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A quantitative assessment of the state and evolution of city‒lake relationships using a symbiosis model in the Taihu Lake Basin 认领 引用
1
作者 LI Pingxing CAO Hui +1 位作者 LIU Hongguang HE Jiang 《Journal of Geographical Sciences》 SCIE CSCD 2026年第4期825-848,共24页
To promote the harmonious coexistence of cities and lakes and to achieve Sustainable Development Goals in the Taihu Lake Basin,we developed an analytical framework for city-lake symbiosis(CLS)on the basis of symbiosis... To promote the harmonious coexistence of cities and lakes and to achieve Sustainable Development Goals in the Taihu Lake Basin,we developed an analytical framework for city-lake symbiosis(CLS)on the basis of symbiosis theory.Using the Lotka-Volterra(L-V)model and a coordination degree model,we assessed the state and evolution of the CLS relationship.The findings reveal that urban development levels increased steadily from 27.36 in 1980 to 78.90 in 2020,whereas the ecological conditions of Taihu Lake initially decreased,followed by slow and fluctuating recovery.Overall,cities and Taihu Lake exhibited a“mutualism”relationship,withαandβvalues of-1.89 and-1.77,respectively,and a general upward trend in the degree of coordination over the study period.However,during the periods 1980-1998 and 2012-2016,the relationship displayed a pattern of“mutual damage”.The adverse effects of urban development accumulated gradually,in contrast to the rapid and abrupt deterioration observed in the lake.Ecological recovery in Taihu Lake progressed slowly and unevenly,stabilizing only after 2016 into a phase of sustained improvement.We recommend enhanced and coordinated efforts in ecological restoration and environmental governance to support this positive trajectory. 展开更多
关键词 human-nature relationship city‒lake symbiosis(CLS) Lotka-Volterra model degree of symbiotic coordination Taihu Lake Basin
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Enhancing quantitative structure-property relationship models by integrating complete molecular structure with deep learning 认领 引用
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作者 Bo Ouyang Dian Zhang +2 位作者 Zhe Chen Zhao-Quan Wen Zheng-Hong Luo 《ENGINEERING Chemical Engineering》 SCIE EI CAS CSCD 2026年第3期13-23,共11页
Traditional quantitative structure-property relationship(QSPR)methods rely on molecular descriptors to quantify molecular structures and establish correlations with physical properties.In this study,we propose an appr... Traditional quantitative structure-property relationship(QSPR)methods rely on molecular descriptors to quantify molecular structures and establish correlations with physical properties.In this study,we propose an approach that incorporates complete molecular structures to refine traditional QSPR methods and improve predictive accuracy.The supercritical properties used for modeling are collected from the literature.Molecular structures are optimized using density functional theory,from which molecular descriptors are derived.Both the structures and descriptors serve as inputs to the models developed in this work.Three models are constructed:a traditional artificial neural network model,a ResNet model,and a convolutional neural network(CNN)-enhanced model.Comparison with the JOBACK method shows that the CNN-enhanced model achieves higher predictive accuracy,whereas the ResNet model,which relies solely on molecular structures,suffers from pronounced overfitting. 展开更多
关键词 quantitative structure-property relationship supercritical properties artificial neural network molecular structure convolutional neural network
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Experimental techniques for qualitative and quantitative characterization of shale oil reservoir space,minerals,and fluids 认领 引用 被引量：1
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作者 Siyu Chen Zhenkai Huang +6 位作者 Guangyou Zhu Xi Li Zhiyong Chen Ruilin Wang Yue Huang Shengnan Liu Bijun Huang 《Energy Geoscience》 EI CAS CSCD 2026年第2期1-16,共16页
Characterizing shale oil reservoirs encompassing pore space,mineralogy,and fluids is fundamental to effective exploration and development.Recent advances in experimental techniques have significantly improved both the... Characterizing shale oil reservoirs encompassing pore space,mineralogy,and fluids is fundamental to effective exploration and development.Recent advances in experimental techniques have significantly improved both the qualitative and quantitative analysis of these components;however,a comprehensive systematic review is lacking.High-resolution imaging technologies,such as Scanning Electron Microscopy(SEM),Field Emission Scanning Electron Microscopy(FE-SEM),and Focused Ion Beam Scanning Electron Microscopy(FIB-SEM),enable detailed visualization of pore structures.Gas adsorption and high-pressure mercury intrusion methods provide accurate pore-scale quantification.Moreover,techniques like X-ray Diffraction(XRD),X-ray Fluorescence Spectroscopy(XRF),and Electron Probe Microanalysis(EPMA)allow precise mineral identification and compositional analysis.Confocal Scanning Laser Microscopy(CSLM),Raman Spectroscopy,Nuclear Magnetic Resonance(NMR),and Rock Pyrolysis provide insights into fluid occurrence and content within shale reservoirs.Based on a comprehensive review of existing research,this study identifies several key future directions:(1)addressing the challenges of nanopore observation in reservoir space characterization while minimizing the impact of sample preparation on pore structure;(2)improving the accuracy of quantitative mineral analysis and developing advanced new technologies for the precise measurement of complex mineral compositions;(3)enhancing the fluid quantitative evaluation of fluids by more effectively restoring subsurface geological conditions.This paper presents a current synthesis and forward-looking perspective on experimental techniques supporting shale oil exploration,aiming to guide future research and technological innovation in this field. 展开更多
