Prydz Bay,East Antarctica,is a critical region for studying ocean–sea ice–ice shelf interactions and their role in the global climate system.This review synthesizes the advancements in numerical modeling of physical...Prydz Bay,East Antarctica,is a critical region for studying ocean–sea ice–ice shelf interactions and their role in the global climate system.This review synthesizes the advancements in numerical modeling of physical oceanographic processes in Prydz Bay,highlighting the evolution from early one-dimensional thermodynamic models to contemporary high-resolution,three-dimensional coupled ocean–sea ice–ice shelf frameworks.We discuss key milestones in understanding processes such as frazil ice dynamics and its impact on the basal mass balance of the Amery Ice Shelf,the pathways and mechanisms of Modified Circumpolar Deep Water intrusions,and the dynamic influences of large icebergs on regional circulation.Despite significant progress,challenges remain in integrating multi-component interactions and achieving long-term,high-resolution climate projections.Future efforts should focus on developing fully coupled models that incorporate atmosphere–ocean–sea ice–ice shelf–iceberg interactions,supported by enhanced observational networks and improved computational efficiency.This review underscores the importance of continued modeling advancement to better predict the responses of Antarctic ice shelves and polar climate to global change.展开更多
Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model...Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.展开更多
This study compares the relative efficacy of the continuation task and the model-as-feedbackwriting (MAFW) task in EFL writing development. Ninety intermediate-level Chinese EFL learnerswere randomly assigned to a con...This study compares the relative efficacy of the continuation task and the model-as-feedbackwriting (MAFW) task in EFL writing development. Ninety intermediate-level Chinese EFL learnerswere randomly assigned to a continuation group, a MAFW group, and a control group, each with30 learners. A pretest and a posttest were used to gauge L2 writing development. Results showedthat the continuation task outperformed the MAFW task not only in enhancing the overall qualityof L2 writing, but also in promoting the quality of three components of L2 writing, namely, content,organization, and language. The finding has important implications for L2 writing teaching andlearning.展开更多
Advances in Alzheimer's disease(AD)research have deepened our understanding,yet the mechanisms driving its progression remain unclear.Although a range of in vivo biomarkers is now available(e.g.,measurements of am...Advances in Alzheimer's disease(AD)research have deepened our understanding,yet the mechanisms driving its progression remain unclear.Although a range of in vivo biomarkers is now available(e.g.,measurements of amyloidbeta(Aβ)and ta u accumulation-the molecular hallmarks of AD-structural magnetic resonance imaging(MRI),assessments of brain metabolism,and,more recently,blood-based markers),a definitive diagnosis of AD continues to be challenging.For example,Frisoni et al.展开更多
The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seco...The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.展开更多
By encouraging collaboration,attracting young entrepreneurs,and setting up village-invested enterprises,rural communities in Zhejiang Province are growing their income streams.“Over the past years,we have seen more a...By encouraging collaboration,attracting young entrepreneurs,and setting up village-invested enterprises,rural communities in Zhejiang Province are growing their income streams.“Over the past years,we have seen more and more tourists coming to our village,and their stay here has grown longer.Many even said they don’t want to leave,”Pan Chunlin,a resident of Yucun Village in Anji County of Huzhou City,east China’s Zhejiang Province,told China Today.Pan is the owner of the Chunlin Lodge,a bed&breakfast(B&B)which received more than 70,000 visitors last year,generating over RMB 4 million in revenue.展开更多
BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suita...BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suitable for rapid clinical application.METHODS:In this multi-center retrospective cohort study,AAS patient data from three hospitals were analyzed.The modeling cohort included data from the First Affiliated Hospital of Zhengzhou University and the People’s Hospital of Xinjiang Uygur Autonomous Region,with Peking University Third Hospital data serving as the external test set.Four machine learning algorithms—logistic regression(LR),multilayer perceptron(MLP),Gaussian naive Bayes(GNB),and random forest(RF)—were used to develop predictive models based on 34 early-accessible clinical variables.A simplifi ed model was then derived based on fi ve key variables(Stanford type,pericardial eff usion,asymmetric peripheral arterial pulsation,decreased bowel sounds,and dyspnea)via Least Absolute Shrinkage and Selection Operator(LASSO)regression to improve ED applicability.RESULTS:A total of 929 patients were included in the modeling cohort,and 210 were included in the external test set.Four machine learning models based on 34 clinical variables were developed,achieving internal and external validation AUCs of 0.85-0.90 and 0.73-0.85,respectively.The simplifi ed model incorporating fi ve key variables demonstrated internal and external validation AUCs of 0.71-0.86 and 0.75-0.78,respectively.Both models showed robust calibration and predictive stability across datasets.CONCLUSION:Both kinds of models were built based on machine learning tools,and proved to have certain prediction performance and extrapolation.展开更多
Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual pat...Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual patient responses towards different drugs.This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations.Methods:Tumor and adjacent tissues from female breast cancer patients were collected during surgery.Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models.The obtained patient-derived conditional reprogramming breast cancer(CRBC)cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres to form 3D culture models.Comparisons between 2D and 3D models were made using immunohistochemistry(tumor markers),MTS assays(cell viability),flow cytometry(apoptosis),transwell assays(migration),and Western blotting(protein expression).Drug sensitivity tests were conducted to evaluate patient-specific responses to anti-cancer agents.Results:2D and 3D culture models were successfully established using samples from eight patients.The 3D models retained histological and marker characteristics of the original tumors.Compared to 2D cultures,3D models exhibited increased apoptosis,enhanced drug resistance,elevated stem cell marker expression,and greater migration ability—features more reflective of in vivo tumor behavior.Conclusion:Patient-derived 3D CRBC models effectively mimic the in vivo tumor microenvironment and demonstrate stronger resistance to anti-cancer drugs than 2D models.These hydrogel-based models offer a cost-effective and clinically relevant platform for drug screening and personalized breast cancer treatment.展开更多
Amid the lingering chill of a Beijing spring during China’s annual Two Sessions,Zheng Wangchun strode into the lounge after finishing the morning’s group discussion.The deputy to the National People’s Congress and ...Amid the lingering chill of a Beijing spring during China’s annual Two Sessions,Zheng Wangchun strode into the lounge after finishing the morning’s group discussion.The deputy to the National People’s Congress and secretary of the CPC Gulu Village Branch,better known as Cliff Village,in Hanyuan County,Ya’an City,Sichuan Province,was still dressed in his Yi ethnic waistcoat.展开更多
The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cereb...The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.展开更多
Building reliable intent-based,task-oriented dialog systems typically requires substantial manual effort:designers must derive intents,entities,responses,and control logic from raw conversational data,then iterate unt...Building reliable intent-based,task-oriented dialog systems typically requires substantial manual effort:designers must derive intents,entities,responses,and control logic from raw conversational data,then iterate until the assistant behaves consistently.This paper investigates how far large language models(LLMs)can automate this development.In this paper,we use two reference corpora,Let’s Go(English,public transport)and MEDIA(French,hotel booking),to prompt four LLM families(GPT-4o,Claude,Gemini,Mistral Small)and generate the core specifications required by the rasa platform.These include intent sets with example utterances,entity definitions with slot mappings,response templates,and basic dialog flows.To structure this process,we introduce a model-and platform-agnostic pipelinewith two phases.The first normalizes and validates LLM-generated artifacts,enforcing crossfile consistency andmaking slot usage explicit.The second uses a lightweight dialog harness that runs scripted tests and incrementally patches failure points until conversations complete reliably.Across eight projects,all models required some targeted repairs before training.After applying our pipeline,all reached≥70%task completion(many above 84%),while NLU performance ranged from mid-0.6 to 1.0 macro-F1 depending on domain breadth.These results show that,with modest guidance,current LLMs can produce workable end-to-end dialog prototypes directly fromraw transcripts.Our main contributions are:(i)a reusable bootstrap method aligned with industry domain-specific languages(DSLs),(ii)a small set of high-impact corrective patterns,and(iii)a simple but effective harness for closed-loop refinement across conversational platforms.展开更多
This study systematically reviews the development history and key technological breakthroughs of large gas fields in the Ordos Basin,and summarizes the development models of three gas reservoir types,low-permeability ...This study systematically reviews the development history and key technological breakthroughs of large gas fields in the Ordos Basin,and summarizes the development models of three gas reservoir types,low-permeability carbonate,low-permeability sandstone and tight sandstone,as well as the progress in deep coal-rock gas development.The current challenges and future development directions are also discussed.Mature development models have been formed for the three representative types of gas reservoirs in the Ordos Basin:(1)Low-permeability carbonate reservoir development model featuring groove fine-scale characterization and three-dimensional vertical succession between Upper and Lower Paleozoic formations.(2)Low-permeability sandstone reservoir development model emphasizing horizontal well pressure-depletion production and vertical well pressure-controlled production.(3)Tight sandstone gas reservoir development model focusing on single-well productivity enhancement and well placement optimization.In deep coal-rock gas development,significant progress has been achieved in reservoir evaluation,sweet spot prediction,and geosteering of horizontal wells.The three types of reservoirs have entered the mid-to-late stages of the development,when the main challenge lies in accurately characterizing residual gas,evaluating secondary gas-bearing layers,and developing precise potential-tapping strategies.In contrast,for the early-stage development of deep coal-rock gas,continuous technological upgrades and cost reduction are essential to achieving economically viable large-scale development.Four key directions of future research and technological breakthroughs are proposed:(1)Utilizing dual-porosity(fracture-matrix)modeling techniques in low-permeability carbonate reservoirs to delineate the volume and distribution of remaining gas in secondary pay zones,supporting well pattern optimization and production enhancement of existing wells.(2)Integrating well-log and seismic data to characterize reservoir spatial distribution of successive strata,enhancing drilling success rates in low-permeability sandstone reservoirs.(3)Utilizing the advantages of horizontal wells to penetrate effective reservoirs laterally,achieving meter-scale quantification of small-scale single sand bodies in tight gas reservoirs,and applying high-resolution 3D geological models to clarify the distribution of remaining gas and guide well placement optimization.(4)Further strengthening the evaluation of deep coal-rock gas in terms of resource potential,well type and pattern,reservoir stimulation,single-well performance,and economic viability.展开更多
Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-li...Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and disease.To enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture.This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid system.This cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology testing.As a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins.Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature differentiation.Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic locations.The convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.展开更多
Based on the comprehensive analysis of data from petrology and mineralogy,well logging,seismic surveys,paleontology,and geochemistry,a detailed research was conducted on paleoenvironmental and paleoclimatic conditions...Based on the comprehensive analysis of data from petrology and mineralogy,well logging,seismic surveys,paleontology,and geochemistry,a detailed research was conducted on paleoenvironmental and paleoclimatic conditions,and modeling of the source rocks in the second member of the Eocene Wenchang Formation(Wen 2 Member)in the Northern Shunde Subsag at the southwestern margin of the Pearl River Mouth Basin.The Wen 2 Member hosts excellent,thick lacustrine source rocks with strong longitudinal heterogeneity and an average total organic carbon(TOC)content of over 4.9%.The Wen 2 Member can be divided into three units(I,II,III)from bottom to top.Unit I features excellent source rocks with Type I organic matters(average TOC of 5.9%)primarily sourced from lake organisms;Unit II hosts source rocks dominated by Type II2 organic matters(average TOC of 2.2%),which are originated from mixed sources dominated by terrestrial input.Unit III contains good to excellent source rocks dominated by Type II1 organic matters(average TOC of 4.9%),which are mainly contributed by lake organisms and partially by terrestrial input.Under the background of rapid subsidence and limited source supply during intense rifting period in the Eocene,excellent source rocks were developed in Wen 2 Member in the Northern Shunde Subsag under the coordinated control of warm and humid climate,volcanic activity,and deep-water reducing conditions.During the deposition of Unit I,the warm and humid climate and volcanic activity promoted the proliferation of lake algaes,primarily Granodiscus,resulting in high initial productivity,and deep-water reducing conditions enabled satisfactory preservation of organic matters.These factors jointly controlled the development and occurrence of excellent source rocks.During the deposition of Unit II,a transition from warm to cool and semi-arid paleoclimatic conditions led to a decrease in lake algaes and initial productivity.Additionally,enhanced terrestrial input and shallow-water,weakly oxidizing water conditions caused a significant dilution and decomposition of organic matters,degrading the quality of source rocks.During the deposition of Unit III,when the paleoclimatic conditions are cool and humid,Pediastrum and Botryococcus began to thrive,leading to an increase in productivity.Meanwhile,the reducing environment of semi-deep water facilitated the preservation of excellent source rocks,albeit slightly inferior to those in Unit I.The study results clarify the differential origins and development models of various source rocks in the Shunde Sag,offering valuable guidance for evaluating source rocks and selecting petroleum exploration targets in similar marginal sags.展开更多
The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures.However,the lack of systematic and contin...The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures.However,the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies.Thus,we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina.In this study,we showed that postnatal retinal explants undergo normal development,and exhibit a consistent structure and timeline with retinas in vivo.Initially,we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells.We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin,respectively.Ki-67-and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis,and exhibited a high degree of similarity in abundance and distribution between groups.Additionally,we used Ceh-10 homeodomain-containing homolog,glutamate-ammonia ligase(glutamine synthetase),neuronal nuclei,and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells,Müller glia,mature neurons,and microglia,respectively.The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas.Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development.The findings confirm the accuracy and credibility of this model and support its use for long-term,systematic,and continuous observation.展开更多
With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration wi...With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.展开更多
