Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable,the paper explores a data-driven adaptive iterative learning control(DDAILC)strategy that interacts with ...Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable,the paper explores a data-driven adaptive iterative learning control(DDAILC)strategy that interacts with the pulse response iterative correction(PRIC).The mechanism is to formulate the correction performance index as a linear summation of the quadratic correction error of the pulse response and the quadratic tracking error.The correction algorithm of the pulse response arrives and the correction error goes down in a monotonic way.It also discusses the conditional relationship between the declining rate of the correction error and the correction ratio.A DDAILC algorithm is designed by means of substituting the exact pulse response of the gain-optimized iterative learning control(GOILC)with its approximated one updated in the correction algorithm.The convergences regarding tracking error and correction error are obtained monotonically.Finally,numerical simulation verifies the validity and effectiveness.展开更多
In this paper,we study the uniqueness of positive solutions to the following semilinear equations{-Δu=λ|x|^(α)ue^(u^(2)),in B_(1),u=0,onδB_(1)ueu2;in B_(1);u=0;on@B_(1);whereλ>0,α>-2;B_(1)denotes the unit ...In this paper,we study the uniqueness of positive solutions to the following semilinear equations{-Δu=λ|x|^(α)ue^(u^(2)),in B_(1),u=0,onδB_(1)ueu2;in B_(1);u=0;on@B_(1);whereλ>0,α>-2;B_(1)denotes the unit disk in R^(2):By delicate and relatively complicated computation of radial solutions to the above equation and the asymptotic expansion of solutions near the boundary of B_(1),the uniqueness of positive solutions is obtained.The results of this paper extend the uniqueness result for the semilinear equation with critical exponential growth in CHEN et al.(2022)to the case that includes a Henon term.展开更多
This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis f...This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis framework for the Chengdu real estate market.By using the Adaptive Neuro-Fuzzy Inference System(ANFIS)prediction model,spatial GIS(Geographic Information System analysis)analysis,and interactive dashboards,this study reveals market differentiation,policy impacts,and changes in demand structure,thereby providing decision support for the government,enterprises,and homebuyers.展开更多
To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance dat...To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.展开更多
Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations a...Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations and lack prior knowledge of model parameters,which is essential for Bayesian parameter inversion to enhance accuracy and reduce uncertainty.This study introduces a datadriven approach to establishing prior knowledge of earth-rockfill dams.Driving factors are utilized to determine the potential range of model parameters,and settlement changes within this range are calculated.The results are iteratively compared with actual monitoring data until the calculated range encompasses the observed data,thereby providing prior knowledge of the model parameters.The proposed method is applied to the right-bank earth-rockfilldam of Danjiangkou.Employing a Gibbs sample size of 30,000,the proposed method effectively calibrates the prior knowledge of the wetting model parameters,achieving a root mean square error(RMSE)of 5.18 mm for the settlement predictions.By comparison,the use of non-informative priors with sample sizes of 30,000 and 50,000 results in significantly larger RMSE values of 11.97 mm and 16.07 mm,respectively.Furthermore,the computational efficiencyof the proposed method is demonstrated by an inversion computation time of 902 s for 30,000 samples,which is notably shorter than the 1026 s and 1558 s required for noninformative priors with 30,000 and 50,000 samples,respectively.These findingsunderscore the superior performance of the proposed approach in terms of both prediction accuracy and computational efficiency.These results demonstrate that the proposed method not only improves the predictive accuracy but also enhances the computational efficiency,enabling optimal parameter identificationwith reduced computational effort.This approach provides a robust and efficientframework for advancing dam safety assessments.展开更多
Soil organic carbon(SOC)dynamics significantly influence ecosystem carbon source-sink balance,particularly in agroecosystems.However,uncertainty remains regarding optimal land use types for maximizing farmland carbon ...Soil organic carbon(SOC)dynamics significantly influence ecosystem carbon source-sink balance,particularly in agroecosystems.However,uncertainty remains regarding optimal land use types for maximizing farmland carbon storage across different soil types,and identifying effective land management practices for enhanced carbon accumulation is essential for reducing agricultural emissions and strengthening carbon sinks.This study examined SOC variations in eastern Yunnan’s subtropical highlands(2,132 sites),analyzing topsoil(0–20 cm)across five land uses(dryland,irrigated land,forestland,grassland and plantation)of five soil types(red,yellow,yellowbrown,brown,purple).The investigation explored relationships between SOC and edaphic factors(26 elements)to determine SOC influencing factors.The study area demonstrated a mean SOC content of 27.78 g kg^(–1),with distinct spatial heterogeneity characterized by lower values in the southwestern sector and higher concentrations in the northeastern region.Brown soils displayed the highest SOC content(P<0.05),followed by yellow-brown then red,yellow,and purple soils.Irrigation significantly enhanced SOC storage,particularly in brown soils where irrigated land contained 2.2-,2.4-,and 1.6-times higher SOC than forestland,grassland,and dryland,respectively.Similar irrigation benefits occurred in purple,yellow,and yellow-brown soils,indicating moisture limitation as the primary SOC constraint.Notably,SOC exhibited strong positive correlations with nitrogen,sulfur,and selenium.Nitrogen fertilization demonstrated dual benefits:enhancing SOC sequestration and promoting Se enrichment in crops,potentially supporting specialty agriculture.Although land use impacts on SOC varied across soil types(P>0.05),irrigation consistently emerged as the optimal management for carbon sink enhancement.These findings suggest that targeted water management could effectively reduce farmland carbon emissions in moisture-limited subtropical highlands.Strategic nitrogen application offers co-benefits for soil fertility and selenium biofortification,providing practical pathways for climate-smart agriculture in similar ecoregions.展开更多
