In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of kn...Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiote...Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.展开更多
Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visite...Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visited our hospital from January 2024 to December 2024 were selected as samples and randomly divided into groups.The observation group received rehabilitation nursing based on the mind mapping model combined with psychological intervention,while the control group received routine intervention.The differences in emotional scores,self-care ability scores,compliance,and complications were compared between the two groups.Results:The anxiety(SAS)and depression(SDS)scores of the observation group were lower than those of the control group,while the self-care ability scale(ESCA)score was higher than that of the control group(P<0.05).The compliance rate of the observation group was higher than that of the control group(P<0.05).The complication rate of NS in the observation group was lower than that in the control group(P<0.05).Conclusion:Rehabilitation nursing based on the mind mapping model combined with psychological intervention can enhance self-care ability,reduce negative emotions,and reduce complications in NS nursing,which is efficient and feasible.展开更多
Background:Due to the widespread use of cell phone devices today,numerous re-search studies have focused on the adverse effects of electromagnetic radiation on human neuropsychological and reproductive systems.In most...Background:Due to the widespread use of cell phone devices today,numerous re-search studies have focused on the adverse effects of electromagnetic radiation on human neuropsychological and reproductive systems.In most studies,oxidative stress has been identified as the primary pathophysiological mechanism underlying the harmful effects of electromagnetic waves.This paper aims to provide a holistic review of the protective effects of melatonin against cell phone-induced electromag-netic waves on various organs.Methods:This study is a systematic review of articles chosen by searching Google Scholar,PubMed,Embase,Scopus,Web of Science,and Science Direct using the key-words‘melatonin’,‘cell phone radiation’,and‘animal model’.The search focused on articles written in English,which were reviewed and evaluated.The PRISMA process was used to review the articles chosen for the study,and the JBI checklist was used to check the quality of the reviewed articles.Results:In the final review of 11 valid quality-checked articles,the effects of me-latonin in the intervention group,the effects of electromagnetic waves in the case group,and the amount of melatonin in the chosen organ,i.e.brain,skin,eyes,testis and the kidney were thoroughly examined.The review showed that electromagnetic waves increase cellular anti-oxidative activity in different tissues such as the brain,the skin,the eyes,the testis,and the kidneys.Melatonin can considerably augment the anti-oxidative system of cells and protect tissues;these measurements were sig-nificantly increased in control groups.Electromagnetic waves can induce tissue atro-phy and cell death in various organs including the brain and the skin and this effect was highly decreased by melatonin.Conclusion:Our review confirms that melatonin effectively protects the organs of an-imal models against electromagnetic waves.In light of this conclusion and the current world-wide use of melatonin,future studies should advance to the stages of human clinical trials.We also recommend that more research in the field of melatonin physi-ology is conducted in order to protect exposed cells from dying and that melatonin should be considered as a pharmaceutical option for treating the complications result-ing from electromagnetic waves in humans.展开更多
Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diver...Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.展开更多
Although previous studies have demonstrated that transcranial focused ultrasound stimulation protects the ischemic brain,clear criteria for the stimulation time window and intensity are lacking.Electrical impedance to...Although previous studies have demonstrated that transcranial focused ultrasound stimulation protects the ischemic brain,clear criteria for the stimulation time window and intensity are lacking.Electrical impedance tomography enables real-time monitoring of changes in cerebral blood perfusion within the ischemic brain,but investigating the feasibility of using this method to assess post-stroke rehabilitation in vivo remains critical.In this study,ischemic stroke was induced in rats through middle cerebral artery occlusion surgery.Transcranial focused ultrasound stimulation was used to treat the rat model of ischemia,and electrical impedance tomography was used to measure impedance during both the acute stage of ischemia and the rehabilitation stage following the stimulation.Electrical impedance tomography results indicated that cerebral impedance increased after the onset of ischemia and decreased following transcranial focused ultrasound stimulation.Furthermore,the stimulation promoted motor function recovery,reduced cerebral infarction volume in the rat model of ischemic stroke,and induced the expression of brain-derived neurotrophic factor in the ischemic brain.Our results also revealed a significant correlation between the impedance of the ischemic brain post-intervention and improvements in behavioral scores and infarct volume.This study shows that daily administration of transcranial focused ultrasound stimulation for 20 minutes to the ischemic hemisphere 24 hours after cerebral ischemia enhanced motor recovery in a rat model of ischemia.Additionally,our findings indicate that electrical impedance tomography can serve as a valuable tool for quantitatively evaluating rehabilitation after ischemic stroke in vivo.These findings suggest the feasibility of using impedance data collected via electrical impedance tomography to clinically assess the effects of rehabilitatory interventions for patients with ischemic stroke.展开更多
