby restraining the further development of PACA in automotive acoustics.In this work,we propose a PACA scheme using discontinuous isogeometric boundary element method(IGABEM)to build an easily implementable and efficient method to identify the relative acoustic contributions of each automotive body panel.Discontinuous IGABEMis more accurate and converges faster than continuous BEM and IGABEM in the interior sound pressure evaluation of automotive compartments.In this work,a contribution ratio is defined to estimate the relative acoustic contribution of the structure panels;it can be calculated by reusing the coefficient matrix that has already been generated in the sound pressure evaluation process.The utilization of the parallel technique enables the proposed method to be more efficient than conventional methods;it is validated in two numerical examples,including a car passenger compartment subjected to realistic boundary conditions.A sound pressure response experiment based on a steel box is conducted to verify the accuracy of the interior sound pressure calculation using discontinuous IGABEM.This work is expected to promote the practical process of IGABEM for application in automotive acoustic problems.展开更多
Selective catalytic reduction(SCR)is a technology by which nitrogen oxides are converted with the aid of a catalyst into diatomic nitrogen and water.It is known that the catalyst can be easily eroded if a cement kiln ...Selective catalytic reduction(SCR)is a technology by which nitrogen oxides are converted with the aid of a catalyst into diatomic nitrogen and water.It is known that the catalyst can be easily eroded if a cement kiln with a high-dust content is considered.To understand this process,numerical simulations have been carried out considering a single catalyst channel in order to study the collision and erosion of fly ash and catalysts at meso scale.Based on a response surface methodology,the effects of five factors on the erosion rate have been studied,namely,the catalyst particle velocity,the particle size,the particle concentration,the incidence angle and the catalyst porosity.The results show that the influence of particle velocity,particle size and particle concentration is statistically significant and the particle size and incidence angle have a significant effect on the erosion rate.A quadratic polynomial prediction model for the erosion rate of honeycomb catalysts in cement kiln SCR reactors is finally proposed to support the future optimization of these systems.展开更多
BACKGROUND Pancreatoduodenectomy(PD)is the most effective surgical procedure to remove a pancreatic tumor,but the prevalent postoperative complications,including postoperative pancreatic fistula(POPF),can be life-thre...BACKGROUND Pancreatoduodenectomy(PD)is the most effective surgical procedure to remove a pancreatic tumor,but the prevalent postoperative complications,including postoperative pancreatic fistula(POPF),can be life-threatening.Thus far,there is no consensus about the prevention of POPF.AIM To determine possible prognostic factors and investigate the clinical effects of modified duct-to-mucosa pancreaticojejunostomy(PJ)on POPF development.METHODS We retrospectively collected and analyzed the data of 215 patients who under-went PD between January 2017 and February 2022 in our surgery center.The risk factors for POPF were analyzed by univariate analysis and multivariate logistic regression analysis.Then,we stratified patients by anastomotic technique(end-to-side invagination PJ vs modified duct-to-mucosa PJ)to conduct a comparative study.RESULTS A total of 108 patients received traditional end-to-side invagination PJ,and 107 received modified duct-to-mucosa PJ.Overall,58.6%of patients had various complications,and 0.9%of patients died after PD.Univariate and multivariate logistic regression analyses showed that anastomotic approaches,main pancreatic duct(MPD)diameter and pancreatic texture were significantly associated with the incidence of POPF.Additionally,the POPF incidence and operation time in patients receiving modified duct-to-mucosa PJ were 11.2%and 283.4 min,respectively,which were significantly lower than those in patients receiving traditional end-to-side invagination PJ(27.8%and 333.2 minutes).CONCLUSION Anastomotic approach,MPD diameter and pancreatic texture are major risk factors for POPF development.Compared with traditional end-to-side invagination PJ,modified duct-to-mucosa PJ is a simpler and more efficient technique that results in a lower incidence of POPF.Further studies are needed to validate our findings and explore the clinical applicability of our technique for laparoscopic and robotic PD.展开更多
