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Morphological changes and gibberellin-related gene expression patterns during fruit growth and development of Amomum villosum 认领 引用 被引量：1
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作者 LÜ Bingding ZHANG Yuyi +5 位作者 TANG Liyun HU Jiajia SU Jing XU Jie HE Zhuohang HE Guozhen 《中山大学学报（自然科学版）（中英文）》 CAS CSCD 北大核心 2026年第3期19-32,共14页
The fruit of Amomum villosum is highly valued for its medicinal and edible properties.However,the fruit abscission rate is exceptionally high,resulting in low unit yield.To better understand the fruit growth and devel... The fruit of Amomum villosum is highly valued for its medicinal and edible properties.However,the fruit abscission rate is exceptionally high,resulting in low unit yield.To better understand the fruit growth and development,this study investigated the characteristic changes of fruits and the expression patterns of GA-related genes in both fruits and fruit stalks.Results revealed that it takes approximately 90 days for the ovary of A.villosum to reach maturity.Fruit growth pattern exhibited a slow-fast-slow trend,with the peak of fruit weight accumulation occurring between the 14 and 25 days after artificial pollination(DAP).Before the 27 DAP,significant changes were observed in the ovary,fruit color,pericarp thickness,and fruit thorn length.Additionally,ten candidate GA-related genes,including 1 GA13ox,1 GA20ox,1 GA3ox,2 GA2oxs,4 GID1cs,and 1 DELLA,were analyzed using bioinformatics tools.The GA-related genes in fruit and fruit stalk exhibited significant correlations with fruit growth/development and fruit dropping.Overall,the fruit growth and development law,and the expression patterns of GA-related genes provided a theoretical foundation for further functional study and the screening of candidate genes for potential applications in A.villosum. 展开更多
关键词 Amomum villosum gibberellin fruit development gene expression pattern bioinformatic
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Influence of grazing patterns on the stability of soil aggregates in semi-arid grasslands 认领 引用 被引量：1
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作者 LI Haonian MENG Ruibing +2 位作者 MENG Zhongju GE Rile WU Xiaolong 《Journal of Arid Land》 SCIE CAS CSCD 2026年第2期322-338,共17页
Global grassland degradation necessitates the identification of sustainable grazing management strategies.In semi-arid regions,grazing exclusion(GE),cold-season grazing(CG),and free grazing(FG)represent common practic... Global grassland degradation necessitates the identification of sustainable grazing management strategies.In semi-arid regions,grazing exclusion(GE),cold-season grazing(CG),and free grazing(FG)represent common practices in grassland ecosystems,yet the long-term ecological consequences of these patterns on plant community structure and soil aggregate stability remain inadequately elucidated.In this study,we evaluated the effects of GE,CG,and FG on soil organic carbon,soil water content,soil bulk density,soil aggregates,and vegetation indicators in Xilamuren steppe,a semi-arid grassland in northern China through field sampling and laboratory analyses in 2024.Our findings revealed that,compared to CG and FG,GE significantly enhanced aboveground and belowground biomass,species diversity,and soil physical-chemical properties in the 0–30 cm layer.The dominant plant species in GE and CG sites were Stipa krylovii,Leymus chinensis,and Agropyron cristatum,whereas Stipa krylovii,Artemisia frigida,and Leymus chinensis were predominant in FG site.Different grazing patterns led to distinct soil aggregate distributions,with>2.00 andCG>FG.Furthermore,random forest modeling identified plant species diversity,plant growth traits,and grazing patterns as the primary determinants of soil aggregate stability.Collectively,these results offer valuable insights into the sustainable management and ecological restoration of semi-arid grasslands under different grazing pressures. 展开更多
关键词 soil aggregate stability grazing patterns grazing exclusion species diversity soil physical-chemical properties semi-arid grasslands
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Big data-driven analysis of shale gas enrichment patterns:A case study of the Wufeng–Longmaxi Formation in the Sichuan Basin and its periphery 认领 引用 被引量：1
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作者 Zongquan Hu Jin Meng +10 位作者 Wei Du Yitian Xiao Chuanxiang Sun Guanping Wang Baojian Shen Tianrui Ye Dongjun Feng Zengqin Liu Longfei Lu Ruyue Wang Qianru Wang 《Energy Geoscience》 EI CAS CSCD 2026年第1期166-178,共13页
The Wufeng–Longmaxi Formation derives its name from the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation,found in sequence in the Sichuan Basin.This formation hosts rich shale gas reservoir... The Wufeng–Longmaxi Formation derives its name from the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation,found in sequence in the Sichuan Basin.This formation hosts rich shale gas reservoirs,and its shale gas enrichment patterns are examined in this study using data from 1197 shale samples collected from 14 wells.Five basic and three key parameters,eight in all,are assessed for each sample.The five basic parameters include burial depth and the contents of four mineral types—quartz,clay,carbonate,and other minerals;the three key parameters,representing shale gas enrichment,are total organic carbon(TOC)content,porosity,and gas content.The SHapley Additive exPlanations(SHAP)analysis originated in game theory is used here in an interpretable machine learning framework,to address issues of heterogeneous data structure,noisy relationships,and multi-objective optimization.An evaluation of the ranking,contribution values,and conditions of changes for these parameters offers new quantitative insights into shale gas enrichment patterns.A quantitative analysis of the relationship between data-sets identifies the primary factors controlling TOC,porosity,and gas content of shale gas reservoirs.The results show that TOC and porosity jointly influence gas content;mineral content has a significant impact on both,TOC and porosity;and the burial depth governs porosity which,in turn,affects the conditions under which shale gas is preserved.Input parameter thresholds are also determined and provide a basis for the establishment of quantitative criteria to evaluate shale gas enrichment.The predictive accuracy of the model used in this study is significantly improved by the step-wise addition of two input parameters,namely TOC and porosity,separately and together.Thus,the game theory method in big data-driven analysis uses a combination of TOC and porosity to evaluate the gas content with encouraging results—suggesting that these are the key parameters that indicate source rock and reservoir properties. 展开更多