关键词 Experimental technique Shale oil Reservoir space Mineral analysis Fluid characterization Qualitative and quantitative analysis
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Quantitative calibration method for the evolution of mechanical properties of gas-containing coal under mining-induced stress and microscopic failure evaluation 认领 引用
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作者 Zeqi Wang Liang Yuan +2 位作者 Bin Hu Bo Li Laisheng Huang 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2026年第3期475-497,共23页
Current quantitative characterization methods for the mechanical response and damage evolution of coal seams at different burial depths under mining-induced stress remains insufficient.To address this,this study estab... Current quantitative characterization methods for the mechanical response and damage evolution of coal seams at different burial depths under mining-induced stress remains insufficient.To address this,this study establishes a quantitative characterization model for the evolution of mechanical properties in gas-bearing coal masses at varying burial depths.It innovatively introduces a dual damage quantification technique and develops a coupled damage evolution model that comprehensively considers energy evolution,effective mining-induced stress,permeability,and a damage sensitivity coefficient,followed by extensive analysis.Key findings include:coal damage exhibits heterogeneous evolutionary characteristics under mining-induced stress;based on the theory of irreversible deformation,the proposed damage characterization equation can effectively determine the critical damage threshold of coal;the three-parameter EXP function model is more suitable for characterizing the time-dependent damage process of coal under mining-induced stress;a new characterization method for the coal brittleness evaluation index is proposed,revealing an 800 m burial depth boundary for the coal brittleness index;at the microscopic level,achieving quantitative characterization of the correlation between peak stress and the average reduction in functional groups during mining-induced failure of coal at different burial depths.Finally,the mapping relationship between laboratory experimental parameters and field monitoring indicators for early warning of coal mine dynamic disasters is established. 展开更多
关键词 Mining-induced stress Coupled damage Quantitative characterization Energy evolution
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Quantitative regulation of DOM on ferrihydrite colloids migration in saturated kaolinite and MgAl-LDH-coated sand columns 认领 引用
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作者 Lijuan Zeng Guining Lu +6 位作者 Feng Jiang Ying-Jie Zhang Xiaohu Jin Yajing Huang Xiaoyao Wang Xiaoyun Yi Zhi Dang 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第3期600-611,共12页
The adsorption of ferrihydrite colloids(Fh-NPs)on solid-phase media is the main factor determining their migration.However,most studies on colloids migration only provide qualitative descriptions.This study explored t... The adsorption of ferrihydrite colloids(Fh-NPs)on solid-phase media is the main factor determining their migration.However,most studies on colloids migration only provide qualitative descriptions.This study explored the impact and mechanisms of humic acids(HAs)and fulvic acids(FAs)on Fh-NPs migration in different saturated media via quantitative adsorption analysis.The coexistence of high HAs/FAs concentration promoted the migration of Fh-NPs in the negatively charged kaolinite-coated sand columns,but hindered migration in the positively charged MgAl-layered double hydroxides(LDH)-coated sand columns.The high HAs/FAs concentration combined with Fh-NPs reversed the surface positive charge of Fh-NPs,reducing adsorption capacity of kaolinite for Fh-NPs to 1.93/3.93 mg/g(from 20.8 mg/g without HAs/FAs)and increasing that of LDH for Fh-NPs to 31.1/30.6 mg/g(from nearly 0 mg/g without HAs/FAs).HAs/FAs could also combine with LDH to form a composite solid phase,thereby increasing the adsorption capacity of the solid phase for Fh-NPs.Furthermore,the influence of HAs on the Fh-NPs migration behavior was more significant than that of FAs due to the stronger binding interaction between HAs and Fh-NPs.Fluorescence spectroscopy combined with two-dimensional correlation spectroscopy revealed that Fh-NPs that preferentially combined with HAs/FAs caused a decrease in the ability of HAs/FAs to complex with kaolinite and LDH.The results of the present study provided a deep understanding of the migration mechanism of Fh-NPs and HAs/FAs in the soil environment,and provided scientific basis for predicting the geochemical behavior of pollutants or carbon in the soil environment. 展开更多
关键词 Ferrihydrite colloids Dissolved organic matter(DOM) Solid phases Migration Quantitative analysis
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Bi-Objective Optimization of Distribution Network Reliability Enhancement Using Quantitative Decomposition 认领 引用
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作者 Chenying Yi Yangjun Zhou +8 位作者 Wei Zhang Like Gao Hongwen Wu Yuanchao Zhou Ke Zhou Weixiang Huang Juntao Pan Shan Li Bin Feng 《Energy Engineering》 EI 2026年第8期262-276,共15页
