Synthetic aperture radar(SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization monitoring.Most presented change detection metho...Synthetic aperture radar(SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization monitoring.Most presented change detection methods are conducted using couples of SAR amplitude images. However, a prior date of surface change is required to select a feasible image pair. We propose an automatic spatio-temporal change detection method by identifying the temporary coherent scatterers. Based on amplitude time series, χ^(2)-test and iterative single pixel change detection are proposed to identify all step-times: the moments of the surface change. Then the parameters, e.g., deformation velocity and relative height, are estimated and corresponding coherent periods are identified by using interferometric phase time series. With identified temporary coherent scatterers, different types of temporal surface changes can be classified using the location of the coherent periods and spatial significant changes are identified combining point density and F values. The main advantage of our method is automatically detecting spatio-temporal surface changes without prior information. Experimental results by the proposed method show that both appearing and disappearing buildings with their step-times are successfully identified and results by ascending and descending SAR images show a good agreement.展开更多
In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Lar...In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.展开更多
High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it...High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.展开更多
To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage p...To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.展开更多
Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accura...Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.展开更多
Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of ...Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of climate change on cotton production and the use of genomic approaches to increase stress tolerance in cotton.This paper discusses the effects of rising temperatures,changing precipitation patterns,and extreme weather events on cotton yield.It then explores various genomic strategies,such as genomic selection and marker-assisted selection,which can be used to develop stress-tolerant cotton varieties.The review emphasizes the need for interdisciplinary research efforts and policy interventions to mitigate the adverse effects of climate change on cotton production.Furthermore,this paper presents advanced prospects,including genomic selection,gene editing,multi-omics integration,highthroughput phenotyping,genomic data sharing,climate-informed breeding,and phenomics-assisted genomic selection,for enhancing stress resilience in cotton.Those innovative approaches can assist cotton researchers and breeders in developing highly resilient cotton varieties capable of withstanding the challenges posed by climate change,ensuring the sustainable and prosperous future of cotton production.展开更多
Based on the discrete wavenumber method, we calculate the fields of dynamic Coulomb rupture stress changes and static stress changes caused by M6.5 earthquake in Wuding, and study their relationship with the subsequen...Based on the discrete wavenumber method, we calculate the fields of dynamic Coulomb rupture stress changes and static stress changes caused by M6.5 earthquake in Wuding, and study their relationship with the subsequent after- shocks. The results show that the spatial distribution patterns of the positive region of dynamic stress peak value and static stress peak value are similarly asymmetric, which are basically identical with distribution features of aftershock. The dynamic stress peak value and the static stress in the positive region are more than 0.1 MPa and 0.01 MPa of the triggering threshold, respectively, which indicates that the dynamic and static stresses are helpful for the occurrence of aftershock. This suggests that both influences of dynamic and static stresses should be con- sidered other than only either of them when studying aftershock triggering in near field.展开更多
To study the mechanism of rockburst and its spatio-temporal evolution criterion,a rockburst simulation experiment was performed on granite specimens,each with a prefabricated circular hole,under different lateral load...To study the mechanism of rockburst and its spatio-temporal evolution criterion,a rockburst simulation experiment was performed on granite specimens,each with a prefabricated circular hole,under different lateral loads.Using micro camera,acoustic emission(AE)system,and infrared thermal imager,the AE characteristics and thermal radiation temperature migration were studied during the rockburst process.Then,the failure mode and damage evolution of the surrounding rock were analyzed.The results demonstrate that increasing the lateral load can first increase and then reduce the bearing capacity of the hole.In this experiment,the hole failure process could be divided into four periods:quiet,particle ejection,stability failure and collapse.Correspondingly,the AE signals evolved from a calm stage,to have intermittent appearance;then,they were continuous with a sudden increase,and finally increased dramatically.The failure of the surrounding rock was mainly tensile failure,while shear failure tended to first increase and then decrease.Meanwhile,damage to the hole increased gradually during the particle ejection period,whereas damage to the rockburst mainly occurred in the stability failure period.The thermal radiation temperature migration exhibited warming in shallow parts,inward expansion,cooling in the shallow parts with free surface heating,inward expansion,a sudden rise in temperature of the rockburst pits,and finally specimen failure.The initial reinforcement support should fully contribute to surface support.Furthermore,an appropriate tensile capacity and good energy absorption capacity should be established in support systems for high-stress roadways.展开更多