关键词 Big data-driven analysis Primary controlling factor Shale gas enrichment pattern Wufeng–Longmaxi Formation Sichuan basin
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Seasonal emission patterns of airborne phytoncides in temperate forests from autumn to early spring:a case study of Xishui National Forest Park(Yichun,Northeast China) 认领 引用
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作者 Hongda Cai Yitong Wang +6 位作者 Xianwen Huang Sen Zhang Yankun Liu Jian Zhang Dongmei Zhao Peng Zhao Xiuhua Zhao 《Journal of Forestry Research》 SCIE EI CAS CSCD 2026年第1期256-271,共16页
Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio ac... Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio active compounds) remain poorly understood,limiting their therapeutic application.This study provides the first comprehensive characterization of spatiotemporal dynamics in airborne phytoncides and their synergistic interactions with environmental factors throughout the autumn-early spring seasonal transition in a temperate forest ecosystem.We analyzed the compositional dynamics of phytoncides and terpenoid content variations using thermal desorption-gas chromatography-mass spectrometry(TD-GC-MS) from September 2024 to March 2025.This period encompassed seasonal transitions from autumn to early spring,including diurnal variations in September and snowfall events in November.The method demonstrated detection limits(LODs) ranging from 1.35 to 5.33 ng m-3 and quantification limits(LOQs) from 4.09 to 16.15 ng m-3.Our results revealed pronounced seasonal fluctuations in phytoncide composition.In September,terpenoids,esters,alcohols,and alkanes displayed a diurnal "decrease-increase" trend,whereas aldehydes and ketones peaked at midday.Notably,esters and alcohols were undetectable in November and January.By January,terpenoids reached their lowest proportion(0.17±0.02%) at noon.Five terpenoids(α-pinene,myrcene,D-limonene,camphene,p-cymene) were detected in September,four(α-pinene,D-limonene,camphene,p-cymene) in November,two(D-limonene,p-cymene) in January,and only p-cymene in March.The total concentration and emission rate of the five terpenoids peaked in September afternoons at 1961.58±106.67 ng m-3 and653.86±35.56 ng m-3 h-1,respectively.Nocturnal emissions(32131.95±2522.21 ng m-3) significantly surpassed daytime levels(14473.04±958.49 ng m-3),with emission rates escalating from 1447.30±95.85 ng m-3 h-1(day) to 5355.33±420.37 ng m-3 h-1(night),marking a3.7-fold increase.Snowfall dramatically elevated terpenoid concentrations(pre-snowfall:158.58±14.12 ng m-3;post-snowfall:1080.57±57.76 ng m-3) and emission rates(pre-snowfall:52.86±4.71 ng m-3 h-1;post-snowfall:360.19±19.25 ng m-3 h-1),reflecting a 6.8-fold surge.This study underscores the profound influence of light intensity,seasonal shifts,and climatic conditions on airborne phytoncide levels,offering a scientific foundation for optimizing forest therapy and ecotourism strategies. 展开更多
关键词 Phytoncides Seasonal variation Diurnal-nocturnal patterns Snowfall impact Emission patterns
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Hydrogeological flow patterns and hydrochemical driving forces of groundwater in a typical coastal hilly region of the Jinjiang watershed,Southeast China:Recommendations for water pollution control and management 认领 引用 被引量：1
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作者 Zhong-shuang Cheng Chen Su +4 位作者 Wen-zhong Wang Bing-yan Li En-de Zuo Yu-meng Tian Zhao-xian Zheng 《China Geology》 CAS CSCD 2026年第2期316-332,共17页
Coastal groundwater(CGW)systems in rapidly urbanizing regions face critical challenges in achieving Sustainable Development Goal(SDG),where anthropogenic pressures intersect with hydrogeological vulnerability.This stu... Coastal groundwater(CGW)systems in rapidly urbanizing regions face critical challenges in achieving Sustainable Development Goal(SDG),where anthropogenic pressures intersect with hydrogeological vulnerability.This study employs coupled isotopic-hydrogeochemical analysis and geostatistics to unravel hydrochemical driving forces compromising groundwater quality in the Jinjiang Downstream Watershed(DJW),Southeast China.The results indicated that groundwater was predominantly recharged from local atmospheric precipitation and lateral recharge from the adjacent boundaries.Hydrochemical distributions exhibited a distinct pattern,transitioning from HCO3-Ca to HCO3·Cl-Ca,and then to Cl-Mg·Ca/Na·Ca,reflecting processes ranging from freshwater recharge to seawater intrusion(SWI).Elevated nitrates were primarily attributed to domestic sewage leakage and septic tank leaching.Additionally,preferential flow posed a risk to deep groundwater quality,by facilitating the rapid transport of contaminants through rock fractures.Key driving forces of hydrochemistry included silicate dissolution with local runoff paths,SWI,and human activities.The study advocates for a governance paradigm integrating electrochemical sensor networks with machine learning-driven contaminant prediction and phased membrane bioreactor deployment,which synergistically reduce nitrate fluxes while maintaining aquifer freshening processes.This integrated approach establishes a scalable model for SDG-aligned groundwater management in vulnerable coastal zones,demonstrating how process-based insights can bridge scientific discovery and water security implementation. 展开更多
关键词 Groundwater flow pattern Atmospheric precipitation Hydrochemistry Nitrate Driving forces Seawater intrusion Electrochemical sensor networks Machine learning Coastal area Sustainable Development Goal(SDG) Groundwater management Hydrogeological survey engineering
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Revealing global patterns of teleconnections in armed conflict 认领 引用
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作者 ZHUO Jun WU Jiajie +4 位作者 HAO Mengmeng DING Fangyu CHEN Shuai DONG Jiping JIANG Dong 《Journal of Geographical Sciences》 SCIE CSCD 2026年第4期1038-1056,共19页