Ensuring reliability in distribution networks is essential under increasing operational and economic constraints.Traditional planning models rely on power flow calculations,leading to high computational costs and poor... Ensuring reliability in distribution networks is essential under increasing operational and economic constraints.Traditional planning models rely on power flow calculations,leading to high computational costs and poor scalability.This study proposes a quantitative decomposition framework that establishes a direct linkage among reliability improvement measures,reliability parameters,and reliability indices,enabling fast and analytical reliability evaluation without power flow analysis.A bi-objective optimization model is developed to minimize both reliability indices(SAIDI)and investment costs,solved using Pareto-based multi-objective PSO combined with the TOPSIS method.Case studies on a 519-node distribution network demonstrate that the proposed approach achieves significant reliability improvement with superior computational efficiency,offering a practical and scalable tool for reliabilityoriented distribution planning. 展开更多
关键词 Distribution network reliability improvement measures quantitative analysis optimization decision
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A quantitative interpretation method of gas kick driven by physicsinformed neural network 认领 引用
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作者 Hong-Wei Yang Biao Wang +5 位作者 Jun Li Geng Zhang Gong-Hui Liu Jia-Hao Zhan Zhen-Yu Long Chao Wang 《Petroleum Science》 SCIE EI CAS CSCD 2026年第5期2599-2621,共23页
To address the challenges associated with predicting wellbore fluid flow behavior and gas kick rates in deep,complex formations following gas kick events,this study develops a quantitative interpretation method of gas... To address the challenges associated with predicting wellbore fluid flow behavior and gas kick rates in deep,complex formations following gas kick events,this study develops a quantitative interpretation method of gas kick driven by physics-informed neural network(PINN).The proposed method integrates a physical model of gas—liquid two-phase flow in the wellbore into the neural network by formulating it as a loss function,leveraging annulus temperature and pressure data obtained from downhole dual measurement tools.The feasibility and effectiveness of this method are evaluated through comparative analysis.The result indicates that duringgas kick occurrences,this method achieves mean relative errors of 8.49%and 9.07%for the predicted gas volume fraction and apparent gas phase velocity between the dual measurement points,respectively,and 3.76%for the bottomhole gas kick rate,without the need for mesh discretization or predefined initial conditions,demonstrating strong applicability in field scenarios.Compared to the unscented Kalman filter(UKF)and genetic algorithm(GA),this method exhibits higher prediction accuracy and stability due to its global optimization capability,overcoming the divergence issues encountered by UKF and GA during point-wise recursive predictions under noisy pressure data conditions.Integrating this method with downhole dual measurement tools can provide valuable guidance for blowout risk assessment,well-control method selection,and well-killing parameter design after a gas kick. 展开更多
关键词 Gas kick Quantitative interpretation Physics-informed neural network Downhole dual measurement tools Partial differential equation
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Quantitative Profiling of Tabular Biomedical Benchmark Datasets:A Meta-Learning Perspective for Algorithm Selection 认领 引用
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作者 Yiyan Zhang Yi Xin Qin Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第7期1291-1309,共19页
Medical data has specificity compared to other fields of data,and the description of medical data characteristics is still in a qualitative stage.This study included 293 sub-datasets of 138 independent datasets.First,... Medical data has specificity compared to other fields of data,and the description of medical data characteristics is still in a qualitative stage.This study included 293 sub-datasets of 138 independent datasets.First,data preprocessing was performed using methods such as incomplete data removal,inconsistent data normalization,and data integration.Then,the characteristics of 293 research datasets were quantified using 26 indicators in three categories:simple indicators,statistical indicators,and informational indicators.Furthermore,statistical analysis was performed on the above-mentioned quantitative characteristics,and stepwise regression and decision tree methods were used for modeling learning.The characteristics of the biological and medical datasets in the study were compared with those of other fields’datasets.By comparing the results of statistical analysis and learning modeling,the study found that the sample size of medical datasets included in the UCI database analyzed in this paper is small,most within 1000.The harmonic mean or geometric mean of continuous variables is significantly higher than the data from other fields.That is to say,the scope of the continuous variable range is large.This study uses quantitative indicators to describe the characteristics of medical datasets to avoid the decrease in credibility caused by subjective analysis,and lays a foundation for further algorithm applicability research. 展开更多
关键词 Characteristics of datasets medical data quantitative representation decision tree
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Engineering a γ-glutamyl transpeptidase-activated fluorogenic probe for quantitative visualization and imaging-guided tumor resection 认领 引用