基金the financial support from the Key Research and Development Program of Ningxia Hui Autonomous Region of China(2021BEF02008)the National Natural Science Foundation of China(32272330)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Western diet(rich in highly refined sugar and fat)can induce a range of metabolic dysfunctions in animals and humans,including neuroinflammation and cognitive function decline.Neuroinflammation and cognitive impairment,two critical pathological characteristics of Alzheimer’s disease,have been closely associated with microbial alteration via the gut-brain axis.Thus,the present study aimed to investigate the influence of 2-O-β-D-glucopyranosyl-L-ascorbic acid(AA-2βG)isolated from the fruits of Lycium barbarum on preventing the high-fructose diet(HFrD)induced neuroinflammation in mice.It was found that AA-2βG prevented HFr D-induced cognitive deficits.AA-2βG also predominantly enhanced the gut barrier integrity,decreased lipopolysaccharide entry into the circulation,which subsequently countered the activation of glial cells and neuroinflammatory response.These beneficial effects were transmissible by horizontal fecal microbiome transplantation,transferring from AA-2βG fed mice to HFr D fed mice.Additionally,AA-2βG exerted neuroprotective effects involving the enrichment of Lactobacillus and Akkermansia,potentially beneficial intestinal bacteria.The present study provided the evidence that AA-2βG could improve indices of cognition and neuroinflammmation via modulating gut dybiosis and preventing leaky gut.As a potential functional food ingredient,AA-2βG may be applied to attenuate neuroinflammation associated with Western-style diets.
基金granted by the National Key R&D Program of China (2021YFD21001005)National Natural Science Foundation of China (31972102,32101980)+1 种基金Special key project of Chongqing technology innovation and application development (cstc2021jscx-cylhX0014)Chongqing Technology Innovation and Application Development Special Project (cstc2021jscx-tpyzxX0014)。
文摘This study aimed to characterize and identify calcium-chelating peptides from rabbit bone collagen and explore the underlying chelating mechanism.Collagen peptides and calcium were extracted from rabbit bone by instant ejection steam explosion(ICSE)combined with enzymatic hydrolysis,followed by chelation reaction to prepare rabbit bone peptide-calcium chelate(RBCP-Ca).The chelating sites were further analyzed by liquid chromatography-tandem mass(LC-MS/MS)spectrometry while the chelating mechanism and binding modes were investigated.The structural characterization revealed that RBCP successfully chelated with calcium ions.Furthermore,LC-MS/MS analysis indicated that the binding sites included both acidic amino acids(Asp and Glu)and basic amino acids(Lys and Arg),Interestingly,three binding modes,namely Inter-Linking,Loop-Linking and Mono-Linking were for the first time found,while Inter-Linking mode accounted for the highest proportion(75.1%),suggesting that chelation of calcium ions frequently occurred between two peptides.Overall,this study provides a theoretical basis for the elucidation of chelation mechanism of calcium-chelating peptides.
文摘Transcription Terminators (TTs) play an impor-tant role in bacterial RNA transcription. Some bacteria are known to have Species-Specific Subsequences (SSS) in their TTs, which are be-lieved containing useful clues to bacterial evolu-tion. The SSS can be identified using biological methods which, however, tend to be costly and time-consuming due to the vast number of sub-sequences to experiment on. In this paper, we study the problem from a computational per-spective and propose a computing method to identify the SSS. Given DNA sequences of a tar-get species, some of which are known to contain a TT while others not, our method uses machine learning techniques and is done in three steps. First, we find all frequent subsequences from the given sequences, and show that this can be effi-ciently done using generalized suffix trees. Sec-ond, we use these subsequences as features to characterize the original DNA sequences and train a classification model using Support Vector Machines (SVM), one of the currently most effec-tive machine learning techniques. Using the pa-rameters of the resulting SVM model, we define a measure called subsequence specificity to rank the frequent subsequences, and output the one with the highest rank as the SSS. Our experi-ments show that the SSS found by the proposed method are very close to those determined by biological experiments. This suggests that our method, though purely computational, can help efficiently locate the SSS by effectively narrowing down the search space.