Type 1 diabetes(T1D)is defined by autoimmune-mediated destruction of the insulin-producing pancreatic β-cells.Impaired insulin secretion due to β-cell apoptosis and islet massloss is the main feature of T1D[1].Curre...Type 1 diabetes(T1D)is defined by autoimmune-mediated destruction of the insulin-producing pancreatic β-cells.Impaired insulin secretion due to β-cell apoptosis and islet massloss is the main feature of T1D[1].Current therapeutic strategies for T1D are mainly through subcutaneous administration of insulin or islet/pancreas transplantation.展开更多
[Objectives]To analyze the clinical characteristics,distribution of traditional Chinese medicine(TCM)syndrome types,spectrum of comorbidities,and complications among inpatients with gout.[Methods]Data from 592 gout pa...[Objectives]To analyze the clinical characteristics,distribution of traditional Chinese medicine(TCM)syndrome types,spectrum of comorbidities,and complications among inpatients with gout.[Methods]Data from 592 gout patients admitted in the Department of Rheumatology at Wuxi Traditional Chinese Medicine Hospital between January 2018 and December 2024 were retrospectively collected.The data collected encompassed patient gender,age,TCM syndrome types,underlying comorbidities,infection status,and major complications,including renal insufficiency,interstitial lung disease,and osteoporosis.Descriptive statistical analyses were subsequently performed.[Results]Among the 592 inpatients,80.75%were male and 19.25%were female.A total of 94.76%patients had at least one underlying condition,with hypertension(80.74%),cerebral infarction(29.59%),heart disease(24.24%),and diabetes(21.56%)being the most prevalent.The primary TCM syndrome types identified were damp-heat obstruction syndrome(63.51%)and phlegm-stasis obstruction syndrome(21.11%).During hospitalization,20.94%of patients experienced concurrent infections,predominantly pulmonary infections(38.10%).The principal complications observed included renal insufficiency(32.09%),interstitial lung disease(18.75%),and osteoporosis(9.29%).[Conclusions]Inpatients diagnosed with gout often present with complex conditions and a high burden of comorbidities,predominantly cardiovascular and cerebrovascular diseases,as well as metabolic disorders.Additionally,there is a high incidence of infections and renal insufficiency within this population.TCM syndrome types in these patients are primarily characterized by damp-heat obstruction.In clinical practice,a comprehensive management approach that incorporates multidisciplinary collaboration is recommended.Alongside the control of uric acid levels and joint inflammation,proactive screening and management of comorbidities and related complications are essential.展开更多
Soil fertility and forest structure influence tree carbon stocks.However,it remains unclear how tree mycorrhizal types affect these relationships.This study addressed the question of how aboveground and belowground tr...Soil fertility and forest structure influence tree carbon stocks.However,it remains unclear how tree mycorrhizal types affect these relationships.This study addressed the question of how aboveground and belowground tree carbon stocks in soils with different mycorrhizal types are affected by soil fertility and forest structure.Tree demographic data were used from a 21.12-ha study area collected over a ten-year period(2009-2019),covering 43species of woody plants and more than 50,000 individuals.Relationships between tree carbon stock,soil fertility and forest structure(stand density,diameter variation,species diversity and spatial distribution)were examined,as well as whether these relationships differed between arbuscular mycorrhiza and ectomycorrhizal mycorrhiza groups in a typical temperate conifer and broad-leaved mixed forest.We found that total tree carbon stock was positively impacted by variations in stand density and tree diameter but negatively influenced by soil fertility,tree species diversity and uniform angle index.Soil fertility promoted carbon stock of trees associated with arbuscular mycorrhiza(AM)but inhibited the carbon stock of trees with ectomycorrhizal mycorrhiza fungi(EcM).Carbon stock of AM trees was mainly influenced by soil fertility,while carbon stock of EcM trees was influenced by stand density.Our findings show that mycorrhizae types mediate the impact of stand structure and soil fertility on tree carbon stocks and provides new evidence on how forest tree carbon stocks may be enhanced based on the types of mycorrhizal associations.Tree species with different mycorrhizal types can be managed in different ways.展开更多