Understanding the complex interactions among armed conflict events is important for the simulation and prediction of conflict risks.Many studies have suggested that conflict events affect neighbouring regions.Here we ... Understanding the complex interactions among armed conflict events is important for the simulation and prediction of conflict risks.Many studies have suggested that conflict events affect neighbouring regions.Here we find that conflicts exhibit not only localized effects but also significant teleconnections.By applying complex network analysis,the spatiotemporal scale of conflict teleconnections is quantified,revealing a characteristic spatial distance of approximately 1500 km and a rapid propagation delay of about 10 days.Moreover,distinct teleconnection patterns are identified through network coefficients.Eight major hubs,located in South Asia,the Middle East,and Sub-Saharan Africa,emerge and exhibit pronounced spatial heterogeneity in their interactions.Furthermore,analysis of the underlying driving mechanisms indicates that differences in teleconnection patterns are likely associated with the flows of energy,materials,and information,with information playing the predominant role in shaping these interactions.These findings provide insights into long-distance interactions in armed conflict,offering a better understanding of conflict risk. 展开更多
关键词 armed conflict teleconnection patterns complex network
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Thoughts on the scientific research of the connotation of traditional Chinese medicine patterns 认领 引用
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作者 Kang Xie Yulin Ouyang +1 位作者 Yong Wang Chun Li 《Journal of Traditional Chinese Medical Sciences》 CAS CSCD 2026年第1期3-11,共9页
Traditional Chinese medicine(TCM)is a holistic medical system that classifies and treats diseases based on the concept of patterns.These patterns describe the pathophysiological process of a disease at a specific stag... Traditional Chinese medicine(TCM)is a holistic medical system that classifies and treats diseases based on the concept of patterns.These patterns describe the pathophysiological process of a disease at a specific stage,reflecting both external signs and internal features.TCM patterns are central to pattern differentiation,treatment,clinical practice,and theoretical development in TCM.However,scientific explanation of TCM patterns remains limited because of subjective diagnostic criteria,the absence of a standardized experimental medical system,and unclear biological mechanisms,which restrict the modernization and globalization of TCM.Addressing challenges such as strong subjectivity in diagnosis,lack of standardized experimental systems,and unclear biological mechanisms is necessary to clarify the scientific meaning of TCM patterns and to provide technical approaches for the modernization and globalization of TCM.A strategy focused on“pathogenic factors,genetic predisposition,and disease progression stages”was adopted.This approach included the following:(Ⅰ)constructing disease-pattern integrated biological models with animal models,organoids,and multi-organ chips;(Ⅱ)applying multi-omics technologies,such as spatial omics,single-cell omics,and dynamic metabolic flux omics;(Ⅲ)using artificial intelligence(AI)and big data for data integration and prediction of pattern evolution;and(Ⅳ)validating formula–pattern associations through the“pattern differentiation through formula efficacy”approach.These strategies directly address the main obstacles in TCM pattern research by providing objective,quantifiable,and reproducible methodologies.Constructing disease-pattern integrated models enabled cross-scale research platforms.Applying multi-omics technologies allowed analysis of complex biological bases.AI and big data approaches addressed challenges related to heterogeneous data.The“formula-based pattern differentiation”approach supported precise interventions and the development of new drugs.This interdisciplinary framework advances TCM pattern research by moving from empirical description to objective quantification.By integrating innovative approaches,the study establishes a foundation for systematic,evidence-based TCM diagnosis and treatment,supporting accuracy and promoting international recognition and modernization of TCM.The study shows that combining multi-omics technologies,AI-driven data analysis,and disease-pattern models enables objective quantification of TCM patterns and clarifies their biological mechanisms. 展开更多
关键词 Traditional Chinese medicine patterns Disease-pattern integrated model Multi-omics technology Artificial intelligence Pattern differentiation through formula efficacy
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Propagation patterns of hydrological droughts in the source region of Yellow River:Insights from standardized versus threshold‐based approaches 认领 引用
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作者 Jiefeng Wu Huaxia Yao +5 位作者 Pengyu An Qiangkun Li Jinxu Han Dejian Zhang Xuemei Li Guoqing Wang 《River》 EI CSCD 2026年第1期55-68,共14页
Understanding the propagation patterns of hydrological droughts is crucial for drought prevention,disaster mitigation,and water resource management.Two common methodological frameworks are employed:standardized indice... Understanding the propagation patterns of hydrological droughts is crucial for drought prevention,disaster mitigation,and water resource management.Two common methodological frameworks are employed:standardized indices,represented by the Standardized Streamflow Index(SSI),and threshold‐based(nonstandardized)indices,represented by the variable drought threshold(VDT)and fixed drought threshold(FDT).However,differences and similarities between these two types of methods in identifying hydrological droughts and characterizing their propagation patterns(e.g.,onset,peak intensity,and termination)have not been systematically examined.To address this gap,the source region of Yellow River basin(SRYB),an area with relatively limited human influence,is selected as a case study.The results reveal several key similarities and distinctions:(i)The average duration of hydrological droughts during 1956–2022 is similar between SSI and VDT,but significantly longer when identified by FDT.The average severity derived from FDT is lower than that from VDT.