基金supported by National Natural Science Foundation of China (No. 62076251)sponsored by IMT-2020(5G) Promotion Group 5G+AI Work Group+3 种基金jointly sponsored by China Academy of Information and Communications TechnologyGuangdong OPPO Mobile Telecommunications Corp., Ltdvivo Mobile Communication Co., LtdHuawei Technologies Co., Ltd
文摘Artificial intelligence(AI)models are promising to improve the accuracy of wireless positioning systems,particularly in indoor environments where unpredictable radio propagation channel is a great challenge.Although great efforts have been made to explore the effectiveness of different AI models,it is still an open problem whether these models,trained with the data collected from all base stations(BSs),could work when some BSs are unavailable.In this paper,we make the first effort to enhance the generalization ability of AI wireless positioning model to adapt to the scenario where only partial BSs work.Particularly,a Siamese Network based Wireless Positioning Model(SNWPM)is proposed to predict the location of mobile user equipment from channel state information(CSI)collected from 5G BSs.Furthermore,a Feature Aware Attention Module(FAAM)is introduced to reinforce the capability of feature extraction from CSI data.Experiments are conducted on the 2022 Wireless Communication AI Competition(WAIC)dataset.The proposed SNWPM achieves decimeter-level positioning accuracy even if the data of partial BSs are unavailable.Compared with other AI models,the proposed SNWPM can reduce the positioning error by nearly 50%to more than 60%while using less parameters and lower computation resources.
基金Project supported by the National Key Research and Development Program of China(Grant No.2019YFB2205102)the National Natural Science Foundation of China(Grant Nos.61974164,62074166,61804181,62004219,62004220,and 62104256).
文摘Memristor-based neuromorphic computing shows great potential for high-speed and high-throughput signal processing applications,such as electroencephalogram(EEG)signal processing.Nonetheless,the size of one-transistor one-resistor(1T1R)memristor arrays is limited by the non-ideality of the devices,which prevents the hardware implementation of large and complex networks.In this work,we propose the depthwise separable convolution and bidirectional gate recurrent unit(DSC-BiGRU)network,a lightweight and highly robust hybrid neural network based on 1T1R arrays that enables efficient processing of EEG signals in the temporal,frequency and spatial domains by hybridizing DSC and BiGRU blocks.The network size is reduced and the network robustness is improved while ensuring the network classification accuracy.In the simulation,the measured non-idealities of the 1T1R array are brought into the network through statistical analysis.Compared with traditional convolutional networks,the network parameters are reduced by 95%and the network classification accuracy is improved by 21%at a 95%array yield rate and 5%tolerable error.This work demonstrates that lightweight and highly robust networks based on memristor arrays hold great promise for applications that rely on low consumption and high efficiency.
基金The National Marine Public Welfare Research Project of China under contract No.201305030the Open Fund from Observation and Research Station of Bohai Strait Eco-Corridor under contract No.BH202201.
文摘Taxonomic sufficiency(TS)refers to identifying taxa to a taxonomic level sufficient to detect community changes in stressed environments and may provide a cost-effective approach in routine monitoring programs.However,there is still limited information regarding the seasonal impact of applying TS and its implications for the ecological quality evaluation in the estuarine ecosystem.This study investigated the relationship between the multivariate-AZTI’s Marine Biotic Index(M-AMBI)and environmental variables in three seasons(i.e.,spring,summer,and autumn)in the Liaohe River Estuary.We tested the reliability of TS for simplifying the M-AMBI methodology.The results showed that family and genus level data could reproduce the spatial-temporal patterns of community structure at the species level.The M-AMBI values showed a consistent spatial distribution pattern in all sampling seasons,with a decreasing trend with the increasing distance from the estuary mouth.Both genus and family level data performed nearly as well as species level in detecting the seasonal variations of pollutants(i.e.,nutrients and total organic content).The family level M-AMBI was feasible to discern stress in the Liaohe River Estuary because of the high aggregation ratios at different taxonomic levels in all sampling seasons.These findings suggest that applying taxonomic sufficiency based on the M-AMBI provides an efficient approach for evaluating ecological quality in the Liaohe River Estuary.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(LGF19H090023)the National Natural Science Foundation of China(81801785 and 82172056)+5 种基金the National Key Research and Development Program of China(2019YFC1711800)the Key Research and Development Program of Shanxi(2020ZDLSF04-03)This work was partly supported by the grants from the Zhejiang Lab(2019KE0AD01 and 2021KE0AB04)the Zhejiang University Global Partnership Fund(100000-11320)the Shanghai Municipal Science and Technology Major Project(2021SHZDZX0100)the Fundamental Research Funds for the Central Universities.
