Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite ...Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.展开更多
To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and ge...To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and geographically and temporally weighted regression(GTWR)model to analyze the spatial-temporal patterns and the corresponding driving mechanisms of its urban-rural coordination since 1990.The results are as follows.First,the urban-rural coupling coordination degree in Northeast China was very low and improved slowly,but its stages of evolution is a good interpretation of the strategic arrangements of China's urbanization.Second,the urban-rural coupling coordination degree in Northeast China had spatial differences and was characterized by central polarization,converging on urban agglomeration,which was high in the south and low in the north.Moreover,the gap between the north and south weakened.Third,the spatial-temporal evolution of the urban-rural coordination relationship in Northeast China was influenced by pulling from the central cities,pushing from rural transformation,and government regulations.The influence intensity of the three mechanisms was weak,but the pulling from the central cities was stronger than that of the other two mechanisms.Furthermore,the spatial difference between the three mechanisms determines the spatial pattern and its evolution of the urban-rural coordination relationship in Northeast China.Fourth,to promote the development of urban-rural coordination in Northeast China,it is essential to advance urban-rural economic correlation,enhance the government^role in regulating and guiding,and adopt different policies for each region in Northeast China.展开更多
A numerical method was used in order to establish the constitutive relationship of sands under different stress paths, Firstly, based on the numerical method modeling the constitutive law of sands, the elastoplastic c...A numerical method was used in order to establish the constitutive relationship of sands under different stress paths, Firstly, based on the numerical method modeling the constitutive law of sands, the elastoplastic constitutive relationship of sand was established for three paths： the constant proportion of principle stress path, the conventional triaxial compression （CTC） path, and the p=constant （TC） path. The yield lines of plastic volumetric strain and plastic generalized shear strain were given. Through visualization, the three dimensional surface of the stress-strain relationship in the whole stress field （p, q） obtained under the three paths was plotted. Also, by comparing the stress-strain surfaces and yield locus of the three stress paths, the differences were found to be obvious, which demonstrates that the influence of the stress paths on constitutive law was not neglected. The numerical modeling method overcame the difficulty of finding an analytical expression for plastic potential. The results simulated the experimental data with an accuracy of 90% on average, so the constitutive model established in this paper provides an effective constitutive equation for this kind of engineering, reflecting the effect of practical stress paths that occur in sands.展开更多
Human trajectory prediction is essential and promising in many related applications. This is challenging due to the uncertainty of human behaviors, which can be influenced not only by himself, but also by the surround...Human trajectory prediction is essential and promising in many related applications. This is challenging due to the uncertainty of human behaviors, which can be influenced not only by himself, but also by the surrounding environment. Recent works based on long-short term memory(LSTM) models have brought tremendous improvements on the task of trajectory prediction. However, most of them focus on the spatial influence of humans but ignore the temporal influence. In this paper, we propose a novel spatial-temporal attention(ST-Attention) model,which studies spatial and temporal affinities jointly. Specifically,we introduce an attention mechanism to extract temporal affinity,learning the importance for historical trajectory information at different time instants. To explore spatial affinity, a deep neural network is employed to measure different importance of the neighbors. Experimental results show that our method achieves competitive performance compared with state-of-the-art methods on publicly available datasets.展开更多
Understanding the relationship between tree height （H） and diameter at breast height （D） is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its appli...Understanding the relationship between tree height （H） and diameter at breast height （D） is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its applicability for unevenly aged stands of moso bamboo forest at a regional scale. Field data were collected for 21 plots. Based on these data, we identified two strong power relationships： a corre- lation between the mean bamboo height （Hm） and the upper mean H （Hu）, and a correlation between the mean D （Din） and the upper mean D （Du）. Simulation results derived from the aUometric equation model were in good agreement with observed culms derived from the field data for the 21 stands, with a root-mean-square error and relative root-mean-square error of 1.40 m and 13.41%, respectively. These results demonstrate that the allometric equation model had a strong predictive power in the unevenly aged stands at a regional scale. In addition, the estimated average height-diameter （H-D） model for South Anhui Province was used to predict H for the same type of bamboo in Hunan Province based on the measured D, and the results were highly similar. The allometric equation model has multiple uses at the regional scale, including the evaluation of the variation in the H- D relationship among regions. The model describes the average H-D relationship without considering the effects caused by variation in site conditions, tree density and other factors.展开更多
Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.展开更多
How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image re...How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.展开更多
Through analyzing 7 Ib-type samples of synthetic single diamonds by their DTA and TG in air, we ascertained the extrapolated onset temperature on the curves of DTA as the characteristic temperature of their thermal st...Through analyzing 7 Ib-type samples of synthetic single diamonds by their DTA and TG in air, we ascertained the extrapolated onset temperature on the curves of DTA as the characteristic temperature of their thermal stabilities. Based on the grey system theory, we analyzed 4 factors influential in the thermal stability by the grey relationship analysis, a quantitative method, and derived the grey relationship sequence, that is, the rank of the influence extent of 4 factors on the thermal stability. Furthermore, we established the grey forecasting model, namely GM(1,5), for predicting the thermal stability of single diamonds with their intrinsic properties, which was then examined by a deviation-probability examination. The results illustrate that it is reasonable to take the Extrapolated Onset Temperature in DTA as the characteristic temperature for thermal stability (TS) of Ib-type synthetic single diamonds. The nitrogen content and grain shape regularity of diamonds are dominating factors. Likewise, grain size and compressive strength are minor factors. In addition, GM(1,5) can be used to predict the thermal stability of Ib-type synthetic single diamonds available. The precision rank of GM(1,5) is ‘GOOD’.展开更多
In the last issue,two case reports separately present examples of the extremely rare and complex congenital heart diseases that show concordant atrioventricular connections to the L-looped ventricles in the presence o...In the last issue,two case reports separately present examples of the extremely rare and complex congenital heart diseases that show concordant atrioventricular connections to the L-looped ventricles in the presence of situs solitus.Both cases highlight that the relationship between the two ventricles within the ventricular mass is not always harmonious with the given atrioventricular connection.Such disharmony between the connections and relationships requires careful assessment of the three basic facets of cardiac building blocks,namely their morphology,the relationship of their component parts,and their connections with the adjacent segments.3D imaging and printing can now facilitate an otherwise difficult diagnosis in such complex situations.Rotation of either the 3D images or the models permit accurate assessment of the ventricular topologic pattern by creating the right ventricular en-face septal view,thus facilitating placement of the observer’s hands.As we now emphasize,an alternative approach,which might prove more attractive to imagers,is to rotate the ventricular mass to provide the ventricular apical view,thus permitting determination of the ventricular relationship without using the hands.展开更多
Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 k...Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.展开更多
Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation ind...Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation index （NDVI） from remotely-sensed imagery, dividing human-induced land degradation from vegetation dynamics due to climate change is not a trivial task. This paper presented a multilevel statistical modeling of the NDVI-rainfall relationship to detect human-induced land degradation at local and landscape scales in the Ordos Plateau of Inner Mongolia, China, and recognized that anthropogenic activities result in either positive （land restoration and re-vegetation） or negative （degradation） trends. Linear regressions were used to assess the accuracy of the multi- level statistical model. The results show that： （1） land restoration was the dominant process in the Ordos Plateau between 1998 and 2012; （2） the effect of the statistical removal of precipitation revealed areas of human-induced land degradation and improvement, the latter reflecting successful restoration projects and changes in land man- agement in many parts of the Ordos; （3） compared to a simple linear regression, multilevel statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. Additional factors should be included when analyzing the NDVI-rainfall relationship and detecting human-induced loss of vegetation cover in drylands to improve the accuracy of the approach and elimi- nate some observed non-significant residual trends.展开更多
Precipitation and surface temperature are two important quantities whose variations are closely related through various physical processes. In the present study, we evaluated the precipitation-surface temperature （P-...Precipitation and surface temperature are two important quantities whose variations are closely related through various physical processes. In the present study, we evaluated the precipitation-surface temperature （P-T） relationship in 17 climate models involved in the Coupled Model Intercomparison Project Phase 5 （CMIP5） for the IPCC Assessment Report version 5. Most models performed reasonably well at simulat- ing the large-scale features of the P-T correlation distribution. Based on the pattern correlation of the P-T correlation distribution, the models performed better in November-December-January-February-March （NDJFM） than in May-June-July-August-September （MJJAS） except for the mid-latitudes of the North- ern Hemisphere, and the performance was generally better over the land than over the ocean. Seasonal dependence