OBJECTIVE There is growing evidence that uridine may act as an endogenous neuromodulator with a potential signaling role in the central nervous system in addition to its function in pyrimidine metabolism.We previously...OBJECTIVE There is growing evidence that uridine may act as an endogenous neuromodulator with a potential signaling role in the central nervous system in addition to its function in pyrimidine metabolism.We previously found that acute morphine treatment significantly increased uridine release in the dorsal striatum of mice,while the mechanism involved in morphine-induced uridine release and the role of uridine in morphine-induced neurobehavioral changes have not been understood.METHODS Uridine release in the dorsal striatum of mice was assessed by in vivo microdialysis coupled with high performance liquid chromatography(HPLC) after morphine treatment.Western blotting and immunofluorescence were used to evaluate the expression of uridine-related proteins.Morphine-induced neurobehavioral changes were assessed by locomotor activity,behavioral sensitization and conditioned place preference(CPP)test.The expression of NT5E,an extracellular enzyme involved in formation of nucleosides,including uridine,was specifically knocked down in the dorsal striatum of mice using adeno-associated virus(AAV)-mediated short hairpin RNA(shRNA).RESULTS Both acute and chronic morphine administration significantly increased uridine release in the dorsal striatum,and this was associated with upregulation of NT5E but not other uridine-related proteins.Inhibition of NT5E with APCP or shRNA markedly inhibited morphine-induced uridine release in the dorsal striatum and related neurobehavioral changes,including hyperlocomotor activity,behavioral sensitization and CPP.CONCLUSION The present study increases our understanding of the contribution of NT5E in regulating morphine-induced neurobehavioral changes,at least as related to uridine,and suggests that NT5E may be a novel therapeutic target to manage morphine abuse.展开更多
Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-bas...Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-based) incremental updating (E-BIU) is proposed in this paper. At first, the relationship among the events, spatial changes and the database operations is analyzed, then a total architecture of E-BIU implementation is designed, which includes an event queue, three managers and two sets of rules, each component is presented in detail. The process of the E-BIU of master STDB is described successively. An example of building’s incremental updating is given to illustrate this approach at the end. The result shows that E-BIU is an efficient automatic updating approach for master STDB.展开更多
Calcined ginger nuts admixed by fly ash and quartz sand(CGN-(F+S))has been validated to be basically compatible to earthen sites as an anchor grout.Accelerated ageing tests including water stability test,temperature a...Calcined ginger nuts admixed by fly ash and quartz sand(CGN-(F+S))has been validated to be basically compatible to earthen sites as an anchor grout.Accelerated ageing tests including water stability test,temperature and humidity cycling test,soundness test and alkali resistance test are conducted with the objective to further research the property changes of CGN-(F+S)grout.Density,surface hardness,water penetration capacity,water permeability capacity,soluble salt,scanning electron microscopy(SEM)images and energy dispersive spectrometry(EDS)spectrum of these samples have been tested after accelerated ageing tests.The results show that densities of samples decrease,surface hardness,water penetration capacity and water permeability capacity of samples increase generally.Besides,soluble salt analysis,SEM and EDS results well corroborate the changes.Based on the results it can be concluded that property changes are most serious after temperature and humidity cycling test,followed by water stability,soundness and alkali resistance test in sequence.But in general,CGN-(F+S)still has good durability.展开更多
In this research,geological and hydrodynamic induced changes in the Kiashahr-Dastak coastal zone (SW Caspian Sea)were investigated based on aerial photographs(1967 and 1993)and ETM satellite images(2002)of the region ...In this research,geological and hydrodynamic induced changes in the Kiashahr-Dastak coastal zone (SW Caspian Sea)were investigated based on aerial photographs(1967 and 1993)and ETM satellite images(2002)of the region utilizing GIS based softwares.The results were represented as erosional and sedimenttation maps during this time spam.GIS based studies and field investigations show that展开更多
The Fourth Assessment Report of IPCC(IPCC AR4)concluded that average Northern Hemisphere temperatures during the second half of the 20th century were very likely higher than that of any other 50-year period in the las...The Fourth Assessment Report of IPCC(IPCC AR4)concluded that average Northern Hemisphere temperatures during the second half of the 20th century were very likely higher than that of any other 50-year period in the last 500 years and likely the highest in at least the past 1300 years.However,after evaluating Global or Northern Hemisphere temperature change series derived from ice cores,tree rings,展开更多
Food security is a human right,within a global context by aligning the opportunities to eliminate poverty,to attain the peace,the rational and implications of sustainable use and judicious management of natural resour...Food security is a human right,within a global context by aligning the opportunities to eliminate poverty,to attain the peace,the rational and implications of sustainable use and judicious management of natural resources,are the road map,to combat the disasters.The prevailing International tension with respect to climate change suggests that the food security can be achieved by penetrating,in depth,the agricultural research.Pakistan is under threat to展开更多
