Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To thi...Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.展开更多
Dunhuang medicine is an important part of Dunhuang studies,boasting rich and comprehensive connotations.It records more than 1,000 Dunhuang medical prescriptions,involving internal,external,gynecological,pediatric,Bud...Dunhuang medicine is an important part of Dunhuang studies,boasting rich and comprehensive connotations.It records more than 1,000 Dunhuang medical prescriptions,involving internal,external,gynecological,pediatric,Buddhist,and Daoist medicine,and has demonstrated good clinical effects.However,the mechanism of action of relevant Dunhuang medical prescriptions is still unclear,existing research lacks systematic review and summarization,which has limited their further development.At the same time,the inheritance,innovation,and transformation of Dunhuang medicine are critical issues for the development of Dunhuang medicine,which has important guiding significance for the future development of Dunhuang medicine.Therefore,this study systematically summarizes the experimental research progress of Dunhuang medical prescriptions[except for those contained in Fu Xing Jue Zang Fu Yong Yao Fa Yao(《辅行诀脏腑用药法要》The Guideline to Use Medicines for Zang-fu)],and seven such prescriptions were selected based on three criteria:well-preserved texts,no prior transmission to the outside world,and having extensive research and clinical application over the past decade.The findings indicate that this type of prescription is applicable to a broad spectrum of diseases and has a promising application prospect in health preservation and disease prevention,as it exerts therapeutic effects through multiple targets and pathways.Based on this,specific strategies for the transformation of Dunhuang characteristic prescriptions were proposed from three aspects:inheritance,innovative development,and transformation strategies,aiming to provide insights for the future development of Dunhuang medical prescriptions.展开更多
Doping plays a pivotal role in enhancing the performance of organic semiconductors(OSCs)for advanced optoelectronic and thermoelectric applications.In this study,we systematically investigated the doping performance a...Doping plays a pivotal role in enhancing the performance of organic semiconductors(OSCs)for advanced optoelectronic and thermoelectric applications.In this study,we systematically investigated the doping performance and applicability of the ionic dopant 4-isopropyl-4′-methyldiphenyliodonium tetrakis(penta-fluorophenyl-borate)(DPI-TPFB)as a p-dopant for OSCs.Using the p-type OSC PBBT-2T as a model system,we demonstrated that DPI-TPFB shows significant doping effect,as confirmed by ESR spectra,ultraviolet-visible-near-infrared(UV-vis-NIR)absorption,and work function analysis,and enhances the electronic conductivity of PBBT-2T films by over four orders of magnitude.Furthermore,DPI-TPFB exhibited broad doping applicability,effectively doping various p-type OSCs and even imparting p-type characteristics to the n-type OSC N2200,transforming its intrinsic n-type behavior into p-type.The application of DPI-TPFB-doped PBBT-2T films in organic thermoelectric devices(OTEs)was also explored,achieving a power factor of approximately 10μW·m^(-1)·K^(-2).These findings highlight the potential of DPI-TPFB as a versatile and efficient dopant for integration into organic optoelectronic and thermoelectric devices.展开更多
Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interact...Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.展开更多
Background:The development of gastric cancer(GC)encompasses precancerous conditions like chronic atrophic gastritis(CAG)and premalignant lesions of gastric cancer(PLGC).In these situations,abnormal Notch signaling res...Background:The development of gastric cancer(GC)encompasses precancerous conditions like chronic atrophic gastritis(CAG)and premalignant lesions of gastric cancer(PLGC).In these situations,abnormal Notch signaling results in mucosal impairment and the initiation of cancer.Banxia Xiexin Decoction(BXD),a well-known formula in traditional Chinese medicine(TCM),shows promise in treating gastric disorders,but its mechanisms in gastric restoration remain unclear.Methods:Using MNNG-induced CAG and PLGC rat models,BXD was administered for 12 weeks.Gastric mucosal pathology was assessed via hematoxylin-eosin staining.Proliferation(Ki-67)and angiogenesis(VEGFA)markers were evaluated by immunohistochemistry.Network pharmacology identified BXD’s targets and pathways.Notch pathway components(Notch1,Jagged1,Dll4,Hes1)were analyzed via qPCR,Western blot,and immunohistochemistry.Results:BXD significantly ameliorated mucosal atrophy,glandular structural disorder,and dysplasia in CAG and PLGC rats.Network pharmacology revealed 323 overlapping targets between BXD and PLGC,with Notch signaling as a central pathway.BXD downregulated Notch1,Jagged1,Dll4,and Hes1 expression at transcriptional and protein levels,suppressed Ki-67(proliferation)and VEGFA(angiogenesis)overexpression,and restored gastric mucosal integrity.Conclusion:BXD inhibits Notch signaling,reduces aberrant proliferation and angiogenesis,and interrupts Correa’s gastric carcinogenesis cascade.This study provides mechanistic evidence supporting BXD as a TCM-based intervention for gastric precancerous lesions.展开更多