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作者 Meng Zhao Yan Chen +8 位作者 Chenshuo Zhang Jianan Ding Qiulian Mao Yuqi Zhang Yinjia Gao Yongxiang Bai Laiqing Xie Guohua Fan Haibin Shi 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第3期577-582,共6页
Quantitative visualization of pivotal biomarkers and accurate delineation of tumor lesion boundary are highly significant to assist surgeon precisely resect the tumors and reduce the risk of recurrence.Activatable flu... Quantitative visualization of pivotal biomarkers and accurate delineation of tumor lesion boundary are highly significant to assist surgeon precisely resect the tumors and reduce the risk of recurrence.Activatable fluorescent probes hold great promise for intraoperative guidance of tumor surgery with high signal-to-background ratio(SBR).Here,we report a γ-glutamyl transpeptidase(GGT)-activated fluorogenic probe Indol-Glu for quantitative visualization of GGT and fluorescence-guided tumor resection.The fluorescence of Indol-Glu was initially“off”state but was specifically activated by GGT to produce enhanced near-infrared(NIR)fluorescence(~37-fold at 741 nm).It is also accompanied by the formation of self-assemblies in the tumor microenvironment resulting in prolonged retention in tumor tissues,which was demonstrated to be able to apply for NIR imaging-guided surgical resection of GGT-overexpressed luciferase-transfected hepatocellular carcinoma(HCC/Luc)tumor.More notably,taking advantage of the ratiometric photoacoustic signal(PA690/PA800)characteristic of Indol-Glu under the digestion of GGT,quantitative visual assessment of GGT activities in various tumor models was achieved in living mice.We believe that this research work may offer a powerful tool for precise diagnosis and surgical resection of malignant tumors. 展开更多
关键词 Activatable fluorogenic probe γ-Glutamyl transpeptidase Ratiometric photoacoustic imaging Quantitative visualization NIR imaging-guided surgery
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Quantitative correlation between solidification front steel speed and solidified shell surface temperature in a slab continuous casting mold 认领 引用
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作者 Wen-Jie Rong Yan Jiang +3 位作者 Xin-Yi Li Zhong-Qiu Liu Bao-Kuan Li Cheng-Jun Liu 《Journal of Iron and Steel Research International》 SCIE EI CSCD 2026年第4期29-42,共14页
The flow of molten steel at the solidification front in a continuous casting mold has a significant impact on slab quality.However,due to the high temperature and opacity of the mold,direct velocity measurements are e... The flow of molten steel at the solidification front in a continuous casting mold has a significant impact on slab quality.However,due to the high temperature and opacity of the mold,direct velocity measurements are extremely challenging.The functional relationship between flow speed at the solidification front and the temperature of the outer surface of the solidified shell is derived heat conduction equations.Subsequently,a coupled flow-heat transfer-solidification model for the mold is developed to numerically determine the flow speed and temperature distribution.Based on thermocouple installation positions and the impingement point location of the molten steel jet on the narrow face of the mold,33 sampling points are selected along both the narrow/wide face centerline and corresponding heights at the solidification front.Finally,the flow speed at the solidification front is fitted as a function of the outer surface temperature of solidified shell and the distance from the meniscus,with detailed analysis of its distribution characteristics. 展开更多
关键词 Continuous casting mold Solidification front steel velocity Solidified shell surface temperature Heat transfer Quantitative correlation
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Clinical study of repetitive transcranial magnetic stimulation in the rehabilitation of post-stroke depression:A Quantitative Insomnia Sleep Inventory monitoring evaluation 认领 引用
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作者 Ai-Ming Gu Chao Liu +3 位作者 Jian-Hong Chen Ru-Ya Guo Chao Liang Xing-Shi Chen 《World Journal of Psychiatry》 SCIE 2026年第3期110-117,共8页
BACKGROUND Jiaxing Hospital of Traditional Chinese Medicine introduced transcranial magnetic stimulation(TMS)technology in 2019.In practical application,it was found that different types of equipment and technical par... BACKGROUND Jiaxing Hospital of Traditional Chinese Medicine introduced transcranial magnetic stimulation(TMS)technology in 2019.In practical application,it was found that different types of equipment and technical parameters could lead to differences in therapeutic effects.Therefore,our hospital selected a Danish-made TMS device,which ranked second in the Chinese market,and conducted tests on Gu AM et al.rTMS for PSD rehab http://gffzz4205af39ffde493es9u9cobbccpnx6kkc.ffgz.tsg.suse.edu.cn/10.5498/wjp.v16.i3.1160942 March 19,2026 Volume 16 Issue 3 patients with post-stroke depression(PSD)from March 2019 to September 2023.Before the test,a plan was formulated based on the quality status before and after the inspection.Two evaluators independently controlled the quality of the plan.The repetitive TMS(rTMS)and Quantitative Insomnia Sleep Inventory(QUISI)data were separately stored and verified independently by the two evaluators.AIM To investigate the effect of rTMS and QUISI on the sleep and rehabilitation of patients with PSD.METHODS From March 2019 to December 2023,subjects who were admitted to the Department of Rehabilitation of the Jiaxing Hospital of Traditional Chinese Medicine,Shanghai Mental Health Center,and National Medical Centre for Psychiatric Disorders were enrolled.A total of 108 patients with PSD were enrolled:54 patients in the observation group and 54 in the control