was more obvious over the land than over the ocean and was more obvious over the mid- and high-latitudes than over the tropics. All of the models appear to have had difficulty capturing the P-T correlation distribution over the mid-latitudes of the Southern Hemisphere in MJJAS. The spatial variabil- ity of the P-T correlation in the models was overestimated compared to observations. This overestimation tended to be larger over the land than over the ocean and larger over the mid- and high-latitudes than over the tropics. Based on analyses of selected model ensemble simulations, the spread of the P-T correlation among the ensemble members appears to have been small. While the performance in the P-T correlation provides a general direction for future improvement of climate models, the specific reasons for the discrep- ancies between models and observations remain to be revealed with detailed and comprehensive evaluations in various aspects.展开更多
An oil-in-water (O/W) solvent evaporation method was used to prepare biodegradable microspheresbased on poly(D,L-lactic acid) (PLA). Nifedipine, a hydrophobic drug, was chosen as a model molecule in the studyof drug e...An oil-in-water (O/W) solvent evaporation method was used to prepare biodegradable microspheresbased on poly(D,L-lactic acid) (PLA). Nifedipine, a hydrophobic drug, was chosen as a model molecule in the studyof drug entrapment and release. Effect of preparation conditions on the size, morphology, drug loading, and releaseprofiles of micropheres was investigated. Based on in vitro release experimental findings, a diffusion/dissolutionmodel was presented for quantitative description of the resulting release behaviors and drug release kinetics fromPLA microspheres analyzed. The mathematical models were used to predict the effect of microstructure on theresulting drug release. It provided an approach to determine the suitable structure parameters for microspheres toachieve desired drug release behaviors.展开更多
In order to investigate the basic mechanical properties and stress strain relationship model for bamboo scrimber manufactured based on a new technique,a large quantities of experiments have been carried out.Based on t...In order to investigate the basic mechanical properties and stress strain relationship model for bamboo scrimber manufactured based on a new technique,a large quantities of experiments have been carried out.Based on the analysis of the test results,the following conclusions can be drawn.Two main typical failure modes were classified for bamboo scrimber specimens both under tension parallel to grain and tension perpendicular to grain.Brittle failure happened for all tensile tests.The slope values for the elastic stages have bigger discreteness compared with those for the specimens under tensile parallel to grain.The failure modes for bamboo scrimber specimens under compression parallel to grain could be divided into four.Only one main failure mode happened both for the bending specimens and the shear specimens.With the COV values of 28.64 and 25.72 respectively,the values for the strength and elastic modulus under tensile perpendicular to grain have the largest discreteness for bamboo scrimber.From the point of CHV values,the relationship among the mechanical parameters for bamboo scrimber were proposed based on the test results.Compared with other green building materials,bamboo scrimber manufactured based on a new technique has better mechanical performance and could be used in construction area.Three stress strain relationship models which are four-linear model,quadratic function model,and cubic function model were proposed for bamboo scrimber specimens manufactured based on a new technique.The latter two models gives better prediction for stress strain relationship in elastic plastic stage.展开更多
Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research h...Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.展开更多
Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship am...Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.展开更多
Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Ab...Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.展开更多
Direct coal liquefaction(DCL)is an important and effective method of converting coal into high-valueadded chemicals and fuel oil.In DCL,heating the direct coal liquefaction solvent(DCLS)from low to high temperature an...Direct coal liquefaction(DCL)is an important and effective method of converting coal into high-valueadded chemicals and fuel oil.In DCL,heating the direct coal liquefaction solvent(DCLS)from low to high temperature and pre-hydrogenation of the DCLS are critical steps.Therefore,studying the dissolution of hydrogen in DCLS under liquefaction conditions gains importance.However,it is difficult to precisely determine hydrogen solubility only by experiments,especially under the actual DCL conditions.To address this issue,we developed a prediction model of hydrogen solubility in a single solvent based on the machine-learning quantitative structure–property relationship(ML-QSPR)methods.The results showed that the squared correlation coefficient R^(2)=0.92 and root mean square error RMSE=0.095,indicating the model’s good statistical performance.The external validation of the model also reveals excellent accuracy and predictive ability.Molecular polarization(a)is the main factor affecting the dissolution of hydrogen in DCLS.The hydrogen solubility in acyclic alkanes increases with increasing carbon number.Whereas in polycyclic aromatics,it decreases with increasing ring number,and in hydrogenated aromatics,it increases with hydrogenation degree.This work provides a new reference for the selection and proportioning of DCLS,i.e.,a solvent with higher hydrogen solubility can be added to provide active hydrogen for the reaction and thus reduce the hydrogen pressure.Besides,it brings important insight into the theoretical significance and practical value of the DCL.展开更多