(ii)All three methods effectively capture the spatial propagation behavior of hydrological droughts across the SRYB,which generally exhibits a decreasing intensity from upstream to downstream.(iii)Marked differences exist in the intra‑annual timing of event occurrences:SSI and VDT show an approximately even monthly distribution,whereas FDT indicates a pronounced concentration of drought events in low‐flow periods.(iv)The onset,peak intensity,and termination of hydrological droughts identified by FDT align well with wet‐dry transitions,a feature not reflected in the results from SSI or VDT.(v)These discrepancies stem from the“relative”nature of SSI and VDT—which evaluate drought events against reference‐period thresholds,leading to similar average durations and uniform seasonal distributions—and the“absolute”nature of FDT,which uses inherent low‐flow thresholds,resulting in longer durations,reduced severity,seasonal concentration,and better alignment with wet‐dry transitions.This study provides critical and actionable insights for selecting appropriate hydrological drought identification methods,thereby supporting sustainable water resource management and enhancing water security under drought conditions. 展开更多
关键词 drought indices drought mitigation evolution patterns methodological comparison
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Thermal stability design for flexural wave bandgap of metamaterial plates with perforated and pre-curved patterns 认领 引用
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作者 Qian GENG Xing ZHOU +3 位作者 Mengyang WANG Xiongwei YANG Zhushan SHAO Yueming LI 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2026年第3期443-472,I0001-I0004,共30页
A design idea for single-component metamaterial plates is proposed to achieve the thermal stability of flexural wave bandgap by the perforated and pre-curved patterns.The band structure analysis suggests that perforat... A design idea for single-component metamaterial plates is proposed to achieve the thermal stability of flexural wave bandgap by the perforated and pre-curved patterns.The band structure analysis suggests that perforation can release part of the in-plane thermal expansion to weaken the softening effect of thermal stress.Introducing precurved components to the perforated structure will stop the decrement of the bandgap frequency in thermal environment,and even make the frequency higher with appropriate structural parameters.The bending stiffness of the heated plate is enhanced by the thermal deflection induced stiffening effect of the pre-curved components.The segmented pre-curved component presents a strong ability to resist the thermal influence on the flexural wave bandgap.A simplified model is established for the local structure of the precurved component.The theoretical calculations explain the thermally induced frequency increment of the bandgap and the discrepancy in the thermal response between the two pre-curved models.The transmittance of flexural wave validates the effectiveness of the proposed design. 展开更多
关键词 metamaterial plate flexural vibration bandgap perforation pre-curved pattern thermal stability
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Effects of wetland connectivity on plant communities and vegetation patterns in the Qaidam Basin 认领 引用
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作者 YUE Yifan MA Dengke +3 位作者 MA Yuanyuan KANG Wenrong ZHOU Guoying ZHAO Wenzhi 《Journal of Arid Land》 SCIE CAS CSCD 2026年第4期696-714,共19页
The Qaidam Basin,a typical alpine arid inland basin on the northern Qinghai-Xizang Plateau,China,hosts wetland ecosystems that are strongly constrained by topography and extreme climate.These ecosystems exhibit pronou... The Qaidam Basin,a typical alpine arid inland basin on the northern Qinghai-Xizang Plateau,China,hosts wetland ecosystems that are strongly constrained by topography and extreme climate.These ecosystems exhibit pronounced spatiotemporal heterogeneity and fragmented distribution patterns,rendering them highly sensitive to environmental change.This study integrated Sentinel-2 remote sensing imagery with the SedInConnect model to delineate wetland patch distributions and calculate the Index of Connectivity(IC)values across the basin.Based on IC values,we stratified field sampling sites into high-,moderate-,and lowconnectivity gradient groups to analyze the relationships among plant community characteristics,vegetation spatial patterns,and wetland connectivity in the Qaidam Basin.Partial Least Squares Path Modeling(PLSPM)was further employed to quantify the driving mechanisms underlying wetland vegetation characteristics.The results revealed that wetland connectivity across the basin was generally low,with IC values up to 1.32 and displaying a west-to-east decreasing gradient.The west and northwest were characterized by relatively continuous high-connectivity wetland networks,while fragmented and low-connectivity wetlands predominated in the east and southeast.Connectivity regulated wetland vegetation patterns primarily by affecting patch size,fragmentation,and internal adjacency.High-connectivity areas had higher class area(CA),largest patch index(LPI),and area-weighted mean patch size(AREA_AM)than low-connectivity areas.Connectivity had the strongest effect on vegetation coverage,which declined sharply from 87.577%in highconnectivity areas to 12.152%in low-connectivity areas.Meanwhile,species diversity showed a moderately negative response to connectivity changes,whereas species evenness remained relatively unaffected.PLS-PM explained 78.300%and 67.500%of the variance in vegetation community and vegetation pattern,respectively.Climate played a dominant role in shaping vegetation characteristics,with significant negative effects on both vegetation community and pattern.Topography influenced vegetation indirectly through climate,and connectivity was influenced by both drivers and exerted positive effects on vegetation community and pattern.This study reveals the multi-pathway driving mechanisms underlying vegetation pattern formation in alpine wetlands,providing a theoretical foundation and decision-support framework for the scientific conservation and adaptive management of wetlands in the Qaidam Basin. 展开更多