This paper develops a residual-based adaptive refinement physics-informed neural networks(RAR-PINNs)method for solving the Gross–Pitaevskii(GP)equation and Hirota equation,two paradigmatic nonlinear partial different...This paper develops a residual-based adaptive refinement physics-informed neural networks(RAR-PINNs)method for solving the Gross–Pitaevskii(GP)equation and Hirota equation,two paradigmatic nonlinear partial differential equations(PDEs)governing quantum condensates and optical rogue waves,respectively.The key innovation lies in the adaptive sampling strategy that dynamically allocates computational resources to regions with large PDE residuals,addressing critical limitations of conventional PINNs in handling:(1)Strong nonlinearities(|u|^(2)u terms)in the GP equation;(2)High-order derivatives(u_(xxx))in the Hirota equation;(3)Multi-scale solution structures.Through rigorous numerical experiments,we demonstrate that RAR-PINNs achieve superior accuracy[relative L^(2)errors of O(10^(−3))]and computational efficiency(faster than standard PINNs)for both equations.The method successfully captures:(1)Bright solitons in the GP equation;(2)First-and second-order rogue waves in the Hirota equation.The RAR adaptive sampling method demonstrates particularly remarkable effectiveness in solving steep gradient problems.Compared with uniform sampling methods,the errors of simulation results are reduced by two orders of magnitude.This study establishes a general framework for data-driven solutions of high-order nonlinear PDEs with complex solution structures.展开更多
Insight into the carbon turnover in soil aggregates and density fractions is essential for reducing the uncertainty in estimating carbon pools on the Tibetan Plateau,and how they vary with land use type is unclear.In ...Insight into the carbon turnover in soil aggregates and density fractions is essential for reducing the uncertainty in estimating carbon pools on the Tibetan Plateau,and how they vary with land use type is unclear.In this study,the effect of land use type on carbon storage and fractionation was quantified based on organic carbon and its ^(13)C abundance at the microscale of soil aggregates and density fractions in Tibetan alpine ecosystems.The sequence of soil aggregate destruction in the land use types of plantation(13.1%)<shrubland(32.7%)<grassland(47.9%)<farmland(61.8%)shows that plantations strengthen the soil structure.Plantation land had a greater contribution of light fraction organic carbon(28.3%)but a lower contribution of mineral-associated organic carbon(40.6%)to the carbon stock compared to farmland(13.5 and 70.3%).Interestingly,plantation land enhanced the aggregational differentiation of organic carbon and ^(13)C in each density fraction,whereas no such phenomenon existed in the soil organic carbon.Carbon isotope analyses revealed that carbon transfer in the plantation land occurred from the light fraction in macroaggregates(–24.9‰)to the mineral-associated fraction in microaggregates(–19.9‰).When compared to the other three land use types,the low transferability of carbon in aggregates and density fractions in plantation land provides a stable carbon pool for the Tibetan Plateau.This study shows that plantations can mitigate global climate change by slowing carbon transfer and increasing carbon storage at the microscale of aggregates and density fractions in alpine regions.展开更多
The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and e...The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.展开更多
AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).MET...AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.展开更多
Interfacial superconductivity(IS)has been a topic of intense interest in condensed matter physics,due to its unique properties and exotic photoelectrical performance.However,there are few reports about IS systems cons...Interfacial superconductivity(IS)has been a topic of intense interest in condensed matter physics,due to its unique properties and exotic photoelectrical performance.However,there are few reports about IS systems consisting of two insulators.Here,motivated by the emergence of an insulator-metal transition in type-Ⅲ heterostructures and the superconductivity in some“special”two-dimensional(2D)semiconductors via electron doping,we predict that the 2D heterostructure SnSe_(2)/PtTe_(2) is a model system for realizing IS by using firstprinciples calculations.Our results show that due to slight but crucial interlayer charge transfer,SnSe_(2)/PtTe_(2) turns to be a type-Ⅲ heterostructure with metallic properties and shows a superconducting transition with the critical temperature(T_(c))of 3.73 K.Similar to the enhanced electron–phonon coupling(EPC)in the electrondoped SnSe_(2) monolayer,the IS in the SnSe_(2)/PtTe_(2) heterostructure mainly originates from the metallized SnSe_(2) layer.Furthermore,we find that its superconductivity is sensitive to tensile lattice strain,forming a domeshaped superconducting phase diagram.Remarkably,at 7%biaxial tensile strain,the superconducting T_(c) can increase more than twofold(8.80 K),resulting from softened acoustic phonons at the𝑀point and enhanced EPC strength.Our study provides a concrete example for realizing IS in type-Ⅲ heterostructures,which waits for future experimental verification.展开更多
Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders...Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.展开更多
Background:To determine whether initiating a glucagon-like peptide-1 receptor agonist(GLP-1 RA)within 3 months of type 2 diabetes(T2DM)diagnosis alters the subsequent risk of overall and site-specific cancer and wheth...Background:To determine whether initiating a glucagon-like peptide-1 receptor agonist(GLP-1 RA)within 3 months of type 2 diabetes(T2DM)diagnosis alters the subsequent risk of overall and site-specific cancer and whether this association differs by baseline body-mass index(BMI).Methods:This retrospective cohort study used electronic health records from the TriNetX U.S.research network.Adults aged 20 years or older diagnosed with T2DM between 2016 and 2024 were included if they received any hypoglycemic agents within 3 months before and after diagnosis.Following 1:1 propensity score matching,both the GLP-1 RA user and non-user groups included 183,264 patients.The study outcome was defined as a diagnosis of malignant neoplasms.Hazard ratios(HRs)for overall and site-specific cancer risk were estimated using Cox proportional hazards models.Kaplan–Meier analysis and stratified analysis by BMI were performed.Results:Early GLP-1 RA use demonstrated a modest but significant association with reduced overall cancer risk(HR 0.93;95%CI:0.90–0.96).Reduced risks were noted for cancers of the digestive(HR 0.81),respiratory(HR 0.66),and female genital(HR 0.87)systems.In stratified analysis,benefits were more pronounced in patients with BMI≥30,particularly for pancreatic and colorectal cancers.Conclusion:Early initiation of GLP-1 receptor agonists in patients with diagnosed T2DM was associated with a modest reduction in overall cancer risk,particularly among individuals with obesity.These findings highlight the dual metabolic and oncologic value of prompt GLP-1 RA therapy.展开更多