Objective:To explore multiple relationships in traditional Chinese medicine(TCM)knowledge by comparing binary and multiple relationships during knowledge organization.Methods:Characteristics of binary and multiple sem...Objective:To explore multiple relationships in traditional Chinese medicine(TCM)knowledge by comparing binary and multiple relationships during knowledge organization.Methods:Characteristics of binary and multiple semantic relationships as well as their associations are described.A method to classify multiple relationships based on the involvement of time is proposed and theoretically validated using examples from the ancient TCM classic Important Formulas Worth a Thousand Gold Pieces.The classification includes parallel multiple relationships,restricted multiple relationships,multiple relationships that involve time,and multiple relationships that involve time restriction.Next,construction of multiple semantic relationships for TCM concepts in each classification using Protege,an ontology editing tool is described.Results:Protege is superior to a binary relationship and less than ideal with multiple relationships during the constitution of concept relationships.Conclusion:When applied in TCM,the semantic relationships constructed by Protege are superior than those constructed by correlation and/or attribute relationships,but less ideal than those constructed by the human cognitive process.展开更多
A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model exten...A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model extending existing 2D methods into 3D space. Geologic models with different scales are organized by segmenting data into orthogonal blocks. A flow diagram illustrates an octree method for upscaling between blocks with different scales. Upscaling data from the smallest unit cells takes into account their average size and the Burgers vector when there are mismatches. A geocellular model of the Chengdao Reservoir of the Shengli Oilfield, China is taken as an illustrative case, showing that the methods proposed can construct a multi-scale geologic model correctly and display data from the multi-scale model effectively in 3D.展开更多
基金supported by the Major Research Instrument Development Project of the National Natural Science Foundation of China(82327810)the Foundation of the President of Hebei University(XZJJ202202)the Hebei Province“333 talent project”(A202101058).
文摘Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
基金Under the auspices of National Natural Science Foundation of China(No.41401182,41501173)Youth Fund for Humanities and Social Sciences of the Ministry of Education of China(No.19YJC630177)+2 种基金Natural Science Foundation of Heilongjiang Province(No.LH2019D008)University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(No.UNPYSCT-2018194)Talent Introduction Project of Southwest University(No.SWU019020)。
文摘To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and geographically and temporally weighted regression(GTWR)model to analyze the spatial-temporal patterns and the corresponding driving mechanisms of its urban-rural coordination since 1990.The results are as follows.First,the urban-rural coupling coordination degree in Northeast China was very low and improved slowly,but its stages of evolution is a good interpretation of the strategic arrangements of China's urbanization.Second,the urban-rural coupling coordination degree in Northeast China had spatial differences and was characterized by central polarization,converging on urban agglomeration,which was high in the south and low in the north.Moreover,the gap between the north and south weakened.Third,the spatial-temporal evolution of the urban-rural coordination relationship in Northeast China was influenced by pulling from the central cities,pushing from rural transformation,and government regulations.The influence intensity of the three mechanisms was weak,but the pulling from the central cities was stronger than that of the other two mechanisms.Furthermore,the spatial difference between the three mechanisms determines the spatial pattern and its evolution of the urban-rural coordination relationship in Northeast China.Fourth,to promote the development of urban-rural coordination in Northeast China,it is essential to advance urban-rural economic correlation,enhance the government^role in regulating and guiding,and adopt different policies for each region in Northeast China.
文摘A numerical method was used in order to establish the constitutive relationship of sands under different stress paths, Firstly, based on the numerical method modeling the constitutive law of sands, the elastoplastic constitutive relationship of sand was established for three paths： the constant proportion of principle stress path, the conventional triaxial compression （CTC） path, and the p=constant （TC） path. The yield lines of plastic volumetric strain and plastic generalized shear strain were given. Through visualization, the three dimensional surface of the stress-strain relationship in the whole stress field （p, q） obtained under the three paths was plotted. Also, by comparing the stress-strain surfaces and yield locus of the three stress paths, the differences were found to be obvious, which demonstrates that the influence of the stress paths on constitutive law was not neglected. The numerical modeling method overcame the difficulty of finding an analytical expression for plastic potential. The results simulated the experimental data with an accuracy of 90% on average, so the constitutive model established in this paper provides an effective constitutive equation for this kind of engineering, reflecting the effect of practical stress paths that occur in sands.