group.Sixty-eight normal volunteers were also included.Both the observation group and the control group received venlafaxine 150 mg/day sustained-release therapy.The observation group was given venlafaxine combined with rTMS.The control group was treated with venlafaxine combined with rTMS pseudo stimulation.The two groups underwent 42 treatment sessions over 14 weeks.The Hamilton Depression Rating Scale-17 scores were compared between the two groups before and after treatment,and the changes in QUISI were compared with healthy volunteers.RESULTS The Hamilton Depression Rating Scale-17 scores in the two groups were significantly reduced after treatment,and the improvement was more significant in the observation group(P<0.05).Before treatment,the sleep latency in the two groups of patients by QUISI was delayed compared to normal volunteers,and the sleep efficiency and maintenance rate were lower than those in normal volunteers,with statistical significance(P<0.05-0.01).After 14 weeks of treatment,the sleep latency period in the observation group QUISI shifted forward,indicating an increase in sleep efficiency and maintenance rate.The differences between the observation group and the control group were statistically significant(P<0.01).After a 3-month rehabilitation evaluation,the total effective rate of patients in the observation group was significantly higher than that in the control group(P<0.05).CONCLUSION rTMS treatment has a positive effect on PSD in clinical practice.QUISI monitoring can be used for rehabilitation assessment. 展开更多
关键词 Post-stroke depression Repetitive transcranial magnetic stimulation Quantitative Insomnia Sleep Inventory monitoring Evaluation of rehabilitation Clinical study
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Safety evaluation of rectisol process based on quantitative hazard and operability analysis 认领 引用 被引量：1
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作者 Haiyan Zhang Peirui Li +6 位作者 Zhonglin Zhang Xiaogang Hao Yuan Zhou Xiaolu Wu Jingxuan Yang Abuliti Abudulad Guoqing Guan 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2026年第2期33-44,共12页
In order to break through the limitations of the traditional hazard and operability(HAZOP)analysis,this study established a gray evaluation model based on gray theory for the riskiness ranking of deviations and semi-q... In order to break through the limitations of the traditional hazard and operability(HAZOP)analysis,this study established a gray evaluation model based on gray theory for the riskiness ranking of deviations and semi-quantitative analysis of risk levels.A quantitative HAZOP analysis combining HAZOP with Aspen Plus,Aspen Dynamics,Fault Tree Analysis(FTA),Risk Matrix and Layer of Protection Analysis(LOPA)was performed for high risk deviations.The dynamic model of the methanol washing unit in the rectisol process was established by Aspen Dynamics and the effects of different deviations on the risk indicators and operability indicators were investigated.Then,the risk of deviations was ranked according to the simulation results and the high-risk deviations were identified.Subsequently,the sensitivity analysis module of Aspen Plus software was used to calculate the fluctuationrange of highrisk deviations,whose results were imported into Aspen Dynamics to simulate and analyze the risk level of accidents,and then FTA was used to quantify the probability of accidents.Synchronizing the two to the risk matrix determined the deviations to have initial risk ratings of 10 and 15,both of which are high-risk deviations.The HAZOP quantitative analysis report is finalizedafter reducing the residual risk level of the deviation to 9(low risk)through LOPA analysis.The results of the case study showed that the method can verify the accuracy of the gray evaluation model to a certain extent,and the quantitative HAZOP analysis report is of guiding significancefor actual production. 展开更多
关键词 Quantitative HAZOP analysis Rectisol process Gray evaluation model Aspen Plus Dynamic process simulation Deviation riskiness ranking
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A NIR and ratiometric fluorescent probe for quantitative detection of SO2 derivatives in Chinese medicinal materials and bioimaging in vivo 认领 引用 被引量：1
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作者 Meitong Wu Ke Wu +7 位作者 Shumin Feng Li Xu Mi Lei Jianmei Chen Shuang Li Mian Qin Dahui Liu Guoqiang Feng 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第1期434-439,共6页
Sulfur dioxide(SO2) and its derivatives have been recognized as harmful environmental pollutants.However,they are often produced during the processing of traditional Chinese medicines,potentially compromising the q... Sulfur dioxide(SO2) and its derivatives have been recognized as harmful environmental pollutants.However,they are often produced during the processing of traditional Chinese medicines,potentially compromising the quality of these medicinal materials and contributing to various health issues.Due to a lack of effective monitoring and imaging tools,the physiological effects of excessive SO2 residues in traditional Chinese medicine remain unclear.Therefore,developing a rapid and effective tool for detecting SO2 is crucial for understanding its metabolic pathways and effects in vivo.In this study,we developed a near infrared(NIR) and ratiometric fluorescent probe,NIR-RS,which exhibits high sensitivity,selectivity,and rapid response for SO2 detection.Notably,NIR-RS accurately quantifies SO2 contents in Pinelliae rhizoma(P.rhizoma) samples,with recovery rates from 98.46 % to 102.40 %,and relative standard deviations(RSDs)< 5.0 %.For bioimaging applications,NIR-RS has low cytotoxicity and good mitochondrial-targeting