Background:One of the first hundred traditional Chinese medicines(TCM)formulas administered in China,Qianghuo Shengshi Decoction(QSD)has a positive clinical and therapeutic impact on rheumatoid arthritis(RA).Even so,t...Background:One of the first hundred traditional Chinese medicines(TCM)formulas administered in China,Qianghuo Shengshi Decoction(QSD)has a positive clinical and therapeutic impact on rheumatoid arthritis(RA).Even so,there is still not enough knowledge on the active ingredients and possible ways that QSDs might work to treat RA.This study systematically investigated the active ingredients and mechanisms of action of QSD for treating wind-cold-dampness arthralgia type RA.Methods:UHPLC-QE-MS and network pharmacology techniques were employed to predict the potential active constituents,targets,and associated signalling pathways.Then,the therapeutic effect of QSD was examined using a wind-cold-dampness arthralgia paralytic RA rat model.Finally,the complex mechanism was comprehensively elucidated by integrating transcriptomics and network pharmacology.The above mechanisms were also verified by molecular docking,immunohistochemistry and Western blot.Results:UHPLC-QE-MS and network pharmacology analysis revealed that ferulic acid,imperatorin,magnolol,quercetin,and scopoletin could be the primary constituents in QSD responsible for its anti-RA effects.Animal experiments showed that QSD can significantly inhibit rat joint swelling degree,decrease the content of serum rheumatoid factor(RF),interleukin(IL)-1β,tumor necrosis factor-alpha(TNF-α),IL-6,and anti-citrullinated protein antibodies(ACPA),and increase the content of IL-4,IL-10 to relieve the clinical symptoms of wind-cold-dampness arthralgia type RA.The mechanistic study showed that QSD may effectively inhibit rat synovial hyperplasia via promoting autophagy and apoptosis of synovial cells by regulating the PI3K/Akt/mTOR signalling pathway.Conclusion:This study identifies key active ingredients in QSD and elucidates its potential mechanism for treating wind-cold-dampness arthralgia type RA,providing a basis for the clinical application of QSD.展开更多
Concerns about the long-term safety and efficacy of glibenclamide(GLIB),a type 2 diabetes mellitus(T2DM)treatment,have been reported[1].Recent evidence indicates the gut microbiota composition significantly affects ho...Concerns about the long-term safety and efficacy of glibenclamide(GLIB),a type 2 diabetes mellitus(T2DM)treatment,have been reported[1].Recent evidence indicates the gut microbiota composition significantly affects host glucose metabolism and drugbioavailability,increasingthe efficacy of T2DM therapy[2].In this context,probiotic-drug coadministration,an emerging adjunct approach for treating metabolic diseases,improves therapeutic outcomes and ameliorates side effects[3].展开更多
With the efficient and intelligent development of computer-based big data processing,applying machine learning methods to the processing and interpretation of logging data in the field of geophysical well logging has ...With the efficient and intelligent development of computer-based big data processing,applying machine learning methods to the processing and interpretation of logging data in the field of geophysical well logging has broad potential for improving production efficiency.Currently,the Jiyuan Oilfield in the Ordos Basin relies mainly on manual reprocessing and interpretation of old well logging data to identify different fluid types in low-contrast reservoirs,guiding subsequent production work.This study uses well logging data from the Chang 1 reservoir,partitioning the dataset based on individual wells for model training and testing.A deep learning model for intelligent reservoir fluid identification was constructed by incorporating the focal loss function.Comparative validations with five other models,including logistic regression(LR),naive Bayes(NB),gradient boosting decision trees(GBDT),random forest(RF),and support vector machine(SVM),show that this model demonstrates superior identification performance and significantly improves the accuracy of identifying oil-bearing fluids.Mutual information analysis reveals the model's differential dependency on various logging parameters for reservoir fluid identification.This model provides important references and a basis for conducting regional studies and revisiting old wells,demonstrating practical value that can be widely applied.展开更多
基金supported by the National Natural Science Foundation of China(619733380).
文摘Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable,the paper explores a data-driven adaptive iterative learning control(DDAILC)strategy that interacts with the pulse response iterative correction(PRIC).The mechanism is to formulate the correction performance index as a linear summation of the quadratic correction error of the pulse response and the quadratic tracking error.The correction algorithm of the pulse response arrives and the correction error goes down in a monotonic way.It also discusses the conditional relationship between the declining rate of the correction error and the correction ratio.A DDAILC algorithm is designed by means of substituting the exact pulse response of the gain-optimized iterative learning control(GOILC)with its approximated one updated in the correction algorithm.The convergences regarding tracking error and correction error are obtained monotonically.Finally,numerical simulation verifies the validity and effectiveness.