Dynamic changes of a microbial community for lignocellulose degradation were explored in details. Community composition and development were investigated by the means of denaturing gradient gel electrophoresis （DGGE...Dynamic changes of a microbial community for lignocellulose degradation were explored in details. Community composition and development were investigated by the means of denaturing gradient gel electrophoresis （DGGE）, and results showed that the microbial community was constituted of 14 kinds of bacteria and presented the fluctuation in some degrees with fermentation. Furthmore, the result of cluster analysis of DGGE pattern was accordant with growth curve, and the degradation process was divided into three stages： initial stage （0-12 h）, intermediate stage （24-144 h） and end stage （144-216 h）.展开更多
Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-de...Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.展开更多
The East African Rift extending across Djibouti, Ethiopia and Kenya is characterized by low level of economic development,high level of poverty,increasing population,scarce natural resources(land,water, and environmen...The East African Rift extending across Djibouti, Ethiopia and Kenya is characterized by low level of economic development,high level of poverty,increasing population,scarce natural resources(land,water, and environment),complex and rich ecosystems, increasing desertification and degrading biodiversity, underdeveloped regional trade and market,water resources mainly stored in groundwater and展开更多
In order to understand the temporal changes of botanical composition in grassland ecosystem, and to clarify the relation between these changes and environmental impacts, such as climatic factors and artificial disturb...In order to understand the temporal changes of botanical composition in grassland ecosystem, and to clarify the relation between these changes and environmental impacts, such as climatic factors and artificial disturbance, a grazing trail was carried out during a 21-year period from 1974 at a sown grassland of the National Grassland Research Institute, located in Nishinasuno, the central area of Japan. The data sets of biomass for each mouth(from April to November)of the 21 year period were analyzed in this paper. The botanical composition of aboveground biomass varied greatly with both season and year. The biomass ratio of improved herbage species to invaded native plants gradually decreased each year. This may have been owing to meteorological factors, such as low air-temperature in winter, dry and hot summers, grassland management(including grazing intensity and fertilizer application), and inter-specific competition between native and introduced herbage plants.展开更多
基金supported by the National Natural Science Foundation of China (42074022)。
文摘Synthetic aperture radar(SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization monitoring.Most presented change detection methods are conducted using couples of SAR amplitude images. However, a prior date of surface change is required to select a feasible image pair. We propose an automatic spatio-temporal change detection method by identifying the temporary coherent scatterers. Based on amplitude time series, χ^(2)-test and iterative single pixel change detection are proposed to identify all step-times: the moments of the surface change. Then the parameters, e.g., deformation velocity and relative height, are estimated and corresponding coherent periods are identified by using interferometric phase time series. With identified temporary coherent scatterers, different types of temporal surface changes can be classified using the location of the coherent periods and spatial significant changes are identified combining point density and F values. The main advantage of our method is automatically detecting spatio-temporal surface changes without prior information. Experimental results by the proposed method show that both appearing and disappearing buildings with their step-times are successfully identified and results by ascending and descending SAR images show a good agreement.
基金supported by Beijing Insititute of Technology Research Fund Program for Young Scholars(2020X04104)。
文摘In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.
基金Key Basic Research Project of Strengthening the Foundations Plan of China (Grant No.2019-JCJQ-ZD-360-12)National Defense Basic Scientific Research Program of China (Grant No.JCKY2021208B011)to provide fund for conducting experiments。
文摘High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.
基金supported by National Natural Science Foundation of China(Grant No.62073256)the Shaanxi Provincial Science and Technology Department(Grant No.2023-YBGY-342).
文摘To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.
文摘Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.
基金supported by major national R&D projects(No.2023ZD04040-01)National Natural Science Foundation of China(No.5201101621)National Key R&D Plan(No.2022YFD1200304).
文摘Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of climate change on cotton production and the use of genomic approaches to increase stress tolerance in cotton.This paper discusses the effects of rising temperatures,changing precipitation patterns,and extreme weather events on cotton yield.It then explores various genomic strategies,such as genomic selection and marker-assisted selection,which can be used to develop stress-tolerant cotton varieties.The review emphasizes the need for interdisciplinary research efforts and policy interventions to mitigate the adverse effects of climate change on cotton production.Furthermore,this paper presents advanced prospects,including genomic selection,gene editing,multi-omics integration,highthroughput phenotyping,genomic data sharing,climate-informed breeding,and phenomics-assisted genomic selection,for enhancing stress resilience in cotton.Those innovative approaches can assist cotton researchers and breeders in developing highly resilient cotton varieties capable of withstanding the challenges posed by climate change,ensuring the sustainable and prosperous future of cotton production.