基金supported by the National Key Research and Development Program of China(2018AAA0101005,2018AAA0102404)the Program of the Huawei Technologies Co.Ltd.(FA2018111061SOW12)+1 种基金the National Natural Science Foundation of China(61773054)the Youth Research Fund of the State Key Laboratory of Complex Systems Management and Control(20190213)。
文摘Human trajectory prediction is essential and promising in many related applications. This is challenging due to the uncertainty of human behaviors, which can be influenced not only by himself, but also by the surrounding environment. Recent works based on long-short term memory(LSTM) models have brought tremendous improvements on the task of trajectory prediction. However, most of them focus on the spatial influence of humans but ignore the temporal influence. In this paper, we propose a novel spatial-temporal attention(ST-Attention) model,which studies spatial and temporal affinities jointly. Specifically,we introduce an attention mechanism to extract temporal affinity,learning the importance for historical trajectory information at different time instants. To explore spatial affinity, a deep neural network is employed to measure different importance of the neighbors. Experimental results show that our method achieves competitive performance compared with state-of-the-art methods on publicly available datasets.
基金financially supported by the Special Fund for Basic Scientific Research of International Centre for Bamboo and Rattan(1632014003)National Natural Science Foundation of China(31101148 and 31300177)
文摘Understanding the relationship between tree height （H） and diameter at breast height （D） is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its applicability for unevenly aged stands of moso bamboo forest at a regional scale. Field data were collected for 21 plots. Based on these data, we identified two strong power relationships： a corre- lation between the mean bamboo height （Hm） and the upper mean H （Hu）, and a correlation between the mean D （Din） and the upper mean D （Du）. Simulation results derived from the aUometric equation model were in good agreement with observed culms derived from the field data for the 21 stands, with a root-mean-square error and relative root-mean-square error of 1.40 m and 13.41%, respectively. These results demonstrate that the allometric equation model had a strong predictive power in the unevenly aged stands at a regional scale. In addition, the estimated average height-diameter （H-D） model for South Anhui Province was used to predict H for the same type of bamboo in Hunan Province based on the measured D, and the results were highly similar. The allometric equation model has multiple uses at the regional scale, including the evaluation of the variation in the H- D relationship among regions. The model describes the average H-D relationship without considering the effects caused by variation in site conditions, tree density and other factors.
基金supported by the National Natural Science Foundation of China(Grant Nos.62472149,62376089,62202147)Hubei Provincial Science and Technology Plan Project(2023BCB04100).
文摘Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
文摘How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.
文摘Through analyzing 7 Ib-type samples of synthetic single diamonds by their DTA and TG in air, we ascertained the extrapolated onset temperature on the curves of DTA as the characteristic temperature of their thermal stabilities. Based on the grey system theory, we analyzed 4 factors influential in the thermal stability by the grey relationship analysis, a quantitative method, and derived the grey relationship sequence, that is, the rank of the influence extent of 4 factors on the thermal stability. Furthermore, we established the grey forecasting model, namely GM(1,5), for predicting the thermal stability of single diamonds with their intrinsic properties, which was then examined by a deviation-probability examination. The results illustrate that it is reasonable to take the Extrapolated Onset Temperature in DTA as the characteristic temperature for thermal stability (TS) of Ib-type synthetic single diamonds. The nitrogen content and grain shape regularity of diamonds are dominating factors. Likewise, grain size and compressive strength are minor factors. In addition, GM(1,5) can be used to predict the thermal stability of Ib-type synthetic single diamonds available. The precision rank of GM(1,5) is ‘GOOD’.
文摘In the last issue,two case reports separately present examples of the extremely rare and complex congenital heart diseases that show concordant atrioventricular connections to the L-looped ventricles in the presence of situs solitus.Both cases highlight that the relationship between the two ventricles within the ventricular mass is not always harmonious with the given atrioventricular connection.Such disharmony between the connections and relationships requires careful assessment of the three basic facets of cardiac building blocks,namely their morphology,the relationship of their component parts,and their connections with the adjacent segments.3D imaging and printing can now facilitate an otherwise difficult diagnosis in such complex situations.Rotation of either the 3D images or the models permit accurate assessment of the ventricular topologic pattern by creating the right ventricular en-face septal view,thus facilitating placement of the observer’s hands.As we now emphasize,an alternative approach,which might prove more attractive to imagers,is to rotate the ventricular mass to provide the ventricular apical view,thus permitting determination of the ventricular relationship without using the hands.