基金Supported by the Natural Science Foundation of China(12571122,12061010)。
文摘In this paper,we study the uniqueness of positive solutions to the following semilinear equations{-Δu=λ|x|^(α)ue^(u^(2)),in B_(1),u=0,onδB_(1)ueu2;in B_(1);u=0;on@B_(1);whereλ>0,α>-2;B_(1)denotes the unit disk in R^(2):By delicate and relatively complicated computation of radial solutions to the above equation and the asymptotic expansion of solutions near the boundary of B_(1),the uniqueness of positive solutions is obtained.The results of this paper extend the uniqueness result for the semilinear equation with critical exponential growth in CHEN et al.(2022)to the case that includes a Henon term.
基金Chengdu City Philosophy and Social Sciences Research Center“artificial intelligence+urban communication”theory and Application Research Center Project“Chengdu real estate vertical market public opinion data visualization research”(Project No.RZCC2025017).
文摘This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis framework for the Chengdu real estate market.By using the Adaptive Neuro-Fuzzy Inference System(ANFIS)prediction model,spatial GIS(Geographic Information System analysis)analysis,and interactive dashboards,this study reveals market differentiation,policy impacts,and changes in demand structure,thereby providing decision support for the government,enterprises,and homebuyers.
基金supported in part by the National Natural Science Foundation of China,Grant/Award Number:62003267the Key Research and Development Program of Shaanxi Province,Grant/Award Number:2023-GHZD-33Open Project of the State Key Laboratory of Intelligent Game,Grant/Award Number:ZBKF-23-05。
文摘To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3209504)Natural Science Foundation of Wuhan(Grant No.2024040801020271)the Fundamental Research Funds for Central Public Welfare Research Institutes(Grant No.CKSF2025718/YT).
文摘Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations and lack prior knowledge of model parameters,which is essential for Bayesian parameter inversion to enhance accuracy and reduce uncertainty.This study introduces a datadriven approach to establishing prior knowledge of earth-rockfill dams.Driving factors are utilized to determine the potential range of model parameters,and settlement changes within this range are calculated.The results are iteratively compared with actual monitoring data until the calculated range encompasses the observed data,thereby providing prior knowledge of the model parameters.The proposed method is applied to the right-bank earth-rockfilldam of Danjiangkou.Employing a Gibbs sample size of 30,000,the proposed method effectively calibrates the prior knowledge of the wetting model parameters,achieving a root mean square error(RMSE)of 5.18 mm for the settlement predictions.By comparison,the use of non-informative priors with sample sizes of 30,000 and 50,000 results in significantly larger RMSE values of 11.97 mm and 16.07 mm,respectively.Furthermore,the computational efficiencyof the proposed method is demonstrated by an inversion computation time of 902 s for 30,000 samples,which is notably shorter than the 1026 s and 1558 s required for noninformative priors with 30,000 and 50,000 samples,respectively.These findingsunderscore the superior performance of the proposed approach in terms of both prediction accuracy and computational efficiency.These results demonstrate that the proposed method not only improves the predictive accuracy but also enhances the computational efficiency,enabling optimal parameter identificationwith reduced computational effort.This approach provides a robust and efficientframework for advancing dam safety assessments.
基金funded by the Yunnan Provincial Key Programs for Basic Research Project,China(202301AS070087)the Yunnan Provincial R&D Program,China(202405AF140014 and 202302AO370015)the National Natural Science Foundation of China(42307058).
文摘Soil organic carbon(SOC)dynamics significantly influence ecosystem carbon source-sink balance,particularly in agroecosystems.However,uncertainty remains regarding optimal land use types for maximizing farmland carbon storage across different soil types,and identifying effective land management practices for enhanced carbon accumulation is essential for reducing agricultural emissions and strengthening carbon sinks.This study examined SOC variations in eastern Yunnan’s subtropical highlands(2,132 sites),analyzing topsoil(0–20 cm)across five land uses(dryland,irrigated land,forestland,grassland and plantation)of five soil types(red,yellow,yellowbrown,brown,purple).The investigation explored relationships between SOC and edaphic factors(26 elements)to determine SOC influencing factors.The study area demonstrated a mean SOC content of 27.78 g kg^(–1),with distinct spatial heterogeneity characterized by lower values in the southwestern sector and higher concentrations in the northeastern region.Brown soils displayed the highest SOC content(P<0.05),followed by yellow-brown then red,yellow,and purple soils.Irrigation significantly enhanced SOC storage,particularly in brown soils where irrigated land contained 2.2-,2.4-,and 1.6-times higher SOC than forestland,grassland,and dryland,respectively.Similar irrigation benefits occurred in purple,yellow,and yellow-brown soils,indicating moisture limitation as the primary SOC constraint.Notably,SOC exhibited strong positive correlations with nitrogen,sulfur,and selenium.Nitrogen fertilization demonstrated dual benefits:enhancing SOC sequestration and promoting Se enrichment in crops,potentially supporting specialty agriculture.Although land use impacts on SOC varied across soil types(P>0.05),irrigation consistently emerged as the optimal management for carbon sink enhancement.These findings suggest that targeted water management could effectively reduce farmland carbon emissions in moisture-limited subtropical highlands.Strategic nitrogen application offers co-benefits for soil fertility and selenium biofortification,providing practical pathways for climate-smart agriculture in similar ecoregions.