ability,making it suitable for imaging exogenous and endogenous SO2 in mitochondria.Additionally,NIR-RS was successfully applied to image SO2 content of P.rhizoma samples within cells,revealing that high SO2 residue elevated mitochondria adenosine triphosphate(ATP) content,these findings reveal that P.rhizoma with excessive SO2 can affect the organism's growth mechanisms through alterations in ATP pathways.In vivo,SO2 was found to predominantly accumulate in the liver following gavage with P.rhizoma solution,with accumulation levels increasing in proportion to SO2 residue concentration.High SO2 concentrations in P.rhizoma can cause pulmonary fibrosis and gastric mucosal damage.This work provides a valuable tool for regulating SO2 content in P.rhizoma and may help researcher better understand the metabolism of SO2 derivatives and explore their physiological roles in biological systems. 展开更多
关键词 Fluorescent probe SO2derivatives metabolism Quantitative analysis Pinelliae rhizoma Fluorescent imaging
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Precursory information response and quantitative characterization of multi-component carbon-reinforced lining materials under load failure 认领 引用
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作者 WEI Jia-le YANG Ke +1 位作者 FU Qiang WU Ben-niu 《Journal of Central South University》 SCIE EI CAS CSCD 2026年第3期1280-1306,共27页
The complex stress environment during underground space reuse in deep mines often leads to significant instability in the surrounding rock-lining support structure of roadways.To address this,a multi-component carbon ... The complex stress environment during underground space reuse in deep mines often leads to significant instability in the surrounding rock-lining support structure of roadways.To address this,a multi-component carbon reinforced lining material(CGNC)was developed to improve the mechanical properties and self-sensing capabilities of the surrounding rock-lining support structure,enabling precise identification of precursor information related to surrounding rock-lining instability and failure.In this study,the failure precursor characteristics of the sample are obtained by analyzing the CGNC acoustic emission parameters,resistivity,and full-field main strain during the loading process.By combining the b-value,failure precursor resistivity,and strain monitoring,the precursor information is quantitatively characterized.Finally,a response mechanism for precursor information,based on the integration of"force acoustic-electricity-graph"is established.The results are as follows:1)The optimal content of carbon-based materials is 0.2%graphene(GPE),0.3%nano-carbon black(NCB),and 0.15%carbon nanotube(CNT),which results in an 86.7%increase in the sample's strength.The yield stress can serve as the"failure precursor"for the sample's instability.As the content increases,the"failure precursor"is delayed accordingly.2)As the stress level approaches the yield stress,the b-value decreases sharply,acoustic emission energy increases significantly,and the resistivity and main strain curves nearly synchronously reach the"inflection point",which serves as the precursor to sample failure.3)With increasing carbon-based material content,the synergistic effect of the three materials causes the failure mode of the sample to evolve from uniform single cracking and tensile failure to large-scale fracture and multi-crack tensile-shear composite failure,fundamentally explaining the modification mechanism of carbon-based materials in cement-based composites.These findings provide theoretical support for the instability failure mechanism and early warning system of CGNC. 展开更多
关键词 precursor information underground space of the mine quantitative characterization carbon-reinforced lining materials force-acoustic-electricity-graph
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Applications of quantitative 13C NMR in pharmaceutical analysis:From small molecule drugs to biopolymers 认领 引用
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作者 Qi Tang Sinan Wang +6 位作者 Xiongqi Zhai Seon Beom Kim Prabhakar Achanta Gonzalo R.Malca-Garcia Yuzo Nishizaki Yi Wang Yu Tang 《Journal of Pharmaceutical Analysis》 SCIE CAS CSCD 2026年第1期76-88,共13页
Chemical integrity is indispensable for advancing healthcare by ensuring the availability of high quality,safe,and effective pharmaceutical products.Ingredient quantification is particularly pivotal in this process.Nu... Chemical integrity is indispensable for advancing healthcare by ensuring the availability of high quality,safe,and effective pharmaceutical products.Ingredient quantification is particularly pivotal in this process.Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for both qualitative and quantitative analysis for complex systems.Compared with 1D quantitative 1H NMR(1H qNMR),quantitative13C NMR(13C qNMR)holds some unique advantages.This technique offers a broader chemical shift range and the resulting much lesser signal overlap compare to 1H NMR spectroscopy.This review summarizes relevant studies on the use of13C qNMR as a quantification technique,along with a focus on quantitative principles,influencing factors,and technical improvements of13C NMR.The review also highlights its applicability in quantifying diverse molecular structures in pharmaceutical analysis.In addition,potential of low-field NMR,artificial intelligence(AI)-driven method development,and hyphenation of NMR with other techniques for13C qNMR analysis is discussed and summarized as well.As a versatile method,13C qNMR holds great potential,and ongoing research is expected to unlock its full capabilities and expand its range of applications. 展开更多