As a crucial human activity,dam construction can profoundly impact the surface hydrology patterns.The Three Gorges Reservoir(TGR),as one of the largest hydraulic engineering projects in the world,has gained continuous...As a crucial human activity,dam construction can profoundly impact the surface hydrology patterns.The Three Gorges Reservoir(TGR),as one of the largest hydraulic engineering projects in the world,has gained continuous attention for its eco-hydrological effects.However,further investigation is necessary to understand the runoff and social impacts of the TGR on the Upper Yangtze River.This study first employed a modified SWAT model to simulate runoff,compared scenarios with and without the TGR,and finally evaluated water supply and demand in the Upper Yangtze River.The results showed a significant increasing trend in the surface water area of the Upper Yangtze River from 2000-2020.The modified SWAT model performs well in simulating the runoff,with Nash-Sutcliffe Efficiency and Percent Bias improved by 0.04-0.30 and 2-31.90,respectively.Scenario simulation results revealed that the TGR reduced seasonal differences in runoff.During the flood season,the runoff volume at the Yichang Station in the scenario with the TGR is lower than in the scenario without the TGR,peaking at 4500 m3/s.Conversely,in the dry season,the runoff volume of the scenario with TGR is higher,with a maximum increase of 1500 m3/s.The region exhibiting the greatest runoff variations is the Yangtze River's main stem in the Three Gorges Reservoir region.Besides,the TGR notably alleviated the water supply-demand imbalance in Chongqing during the winter and spring seasons,with a maximum increase of 0.16 in the supplydemand index.This study can contribute significantly to understanding the natural and social impacts of the TGR from the perspective of hydrological and scenario simulation.展开更多
DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expres...DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.展开更多
In this study,we used an extensive sampling network established in central Romania to develop tree height and crown length models.Our analysis included more than 18,000 tree measurements from five different species.In...In this study,we used an extensive sampling network established in central Romania to develop tree height and crown length models.Our analysis included more than 18,000 tree measurements from five different species.Instead of building univariate models for each response variable,we employed a multivariate approach using seemingly unrelated mixed-effects models.These models incorporated variables related to species mixture,tree and stand size,competition,and stand structure.With the inclusion of additional variables in the multivariate seemingly unrelated mixed-effects models,the accuracy of the height prediction models improved by over 10% for all species,whereas the improvement in the crown length models was considerably smaller.Our findings indicate that trees in mixed stands tend to have shorter heights but longer crowns than those in pure stands.We also observed that trees in homogeneous stand structures have shorter crown lengths than those in heterogeneous stands.By employing a multivariate mixed-effects modelling framework,we were able to perform cross-model random-effect predictions,leading to a significant increase in accuracy when both responses were used to calibrate the model.In contrast,the improvement in accuracy was marginal when only height was used for calibration.We demonstrate how multivariate mixed-effects models can be effectively used to develop multi-response allometric models that can be easily calibrated with a limited number of observations while simultaneously achieving better-aligned projections.展开更多
Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution g...Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution grids.This study measures the effectiveness of the Puma optimizer(PO)algorithm in parameter estimation of PSC(perovskite solar cells)dynamic models with hysteresis consideration considering the electric field effects on operation.The models used in this study will incorporate hysteresis effects to capture the time-dependent behavior of PSCs accurately.The PO optimizes the proposed modified triple diode model(TDM)with a variable voltage capacitor and resistances(VVCARs)considering the hysteresis behavior.The suggested PO algorithm contrasts with other wellknown optimizers from the literature to demonstrate its superiority.The results emphasize that the PO realizes a lower RMSE(Root mean square errors),which proves its capability and efficacy in parameter extraction for the models.The statistical results emphasize the efficiency and supremacy of the proposed PO compared to the other well-known competing optimizers.The convergence rates show good,fast,and stable convergence rates with lower RMSE via PO compared to the other five competitive optimizers.Moreover,the lowermean realized via the PO optimizer is illustrated by the box plot for all optimizers.展开更多
The significant threat of wildfires to forest ecology and biodiversity,particularly in tropical and subtropical regions,underscores the necessity for advanced predictive models amidst shifting climate patterns.There i...The significant threat of wildfires to forest ecology and biodiversity,particularly in tropical and subtropical regions,underscores the necessity for advanced predictive models amidst shifting climate patterns.There is a need to evaluate and enhance wildfire prediction methods,focusing on their application during extended periods of intense heat and drought.This study reviews various wildfire modelling approaches,including traditional physical,semi-empirical,numerical,and emerging machine learning(ML)-based models.We critically assess these models’capabilities in predicting fire susceptibility and post-ignition spread,highlighting their strengths and limitations.Our findings indicate that while traditional models provide foundational insights,they often fall short in dynamically estimating parameters and predicting ignition events.Cellular automata models,despite their potential,face challenges in data integration and computational demands.Conversely,ML models demonstrate superior efficiency and accuracy by leveraging diverse datasets,though they encounter interpretability issues.This review recommends hybrid modelling approaches that integrate multiple methods to harness their combined strengths.By incorporating data assimilation techniques with dynamic forecasting models,the predictive capabilities of ML-based predictions can be significantly enhanced.This review underscores the necessity for continued refinement of these models to ensure their reliability in real-world applications,ultimately contributing to more effective wildfire mitigation and management strategies.Future research should focus on improving hybrid models and exploring new data integration methods to advance predictive capabilities.展开更多