In the area of reservoir engineering,the optimization of oil and gas production is a complex task involving a myriad of interconnected decision variables shaping the production system's infrastructure.Traditionall...In the area of reservoir engineering,the optimization of oil and gas production is a complex task involving a myriad of interconnected decision variables shaping the production system's infrastructure.Traditionally,this optimization process was centered on a single objective,such as net present value,return on investment,cumulative oil production,or cumulative water production.However,the inherent complexity of reservoir exploration necessitates a departure from this single-objective approach.Mul-tiple conflicting production and economic indicators must now be considered to enable more precise and robust decision-making.In response to this challenge,researchers have embarked on a journey to explore field development optimization of multiple conflicting criteria,employing the formidable tools of multi-objective optimization algorithms.These algorithms delve into the intricate terrain of production strategy design,seeking to strike a delicate balance between the often-contrasting objectives.Over the years,a plethora of these algorithms have emerged,ranging from a priori methods to a posteriori approach,each offering unique insights and capabilities.This survey endeavors to encapsulate,catego-rize,and scrutinize these invaluable contributions to field development optimization,which grapple with the complexities of multiple conflicting objective functions.Beyond the overview of existing methodologies,we delve into the persisting challenges faced by researchers and practitioners alike.Notably,the application of multi-objective optimization techniques to production optimization is hin-dered by the resource-intensive nature of reservoir simulation,especially when confronted with inherent uncertainties.As a result of this survey,emerging opportunities have been identified that will serve as catalysts for pivotal research endeavors in the future.As intelligent and more efficient algo-rithms continue to evolve,the potential for addressing hitherto insurmountable field development optimization obstacles becomes increasingly viable.This discussion on future prospects aims to inspire critical research,guiding the way toward innovative solutions in the ever-evolving landscape of oil and gas production optimization.展开更多
The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is great...The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.展开更多
With the increasing severity of arsenic(As)pollution,quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the pr...With the increasing severity of arsenic(As)pollution,quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies.Taking the industrialintensive Jinsha River Basin as typical area,a two-dimensional hydrodynamic water quality model coupled with Soil andWater Assessment Tool(SWAT)model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution.The effects of hydro-climate change,hydropower station construction and non-point source emissions on Aswere quantified based on the coupled model.The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream.Due to the enhanced rainfall,the As concentration was significantly higher during the rainy season than the dry season.Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration,but also affected the adsorption and desorption of As in sediment.Furthermore,As concentration increased with the input of non-point source pollution,with the maximum increase about 30%,resulting that non-point sources contributed important pollutant impacts to waterways.The coupled model used in pollutant behavior analysis is generalwith high potential application to predict and mitigate water pollution.展开更多
In the era of AI,especially large models,the importance of open source has become increasingly prominent.First,open source allows innovation to avoid starting from scratch.Through iterative innovation,it promotes tech...In the era of AI,especially large models,the importance of open source has become increasingly prominent.First,open source allows innovation to avoid starting from scratch.Through iterative innovation,it promotes technical exchanges and learning globally.Second,resources required for large model R&D are difficult for a single institution to obtain.The evaluation of general large models also requires the participation of experts from various industries.Third,without open source collaboration,it is difficult to form a unified upper-layer software ecosystem.Therefore,open source has become an important cooperation mechanism to promote the development of AI and large models.There are two cases to illustrate how open source and international standards interact with each other.展开更多
基金supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant nos.SML2021SP306,SML2023SP201)the National Key R&D Program of China(Grant no.2024YFF0506603)+1 种基金the National Natural Science Foundation of China(Grant no.42576020)Guangdong Basic and Applied Basic Research Foundation,China(Grant nos.2024A1515012717,2026A1515012241).
文摘Prydz Bay,East Antarctica,is a critical region for studying ocean–sea ice–ice shelf interactions and their role in the global climate system.This review synthesizes the advancements in numerical modeling of physical oceanographic processes in Prydz Bay,highlighting the evolution from early one-dimensional thermodynamic models to contemporary high-resolution,three-dimensional coupled ocean–sea ice–ice shelf frameworks.We discuss key milestones in understanding processes such as frazil ice dynamics and its impact on the basal mass balance of the Amery Ice Shelf,the pathways and mechanisms of Modified Circumpolar Deep Water intrusions,and the dynamic influences of large icebergs on regional circulation.Despite significant progress,challenges remain in integrating multi-component interactions and achieving long-term,high-resolution climate projections.Future efforts should focus on developing fully coupled models that incorporate atmosphere–ocean–sea ice–ice shelf–iceberg interactions,supported by enhanced observational networks and improved computational efficiency.This review underscores the importance of continued modeling advancement to better predict the responses of Antarctic ice shelves and polar climate to global change.