关键词 13C qNMR Pharmaceutical analysis Quantitative analysis Complex system
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Data-driven corrosion assessment of magnesium alloys:A multi-level graph attention network for quantitative hydrogen-evolution prediction 认领 引用
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作者 Xinqian Zhao Xu Qin +6 位作者 Shouxin Xia Jiabao Long Dabiao Xia Huabao Yang Di Zhao Qinghang Wang Daolun Chen 《Journal of Magnesium and Alloys》 SCIE EI CAS CSCD 2026年第5期527-544,共18页
Magnesium(Mg)alloys are highly valued in aerospace,biomedical and other fields due to their high specific strength.However,nonuniform corrosion failure during service remains a core challenge that restricts their engi... Magnesium(Mg)alloys are highly valued in aerospace,biomedical and other fields due to their high specific strength.However,nonuniform corrosion failure during service remains a core challenge that restricts their engineering applications.Traditional corrosion kinetics models fail to accurately elucidate the cross-scale synergy mechanism between microstructure and macroscopic corrosion behavior.In this study,based on 13 kinds of Mg alloys,20 sets of 100-h hydrogen evolution curves,and characterization data from scanning electron microscopy(SEM)and electron backscatter diffraction(EBSD)information,a multi-level corrosion kinetics database was constructed,covering physicochemical parameters,micro-grain topological structures and second phase features,as well as macroscopic statistical characteristics and temporal dimension.Through machine learning algorithms,key corrosion driving factors were identified,and a multi-level graph attention network modeling framework was proposed,where the grains and grain boundaries were constructed as a graph structure,and the hierarchical interaction modeling between microstructure and corrosion kinetics was realized by combining the attention mechanism.The model has been validated in a new Mg alloy dataset for its predictive capability across compositional systems.This work provides a new computational paradigm and significantly enhances the predictability and efficiency of corrosion-resistant Mg alloy design. 展开更多
关键词 Magnesium alloy Multi-level graph attention network Quantitative hydrogen evolution prediction Microstructure-level corrosion mechanism
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Mining High-Quantitative Periodic Frequent Patterns across Multiple Sequences 认领 引用
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作者 Yan Ge Zhenzhou Zhang Chien-Ming Chen 《Computers, Materials & Continua》 SCIE EI 2026年第8期977-1000,共24页
Periodic pattern mining plays an important role in revealing recurring behavioral regularities from temporal sequence data.Most existing approaches,however,are developed for single-sequence settings and rarely account... Periodic pattern mining plays an important role in revealing recurring behavioral regularities from temporal sequence data.Most existing approaches,however,are developed for single-sequence settings and rarely account for quantitative information or sequence-level constraints when patterns recur across multiple sequences.This limits their usefulness in practical scenarios,where a pattern is expected to be not only periodic but also quantitatively significant in a sufficiently large portion of sequences.In this work,we formulate the problem of mining High-Quantitative Periodic Frequent Patterns(HQPFPS)from multi-sequence databases and propose an efficient algorithm,termed MHQPFPS.The proposed method evaluates pattern significance through a quantitative ratio within each sequence and exploits a sequence-level upper bound to effectively prune unpromising candidates during pattern growth.To support efficient evaluation,a compact list-based structure is introduced to maintain support,periodicity,and quantitative statistics,thereby avoiding repeated scans of the database.These components are combined within a depth-first exploration framework to systematically generate valid patterns while discarding those that fail to satisfy the required periodic or quantitative constraints.Experimental results on both real-world and synthetic datasets show that MHQPFPS is able to extract meaningful high-quantitative periodic patterns across multiple sequences.Moreover,the results indicate that the proposed pruning strategies substantially reduce computational cost in terms of runtime and memory consumption under a wide range of parameter settings. 展开更多
关键词 Data mining high-quantitative periodic patterns multi-sequence databases quantitative pattern mining
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Artificial intelligence in quantitative imaging of esophageal cancer:A review on radiomics,sarcopenia,and survival modeling 认领 引用
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作者 Sivan Sathish Ankita Jain +1 位作者 Kratee Sharma Karthika B 《World Journal of Gastrointestinal Oncology》 SCIE 2026年第7期25-35,共11页
Esophageal cancer remains one of the most lethal malignancies worldwide,with survival outcomes varying widely even among patients with similar clinical stages.Recent advances in artificial intelligence(AI)have enabled... Esophageal cancer remains one of the most lethal malignancies worldwide,with survival outcomes varying widely even among patients with similar clinical stages.Recent advances in artificial intelligence(AI)have enabled the extraction of quantitative imaging features,known as radiomics,from routine computed tomography and positron emission tomography/computed tomography scans,offering new opportunities for precision prognostication.At the same time,body composition metrics such as sarcopenia and visceral adiposity have emerged as important predictors of treatment tolerance and overall survival.This article summarizes current evidence on artificial intelligence-based approaches that integrate tumor radiomics and host body composition for survival modeling in esophageal cancer.It outlines methodological frameworks,model performance,and key predictors identified across studies,and discusses challenges related to data harmonization,feature reproducibility,and clinical translation.The combined use of radiomics and body composition analysis through machine learning offers a promising path toward individualized,image-based survival prediction beyond conventional staging systems. 展开更多