基金supported by the National Natural Science Foundation of China (71273105)the Fundamental Research Funds for the Central Universities,China (2013YB12)
文摘Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.
基金National Basic Research Program of China (2012CB722201)National Natural Science Foundation of China (30970504, 31060320)National Science and Technology Support Program (2011BAC07B01)
文摘Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation index （NDVI） from remotely-sensed imagery, dividing human-induced land degradation from vegetation dynamics due to climate change is not a trivial task. This paper presented a multilevel statistical modeling of the NDVI-rainfall relationship to detect human-induced land degradation at local and landscape scales in the Ordos Plateau of Inner Mongolia, China, and recognized that anthropogenic activities result in either positive （land restoration and re-vegetation） or negative （degradation） trends. Linear regressions were used to assess the accuracy of the multi- level statistical model. The results show that： （1） land restoration was the dominant process in the Ordos Plateau between 1998 and 2012; （2） the effect of the statistical removal of precipitation revealed areas of human-induced land degradation and improvement, the latter reflecting successful restoration projects and changes in land man- agement in many parts of the Ordos; （3） compared to a simple linear regression, multilevel statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. Additional factors should be included when analyzing the NDVI-rainfall relationship and detecting human-induced loss of vegetation cover in drylands to improve the accuracy of the approach and elimi- nate some observed non-significant residual trends.
基金supported by the National Key Basic Research Program of China(Grant No.2009CB421404)the National Natural Science Foundation of China(Grant No.41175076)+2 种基金the Fundamental Research Funds for the Central Universities(Grant No.11lgjc10)the support of a Direct Grant of the Chinese University of Hong Kong(Grant No.2021105)a Hong Kong Research Grants Council Project(CUHK No.403612)
文摘Precipitation and surface temperature are two important quantities whose variations are closely related through various physical processes. In the present study, we evaluated the precipitation-surface temperature （P-T） relationship in 17 climate models involved in the Coupled Model Intercomparison Project Phase 5 （CMIP5） for the IPCC Assessment Report version 5. Most models performed reasonably well at simulat- ing the large-scale features of the P-T correlation distribution. Based on the pattern correlation of the P-T correlation distribution, the models performed better in November-December-January-February-March （NDJFM） than in May-June-July-August-September （MJJAS） except for the mid-latitudes of the North- ern Hemisphere, and the performance was generally better over the land than over the ocean. Seasonal dependence was more obvious over the land than over the ocean and was more obvious over the mid- and high-latitudes than over the tropics. All of the models appear to have had difficulty capturing the P-T correlation distribution over the mid-latitudes of the Southern Hemisphere in MJJAS. The spatial variabil- ity of the P-T correlation in the models was overestimated compared to observations. This overestimation tended to be larger over the land than over the ocean and larger over the mid- and high-latitudes than over the tropics. Based on analyses of selected model ensemble simulations, the spread of the P-T correlation among the ensemble members appears to have been small. While the performance in the P-T correlation provides a general direction for future improvement of climate models, the specific reasons for the discrep- ancies between models and observations remain to be revealed with detailed and comprehensive evaluations in various aspects.
文摘An oil-in-water (O/W) solvent evaporation method was used to prepare biodegradable microspheresbased on poly(D,L-lactic acid) (PLA). Nifedipine, a hydrophobic drug, was chosen as a model molecule in the studyof drug entrapment and release. Effect of preparation conditions on the size, morphology, drug loading, and releaseprofiles of micropheres was investigated. Based on in vitro release experimental findings, a diffusion/dissolutionmodel was presented for quantitative description of the resulting release behaviors and drug release kinetics fromPLA microspheres analyzed. The mathematical models were used to predict the effect of microstructure on theresulting drug release. It provided an approach to determine the suitable structure parameters for microspheres toachieve desired drug release behaviors.