关键词 connectivity gradient wetland vegetation vegetation pattern community characteristics driving mechanisms
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Typical blood parameters and gut microbiota alterations associated with the mutual conversion of cold and hot patterns induced by Chinese herbal medicines 认领 引用
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作者 Yanan Yang Yuxiao Li +2 位作者 Kebin Wang Shengxian Wu Chongming Wu 《Journal of Traditional Chinese Medical Sciences》 CAS CSCD 2026年第1期34-47,共14页
Objective:To elucidate the quantification and standardization of cold and hot patterns,the fundamental concepts in traditional Chinese medicine(TCM).Methods:This randomized cross-controlled trial recruited 30 healthy ... Objective:To elucidate the quantification and standardization of cold and hot patterns,the fundamental concepts in traditional Chinese medicine(TCM).Methods:This randomized cross-controlled trial recruited 30 healthy volunteers.Participants in Group 1 underwent 14 days of Coptis chinensis Franch.(C.chinensis,Huang Lian)treatment to shift their body toward the cold pattern,followed by 7 days of washout and 14 days of Cinnamomum cassia Presl(C.cassia,Rou Gui)treatment to shift their body toward the hot pattern.Participants in Group 2 underwent the opposite treatment.Blood and stool samples were collected for routine blood testing and full-length 16S rRNA metagenomic sequencing.Results:Red blood cells(RBC),hemoglobin(HGB),hematocrit(HCT),and blood platelet count(BPC)were increased by C.chinensis,whereas the mean corpuscular HGB concentration(MCHC)was increased by C.cassia.RBC,HGB,HCT,and BPC were positively associated with the cold pattern but negatively correlated with the hot pattern,whereas MCHC showed opposite relationships.C.chinensis-increased Blautia stercoris was positively correlated with RBC,HGB,and HCT under C.chinensis treatment,whereas C.cassia-enhanced Parabacteroides distasonis_A was positively associated with MCHC under C.cassia treatment.Interestingly,five indicators(RBC,HGB,HCT,Blautia stercoris,and Prevotella copri)had an area under the curve of 0.795 for predicting the cold pattern.Although three indicators(MCHC,Akkermansia sp004167605,and Parabacteroides distasonis_A)showed poor predictive ability for the hot pattern,when the individual’s gut microbiota experienced disturbance by cold Chinese materia medica stimulation,the predictive ability increased to 0.703.Conclusion:This study suggests that blood parameters and gut microbes may be potential indicators of hot and cold TCM patterns,which could benefit the objectivity and scientific rigor of TCM. 展开更多
关键词 Traditional Chinese medicine Pattern differentiation Gut microbiota Coptis chinensis Franch Cinnamomum cassia Presl
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Fracture response patterns in deep to ultra-deep tight sandstones:A comparison based on core and borehole images 认领 引用
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作者 Yu Du Hu-Cheng Deng +7 位作者 Xiao-Fei Hu Hao-Tian Zhang Hong-Hui Wang Cui-Li Wang Mao-Xin Liu Chen-Yang Zhao Shang-Rong Guo Zi-Yun Zheng 《Petroleum Science》 SCIE EI CAS CSCD 2026年第2期541-562,共22页
Natural fractures serve as the primary storage spaces and flow pathways in deep to ultra-deep tight sandstone reservoirs,directly influencing hydrocarbon accumulation,preservation,and production.Borehole images offer ... Natural fractures serve as the primary storage spaces and flow pathways in deep to ultra-deep tight sandstone reservoirs,directly influencing hydrocarbon accumulation,preservation,and production.Borehole images offer intuitive,continuous,and high-resolution identification of natural fractures along the entire borehole.However,relying solely on complete sinusoidal curves from borehole images for fracture identification may lead to omissions,as it overlooks cases where these curves are incomplete or truncated.To address the problems and deficiencies in fracture identification,this study systematically classifies borehole image feature patterns based on core-to-log spatial position restoring.A bidirectional comparison is conducted between natu ral fractures in cores and the fracture image features in borehole images.A quantitative relationship between fracture dip angle,thin layer thickness and borehole radius was established,accompanied by a mathematical expression describing the fracture curve morphology was proposed.These findings enabled the development of an imaging response pattern for natural fractures in deep and ultra-deep tight sandstone reservoirs,incorporating key parameters such as dip angle,through-layer connectivity,and spatial position within the borehole.In the Bashijiqike-Baxigai tight-sandstone reservoirs of the Bozi-Dabei area,we estimate that approximately 24%of coreobserved fractures display distinct linear-pattern features on borehole images,whereas approximately 91%of borehole images features can be correlated with fractures observed in core.Fracture identification rates for natural fractures increased by 17%in water-based mud and by 3%in oil-based mud through the application of the natural fracture image response pattern.Moreover,this study analyzes the deviations in the matching between core fractures and image features.Finally,we further discuss the common sources of error in natural fracture identification using borehole images from multiple perspectives,including missing core responses,inconsistencies between core and borehole image features,distortion of fracture chord curve,inaccurate fracture count,misclassification of fractures,and variations in interpretation under different mud systems.The research addresses the blind spots of traditional methods in fracture identification within thin layers,not only enhancing the detection rate of natural fractu res but also further improving the accuracy of fractu re recognitio n.At the same time,it will contribute to the optimization of fracture characterization,reservoir evaluation,and production forecasting,providing a more reliable data foundation for exploration and development under complex geological conditions. 展开更多
关键词 Borehole images Natural fracture Fracture image features Fracture response pattern Fracture identification Tight sandstone reservoir
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Evaluating corneal topographic patterns in keratoconic eyes and their association with keratoconus changes over time 认领 引用