文摘Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.
文摘This study compares the relative efficacy of the continuation task and the model-as-feedbackwriting (MAFW) task in EFL writing development. Ninety intermediate-level Chinese EFL learnerswere randomly assigned to a continuation group, a MAFW group, and a control group, each with30 learners. A pretest and a posttest were used to gauge L2 writing development. Results showedthat the continuation task outperformed the MAFW task not only in enhancing the overall qualityof L2 writing, but also in promoting the quality of three components of L2 writing, namely, content,organization, and language. The finding has important implications for L2 writing teaching andlearning.
文摘Advances in Alzheimer's disease(AD)research have deepened our understanding,yet the mechanisms driving its progression remain unclear.Although a range of in vivo biomarkers is now available(e.g.,measurements of amyloidbeta(Aβ)and ta u accumulation-the molecular hallmarks of AD-structural magnetic resonance imaging(MRI),assessments of brain metabolism,and,more recently,blood-based markers),a definitive diagnosis of AD continues to be challenging.For example,Frisoni et al.
基金supported in part by the Northeastern University’s 2024 Undergraduate Education and Teaching Reform Research Project:Innovation and Practice of Professional Course Teaching Paradigms in the Context of Digital Education.
文摘The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.
文摘By encouraging collaboration,attracting young entrepreneurs,and setting up village-invested enterprises,rural communities in Zhejiang Province are growing their income streams.“Over the past years,we have seen more and more tourists coming to our village,and their stay here has grown longer.Many even said they don’t want to leave,”Pan Chunlin,a resident of Yucun Village in Anji County of Huzhou City,east China’s Zhejiang Province,told China Today.Pan is the owner of the Chunlin Lodge,a bed&breakfast(B&B)which received more than 70,000 visitors last year,generating over RMB 4 million in revenue.
基金supported by the special fund of the National Clinical Key Specialty Construction Program[(2022)301-2305].
文摘BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suitable for rapid clinical application.METHODS:In this multi-center retrospective cohort study,AAS patient data from three hospitals were analyzed.The modeling cohort included data from the First Affiliated Hospital of Zhengzhou University and the People’s Hospital of Xinjiang Uygur Autonomous Region,with Peking University Third Hospital data serving as the external test set.Four machine learning algorithms—logistic regression(LR),multilayer perceptron(MLP),Gaussian naive Bayes(GNB),and random forest(RF)—were used to develop predictive models based on 34 early-accessible clinical variables.A simplifi ed model was then derived based on fi ve key variables(Stanford type,pericardial eff usion,asymmetric peripheral arterial pulsation,decreased bowel sounds,and dyspnea)via Least Absolute Shrinkage and Selection Operator(LASSO)regression to improve ED applicability.RESULTS:A total of 929 patients were included in the modeling cohort,and 210 were included in the external test set.Four machine learning models based on 34 clinical variables were developed,achieving internal and external validation AUCs of 0.85-0.90 and 0.73-0.85,respectively.The simplifi ed model incorporating fi ve key variables demonstrated internal and external validation AUCs of 0.71-0.86 and 0.75-0.78,respectively.Both models showed robust calibration and predictive stability across datasets.CONCLUSION:Both kinds of models were built based on machine learning tools,and proved to have certain prediction performance and extrapolation.
基金supported by the Natural Science Foundation of Guangdong Province(No.2021B1515120053)Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515140166).
文摘Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual patient responses towards different drugs.This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations.Methods:Tumor and adjacent tissues from female breast cancer patients were collected during surgery.Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models.The obtained patient-derived conditional reprogramming breast cancer(CRBC)cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres to form 3D culture models.Comparisons between 2D and 3D models were made using immunohistochemistry(tumor markers),MTS assays(cell viability),flow cytometry(apoptosis),transwell assays(migration),and Western blotting(protein expression).Drug sensitivity tests were conducted to evaluate patient-specific responses to anti-cancer agents.Results:2D and 3D culture models were successfully established using samples from eight patients.The 3D models retained histological and marker characteristics of the original tumors.Compared to 2D cultures,3D models exhibited increased apoptosis,enhanced drug resistance,elevated stem cell marker expression,and greater migration ability—features more reflective of in vivo tumor behavior.Conclusion:Patient-derived 3D CRBC models effectively mimic the in vivo tumor microenvironment and demonstrate stronger resistance to anti-cancer drugs than 2D models.These hydrogel-based models offer a cost-effective and clinically relevant platform for drug screening and personalized breast cancer treatment.