The development of rodent models that accurately reflect the pathogenesis of alcoholic liver disease(ALD)in humans is crucial for evaluating the nutritional intervention of food bioactive ingredients in ALD.Although v...The development of rodent models that accurately reflect the pathogenesis of alcoholic liver disease(ALD)in humans is crucial for evaluating the nutritional intervention of food bioactive ingredients in ALD.Although various models have been employed to establish ALD models over the past few decades,most successful cases are associated with high mortality rates,operational difficulties,and incompatibility formation mechanism compared to human ALD.However,the ALD models established by oral administration that simulate human drinking behavior often fail to induce significant liver damage.Therefore,it is imperative to explore simple and effective modes of oral administration for establishing ALD models consistent with the pathophysiological process of human ALD.Herein,we summarized the pathogenesis of ALD and discussed several issues related to construct ALD models with rodents(mainly mice and rats)by oral administration,including animal selection,animal feeding,alcohol intervention,and evaluation criteria.The purpose of this review is to provide a standardized and efficient formula for ALD modeling,so as to facilitate efficacy evaluation and mechanism analysis of food bioactive ingredients in ALD.展开更多
This study examines the advent of agent interaction(AIx)as a transformative paradigm in humancomputer interaction(HCI),signifying a notable evolution beyond traditional graphical interfaces and touchscreen interaction...This study examines the advent of agent interaction(AIx)as a transformative paradigm in humancomputer interaction(HCI),signifying a notable evolution beyond traditional graphical interfaces and touchscreen interactions.Within the context of large models,AIx is characterized by its innovative interaction patterns and a plethora of application scenarios that hold great potential.The paper highlights the pivotal role of AIx in shaping the future landscape of the large model industry,emphasizing its adoption and necessity from a user's perspective.This study underscores the pivotal role of AIx in dictating the future trajectory of a large model industry by emphasizing the importance of its adoption and necessity from a user-centric perspective.The fundamental drivers of AIx include the introduction of novel capabilities,replication of capabilities(both anthropomorphic and superhuman),migration of capabilities,aggregation of intelligence,and multiplication of capabilities.These elements are essential for propelling innovation,expanding the frontiers of capability,and realizing the exponential superposition of capabilities,thereby mitigating labor redundancy and addressing a spectrum of human needs.Furthermore,this study provides an in-depth analysis of the structural components and operational mechanisms of agents supported by large models.Such advancements significantly enhance the capacity of agents to tackle complex problems and provide intelligent services,thereby facilitating a more intuitive,adaptive,and personalized engagement between humans and machines.The study further delineates four principal categories of interaction patterns that encompass eight distinct modalities of interaction,corresponding to twenty-one specific scenarios,including applications in smart home systems,health assistance,and elderly care.This emphasizes the significance of this new paradigm in advancing HCI,fostering technological advancements,and redefining user experiences.However,it also acknowledges the challenges and ethical considerations that accompany this paradigm shift,recognizing the need for a balanced approach to harness the full potential of AIx in modern society.展开更多
Background:There are many forms of anabolic steroids,including stanozolol(Winstrol),which are popular for their muscle-building effects but dangerous to the heart.This pre-sent work is aimed at evaluating the pharmaco...Background:There are many forms of anabolic steroids,including stanozolol(Winstrol),which are popular for their muscle-building effects but dangerous to the heart.This pre-sent work is aimed at evaluating the pharmacologica impact of allicin,a natural attribute obtained from garlic,on obstructing cardiac injury in rabbits that received stanozolol.Methods:Thirty rabbits were divided into three groups:control,stanozolol-treated,and stanozolol plus allicin.Cardiac function was assessed by measuring troponin,creatine kinase(CK),Galectin-3,and GDF-15.Oxidative stress and antioxidant markers,includ-ing malondialdehyde(MDA),glutathione,and catalase,were analyzed.Inflammatory mediators such as C-reactive protein(CRP),interleukin-6(IL-6),NF-κB,iNOS,nitric oxide(NO),tumor necrosis factor-alpha(TNF-α),and interleukin-1 beta(IL-1β)were evaluated.Lipid profile parameters,including total cholesterol,low-density lipoprotein(LDL),and high-density lipoprotein(HDL),were measured.Histopathological examina-tion assessed myocardial damage,fibrosis,and collagen deposition.Results:Stanozolol administration significantly increased cardiac damage markers,oxidative stress,and inflammatory mediators while causing dyslipidemia,characterized by elevated LDL and total cholesterol and reduced HDL.Allicin co-administration effectively countered these effects by reducing oxidative stress and inflammation,restoring antioxidant balance,and improving lipid profiles.Histopathological analysis revealed severe myocardial disor-ganization,necrosis,and fibrosis in the stanozolol group,whereas the allicin-treated group exhibited preserved myocardial structure with reduced collagen deposition.Conclusion:Allicin significantly mitigates stanozolol-induced cardiotoxicity by reduc-ing oxidative stress,inflammation,lipid dysregulation,and myocardial damage,as evidenced by biochemical and histopathological findings.These results suggest that allicin may serve as a potential therapeutic agent to counteract the cardiovascular risks associated with anabolic steroid use.展开更多