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作者 Hassan Hashemi Alireza Jamali +2 位作者 Payam Nabovati Alireza Hashemi Mehdi Khabazkhoob 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2026年第5期891-900,共10页
AIM:To evaluate various corneal topographic patterns in keratoconus(KCN)and their association with disease progression.METHODS:A retrospective cohort study was conducted on 636 eyes of 335 KCN patients(396 males,240 f... AIM:To evaluate various corneal topographic patterns in keratoconus(KCN)and their association with disease progression.METHODS:A retrospective cohort study was conducted on 636 eyes of 335 KCN patients(396 males,240 females)with a mean age of 30.95±7.95y.Participants underwent two ocular examinations,including corneal tomography using the Pentacam-HR.Topographic patterns were classified based on axial curvature,and KCN progression was defined as a change of≥1.00 D in maximum keratometry(Kmax).Accordingly,evaluated eyes were categorized into progressive,regressive,and stable groups.RESULTS:The most common topographic pattern was asymmetric bowtie with inferior steepening(AB-IS,27.4%)in both males(26.8%)and females(28.3%).In the regressive group,asymmetric bowtie with skewed radial axes(21.3%)was most frequent,while AB-IS(31.3%)and inferior steepening(IS,25.9%)dominated the stable and progressive groups,respectively.Significant differences were observed in corneal parameters across patterns:the oval pattern exhibited the most negative spherical equivalent and the lowest corrected visual acuity,whereas the irregular pattern showed the highest Kmax values in the first examination(P<0.05).The asymmetric bowtie with superior steepening(AB-SS)pattern also exhibited the least curvature.In terms of changes in topographic parameters over time,variations were observed in certain parameters across different patterns.Notably,the irregular pattern exhibited the most significant changes in Kmax between the two examinations.Although the AB-SS tended to regressed,the AB-IS and IS patterns showed a tendency toward progression(P<0.05).Changes in most components of the KCN screening indices also varied significantly across patterns(P<0.05).CONCLUSION:Corneal topographic patterns in KCN exhibit distinct characteristics and progression rates.Understanding these patterns can aid in predicting disease progression and tailoring treatment strategies. 展开更多
关键词 keratoconus axial topography topographic pattern progression regression
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Hydrocarbon enrichment patterns and exploration targets in the Paleogene Liushagang Formation,Wushi Sag,Beibuwan Basin,China 认领 引用
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作者 WU Keqiang HU Desheng +2 位作者 YOU Junjun MAN Xiao XU Shouli 《Petroleum Exploration and Development》 SCIE 2026年第2期299-310,共12页
The Paleogene Liushagang Formation in the Wushi Sag of the Beibuwan Basin is characterized by dispersed hydrocarbon distribution,small-scale residual exploration targets and large burial depth.Based on data from drill... The Paleogene Liushagang Formation in the Wushi Sag of the Beibuwan Basin is characterized by dispersed hydrocarbon distribution,small-scale residual exploration targets and large burial depth.Based on data from drilling,laboratory experiments,and geophysic analysis,this study systematically investigates the hydrocarbon accumulation conditions and enrichment patterns in the Liushagang Formation.The key findings are obtained in five aspects.First,the structural evolution of the sag involved three distinct stages:early faulting,mid-stage detachment deformation and late adjustment,governed by an“extension–detachment–strike-slip”composite fault system that controlled basin subsidence,depocenter migration and sedimentary environment evolution.Second,three principal source rock intervals in the Eocene Liushagang Formation,concentrated in the southern East Sub-sag under the control of the No.7 Fault Zone,are characterized by considerable thickness and high quality,with the oil shale in the lower part of the second member of Liushagang Formation(lower Liu-2 Member)being the most prolific,providing a robust resource foundation in the sag.Third,four reservoir–seal assemblages are identified,corresponding to three hydrocarbon migration systems:direct source–reservoir contact,fault–sandbody coupling,and fault–structural ridge–sandbody stepwise composite networks.Fourth,three accumulation models are established:“young source,old reservoir”with lateral stepwise migration,“self-sourced and self-stored”intra-source enrichment,and“lower source–upper reservoir”with vertical migration.Fifth,exploration priorities are further delineated,highlighting deep fault-block traps in the central zone of the East Sub-sag,intrasag lithologic traps,and bedrock buried-hill targets with direct source–reservoir connectivity,all demonstrating significant resource potential. 展开更多
关键词 hydrocarbon enrichment pattern accumulation model exploration direction Paleogene Liushagang Formation Wushi Sag Beibuwan Basin
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The influence of three-dimensional gray landscape patterns on urban surface temperature:A case study of Beijing,China 认领 引用
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作者 Linlin Zhao Kun Jia +5 位作者 Yanxu Liu Guofeng Tao Jie Li Bo Yuan Yuran Cui Shijiao Qiao 《Ecological Frontiers》 CSCD 2026年第1期167-177,共11页