基金supported by the National Natural Science Foundation of China(51878354)the Natural Science Foundation of Jiang-su Province(No.BK20181402)+1 种基金Six Peak High-level Talents Project of Jiangsu Provincea Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘In order to investigate the basic mechanical properties and stress strain relationship model for bamboo scrimber manufactured based on a new technique,a large quantities of experiments have been carried out.Based on the analysis of the test results,the following conclusions can be drawn.Two main typical failure modes were classified for bamboo scrimber specimens both under tension parallel to grain and tension perpendicular to grain.Brittle failure happened for all tensile tests.The slope values for the elastic stages have bigger discreteness compared with those for the specimens under tensile parallel to grain.The failure modes for bamboo scrimber specimens under compression parallel to grain could be divided into four.Only one main failure mode happened both for the bending specimens and the shear specimens.With the COV values of 28.64 and 25.72 respectively,the values for the strength and elastic modulus under tensile perpendicular to grain have the largest discreteness for bamboo scrimber.From the point of CHV values,the relationship among the mechanical parameters for bamboo scrimber were proposed based on the test results.Compared with other green building materials,bamboo scrimber manufactured based on a new technique has better mechanical performance and could be used in construction area.Three stress strain relationship models which are four-linear model,quadratic function model,and cubic function model were proposed for bamboo scrimber specimens manufactured based on a new technique.The latter two models gives better prediction for stress strain relationship in elastic plastic stage.
基金funded through the Special Fund for Agro-Scientific Research in the Public Interestthe Special Public Welfare Industry (agriculture) Research-Research and Demonstration of Fisheries Fishing Technology and Fishing Gear (No. 201203018)the National Natural Science Foundation of China (No. 31402350)
文摘Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.
基金the National Natural Science Foundation of China(71871121).
文摘Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_0082)
文摘Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.
基金the financial support from the National Key Research and Development Program of China(2022YFB4101302-01)the National Natural Science Foundation of China(22178243)the science and technology innovation project of China Shenhua Coal to Liquid and Chemical Company Limited(MZYHG-22-02).
文摘Direct coal liquefaction(DCL)is an important and effective method of converting coal into high-valueadded chemicals and fuel oil.In DCL,heating the direct coal liquefaction solvent(DCLS)from low to high temperature and pre-hydrogenation of the DCLS are critical steps.Therefore,studying the dissolution of hydrogen in DCLS under liquefaction conditions gains importance.However,it is difficult to precisely determine hydrogen solubility only by experiments,especially under the actual DCL conditions.To address this issue,we developed a prediction model of hydrogen solubility in a single solvent based on the machine-learning quantitative structure–property relationship(ML-QSPR)methods.The results showed that the squared correlation coefficient R^(2)=0.92 and root mean square error RMSE=0.095,indicating the model’s good statistical performance.The external validation of the model also reveals excellent accuracy and predictive ability.Molecular polarization(a)is the main factor affecting the dissolution of hydrogen in DCLS.The hydrogen solubility in acyclic alkanes increases with increasing carbon number.Whereas in polycyclic aromatics,it decreases with increasing ring number,and in hydrogenated aromatics,it increases with hydrogenation degree.This work provides a new reference for the selection and proportioning of DCLS,i.e.,a solvent with higher hydrogen solubility can be added to provide active hydrogen for the reaction and thus reduce the hydrogen pressure.Besides,it brings important insight into the theoretical significance and practical value of the DCL.
文摘Objective:To explore multiple relationships in traditional Chinese medicine(TCM)knowledge by comparing binary and multiple relationships during knowledge organization.Methods:Characteristics of binary and multiple semantic relationships as well as their associations are described.A method to classify multiple relationships based on the involvement of time is proposed and theoretically validated using examples from the ancient TCM classic Important Formulas Worth a Thousand Gold Pieces.The classification includes parallel multiple relationships,restricted multiple relationships,multiple relationships that involve time,and multiple relationships that involve time restriction.Next,construction of multiple semantic relationships for TCM concepts in each classification using Protege,an ontology editing tool is described.Results:Protege is superior to a binary relationship and less than ideal with multiple relationships during the constitution of concept relationships.Conclusion:When applied in TCM,the semantic relationships constructed by Protege are superior than those constructed by correlation and/or attribute relationships,but less ideal than those constructed by the human cognitive process.
基金supported by the National High-Tech Research & Development Program of China (No. 2009AA062802) the Fundamental Research Funds for the Central Universities of China (No. 12CX06001A)Shandong Provincial Natural Science Foundation, China (No. ZR2011DQ011)
文摘A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model extending existing 2D methods into 3D space. Geologic models with different scales are organized by segmenting data into orthogonal blocks. A flow diagram illustrates an octree method for upscaling between blocks with different scales. Upscaling data from the smallest unit cells takes into account their average size and the Burgers vector when there are mismatches. A geocellular model of the Chengdao Reservoir of the Shengli Oilfield, China is taken as an illustrative case, showing that the methods proposed can construct a multi-scale geologic model correctly and display data from the multi-scale model effectively in 3D.