Non-Schmid(NS)effects in body-centered cubic(BCC)single-phase metals have received special attention in recent years.However,a deep understanding of these effects in the BCC phase of dual-phase(DP)steels has not yet b...Non-Schmid(NS)effects in body-centered cubic(BCC)single-phase metals have received special attention in recent years.However,a deep understanding of these effects in the BCC phase of dual-phase(DP)steels has not yet been reached.This study explores the NS effects in ferrite-martensite DP steels,where the ferrite phase has a BCC crystallographic structure and exhibits NS effects.The influences of NS stress components on the mechanical response of DP steels are studied,including stress/strain partitioning,plastic flow,and yield surface.To this end,the mechanical behavior of the two phases is described by dislocation density-based crystal plasticity constitutive models,with the NS effect only incorporated into the ferrite phase modeling.The NS stress contribution is revealed for two types of microstructures commonly observed in DP steels:equiaxed phases with random grain orientations,and elongated phases with preferred grain orientations.Our results show that,in the case of a microstructure with equiaxed phases,the normal NS stress components play significant roles in tension-compression asymmetry.By contrast,in microstructures with elongated phases,a combined influence of crystallographic texture and NS effect is evident.These findings advance our knowledge of the intricate interplay between microstructural features and NS effects and help to elucidate the mechanisms underlying anisotropic-asymmetric plastic behavior of DP steels.展开更多
We perform a comprehensive study of the electron-doped t-t′-J model on cylinders with density matrix renormalization group(DMRG).We conduct a systematic study on the finite-size and boundary condition effects on t-t...We perform a comprehensive study of the electron-doped t-t′-J model on cylinders with density matrix renormalization group(DMRG).We conduct a systematic study on the finite-size and boundary condition effects on t-t′-J model on cylinders.Periodic and anti-periodic boundary conditions are implemented along the circumference direction,with the system’s width extending up to as large as 8 lattice units.We study doping levels of 1/6,1/8,and 1/12,which represent the most interesting region in the phase diagram of electron-doped cuprates.We find that for width-4 and width-6 systems,the ground state for fixed doping switches between anti-ferromagnetic Neel state and stripe state under different boundary conditions and system widths,indicating the presence of large finite size effect in the t-t′-J model.We also have a careful analysis of the d-wave pairing correlations which also change quantitatively with boundary conditions and widths of the system.However,the pairing correlations are enhanced when the system becomes wider for all dopings,suggesting the existence of possible long-range superconducting order in the thermodynamic limit.The width-8 results are found to be dependent on the starting state in the DMRG calculation for the kept states we can reach.For the width-8 system,only Neel(stripe)state can be stabilized in DMRG calculation for 1/12(1/6)doping,while both stripe and Neel states are stable in the DMRG sweep for 1/8 doping,regardless of the boundary conditions.These results indicate that 1/8 doping is likely to lie on the boundary of a phase transition between the Neel phase with lower doping and the stripe phase with higher doping,consistent with the previous study.The sensitivity of the ground state on boundary conditions and size observed for narrow systems is similar to that found in the t′-Hubbard model,where the t′term introduces frustration and makes the stripe state fragile.The study of different boundary conditions provides a useful tool to check the finite size effect in the future DMRG calculations.展开更多
The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D desi...The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.展开更多
The application of a controllable neutron source for measuring formation porosity in the advancement of nuclear logging has garnered increased attention.The existing porosity algorithm,which is based on the thermal ne...The application of a controllable neutron source for measuring formation porosity in the advancement of nuclear logging has garnered increased attention.The existing porosity algorithm,which is based on the thermal neutron counting ratio,exhibits lower sensitivity in high-porosity regions.To enhance the sensitivity,the effects of elastic and inelastic scattering,which influence the slowing-down of fast neutrons,were theoretically analyzed,and a slowing-down model of fast neutrons was created.Based on this model,a density correction porosity algorithm was proposed based on the relationship between density,thermal neutron counting ratio,and porosity.Finally,the super multifunctional calculation program for nuclear design and safety evaluation(TopMC/SuperMC)was used to create a simulation model for porosity logging,and its applicability was examined.The results demonstrated that the relative error between the calculated and actual porosities was less than 1%,and the influence of deviation in the density measurement was less than 2%.Therefore,the proposed density correction algorithm based on the slowing-down model of fast neutrons can effectively improve the sensitivity in the high-porosity region.This study is expected to serve as a reference for the application of neutron porosity measurements with D–T neutron sources.展开更多
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
基金funded by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation):project ID 431549029-SFB 1451the Marga-und-Walter-Boll-Stiftung(#210-10-15)(to MAR)a stipend from the'Gerok Program'(Faculty of Medicine,University of Cologne,Germany)。
文摘Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金supported by the National Key Research and Development Program of China[grant number 2022YFE0106800]an Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 311024001]+3 种基金a project supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number SML2023SP209]a Research Council of Norway funded project(MAPARC)[grant number 328943]a Nansen Center´s basic institutional funding[grant number 342624]the high-performance computing support from the School of Atmospheric Science at Sun Yat-sen University。
文摘Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.