文摘Amid the lingering chill of a Beijing spring during China’s annual Two Sessions,Zheng Wangchun strode into the lounge after finishing the morning’s group discussion.The deputy to the National People’s Congress and secretary of the CPC Gulu Village Branch,better known as Cliff Village,in Hanyuan County,Ya’an City,Sichuan Province,was still dressed in his Yi ethnic waistcoat.
基金supported by the Grant PID2021-126715OB-IOO financed by MCIN/AEI/10.13039/501100011033 and"ERDFA way of making Europe"by the Grant PI22CⅢ/00055 funded by Instituto de Salud CarlosⅢ(ISCⅢ)+6 种基金the UFIECPY 398/19(PEJ2018-004965) grant to RGS funded by AEI(Spain)the UFIECPY-396/19(PEJ2018-004961)grant financed by MCIN (Spain)FI23CⅢ/00003 grant funded by ISCⅢ-PFIS Spain) to PMMthe UFIECPY 328/22 (PEJ-2021-TL/BMD-21001) grant to LM financed by CAM (Spain)the grant by CAPES (Coordination for the Improvement of Higher Education Personnel)through the PDSE program (Programa de Doutorado Sanduiche no Exterior)to VSCG financed by MEC (Brazil)
文摘The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.
基金This publication is part of the TrustBoost project,that has received funding from MICIU/AEI/10.13039/501100011033,from FEDER,UEIt is a coordinated project by a multidisciplinary team from the Universidad Politécnica de Madrid(UPM)and University of Granada(UGR),with two subprojects that address TrustBoost’s objectives:“Enhancing Trustworthiness in Conversational AI through Multimodal Affective Awareness”(Trust Boost-UPM,ref.PID2023-150584OB-C21)“Breaking the Duality of Conversational AI:Going beyond Guided Conversations While Ensuring Compliance with Domain Rules and Constraints”(Trust Boost-UGR,ref.PID2023-150584OB-C22).
文摘Building reliable intent-based,task-oriented dialog systems typically requires substantial manual effort:designers must derive intents,entities,responses,and control logic from raw conversational data,then iterate until the assistant behaves consistently.This paper investigates how far large language models(LLMs)can automate this development.In this paper,we use two reference corpora,Let’s Go(English,public transport)and MEDIA(French,hotel booking),to prompt four LLM families(GPT-4o,Claude,Gemini,Mistral Small)and generate the core specifications required by the rasa platform.These include intent sets with example utterances,entity definitions with slot mappings,response templates,and basic dialog flows.To structure this process,we introduce a model-and platform-agnostic pipelinewith two phases.The first normalizes and validates LLM-generated artifacts,enforcing crossfile consistency andmaking slot usage explicit.The second uses a lightweight dialog harness that runs scripted tests and incrementally patches failure points until conversations complete reliably.Across eight projects,all models required some targeted repairs before training.After applying our pipeline,all reached≥70%task completion(many above 84%),while NLU performance ranged from mid-0.6 to 1.0 macro-F1 depending on domain breadth.These results show that,with modest guidance,current LLMs can produce workable end-to-end dialog prototypes directly fromraw transcripts.Our main contributions are:(i)a reusable bootstrap method aligned with industry domain-specific languages(DSLs),(ii)a small set of high-impact corrective patterns,and(iii)a simple but effective harness for closed-loop refinement across conversational platforms.