基金supported by the National Natural Science Foundation of China(32325024,32400981,32222024,32271224,32471228,and 82270891)the National Key Research and Development Program of China(2023YFA1800400)+3 种基金the Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission(23SG22)the Noncommunicable Chronic Diseases-National Science and Technology Major Project(2023ZD0507300)the ECNU public platform for Innovation(011)the instruments sharing platform of School of Life Sciences.
文摘Type 1 diabetes(T1D)is defined by autoimmune-mediated destruction of the insulin-producing pancreatic β-cells.Impaired insulin secretion due to β-cell apoptosis and islet massloss is the main feature of T1D[1].Current therapeutic strategies for T1D are mainly through subcutaneous administration of insulin or islet/pancreas transplantation.
基金Supported by Wuxi Taihu Talent Program(202101)Project of Wu Jieping Medical Foundation(320.6750.2023-03-33).
文摘[Objectives]To analyze the clinical characteristics,distribution of traditional Chinese medicine(TCM)syndrome types,spectrum of comorbidities,and complications among inpatients with gout.[Methods]Data from 592 gout patients admitted in the Department of Rheumatology at Wuxi Traditional Chinese Medicine Hospital between January 2018 and December 2024 were retrospectively collected.The data collected encompassed patient gender,age,TCM syndrome types,underlying comorbidities,infection status,and major complications,including renal insufficiency,interstitial lung disease,and osteoporosis.Descriptive statistical analyses were subsequently performed.[Results]Among the 592 inpatients,80.75%were male and 19.25%were female.A total of 94.76%patients had at least one underlying condition,with hypertension(80.74%),cerebral infarction(29.59%),heart disease(24.24%),and diabetes(21.56%)being the most prevalent.The primary TCM syndrome types identified were damp-heat obstruction syndrome(63.51%)and phlegm-stasis obstruction syndrome(21.11%).During hospitalization,20.94%of patients experienced concurrent infections,predominantly pulmonary infections(38.10%).The principal complications observed included renal insufficiency(32.09%),interstitial lung disease(18.75%),and osteoporosis(9.29%).[Conclusions]Inpatients diagnosed with gout often present with complex conditions and a high burden of comorbidities,predominantly cardiovascular and cerebrovascular diseases,as well as metabolic disorders.Additionally,there is a high incidence of infections and renal insufficiency within this population.TCM syndrome types in these patients are primarily characterized by damp-heat obstruction.In clinical practice,a comprehensive management approach that incorporates multidisciplinary collaboration is recommended.Alongside the control of uric acid levels and joint inflammation,proactive screening and management of comorbidities and related complications are essential.
基金supported by the Science and Technology Project of the Department of Transportation of Heilongjiang Province(HJK2023B024-3)the National Key R&D Program of China(2023YFF1304001-01)。
文摘Soil fertility and forest structure influence tree carbon stocks.However,it remains unclear how tree mycorrhizal types affect these relationships.This study addressed the question of how aboveground and belowground tree carbon stocks in soils with different mycorrhizal types are affected by soil fertility and forest structure.Tree demographic data were used from a 21.12-ha study area collected over a ten-year period(2009-2019),covering 43species of woody plants and more than 50,000 individuals.Relationships between tree carbon stock,soil fertility and forest structure(stand density,diameter variation,species diversity and spatial distribution)were examined,as well as whether these relationships differed between arbuscular mycorrhiza and ectomycorrhizal mycorrhiza groups in a typical temperate conifer and broad-leaved mixed forest.We found that total tree carbon stock was positively impacted by variations in stand density and tree diameter but negatively influenced by soil fertility,tree species diversity and uniform angle index.Soil fertility promoted carbon stock of trees associated with arbuscular mycorrhiza(AM)but inhibited the carbon stock of trees with ectomycorrhizal mycorrhiza fungi(EcM).Carbon stock of AM trees was mainly influenced by soil fertility,while carbon stock of EcM trees was influenced by stand density.Our findings show that mycorrhizae types mediate the impact of stand structure and soil fertility on tree carbon stocks and provides new evidence on how forest tree carbon stocks may be enhanced based on the types of mycorrhizal associations.Tree species with different mycorrhizal types can be managed in different ways.