The rapid urbanization has significantly accelerated the expansion of cities and led to a notable increase in urban land surface temperature(LST).Currently,most studies mainly examine the effects of two-dimensional(2D... The rapid urbanization has significantly accelerated the expansion of cities and led to a notable increase in urban land surface temperature(LST).Currently,most studies mainly examine the effects of two-dimensional(2D)landscape patterns on LST variations,and research investigating the relationship between three-dimensional(3D)urban landscape patterns and LST remains relatively scarce.Therefore,this study utilizes partial correlation analysis and piecewise linear regression to systematically investigate the impacts of gray landscape indicators on LST variations under both 2D and 3D urban patterns,aiming to elucidate the complex relationship between 3D urban landscape patterns and LST dynamics.The results demonstrate that specific 3D building characteristics,particularly the area of low-rise buildings,building aggregation degree,shape complexity,and patch density of mid-rise buildings,serve as effective indicators of urban thermal environment risk.The analysis reveals that increased area-related indicators for low-rise buildings significantly exacerbate the LST rise,whereas modifications to the landscape shape of middle and high-rise buildings contribute to thermal mitigation.Additionally,when gray landscape aggregation exceeds 80%,the spatial concentration of mid-rise buildings exhibits a pronounced positive effect on moderating urban LST.These findings elucidate the mechanisms through which 3D landscape patterns influence urban thermal risks in Beijing,advancing the understanding of urban landscape-ecological processes interactions and providing crucial scientific support for landscape optimization and urban thermal environment risk mitigation strategies. 展开更多
关键词 Land surface temperature 3D landscape patterns Thermal environment risk Landscape optimization
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Structural Feature Selection in Common Spatial Patterns Using Adaptive Sparse Group Lasso 认领 引用
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作者 Yadi Wang Jiahao Zhang +2 位作者 Tengfei Zhou Bingbing Jiang Jiejiang Chen 《CAAI Transactions on Intelligence Technology》 SCIE EI CSCD 2026年第2期367-384,共18页
With the advancement of brain–computer interfaces(BCI),motor imagery(MI)electroencephalogram(EEG)decoding can greatly benefit from spatial filtering features derived from common spatial patterns(CSP).However,CSP-base... With the advancement of brain–computer interfaces(BCI),motor imagery(MI)electroencephalogram(EEG)decoding can greatly benefit from spatial filtering features derived from common spatial patterns(CSP).However,CSP-based features often exhibit high redundancy and intersubject variability.These limitations make the feature selection methods based on sparse learning difficult to effectively balance the heterogeneous contributions of different temporal and spatial components.Moreover,these models tend to prioritise features with larger coefficients,potentially overlooking intrinsic feature importance and compromising the quality of the selected feature subset.To address these issues,we propose an Adaptive Sparse Group Lasso(ASGL)method for structured feature selection,designed to enhance discriminative CSP features whilst suppressing irrelevant components.The proposed method partitions EEG signals into consecutive segments using a sliding window,treating each as a separate feature group.Benefiting from this,the importance of features at both the group level and the within-group level can be effectively quantified through mutual information and copula mutual information,thereby assigning adaptive weights for selective penalisation within the model.This weight construction strategy preserves important features from relevant time intervals and frequency bands.The resulting optimization problem is solved efficiently via the alternating direction method of multipliers(ADMM).Evaluations on simulated and real-world datasets demonstrate that the proposed ASGL outperforms existing methods. 展开更多
关键词 adaptive sparse group lasso brain-computer interfaces common spatial patterns motor imagery EEG structural feature selection
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An image inpainting method based on multiple receptive fields and dynamic matching of damaged patterns 认领 引用
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作者 MENG Jiahao LIU Weirong +2 位作者 SHI Changhong LI Zhijun LIU Jie 《Journal of Southeast University(English Edition)》 EI CAS 2026年第1期121-130,共10页
Current image inpainting models are primarily designed to achieve a large receptive field(RF)using refinement networks to incorporate different scales.However,these models fail to adapt the use of different RFs to the... Current image inpainting models are primarily designed to achieve a large receptive field(RF)using refinement networks to incorporate different scales.However,these models fail to adapt the use of different RFs to the specific patterns of image damage,resulting in artifacts and semantic information confusion in repaired images.To address the problems of artifacts and semantic information confusion,inspired by different sensitivities of different RFs to inpainting the same image damaged patterns,this study proposes an image inpainting method based on multiple receptive fields(MRFs)and dynamic matching of damaged patterns.First,the parallel filter banks are used to extract the MRF feature groups.Second,the features are dynamically weighted and screened,guided by the mask image,to construct a relationship that adaptively matches the most relevant RF to each specific damaged pattern.A fast Fourier convolution based decoder is used to enhance the fusion of global contextual features during the reconstruction of high dimensional features into low dimensional images.Comparative experimental results show that the proposed method achieves better subjective and objective inpainting results on three public datasets:Paris StreetView,CelebA-HQ,and Places2. 展开更多
关键词 image inpainting generative adversarial networks multiple receptive fields(MRFs) dynamic matching of damaged patterns decoder with fast Fourier convolutional
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Anthropogenic activities amplify spatiotemporal variations in regional ecological security patterns dominated by natural factors:Evidence from the West Liaohe River Basin,China 认领 引用
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作者 LYU Xin LI Xiaobing +2 位作者 WANG Kai CAO Wanyu ZHANG Chenhao 《Journal of Arid Land》 SCIE CAS CSCD 2026年第5期752-773,共22页