文摘This study systematically reviews the development history and key technological breakthroughs of large gas fields in the Ordos Basin,and summarizes the development models of three gas reservoir types,low-permeability carbonate,low-permeability sandstone and tight sandstone,as well as the progress in deep coal-rock gas development.The current challenges and future development directions are also discussed.Mature development models have been formed for the three representative types of gas reservoirs in the Ordos Basin:(1)Low-permeability carbonate reservoir development model featuring groove fine-scale characterization and three-dimensional vertical succession between Upper and Lower Paleozoic formations.(2)Low-permeability sandstone reservoir development model emphasizing horizontal well pressure-depletion production and vertical well pressure-controlled production.(3)Tight sandstone gas reservoir development model focusing on single-well productivity enhancement and well placement optimization.In deep coal-rock gas development,significant progress has been achieved in reservoir evaluation,sweet spot prediction,and geosteering of horizontal wells.The three types of reservoirs have entered the mid-to-late stages of the development,when the main challenge lies in accurately characterizing residual gas,evaluating secondary gas-bearing layers,and developing precise potential-tapping strategies.In contrast,for the early-stage development of deep coal-rock gas,continuous technological upgrades and cost reduction are essential to achieving economically viable large-scale development.Four key directions of future research and technological breakthroughs are proposed:(1)Utilizing dual-porosity(fracture-matrix)modeling techniques in low-permeability carbonate reservoirs to delineate the volume and distribution of remaining gas in secondary pay zones,supporting well pattern optimization and production enhancement of existing wells.(2)Integrating well-log and seismic data to characterize reservoir spatial distribution of successive strata,enhancing drilling success rates in low-permeability sandstone reservoirs.(3)Utilizing the advantages of horizontal wells to penetrate effective reservoirs laterally,achieving meter-scale quantification of small-scale single sand bodies in tight gas reservoirs,and applying high-resolution 3D geological models to clarify the distribution of remaining gas and guide well placement optimization.(4)Further strengthening the evaluation of deep coal-rock gas in terms of resource potential,well type and pattern,reservoir stimulation,single-well performance,and economic viability.
基金supported by the National Key R&D Program of China,No.2019YFA0110300(to ZG)the National Natural Science Foundation of China,Nos.81773302(to YF),32070862(to ZG).
文摘Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and disease.To enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture.This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid system.This cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology testing.As a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins.Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature differentiation.Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic locations.The convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.
基金Supported by the Research Project of China National Offshore Oil Corporation(SCKY-2023-HN-3)。
文摘Based on the comprehensive analysis of data from petrology and mineralogy,well logging,seismic surveys,paleontology,and geochemistry,a detailed research was conducted on paleoenvironmental and paleoclimatic conditions,and modeling of the source rocks in the second member of the Eocene Wenchang Formation(Wen 2 Member)in the Northern Shunde Subsag at the southwestern margin of the Pearl River Mouth Basin.The Wen 2 Member hosts excellent,thick lacustrine source rocks with strong longitudinal heterogeneity and an average total organic carbon(TOC)content of over 4.9%.The Wen 2 Member can be divided into three units(I,II,III)from bottom to top.Unit I features excellent source rocks with Type I organic matters(average TOC of 5.9%)primarily sourced from lake organisms;Unit II hosts source rocks dominated by Type II2 organic matters(average TOC of 2.2%),which are originated from mixed sources dominated by terrestrial input.Unit III contains good to excellent source rocks dominated by Type II1 organic matters(average TOC of 4.9%),which are mainly contributed by lake organisms and partially by terrestrial input.Under the background of rapid subsidence and limited source supply during intense rifting period in the Eocene,excellent source rocks were developed in Wen 2 Member in the Northern Shunde Subsag under the coordinated control of warm and humid climate,volcanic activity,and deep-water reducing conditions.During the deposition of Unit I,the warm and humid climate and volcanic activity promoted the proliferation of lake algaes,primarily Granodiscus,resulting in high initial productivity,and deep-water reducing conditions enabled satisfactory preservation of organic matters.These factors jointly controlled the development and occurrence of excellent source rocks.During the deposition of Unit II,a transition from warm to cool and semi-arid paleoclimatic conditions led to a decrease in lake algaes and initial productivity.Additionally,enhanced terrestrial input and shallow-water,weakly oxidizing water conditions caused a significant dilution and decomposition of organic matters,degrading the quality of source rocks.During the deposition of Unit III,when the paleoclimatic conditions are cool and humid,Pediastrum and Botryococcus began to thrive,leading to an increase in productivity.Meanwhile,the reducing environment of semi-deep water facilitated the preservation of excellent source rocks,albeit slightly inferior to those in Unit I.The study results clarify the differential origins and development models of various source rocks in the Shunde Sag,offering valuable guidance for evaluating source rocks and selecting petroleum exploration targets in similar marginal sags.