文摘Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visited our hospital from January 2024 to December 2024 were selected as samples and randomly divided into groups.The observation group received rehabilitation nursing based on the mind mapping model combined with psychological intervention,while the control group received routine intervention.The differences in emotional scores,self-care ability scores,compliance,and complications were compared between the two groups.Results:The anxiety(SAS)and depression(SDS)scores of the observation group were lower than those of the control group,while the self-care ability scale(ESCA)score was higher than that of the control group(P<0.05).The compliance rate of the observation group was higher than that of the control group(P<0.05).The complication rate of NS in the observation group was lower than that in the control group(P<0.05).Conclusion:Rehabilitation nursing based on the mind mapping model combined with psychological intervention can enhance self-care ability,reduce negative emotions,and reduce complications in NS nursing,which is efficient and feasible.
基金Deputy for Research and Technology,Kermanshah University of Medical Sciences,Grant/Award Number:4030031。
文摘Background:Due to the widespread use of cell phone devices today,numerous re-search studies have focused on the adverse effects of electromagnetic radiation on human neuropsychological and reproductive systems.In most studies,oxidative stress has been identified as the primary pathophysiological mechanism underlying the harmful effects of electromagnetic waves.This paper aims to provide a holistic review of the protective effects of melatonin against cell phone-induced electromag-netic waves on various organs.Methods:This study is a systematic review of articles chosen by searching Google Scholar,PubMed,Embase,Scopus,Web of Science,and Science Direct using the key-words‘melatonin’,‘cell phone radiation’,and‘animal model’.The search focused on articles written in English,which were reviewed and evaluated.The PRISMA process was used to review the articles chosen for the study,and the JBI checklist was used to check the quality of the reviewed articles.Results:In the final review of 11 valid quality-checked articles,the effects of me-latonin in the intervention group,the effects of electromagnetic waves in the case group,and the amount of melatonin in the chosen organ,i.e.brain,skin,eyes,testis and the kidney were thoroughly examined.The review showed that electromagnetic waves increase cellular anti-oxidative activity in different tissues such as the brain,the skin,the eyes,the testis,and the kidneys.Melatonin can considerably augment the anti-oxidative system of cells and protect tissues;these measurements were sig-nificantly increased in control groups.Electromagnetic waves can induce tissue atro-phy and cell death in various organs including the brain and the skin and this effect was highly decreased by melatonin.Conclusion:Our review confirms that melatonin effectively protects the organs of an-imal models against electromagnetic waves.In light of this conclusion and the current world-wide use of melatonin,future studies should advance to the stages of human clinical trials.We also recommend that more research in the field of melatonin physi-ology is conducted in order to protect exposed cells from dying and that melatonin should be considered as a pharmaceutical option for treating the complications result-ing from electromagnetic waves in humans.
基金supported by the Laoshan Laboratory[grant number LSKJ202202403]the National Natural Science Foundation of China[grant number 42030410]+1 种基金additionally supported by the Startup Foundation for Introducing Talent of NUISTJiangsu Innovation Research Group[grant number JSSCTD202346]。
文摘Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.
基金supported by the Fundamental Research Funds for the Central Universities,Nos.G2021KY05107,G2021KY05101the National Natural Science Foundation of China,Nos.32071316,32211530049+1 种基金the Natural Science Foundation of Shaanxi Province,No.2022-JM482the Education and Teaching Reform Funds for the Central Universities,No.23GZ230102(all to LL and HH).
文摘Although previous studies have demonstrated that transcranial focused ultrasound stimulation protects the ischemic brain,clear criteria for the stimulation time window and intensity are lacking.Electrical impedance tomography enables real-time monitoring of changes in cerebral blood perfusion within the ischemic brain,but investigating the feasibility of using this method to assess post-stroke rehabilitation in vivo remains critical.In this study,ischemic stroke was induced in rats through middle cerebral artery occlusion surgery.Transcranial focused ultrasound stimulation was used to treat the rat model of ischemia,and electrical impedance tomography was used to measure impedance during both the acute stage of ischemia and the rehabilitation stage following the stimulation.Electrical impedance tomography results indicated that cerebral impedance increased after the onset of ischemia and decreased following transcranial focused ultrasound stimulation.Furthermore,the stimulation promoted motor function recovery,reduced cerebral infarction volume in the rat model of ischemic stroke,and induced the expression of brain-derived neurotrophic factor in the ischemic brain.Our results also revealed a significant correlation between the impedance of the ischemic brain post-intervention and improvements in behavioral scores and infarct volume.This study shows that daily administration of transcranial focused ultrasound stimulation for 20 minutes to the ischemic hemisphere 24 hours after cerebral ischemia enhanced motor recovery in a rat model of ischemia.Additionally,our findings indicate that electrical impedance tomography can serve as a valuable tool for quantitatively evaluating rehabilitation after ischemic stroke in vivo.These findings suggest the feasibility of using impedance data collected via electrical impedance tomography to clinically assess the effects of rehabilitatory interventions for patients with ischemic stroke.