关键词 Esophageal cancer Artificial intelligence Radiomics Deep learning Sarcopenia Survival prediction Quantitative imaging
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Quantitative Stress Testing Using Scalable Digital Twin Simulation with MobileX Pole for Intelligent Mobile Surveillance 认领 引用
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作者 DongHwan Ku Sun Park JongWon Kim 《Computers, Materials & Continua》 SCIE EI 2026年第8期1290-1311,共22页
In future smart cities,ensuring urban safety requires data-driven decision-making through real-time monitoring tailored to dynamic,complex environments.Such surveillance relies on diverse mobile sensor devices,includi... In future smart cities,ensuring urban safety requires data-driven decision-making through real-time monitoring tailored to dynamic,complex environments.Such surveillance relies on diverse mobile sensor devices,including drones,robots,patrol vehicles,and portable sensors.However,scaling and validating these systems directly in the real world is constrained by high costs,safety risks,and limited reproducibility across operating conditions.A scalable Digital Twin(DT)model can overcome these constraints by reproducing real-world mobile surveillance in a virtual environment,enabling large-scale simulations of sensor deployment,communication scenarios,and high-density visual data processing.Nevertheless,digital twins still face well-known limitations such as the reality gap,construction costs,limited coverage of behavioral and social variables,biased learning in AI models,and the need for continuous updates.Many of these issues are expected to be mitigated in the near future as generative AI increasingly automates the construction of virtual environments and objects.Despite these advancements,the systemic resource constraints of integrating large-scale physical sensor streams with virtual rendering remain underexplored.To address this gap,this paper proposes a scalable DT framework for the quantitative stress testing of intelligent mobile surveillance systems.The proposed framework collects real-world visualization data from multiple cameras mounted on MobileX Poles,and supports quantitative stress testing in both virtual and physical environments.It systematically analyzes how computing resource usage varies with the number of smart poles and the total number of camera streams under rendering conditions,thereby quantifying the resource limits of real-world,multi-camera DT simulations. 展开更多
关键词 Quantitative stress testing scalable digital twin MobileX Pole intelligent mobile surveillance
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Quantitative flow ratio virtual pullback index predicts focal coronary artery disease identified on wire-based pullback pressure gradient 认领 引用
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作者 Zhi Hao Teoh Tom Wardill +4 位作者 Michael Zhang Joseph O’Brien Derek P Chew Brian Ko Dennis T L Wong 《World Journal of Cardiology》 2026年第4期17-25,共9页
BACKGROUND Wire-based pressure pullback gradient(PPG)is the reference method for differentiating focal from diffuse coronary artery disease(CAD).However,it requires invasive instrumentation and hyperaemia.The quantita... BACKGROUND Wire-based pressure pullback gradient(PPG)is the reference method for differentiating focal from diffuse coronary artery disease(CAD).However,it requires invasive instrumentation and hyperaemia.The quantitative flow ratio(QFR)-derived PPG[QFR virtual pullback(QVP)index]is a non-invasive alternative.AIM To evaluate the correlation between QVP index and PPG,and to explore the diagnostic performance of QVP index for identifying focal CAD.METHODS We retrospectively studied 74 patients(86 vessels)who underwent coronary angiography,fractional flow reserve(FFR),wire-based PPG,angio-based QFR and QVP index between December 2021 and October 2023.The primary analysis focused on FFR-significant lesions(FFR≤0.75,n=31),as these are clinically relevant for guiding percutaneous coronary intervention.QVP index was calculated from the maximal QFR drop over 20 mm and the length of the epicardial segment with the greatest reduction.Focal disease was defined by PPG>0.73.RESULTS QFR was strongly correlated with FFR(r=0.84,P0.73)with area under the curve of 0.73(P=0.02).A retrospectively derived threshold of QVP index>0.53 yielded 90%sensitivity and 53%specificity(P=0.04),though this cut-off was derived from the same dataset and should be regarded as hypothesis-generating.CONCLUSION QVP index correlates with PPG in FFR-significant lesions and may help to identify focal CAD patterns.However,these findings are hypothesis-generating and derived from a small,retrospective,single-centre cohort without external validation.Prospective multicentre studies are needed to validate cut-offs and determine whether QVP index provides incremental clinical value beyond existing physiological and imaging tools. 展开更多
关键词 Quantitative flow ratio Angio-based fractional flow reserve Pressure pullback gradient Non-invasive Coronary artery disease Coronary physiology
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