Rockfall hazards pose significant risks to both cultural heritage and populated areas,necessitating comprehensive assessment methodologies.Despite extensive research on rockfalls,only a small number of studies have di...Rockfall hazards pose significant risks to both cultural heritage and populated areas,necessitating comprehensive assessment methodologies.Despite extensive research on rockfalls,only a small number of studies have directly compared empirical methods with modelling approaches.This study investigated rockfalls in five settlements within the Cappadocia region of Türkiye,employing both empirical methods and advanced three-dimensional(3D)probabilistic modeling.The energy line angle approach was applied to identify rockfall propagation zones,while high-resolution digital surface models derived from unmanned aerial vehicle(UAV)imagery facilitated detailed 3D rockfall simulations.Cappadocia’s unique geological setting—comprising alternating layers of ignimbrites and weaker fluviolacustrine deposits—renders it highly susceptible to rockfalls intensified by wetting-drying and freeze-thaw cycles.Results indicate that rockfall propagation characteristics vary markedly between settlements:Göre and Tatlarin exhibit shorter runout distances due to basalt-dominated slopes,whereas Akköy,SoğanlıandŞahinefendi display longer trajectories associated with welded ignimbrites.Empirical cone propagation analyses correspond broadly with field observations,but variations in energy line angles(23°-33°)highlight the necessity for site-specific calibration.Comparative evaluations demonstrate that 3D probabilistic modeling better captures local-scale block dynamics and identifies high-risk areas affected by topographic and structural features such as rockfall ditches.These findings emphasize the importance of integrating empirical and 3D approaches to improve hazard zoning,optimize mitigation structures and guide the protection of Cappadocia’s unique cultural heritage landscape.展开更多
Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal ce...Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal cells(MSCs)exhibited greater therapeutic efficacy than CD146-MSCs.These cells enhance epithelial repair through nuclear factor kappa B/cyclooxygenase-2-associated paracrine signaling and secretion of pro-angiogenic factors.We concur that MSCs hold significant promise for ARDS treatment;however,the heterogeneity of cell products is a translational barrier.Phenotype-aware strategies,such as CD146 enrichment,standardized potency assays,and extracellular vesicle profiling,are essential for improving the consistency of these studies.Further-more,advanced preclinical models,such as lung-on-a-chip systems,may provide more predictive insights into the therapeutic mechanisms.This article underscores the importance of CD146+MSCs in ARDS,emphasizes the need for precision in defining cell products,and discusses how integrating subset selection into translational pipelines could enhance the clinical impact of MSC-based therapies.展开更多
Premenstrual dysphoric disorder(PMDD),a subtype of premenstrual syndrome(PMS),involves physical and emotional symptoms that impact patients'daily lives and productivity.A reliable,side-effect-free clinical interve...Premenstrual dysphoric disorder(PMDD),a subtype of premenstrual syndrome(PMS),involves physical and emotional symptoms that impact patients'daily lives and productivity.A reliable,side-effect-free clinical intervention is needed.Shuyu capsule is an effective traditional Chinese medicine preparation for PMDD used in the clinics,but its therapeutic mechanism remains unclear.Previous research has suggested that theγ-aminobutyric acidergic(GABAergic)system in the periaqueductal gray(PAG)may play a role in treating PMDD with traditional Chinese medicine,but there is a lack of functional verification.This study aims to reveal the potential mechanism of the Shuyu capsule in treating PMDD.The study employed an experimental design using female C57BL/6J and Vgat-Cre mice to assess the effects of Shuyu capsules on PMDD,with a focus on the GABAergic system in the dorsal PAG(dPAG).Assessments were conducted using the forced swimming test(FST)to gauge depression-like behaviors and western blot(WB)and immunofluorescence(IF)to measure the numbers of active GABAergic neurons and theγ-aminobutyric acid type A receptor(GABA,R)δsubunit(GABRD)expression.Chemogenetic techniques and adeno-associated virus were specifically used to activate GABAergic neurons and knock down the expression of subunits,respectively,providing insights into the neurobiological mechanisms underpinning the therapeutic effects of Shuyu capsules in treating PMDD.After being stressed by FST,the immobility duration of PMDD mice in the late dioestrus(LD)phase decreased after the Shuyu capsule intervention,implying that it can improve the estrous cycle-dependent depression-like phenotype in PMDD mice.Additionally,the application of Shuyu capsule can downregulate the expression of GABRD and reverse the downtrend of activated GABAergic neurons in the dPAG of PMDD model mice.We also found that single-target manipulation was enough to improve the depressionlike behavior of PMDD model mice.Transgenic mice with GABRD knockout were established,and their behaviors were tested,revealing changes in their exploratory behaviors,indicating that the GABRD may be closely related to anxiety disorders.Shuyu capsule plays an anti-PMDD role by activating GABAergic neurons and downregulating the expression of GABRD in the dPAG.This provides a theoretical basis for the clinical treatment of PMDD with traditional Chinese medicine and promotes the development of drugs for treating PMDD.展开更多