基金supported by the National Natural Science Foundation of China(Nos.41975044,42371354,41801021,42101385)Open Fund of Hubei Luojia Laboratory(No.2201000043)the Fundamental Research Funds for National Universities,China University of Geosciences,Wuhan。
文摘As a crucial human activity,dam construction can profoundly impact the surface hydrology patterns.The Three Gorges Reservoir(TGR),as one of the largest hydraulic engineering projects in the world,has gained continuous attention for its eco-hydrological effects.However,further investigation is necessary to understand the runoff and social impacts of the TGR on the Upper Yangtze River.This study first employed a modified SWAT model to simulate runoff,compared scenarios with and without the TGR,and finally evaluated water supply and demand in the Upper Yangtze River.The results showed a significant increasing trend in the surface water area of the Upper Yangtze River from 2000-2020.The modified SWAT model performs well in simulating the runoff,with Nash-Sutcliffe Efficiency and Percent Bias improved by 0.04-0.30 and 2-31.90,respectively.Scenario simulation results revealed that the TGR reduced seasonal differences in runoff.During the flood season,the runoff volume at the Yichang Station in the scenario with the TGR is lower than in the scenario without the TGR,peaking at 4500 m3/s.Conversely,in the dry season,the runoff volume of the scenario with TGR is higher,with a maximum increase of 1500 m3/s.The region exhibiting the greatest runoff variations is the Yangtze River's main stem in the Three Gorges Reservoir region.Besides,the TGR notably alleviated the water supply-demand imbalance in Chongqing during the winter and spring seasons,with a maximum increase of 0.16 in the supplydemand index.This study can contribute significantly to understanding the natural and social impacts of the TGR from the perspective of hydrological and scenario simulation.
文摘DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.
基金supported by the European Union and the Romanian Government through the Competitiveness Operational Programme 2014–2020, under the project“Increasing the economic competitiveness of the forestry sector and the quality of life through knowledge transfer,technology and CDI skills”(CRESFORLIFE),ID P 40 380/105506, subsidiary contract no. 17/2020partially by the FORCLIMSOC Nucleu Programme (Contract 12N/2023)+2 种基金project PN 23090101CresPerfInst project (Contract 34PFE/December 30, 2021)“Increasing the institutional capacity and performance of INCDS ‘Marin Drǎcea’in RDI activities-CresPer”LM was financially supported by the Research Council of Finland's flagship ecosystem for Forest-Human-Machine Interplay–Building Resilience, Redefining Value Networks and Enabling Meaningful Experiences (UNITE)(decision number 357909)
文摘In this study,we used an extensive sampling network established in central Romania to develop tree height and crown length models.Our analysis included more than 18,000 tree measurements from five different species.Instead of building univariate models for each response variable,we employed a multivariate approach using seemingly unrelated mixed-effects models.These models incorporated variables related to species mixture,tree and stand size,competition,and stand structure.With the inclusion of additional variables in the multivariate seemingly unrelated mixed-effects models,the accuracy of the height prediction models improved by over 10% for all species,whereas the improvement in the crown length models was considerably smaller.Our findings indicate that trees in mixed stands tend to have shorter heights but longer crowns than those in pure stands.We also observed that trees in homogeneous stand structures have shorter crown lengths than those in heterogeneous stands.By employing a multivariate mixed-effects modelling framework,we were able to perform cross-model random-effect predictions,leading to a significant increase in accuracy when both responses were used to calibrate the model.In contrast,the improvement in accuracy was marginal when only height was used for calibration.We demonstrate how multivariate mixed-effects models can be effectively used to develop multi-response allometric models that can be easily calibrated with a limited number of observations while simultaneously achieving better-aligned projections.
基金supported via funding from Prince Sattam Bin Abdulaziz University project number(PSAU/2025/R/1446).
文摘Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution grids.This study measures the effectiveness of the Puma optimizer(PO)algorithm in parameter estimation of PSC(perovskite solar cells)dynamic models with hysteresis consideration considering the electric field effects on operation.The models used in this study will incorporate hysteresis effects to capture the time-dependent behavior of PSCs accurately.The PO optimizes the proposed modified triple diode model(TDM)with a variable voltage capacitor and resistances(VVCARs)considering the hysteresis behavior.The suggested PO algorithm contrasts with other wellknown optimizers from the literature to demonstrate its superiority.The results emphasize that the PO realizes a lower RMSE(Root mean square errors),which proves its capability and efficacy in parameter extraction for the models.The statistical results emphasize the efficiency and supremacy of the proposed PO compared to the other well-known competing optimizers.The convergence rates show good,fast,and stable convergence rates with lower RMSE via PO compared to the other five competitive optimizers.Moreover,the lowermean realized via the PO optimizer is illustrated by the box plot for all optimizers.
基金funding enabled and organized by CAUL and its Member Institutions.