文摘Although the relationship between anesthesia and consciousness has been investigated for decades, our understanding of the underlying neural mechanisms of anesthesia and consciousness remains rudimentary, which limits the development of systems for anesthesia monitoring and consciousness evaluation. Moreover, the current practices for anesthesia monitoring are mainly based on methods that do not provide adequate information and may present obstacles to the precise application of anesthesia. Most recently, there has been a growing trend to utilize brain network analysis to reveal the mechanisms of anesthesia, with the aim of providing novel insights to promote practical application. This review summarizes recent research on brain network studies of anesthesia, and compares the underlying neural mechanisms of consciousness and anesthesia along with the neural signs and measures of the distinct aspects of neural activity. Using the theory of cortical fragmentation as a starting point, we introduce important methods and research involving connectivity and network analysis. We demonstrate that whole-brain multimodal network data can provide important supplementary clinical information. More importantly, this review posits that brain network methods, if simplified, will likely play an important role in improving the current clinical anesthesia monitoring systems.
基金supported by the National Natural Science Foundation of China(U21A20332,52103226,52202275,52203314,and 12204253)the Distinguished Young Scholars Fund of Jiangsu Province(BK20220061)the Fellowship of China Postdoctoral Science Foundation(2021M702382)。
文摘Electrosynthesis of ammonia from the reduction of nitrogen is still confronted with the limited supply of gas reactant in dynamics as well as high activation barrier in thermodynamics.Unfortunately,despite tremendous efforts devoted to electrocatalysts themselves,they still fail to tackle the above two challenges simultaneously.Herein,we employ a heterogeneous catalyst adlayer-composed of crown ethers associated with Li^(+)ions-to achieve the dual promotion of dynamics and thermodynamics for ambient ammonia synthesis.Dynamically,the bound Li^(+)ions interact with the strong quadrupole moment of nitrogen,and trigger considerable reactant flux toward the catalyst.Thermodynamically,Li^(+)associated with the oxygen of crown ether achieves a higher density of states at the Fermi level for the catalyst,enabling effortless electron transfer from the catalysts to nitrogen and thus greatly reducing the activation barrier.As expected,the proof-of-concept system achieves an ammonia yield rate of 168.5μg h^(-1)mg^(-1)and a Faradaic efficiency of 75.3%at-0.3 V vs.RHE.This system-level approach opens up pathways for tackling the two key challenges that have limited the field of ammonia synthesis.
基金The National Key Research and Development Program of China under contract No.2020 YFA0607600。
文摘Marine spatial planning(MSP)is designed to divide the sea area into different types of functional zones,to implement corresponding development activities.However,the long-term impacts of anthropogenic activities associated with MSP practice on the marine microbial biosphere are still unclear.Yalu River Estuary,a coastal region in northeast of China,has been divided into fishery&agricultural(F&A)zone,shipping&port(S&P)zone and marine protected area(MPA)zone by a local MSP guideline that has been run for decades.To examine the effects of long-term executed MSP,benthic bacterial communities from different MSP zones were obtained and compared in this study.The results revealed significant differences in the bacterial community structure and predict functions among different zones.Bacterial genera enriched in different zones were identified,including SBR1031 in MPA,Woeseia and Sva0996 in S&P,and Halioglobus in F&A.In addition,correlations between some bacterial genera and sediment pollutants were uncovered.Furthermore,bacteria related to sulphide production were more abundant in the F&A zone,which was according to the accumulation of sulphides in this area.Moreover,bacteria associated with chemoheterotrophy and fermentation were more predominant in the S&P zone,consistent with high levels of organic matter and petroleum caused by shipping.Our findings indicated benthic bacterial communities could bring to light the anthropogenic activity footprints by different activities induced by long-term MSP practice.
基金This work was supported by the National Natural Science Foundation of China(No.52072105 and No.21676067)Anhui Provincial Natural Science Foundation(No.1908085QE178)the Fundamental Research Funds for the Central Universities(No.JZ2020YYPY0109).