基金supported by the National Natural Science Foundation of China,Nos.81901156(to ZZ),82271200(to ZZ),82171308(to XC)the Fundamental Research Funds for the Central Universities,No.xzy012022035(to ZZ)+1 种基金the Natural Science Foundation of Shaanxi Province,Nos.2021JM-261(to QK),2023-YBSF-303(to ZZ)Traditional Chinese Medicine Project of Shaanxi Province,No.2019-ZZ-JC047(to QK)。
文摘The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures.However,the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies.Thus,we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina.In this study,we showed that postnatal retinal explants undergo normal development,and exhibit a consistent structure and timeline with retinas in vivo.Initially,we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells.We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin,respectively.Ki-67-and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis,and exhibited a high degree of similarity in abundance and distribution between groups.Additionally,we used Ceh-10 homeodomain-containing homolog,glutamate-ammonia ligase(glutamine synthetase),neuronal nuclei,and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells,Müller glia,mature neurons,and microglia,respectively.The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas.Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development.The findings confirm the accuracy and credibility of this model and support its use for long-term,systematic,and continuous observation.
基金Under the auspices of National Natural Science Foundation of China(No.42330510)。
文摘With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.
基金the support of EPIC - Energy Production Innovation Center, hosted by the University of Campinas (UNICAMP) and sponsored by Equinor Brazil and FAPESP - Sao Paulo Research Foundation (2021/04878- 7 and 2017/15736-3)financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nível Superior Brasil (CAPES) - Financing Code 001
文摘In the area of reservoir engineering,the optimization of oil and gas production is a complex task involving a myriad of interconnected decision variables shaping the production system's infrastructure.Traditionally,this optimization process was centered on a single objective,such as net present value,return on investment,cumulative oil production,or cumulative water production.However,the inherent complexity of reservoir exploration necessitates a departure from this single-objective approach.Mul-tiple conflicting production and economic indicators must now be considered to enable more precise and robust decision-making.In response to this challenge,researchers have embarked on a journey to explore field development optimization of multiple conflicting criteria,employing the formidable tools of multi-objective optimization algorithms.These algorithms delve into the intricate terrain of production strategy design,seeking to strike a delicate balance between the often-contrasting objectives.Over the years,a plethora of these algorithms have emerged,ranging from a priori methods to a posteriori approach,each offering unique insights and capabilities.This survey endeavors to encapsulate,catego-rize,and scrutinize these invaluable contributions to field development optimization,which grapple with the complexities of multiple conflicting objective functions.Beyond the overview of existing methodologies,we delve into the persisting challenges faced by researchers and practitioners alike.Notably,the application of multi-objective optimization techniques to production optimization is hin-dered by the resource-intensive nature of reservoir simulation,especially when confronted with inherent uncertainties.As a result of this survey,emerging opportunities have been identified that will serve as catalysts for pivotal research endeavors in the future.As intelligent and more efficient algo-rithms continue to evolve,the potential for addressing hitherto insurmountable field development optimization obstacles becomes increasingly viable.This discussion on future prospects aims to inspire critical research,guiding the way toward innovative solutions in the ever-evolving landscape of oil and gas production optimization.
基金supported and financed by Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology (No.2024yjrc96)Anhui Provincial University Excellent Research and Innovation Team Support Project (No.2022AH010053)+2 种基金National Key Research and Development Program of China (Nos.2023YFC2907602 and 2022YFF1303302)Anhui Provincial Major Science and Technology Project (No.202203a07020011)Open Foundation of Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining (No.EC2023020)。
文摘The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.
基金supported by the National Key Research and Development Program of China(No.2017YFC1502504)the National Natural Science Foundation of China(No.41877531).
文摘With the increasing severity of arsenic(As)pollution,quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies.Taking the industrialintensive Jinsha River Basin as typical area,a two-dimensional hydrodynamic water quality model coupled with Soil andWater Assessment Tool(SWAT)model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution.The effects of hydro-climate change,hydropower station construction and non-point source emissions on Aswere quantified based on the coupled model.The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream.Due to the enhanced rainfall,the As concentration was significantly higher during the rainy season than the dry season.Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration,but also affected the adsorption and desorption of As in sediment.Furthermore,As concentration increased with the input of non-point source pollution,with the maximum increase about 30%,resulting that non-point sources contributed important pollutant impacts to waterways.The coupled model used in pollutant behavior analysis is generalwith high potential application to predict and mitigate water pollution.
文摘In the era of AI,especially large models,the importance of open source has become increasingly prominent.First,open source allows innovation to avoid starting from scratch.Through iterative innovation,it promotes technical exchanges and learning globally.Second,resources required for large model R&D are difficult for a single institution to obtain.The evaluation of general large models also requires the participation of experts from various industries.Third,without open source collaboration,it is difficult to form a unified upper-layer software ecosystem.Therefore,open source has become an important cooperation mechanism to promote the development of AI and large models.There are two cases to illustrate how open source and international standards interact with each other.