文摘Based on the discrete wavenumber method, we calculate the fields of dynamic Coulomb rupture stress changes and static stress changes caused by M6.5 earthquake in Wuding, and study their relationship with the subsequent after- shocks. The results show that the spatial distribution patterns of the positive region of dynamic stress peak value and static stress peak value are similarly asymmetric, which are basically identical with distribution features of aftershock. The dynamic stress peak value and the static stress in the positive region are more than 0.1 MPa and 0.01 MPa of the triggering threshold, respectively, which indicates that the dynamic and static stresses are helpful for the occurrence of aftershock. This suggests that both influences of dynamic and static stresses should be con- sidered other than only either of them when studying aftershock triggering in near field.
基金Project(2017YFC0603003)supported by the National Key Research and Development Project of ChinaProjects(51974009,51674008)supported by the National Natural Science Foundation of China+3 种基金Project(201904a07020010)supported by the Key Research and Development Program of Anhui Province,ChinaProject(2018D187)supported by the Leading Talent Project of Anhui“Special Support Program”,Anhui Provincial Academic and Technology Leaders Research Activities Funding,ChinaProject(gxbjZD2016051)supported by the Excellence Talent Training Program of High School,ChinaProject(2019CX2008)supported by the Graduate Innovation Fund of Anhui University of Science and Technology,China。
文摘To study the mechanism of rockburst and its spatio-temporal evolution criterion,a rockburst simulation experiment was performed on granite specimens,each with a prefabricated circular hole,under different lateral loads.Using micro camera,acoustic emission(AE)system,and infrared thermal imager,the AE characteristics and thermal radiation temperature migration were studied during the rockburst process.Then,the failure mode and damage evolution of the surrounding rock were analyzed.The results demonstrate that increasing the lateral load can first increase and then reduce the bearing capacity of the hole.In this experiment,the hole failure process could be divided into four periods:quiet,particle ejection,stability failure and collapse.Correspondingly,the AE signals evolved from a calm stage,to have intermittent appearance;then,they were continuous with a sudden increase,and finally increased dramatically.The failure of the surrounding rock was mainly tensile failure,while shear failure tended to first increase and then decrease.Meanwhile,damage to the hole increased gradually during the particle ejection period,whereas damage to the rockburst mainly occurred in the stability failure period.The thermal radiation temperature migration exhibited warming in shallow parts,inward expansion,cooling in the shallow parts with free surface heating,inward expansion,a sudden rise in temperature of the rockburst pits,and finally specimen failure.The initial reinforcement support should fully contribute to surface support.Furthermore,an appropriate tensile capacity and good energy absorption capacity should be established in support systems for high-stress roadways.
基金National Natural Science Foundation of China(81373383).
文摘OBJECTIVE There is growing evidence that uridine may act as an endogenous neuromodulator with a potential signaling role in the central nervous system in addition to its function in pyrimidine metabolism.We previously found that acute morphine treatment significantly increased uridine release in the dorsal striatum of mice,while the mechanism involved in morphine-induced uridine release and the role of uridine in morphine-induced neurobehavioral changes have not been understood.METHODS Uridine release in the dorsal striatum of mice was assessed by in vivo microdialysis coupled with high performance liquid chromatography(HPLC) after morphine treatment.Western blotting and immunofluorescence were used to evaluate the expression of uridine-related proteins.Morphine-induced neurobehavioral changes were assessed by locomotor activity,behavioral sensitization and conditioned place preference(CPP)test.The expression of NT5E,an extracellular enzyme involved in formation of nucleosides,including uridine,was specifically knocked down in the dorsal striatum of mice using adeno-associated virus(AAV)-mediated short hairpin RNA(shRNA).RESULTS Both acute and chronic morphine administration significantly increased uridine release in the dorsal striatum,and this was associated with upregulation of NT5E but not other uridine-related proteins.Inhibition of NT5E with APCP or shRNA markedly inhibited morphine-induced uridine release in the dorsal striatum and related neurobehavioral changes,including hyperlocomotor activity,behavioral sensitization and CPP.CONCLUSION The present study increases our understanding of the contribution of NT5E in regulating morphine-induced neurobehavioral changes,at least as related to uridine,and suggests that NT5E may be a novel therapeutic target to manage morphine abuse.