基金supported by the National Natural Science Foundation of China(Grant Nos.12575003 and 12235007)the K.C.Wong Magna Fund in Ningbo University。
文摘This paper develops a residual-based adaptive refinement physics-informed neural networks(RAR-PINNs)method for solving the Gross–Pitaevskii(GP)equation and Hirota equation,two paradigmatic nonlinear partial differential equations(PDEs)governing quantum condensates and optical rogue waves,respectively.The key innovation lies in the adaptive sampling strategy that dynamically allocates computational resources to regions with large PDE residuals,addressing critical limitations of conventional PINNs in handling:(1)Strong nonlinearities(|u|^(2)u terms)in the GP equation;(2)High-order derivatives(u_(xxx))in the Hirota equation;(3)Multi-scale solution structures.Through rigorous numerical experiments,we demonstrate that RAR-PINNs achieve superior accuracy[relative L^(2)errors of O(10^(−3))]and computational efficiency(faster than standard PINNs)for both equations.The method successfully captures:(1)Bright solitons in the GP equation;(2)First-and second-order rogue waves in the Hirota equation.The RAR adaptive sampling method demonstrates particularly remarkable effectiveness in solving steep gradient problems.Compared with uniform sampling methods,the errors of simulation results are reduced by two orders of magnitude.This study establishes a general framework for data-driven solutions of high-order nonlinear PDEs with complex solution structures.
基金financially supported by the National Natural Science Foundation of China (42477044,32171648 and U23A2017)the Hubei Provincial Science and Technology Program,China (2025AFD451 and 2022CFB030)。
文摘Insight into the carbon turnover in soil aggregates and density fractions is essential for reducing the uncertainty in estimating carbon pools on the Tibetan Plateau,and how they vary with land use type is unclear.In this study,the effect of land use type on carbon storage and fractionation was quantified based on organic carbon and its ^(13)C abundance at the microscale of soil aggregates and density fractions in Tibetan alpine ecosystems.The sequence of soil aggregate destruction in the land use types of plantation(13.1%)<shrubland(32.7%)<grassland(47.9%)<farmland(61.8%)shows that plantations strengthen the soil structure.Plantation land had a greater contribution of light fraction organic carbon(28.3%)but a lower contribution of mineral-associated organic carbon(40.6%)to the carbon stock compared to farmland(13.5 and 70.3%).Interestingly,plantation land enhanced the aggregational differentiation of organic carbon and ^(13)C in each density fraction,whereas no such phenomenon existed in the soil organic carbon.Carbon isotope analyses revealed that carbon transfer in the plantation land occurred from the light fraction in macroaggregates(–24.9‰)to the mineral-associated fraction in microaggregates(–19.9‰).When compared to the other three land use types,the low transferability of carbon in aggregates and density fractions in plantation land provides a stable carbon pool for the Tibetan Plateau.This study shows that plantations can mitigate global climate change by slowing carbon transfer and increasing carbon storage at the microscale of aggregates and density fractions in alpine regions.
基金Supported by the National Natural Science Foundation of China(Grant Nos.11961059,1210502)the University Innovation Project of Gansu Province(Grant No.2023B-062)the Gansu Province Basic Research Innovation Group Project(Grant No.23JRRA684).
文摘The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.
基金Supported by Natural Science Foundation of Hunan Province(No.2023JJ70017No.2025JJ50627)Peak Climbing Project of Optometry Hospital Affiliated to Wenzhou Medical University。
文摘AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.
基金supported by the National Key R&D Program of China (Grant Nos.2022YFA1403103 and 2019YFA0308603)the National Natural Science Foundation of China (Grant No.12304167)the Shandong Provincial Natural Science Foundation of China (Grant No.ZR2023QA020)。
文摘Interfacial superconductivity(IS)has been a topic of intense interest in condensed matter physics,due to its unique properties and exotic photoelectrical performance.However,there are few reports about IS systems consisting of two insulators.Here,motivated by the emergence of an insulator-metal transition in type-Ⅲ heterostructures and the superconductivity in some“special”two-dimensional(2D)semiconductors via electron doping,we predict that the 2D heterostructure SnSe_(2)/PtTe_(2) is a model system for realizing IS by using firstprinciples calculations.Our results show that due to slight but crucial interlayer charge transfer,SnSe_(2)/PtTe_(2) turns to be a type-Ⅲ heterostructure with metallic properties and shows a superconducting transition with the critical temperature(T_(c))of 3.73 K.Similar to the enhanced electron–phonon coupling(EPC)in the electrondoped SnSe_(2) monolayer,the IS in the SnSe_(2)/PtTe_(2) heterostructure mainly originates from the metallized SnSe_(2) layer.Furthermore,we find that its superconductivity is sensitive to tensile lattice strain,forming a domeshaped superconducting phase diagram.Remarkably,at 7%biaxial tensile strain,the superconducting T_(c) can increase more than twofold(8.80 K),resulting from softened acoustic phonons at the𝑀point and enhanced EPC strength.Our study provides a concrete example for realizing IS in type-Ⅲ heterostructures,which waits for future experimental verification.
基金supported by the NIA/NIH(1K01AG060040).Studies performed by JN were funded by the NICHD/NIH(5R00HD096117)Microscopy Core Facility supported,in part,with funding from NIH-NCI Cancer Center Support Grant P30 CA016059.
文摘Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.
基金financial support fromthe Chung Shan Medical University Hospital,Taiwan(CSH-2022-A-009).