基金funded by the National Natural Science Foundation of China (Grant No.52175111)。
文摘In automotive industries,panel acoustic contribution analysis(PACA)is used to investigate the contributions of the body panels to the acoustic pressure at a certain point of interest.Currently,PACA is implementedmostly by either experiment-based methods or traditional numerical methods.However,these schemes are effort-consuming and inefficient in solving engineering problems,thereby restraining the further development of PACA in automotive acoustics.In this work,we propose a PACA scheme using discontinuous isogeometric boundary element method(IGABEM)to build an easily implementable and efficient method to identify the relative acoustic contributions of each automotive body panel.Discontinuous IGABEMis more accurate and converges faster than continuous BEM and IGABEM in the interior sound pressure evaluation of automotive compartments.In this work,a contribution ratio is defined to estimate the relative acoustic contribution of the structure panels;it can be calculated by reusing the coefficient matrix that has already been generated in the sound pressure evaluation process.The utilization of the parallel technique enables the proposed method to be more efficient than conventional methods;it is validated in two numerical examples,including a car passenger compartment subjected to realistic boundary conditions.A sound pressure response experiment based on a steel box is conducted to verify the accuracy of the interior sound pressure calculation using discontinuous IGABEM.This work is expected to promote the practical process of IGABEM for application in automotive acoustic problems.
基金supported by the Eco-Environment Project of the Key Research and Development Program of Anhui Province(No.202104i07020016).
文摘Selective catalytic reduction(SCR)is a technology by which nitrogen oxides are converted with the aid of a catalyst into diatomic nitrogen and water.It is known that the catalyst can be easily eroded if a cement kiln with a high-dust content is considered.To understand this process,numerical simulations have been carried out considering a single catalyst channel in order to study the collision and erosion of fly ash and catalysts at meso scale.Based on a response surface methodology,the effects of five factors on the erosion rate have been studied,namely,the catalyst particle velocity,the particle size,the particle concentration,the incidence angle and the catalyst porosity.The results show that the influence of particle velocity,particle size and particle concentration is statistically significant and the particle size and incidence angle have a significant effect on the erosion rate.A quadratic polynomial prediction model for the erosion rate of honeycomb catalysts in cement kiln SCR reactors is finally proposed to support the future optimization of these systems.
基金Supported by Clinical Medical Science and Technology Development Foundation of Jiangsu University,No.JLY2021118Science and Technology Project of Suzhou City,No.SKJY2021039.
文摘BACKGROUND Pancreatoduodenectomy(PD)is the most effective surgical procedure to remove a pancreatic tumor,but the prevalent postoperative complications,including postoperative pancreatic fistula(POPF),can be life-threatening.Thus far,there is no consensus about the prevention of POPF.AIM To determine possible prognostic factors and investigate the clinical effects of modified duct-to-mucosa pancreaticojejunostomy(PJ)on POPF development.METHODS We retrospectively collected and analyzed the data of 215 patients who under-went PD between January 2017 and February 2022 in our surgery center.The risk factors for POPF were analyzed by univariate analysis and multivariate logistic regression analysis.Then,we stratified patients by anastomotic technique(end-to-side invagination PJ vs modified duct-to-mucosa PJ)to conduct a comparative study.RESULTS A total of 108 patients received traditional end-to-side invagination PJ,and 107 received modified duct-to-mucosa PJ.Overall,58.6%of patients had various complications,and 0.9%of patients died after PD.Univariate and multivariate logistic regression analyses showed that anastomotic approaches,main pancreatic duct(MPD)diameter and pancreatic texture were significantly associated with the incidence of POPF.Additionally,the POPF incidence and operation time in patients receiving modified duct-to-mucosa PJ were 11.2%and 283.4 min,respectively,which were significantly lower than those in patients receiving traditional end-to-side invagination PJ(27.8%and 333.2 minutes).CONCLUSION Anastomotic approach,MPD diameter and pancreatic texture are major risk factors for POPF development.Compared with traditional end-to-side invagination PJ,modified duct-to-mucosa PJ is a simpler and more efficient technique that results in a lower incidence of POPF.Further studies are needed to validate our findings and explore the clinical applicability of our technique for laparoscopic and robotic PD.