文摘Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-based) incremental updating (E-BIU) is proposed in this paper. At first, the relationship among the events, spatial changes and the database operations is analyzed, then a total architecture of E-BIU implementation is designed, which includes an event queue, three managers and two sets of rules, each component is presented in detail. The process of the E-BIU of master STDB is described successively. An example of building’s incremental updating is given to illustrate this approach at the end. The result shows that E-BIU is an efficient automatic updating approach for master STDB.
基金Project(51578272)supported by the National Natural Science Foundation of China
文摘Calcined ginger nuts admixed by fly ash and quartz sand(CGN-(F+S))has been validated to be basically compatible to earthen sites as an anchor grout.Accelerated ageing tests including water stability test,temperature and humidity cycling test,soundness test and alkali resistance test are conducted with the objective to further research the property changes of CGN-(F+S)grout.Density,surface hardness,water penetration capacity,water permeability capacity,soluble salt,scanning electron microscopy(SEM)images and energy dispersive spectrometry(EDS)spectrum of these samples have been tested after accelerated ageing tests.The results show that densities of samples decrease,surface hardness,water penetration capacity and water permeability capacity of samples increase generally.Besides,soluble salt analysis,SEM and EDS results well corroborate the changes.Based on the results it can be concluded that property changes are most serious after temperature and humidity cycling test,followed by water stability,soundness and alkali resistance test in sequence.But in general,CGN-(F+S)still has good durability.
文摘In this research,geological and hydrodynamic induced changes in the Kiashahr-Dastak coastal zone (SW Caspian Sea)were investigated based on aerial photographs(1967 and 1993)and ETM satellite images(2002)of the region utilizing GIS based softwares.The results were represented as erosional and sedimenttation maps during this time spam.GIS based studies and field investigations show that
文摘The Fourth Assessment Report of IPCC(IPCC AR4)concluded that average Northern Hemisphere temperatures during the second half of the 20th century were very likely higher than that of any other 50-year period in the last 500 years and likely the highest in at least the past 1300 years.However,after evaluating Global or Northern Hemisphere temperature change series derived from ice cores,tree rings,
文摘Food security is a human right,within a global context by aligning the opportunities to eliminate poverty,to attain the peace,the rational and implications of sustainable use and judicious management of natural resources,are the road map,to combat the disasters.The prevailing International tension with respect to climate change suggests that the food security can be achieved by penetrating,in depth,the agricultural research.Pakistan is under threat to
基金Supported by National Key Technology R&D Program (2006BAD7A 10)National High-tech R&D Program (863 Program) (2007AA100705)
文摘Dynamic changes of a microbial community for lignocellulose degradation were explored in details. Community composition and development were investigated by the means of denaturing gradient gel electrophoresis （DGGE）, and results showed that the microbial community was constituted of 14 kinds of bacteria and presented the fluctuation in some degrees with fermentation. Furthmore, the result of cluster analysis of DGGE pattern was accordant with growth curve, and the degradation process was divided into three stages： initial stage （0-12 h）, intermediate stage （24-144 h） and end stage （144-216 h）.
基金Projects(41601424,41171351)supported by the National Natural Science Foundation of ChinaProject(2012CB719906)supported by the National Basic Research Program of China(973 Program)+2 种基金Project(14JJ1007)supported by the Hunan Natural Science Fund for Distinguished Young Scholars,ChinaProject(2017M610486)supported by the China Postdoctoral Science FoundationProjects(2017YFB0503700,2017YFB0503601)supported by the National Key Research and Development Foundation of China
文摘Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.
文摘The East African Rift extending across Djibouti, Ethiopia and Kenya is characterized by low level of economic development,high level of poverty,increasing population,scarce natural resources(land,water, and environment),complex and rich ecosystems, increasing desertification and degrading biodiversity, underdeveloped regional trade and market,water resources mainly stored in groundwater and
文摘In order to understand the temporal changes of botanical composition in grassland ecosystem, and to clarify the relation between these changes and environmental impacts, such as climatic factors and artificial disturbance, a grazing trail was carried out during a 21-year period from 1974 at a sown grassland of the National Grassland Research Institute, located in Nishinasuno, the central area of Japan. The data sets of biomass for each mouth(from April to November)of the 21 year period were analyzed in this paper. The botanical composition of aboveground biomass varied greatly with both season and year. The biomass ratio of improved herbage species to invaded native plants gradually decreased each year. This may have been owing to meteorological factors, such as low air-temperature in winter, dry and hot summers, grassland management(including grazing intensity and fertilizer application), and inter-specific competition between native and introduced herbage plants.