文摘Background:To determine whether initiating a glucagon-like peptide-1 receptor agonist(GLP-1 RA)within 3 months of type 2 diabetes(T2DM)diagnosis alters the subsequent risk of overall and site-specific cancer and whether this association differs by baseline body-mass index(BMI).Methods:This retrospective cohort study used electronic health records from the TriNetX U.S.research network.Adults aged 20 years or older diagnosed with T2DM between 2016 and 2024 were included if they received any hypoglycemic agents within 3 months before and after diagnosis.Following 1:1 propensity score matching,both the GLP-1 RA user and non-user groups included 183,264 patients.The study outcome was defined as a diagnosis of malignant neoplasms.Hazard ratios(HRs)for overall and site-specific cancer risk were estimated using Cox proportional hazards models.Kaplan–Meier analysis and stratified analysis by BMI were performed.Results:Early GLP-1 RA use demonstrated a modest but significant association with reduced overall cancer risk(HR 0.93;95%CI:0.90–0.96).Reduced risks were noted for cancers of the digestive(HR 0.81),respiratory(HR 0.66),and female genital(HR 0.87)systems.In stratified analysis,benefits were more pronounced in patients with BMI≥30,particularly for pancreatic and colorectal cancers.Conclusion:Early initiation of GLP-1 receptor agonists in patients with diagnosed T2DM was associated with a modest reduction in overall cancer risk,particularly among individuals with obesity.These findings highlight the dual metabolic and oncologic value of prompt GLP-1 RA therapy.
基金the National Natural Science Foundation of China(82204935)the construction project of Zhao Feng National Old Pharmacist Inheritance Studio of State Administration of Traditional Chinese Medicine(National Traditional Chinese Medicine Education Letter[2024]255)+1 种基金the open project of the Key Laboratory of Basic and New Drug Research of Traditional Chinese Medicine in Shaanxi Province(KF202302)the project of Xi’an Municipal Bureau of Science and Technology(23YXYJ0042)for financial support.
文摘Background:One of the first hundred traditional Chinese medicines(TCM)formulas administered in China,Qianghuo Shengshi Decoction(QSD)has a positive clinical and therapeutic impact on rheumatoid arthritis(RA).Even so,there is still not enough knowledge on the active ingredients and possible ways that QSDs might work to treat RA.This study systematically investigated the active ingredients and mechanisms of action of QSD for treating wind-cold-dampness arthralgia type RA.Methods:UHPLC-QE-MS and network pharmacology techniques were employed to predict the potential active constituents,targets,and associated signalling pathways.Then,the therapeutic effect of QSD was examined using a wind-cold-dampness arthralgia paralytic RA rat model.Finally,the complex mechanism was comprehensively elucidated by integrating transcriptomics and network pharmacology.The above mechanisms were also verified by molecular docking,immunohistochemistry and Western blot.Results:UHPLC-QE-MS and network pharmacology analysis revealed that ferulic acid,imperatorin,magnolol,quercetin,and scopoletin could be the primary constituents in QSD responsible for its anti-RA effects.Animal experiments showed that QSD can significantly inhibit rat joint swelling degree,decrease the content of serum rheumatoid factor(RF),interleukin(IL)-1β,tumor necrosis factor-alpha(TNF-α),IL-6,and anti-citrullinated protein antibodies(ACPA),and increase the content of IL-4,IL-10 to relieve the clinical symptoms of wind-cold-dampness arthralgia type RA.The mechanistic study showed that QSD may effectively inhibit rat synovial hyperplasia via promoting autophagy and apoptosis of synovial cells by regulating the PI3K/Akt/mTOR signalling pathway.Conclusion:This study identifies key active ingredients in QSD and elucidates its potential mechanism for treating wind-cold-dampness arthralgia type RA,providing a basis for the clinical application of QSD.
基金supported by the National Natural Science Foundation of China(32525049).
文摘Concerns about the long-term safety and efficacy of glibenclamide(GLIB),a type 2 diabetes mellitus(T2DM)treatment,have been reported[1].Recent evidence indicates the gut microbiota composition significantly affects host glucose metabolism and drugbioavailability,increasingthe efficacy of T2DM therapy[2].In this context,probiotic-drug coadministration,an emerging adjunct approach for treating metabolic diseases,improves therapeutic outcomes and ameliorates side effects[3].
基金supported by a project of the Shaanxi Youth Science and Technology Star(2021KJXX-87)public welfare geological survey projects of Shaanxi Institute of Geologic Survey(20180301,201918 and 202103)。
文摘With the efficient and intelligent development of computer-based big data processing,applying machine learning methods to the processing and interpretation of logging data in the field of geophysical well logging has broad potential for improving production efficiency.Currently,the Jiyuan Oilfield in the Ordos Basin relies mainly on manual reprocessing and interpretation of old well logging data to identify different fluid types in low-contrast reservoirs,guiding subsequent production work.This study uses well logging data from the Chang 1 reservoir,partitioning the dataset based on individual wells for model training and testing.A deep learning model for intelligent reservoir fluid identification was constructed by incorporating the focal loss function.Comparative validations with five other models,including logistic regression(LR),naive Bayes(NB),gradient boosting decision trees(GBDT),random forest(RF),and support vector machine(SVM),show that this model demonstrates superior identification performance and significantly improves the accuracy of identifying oil-bearing fluids.Mutual information analysis reveals the model's differential dependency on various logging parameters for reservoir fluid identification.This model provides important references and a basis for conducting regional studies and revisiting old wells,demonstrating practical value that can be widely applied.