文摘The significant threat of wildfires to forest ecology and biodiversity,particularly in tropical and subtropical regions,underscores the necessity for advanced predictive models amidst shifting climate patterns.There is a need to evaluate and enhance wildfire prediction methods,focusing on their application during extended periods of intense heat and drought.This study reviews various wildfire modelling approaches,including traditional physical,semi-empirical,numerical,and emerging machine learning(ML)-based models.We critically assess these models’capabilities in predicting fire susceptibility and post-ignition spread,highlighting their strengths and limitations.Our findings indicate that while traditional models provide foundational insights,they often fall short in dynamically estimating parameters and predicting ignition events.Cellular automata models,despite their potential,face challenges in data integration and computational demands.Conversely,ML models demonstrate superior efficiency and accuracy by leveraging diverse datasets,though they encounter interpretability issues.This review recommends hybrid modelling approaches that integrate multiple methods to harness their combined strengths.By incorporating data assimilation techniques with dynamic forecasting models,the predictive capabilities of ML-based predictions can be significantly enhanced.This review underscores the necessity for continued refinement of these models to ensure their reliability in real-world applications,ultimately contributing to more effective wildfire mitigation and management strategies.Future research should focus on improving hybrid models and exploring new data integration methods to advance predictive capabilities.
基金supported by the National Natural Science Foundation of China(32430083).
文摘The development of rodent models that accurately reflect the pathogenesis of alcoholic liver disease(ALD)in humans is crucial for evaluating the nutritional intervention of food bioactive ingredients in ALD.Although various models have been employed to establish ALD models over the past few decades,most successful cases are associated with high mortality rates,operational difficulties,and incompatibility formation mechanism compared to human ALD.However,the ALD models established by oral administration that simulate human drinking behavior often fail to induce significant liver damage.Therefore,it is imperative to explore simple and effective modes of oral administration for establishing ALD models consistent with the pathophysiological process of human ALD.Herein,we summarized the pathogenesis of ALD and discussed several issues related to construct ALD models with rodents(mainly mice and rats)by oral administration,including animal selection,animal feeding,alcohol intervention,and evaluation criteria.The purpose of this review is to provide a standardized and efficient formula for ALD modeling,so as to facilitate efficacy evaluation and mechanism analysis of food bioactive ingredients in ALD.
文摘This study examines the advent of agent interaction(AIx)as a transformative paradigm in humancomputer interaction(HCI),signifying a notable evolution beyond traditional graphical interfaces and touchscreen interactions.Within the context of large models,AIx is characterized by its innovative interaction patterns and a plethora of application scenarios that hold great potential.The paper highlights the pivotal role of AIx in shaping the future landscape of the large model industry,emphasizing its adoption and necessity from a user's perspective.This study underscores the pivotal role of AIx in dictating the future trajectory of a large model industry by emphasizing the importance of its adoption and necessity from a user-centric perspective.The fundamental drivers of AIx include the introduction of novel capabilities,replication of capabilities(both anthropomorphic and superhuman),migration of capabilities,aggregation of intelligence,and multiplication of capabilities.These elements are essential for propelling innovation,expanding the frontiers of capability,and realizing the exponential superposition of capabilities,thereby mitigating labor redundancy and addressing a spectrum of human needs.Furthermore,this study provides an in-depth analysis of the structural components and operational mechanisms of agents supported by large models.Such advancements significantly enhance the capacity of agents to tackle complex problems and provide intelligent services,thereby facilitating a more intuitive,adaptive,and personalized engagement between humans and machines.The study further delineates four principal categories of interaction patterns that encompass eight distinct modalities of interaction,corresponding to twenty-one specific scenarios,including applications in smart home systems,health assistance,and elderly care.This emphasizes the significance of this new paradigm in advancing HCI,fostering technological advancements,and redefining user experiences.However,it also acknowledges the challenges and ethical considerations that accompany this paradigm shift,recognizing the need for a balanced approach to harness the full potential of AIx in modern society.
基金the College of Pharmacy, Mustansiriyah University, for providing the necessary facilities and support to carry out this research.
文摘Background:There are many forms of anabolic steroids,including stanozolol(Winstrol),which are popular for their muscle-building effects but dangerous to the heart.This pre-sent work is aimed at evaluating the pharmacologica impact of allicin,a natural attribute obtained from garlic,on obstructing cardiac injury in rabbits that received stanozolol.Methods:Thirty rabbits were divided into three groups:control,stanozolol-treated,and stanozolol plus allicin.Cardiac function was assessed by measuring troponin,creatine kinase(CK),Galectin-3,and GDF-15.Oxidative stress and antioxidant markers,includ-ing malondialdehyde(MDA),glutathione,and catalase,were analyzed.Inflammatory mediators such as C-reactive protein(CRP),interleukin-6(IL-6),NF-κB,iNOS,nitric oxide(NO),tumor necrosis factor-alpha(TNF-α),and interleukin-1 beta(IL-1β)were evaluated.Lipid profile parameters,including total cholesterol,low-density lipoprotein(LDL),and high-density lipoprotein(HDL),were measured.Histopathological examina-tion assessed myocardial damage,fibrosis,and collagen deposition.Results:Stanozolol administration significantly increased cardiac damage markers,oxidative stress,and inflammatory mediators while causing dyslipidemia,characterized by elevated LDL and total cholesterol and reduced HDL.Allicin co-administration effectively countered these effects by reducing oxidative stress and inflammation,restoring antioxidant balance,and improving lipid profiles.Histopathological analysis revealed severe myocardial disor-ganization,necrosis,and fibrosis in the stanozolol group,whereas the allicin-treated group exhibited preserved myocardial structure with reduced collagen deposition.Conclusion:Allicin significantly mitigates stanozolol-induced cardiotoxicity by reduc-ing oxidative stress,inflammation,lipid dysregulation,and myocardial damage,as evidenced by biochemical and histopathological findings.These results suggest that allicin may serve as a potential therapeutic agent to counteract the cardiovascular risks associated with anabolic steroid use.