Ecological security patterns(ESPs)represent an effective way to maintain regional ecological security and promote regional sustainable development.This study investigated the spatiotemporal variations of ESPs in the W... Ecological security patterns(ESPs)represent an effective way to maintain regional ecological security and promote regional sustainable development.This study investigated the spatiotemporal variations of ESPs in the West Liaohe River Basin(WLRB),China during 2000–2020 on the basis of five key ecosystem services(net primary production,soil conservation,habitat quality,water retention,and soil loss by wind).On the basis of the Geodetector model,we initially measured the explanatory rates of various natural and anthropogenic factors on the spatial differentiation of ecological sources and ecological corridors.The Geographically and Temporally Weighted Regression(GTWR)model was subsequently used to elucidate the driving mechanism of ESPs at the interannual scale.During 2000–2020,a"fan-shaped"ESP of"two zones,three belts,and many branches"formed in the WLRB.Natural factors dominated the spatial distribution of ESPs,and the average spatial explanation rate for ecological sources and ecological corridors was 23.86%,which was higher than that of anthropogenic activities(13.29%).However,anthropogenic activities amplified the spatiotemporal variations in ESPs.On this basis,this study proposed an ecological security protection and regulation strategy from three aspects,namely,regional priority,suitability analysis,and risk regulation,which might provide a working direction for regional practical management.This study extends the paradigm of ESP research and offers an important theoretical basis for regional ecological security,from"passive management"to"active management". 展开更多
关键词 ecological security patterns(ESPs) ecosystem services anthropogenic activities Geodetector Geographically and Temporally Weighted Regression(GTWR)model West Liaohe River Basin
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Spatial-temporal Patterns and Influencing Factors of Green and Low-carbon Technology Innovation:Evidence from Chinese Cities 认领 引用
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作者 GAO Xin GU Weinan 《Chinese Geographical Science》 SCIE CAS CSCD 2026年第4期590-605,共16页
As a crucial motivator for China to advance the‘dual carbon'target,green and low-carbon technology innovation(GLCTI)not only provides a technological path for the realization of carbon reduction,zero carbon,and n... As a crucial motivator for China to advance the‘dual carbon'target,green and low-carbon technology innovation(GLCTI)not only provides a technological path for the realization of carbon reduction,zero carbon,and negative carbon but also plays a role in promoting the low-carbon transformation of the socio-economic development.In this case,it is necessary to explore the spatial-temporal characteristics and influencing factors of GLCTI.Green and low-carbon patent data gathered via a web crawler were utilized to indicate the level of GLCTI from 2002 to 2020.Spatial Analysis,Spatial Autocorrelation,and Spatial Durbin Model were used to investigate the spatial-temporal evolution and influencing factors of GLCTI in China.The results show that:1)whether it was the number of patents granted or the number of city participation,fossil energy carbon reduction technology had been leading GLCTI across the country;2)the cities demonstrating stronger GLCTI performance in China are primarily located in the eastern coastal regions and provincial capitals of the central and western areas,with significant spatial differentiation characteristics;3)Chinese urban GLCTI was booming in low-carbon field,and non-resource-based cities had better conditions for the development of GLCTI;4)significant spatial spillover effects and path-dependent features were observed in Chinese urban GLCTI.Talent reserve,financial investment,foreign direct investment,urban economic scale,tertiary industry-based industrial structure,and urban air quality are the key variables to enhance cities'capacity in GLCTI,while the secondary industry-based industrial structure has an inhibitory and constraining effect.The results could provide a practical reference for the development of GLCTI in China and promote the realization of the‘dual-carbon'target. 展开更多
关键词 green and low-carbon technology innovation(GLCTI) spatial-temporal pattern urban-type influencing factor Spatial Durbin Model(SDM) China
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MILOF-TCN:A Hierarchical Edge-Fog Framework for Monitoring Abnormal and Missing Patterns in Electric Vehicle Charging Data 认领 引用
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作者 Hwa-Young Jeong 《Computers, Materials & Continua》 SCIE EI 2026年第9期2004-2024,共21页
The rapid growth of electric vehicle(EV)charging infrastructures has introduced new challenges in monitoring abnormal load behaviors under strict latency and resource constraints.Conventional anomaly detection approac... The rapid growth of electric vehicle(EV)charging infrastructures has introduced new challenges in monitoring abnormal load behaviors under strict latency and resource constraints.Conventional anomaly detection approaches either rely on centralized processing or incur excessive false alarms,limiting their practical applicability in large-scale deployments.This paper proposes a hierarchical edge-fog anomaly detection framework that integrates lightweight edge-level filtering with a fog-level Temporal Convolutional Network(TCN)detector.The edge component suppresses non-informative patterns,while the fog layer performs temporal modeling on selectively forwarded data.This design enables controllable reduction of fog-level processing load.Under corrected end-to-end evaluation on real-world EV charging load data,the hierarchical pipeline should be interpreted as a system operating point rather than a uniformly superior detector.Relative to fog-only TCN-AE inference,the selected routing policy reduces fog workload by 34.9%and shortens average detection delay from 93.6 to 75.6 h,but increases false alarms per day from 0.88 to 7.29 and lowers F1 from 0.547 to 0.455.Sensitivity experiments over routing thresholds reveal a consistent trade-off among fog workload,alert burden,detection delay,and retained anomaly evidence.Additional routing diagnostics show that the primary source of performance degradation is information loss induced by filtering,rather than weakness of the fog detector on the forwarded subset.These findings suggest that hierarchical edge intelligence is a practical but calibration-sensitive direction for scalable anomaly monitoring in EV charging infrastructures. 展开更多
关键词 Edge computing fog computing anomaly detection electric vehicle charging time-series monitoring temporal convolutional networks missing data patterns hierarchical architecture
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