基金supported by the National Natural Science Foundation of China(Grant Nos.12202153 and 12072123).
文摘Non-Schmid(NS)effects in body-centered cubic(BCC)single-phase metals have received special attention in recent years.However,a deep understanding of these effects in the BCC phase of dual-phase(DP)steels has not yet been reached.This study explores the NS effects in ferrite-martensite DP steels,where the ferrite phase has a BCC crystallographic structure and exhibits NS effects.The influences of NS stress components on the mechanical response of DP steels are studied,including stress/strain partitioning,plastic flow,and yield surface.To this end,the mechanical behavior of the two phases is described by dislocation density-based crystal plasticity constitutive models,with the NS effect only incorporated into the ferrite phase modeling.The NS stress contribution is revealed for two types of microstructures commonly observed in DP steels:equiaxed phases with random grain orientations,and elongated phases with preferred grain orientations.Our results show that,in the case of a microstructure with equiaxed phases,the normal NS stress components play significant roles in tension-compression asymmetry.By contrast,in microstructures with elongated phases,a combined influence of crystallographic texture and NS effect is evident.These findings advance our knowledge of the intricate interplay between microstructural features and NS effects and help to elucidate the mechanisms underlying anisotropic-asymmetric plastic behavior of DP steels.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFA1405400)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301902),the National Natural Science Foundation of China(Grant No.12274290)the sponsor-ship from Yangyang Development Fund.
文摘We perform a comprehensive study of the electron-doped t-t′-J model on cylinders with density matrix renormalization group(DMRG).We conduct a systematic study on the finite-size and boundary condition effects on t-t′-J model on cylinders.Periodic and anti-periodic boundary conditions are implemented along the circumference direction,with the system’s width extending up to as large as 8 lattice units.We study doping levels of 1/6,1/8,and 1/12,which represent the most interesting region in the phase diagram of electron-doped cuprates.We find that for width-4 and width-6 systems,the ground state for fixed doping switches between anti-ferromagnetic Neel state and stripe state under different boundary conditions and system widths,indicating the presence of large finite size effect in the t-t′-J model.We also have a careful analysis of the d-wave pairing correlations which also change quantitatively with boundary conditions and widths of the system.However,the pairing correlations are enhanced when the system becomes wider for all dopings,suggesting the existence of possible long-range superconducting order in the thermodynamic limit.The width-8 results are found to be dependent on the starting state in the DMRG calculation for the kept states we can reach.For the width-8 system,only Neel(stripe)state can be stabilized in DMRG calculation for 1/12(1/6)doping,while both stripe and Neel states are stable in the DMRG sweep for 1/8 doping,regardless of the boundary conditions.These results indicate that 1/8 doping is likely to lie on the boundary of a phase transition between the Neel phase with lower doping and the stripe phase with higher doping,consistent with the previous study.The sensitivity of the ground state on boundary conditions and size observed for narrow systems is similar to that found in the t′-Hubbard model,where the t′term introduces frustration and makes the stripe state fragile.The study of different boundary conditions provides a useful tool to check the finite size effect in the future DMRG calculations.
文摘The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.
基金supported by the Anhui Provincial Major Science and Technology Project(No.201903c08020003)the Taishan industrial Experts Program。
文摘The application of a controllable neutron source for measuring formation porosity in the advancement of nuclear logging has garnered increased attention.The existing porosity algorithm,which is based on the thermal neutron counting ratio,exhibits lower sensitivity in high-porosity regions.To enhance the sensitivity,the effects of elastic and inelastic scattering,which influence the slowing-down of fast neutrons,were theoretically analyzed,and a slowing-down model of fast neutrons was created.Based on this model,a density correction porosity algorithm was proposed based on the relationship between density,thermal neutron counting ratio,and porosity.Finally,the super multifunctional calculation program for nuclear design and safety evaluation(TopMC/SuperMC)was used to create a simulation model for porosity logging,and its applicability was examined.The results demonstrated that the relative error between the calculated and actual porosities was less than 1%,and the influence of deviation in the density measurement was less than 2%.Therefore,the proposed density correction algorithm based on the slowing-down model of fast neutrons can effectively improve the sensitivity in the high-porosity region.This study is expected to serve as a reference for the application of neutron porosity measurements with D–T neutron sources.