Remote sensing technology has long been used to detect and map crop diseases.Airborne and satellite imagery acquired during growing seasons can be used not only for early detection and within-season management of some...Remote sensing technology has long been used to detect and map crop diseases.Airborne and satellite imagery acquired during growing seasons can be used not only for early detection and within-season management of some crop diseases,but also for the control of recurring diseases in future seasons.With variable rate technology in precision agriculture,site-specific fungicide application can be made to infested areas if the disease is stable,although traditional uniform application is more appropriate for diseases that can spread rapidly across the field.This article provides a brief overview of remote sensing and precision agriculture technologies that have been used for crop disease detection and management.Specifically,the article illustrates how airborne and satellite imagery and variable rate technology have been used for detecting and mapping cotton root rot,a destructive soilborne fungal disease,in cotton fields and how site-specific fungicide application has been implemented using prescription maps derived from the imagery for effective control of the disease.The overview and methodologies presented in this article should provide researchers,extension personnel,growers,crop consultants,and farm equipment and chemical dealers with practical guidelines for remote sensing detection and effective management of some crop diseases.展开更多
Numerous researches have been published on the application of landslide susceptibility assessment models;however,they were only applied in the same areas as the models were originated,the effect of applying the models...Numerous researches have been published on the application of landslide susceptibility assessment models;however,they were only applied in the same areas as the models were originated,the effect of applying the models to other areas than the origin of the models has not been explored.This study is purposed to develop an optimized random forest(RF)model with best ratios of positive-to-negative cells and 10-fold cross-validation for landslide susceptibility mapping(LSM),and then explore its generalization ability not only in the area where the model is originated but also in area other than the origin of the model.Two typical counties(Fengjie County and Wushan County)in the Three Gorges Reservoir area,China,which have the same terrain and geological conditions,were selected as an example.To begin with,landslide inventory was prepared based on field investigations,satellite images,and historical records,and 1522 landslides were then identified in Fengjie County.22 landslide-conditioning factors under the influence of topography,geology,environmental conditions,and human activities were prepared.Then,combined with 10-fold cross-validation,three typical ratios of positive-to-negative cells,i.e.,1:1,1:5,and 1:10,were adopted for comparative analyses.An optimized RF model(Fengjie-based model)with the best ratios of positive-to-negative cells and 10-fold cross-validation was constructed.Finally,the Fengjie-based model was applied to Fengjie County and Wushan County,and the confusion matrix and area under the receiver operating characteristic(ROC)curve value(AUC)were used to estimate the accuracy.The Fengjie-based model delivered high stability and predictive capability in Fengjie County,indicating a great generalization ability of the model to the area where the model is originated.The LSM in Wushan County generated by the Fengjie-based model had a reasonable reference value,indicating the Fengjiebased model had a great generalization ability in area other than the origin of the model.The Fengjiebased model in this study could be applied in other similar areas/countries with the same terrain and geological conditions,and a LSM may be generated without collecting landslide information for modeling,so as to reduce workload and improve efficiency in practice.展开更多
Existing satellite microwave algorithms for retrieving Sea Surface Temperature （SST） and Wind （SSW） are applicable primarily for non-raining cloudy conditions. With the launch of the Earth Observing System （EOS）...Existing satellite microwave algorithms for retrieving Sea Surface Temperature （SST） and Wind （SSW） are applicable primarily for non-raining cloudy conditions. With the launch of the Earth Observing System （EOS） Aqua satellite in 2002, the Advanced Microwave Scanning Radiometer （AMSRoE） onboard provides some unique measurements at lower frequencies which are sensitive to ocean surface parameters under adverse weather conditions. In this study, a new algorithm is developed to derive SST and SSW for hurricane predictions such as hurricane vortex analysis from the AMSRoE measurements at 6.925 and 10.65 GHz. In the algorithm, the effects of precipitation emission and scattering on the measurements are properly taken into account. The algorithm performances are evaluated with buoy measurements and aircraft dropsonde data. It is found that the root mean square （RMS） errors for SST and SSW are about 1.8 K and 1.9 m s^- 1, respectively, when the results are compared with the buoy data over open oceans under precipitating clouds （e.g., its liquid water path is larger than 0.5 mm）, while they are 1.1 K for SST and 2.0 m s^-1 for SSW, respectively, when the retrievals are validated against the dropsonde measurements over warm oceans. These results indicate that our newly developed algorithm can provide some critical surface information for tropical cycle predictions. Currently, this newly developed algorithm has been implemented into the hybrid variational scheme for the hurricane vortex analysis to provide predictions of SST and SSW fields.展开更多
Intuitionistic hesitant fuzzy set(IHFS)is amixture of two separated notions called intuitionistic fuzzy set(IFS)and hesitant fuzzy set(HFS),as an important technique to cope with uncertain and awkward information in r...Intuitionistic hesitant fuzzy set(IHFS)is amixture of two separated notions called intuitionistic fuzzy set(IFS)and hesitant fuzzy set(HFS),as an important technique to cope with uncertain and awkward information in realistic decision issues.IHFS contains the grades of truth and falsity in the formof the subset of the unit interval.The notion of IHFS was defined by many scholars with different conditions,which contain several weaknesses.Here,keeping in view the problems of already defined IHFSs,we will define IHFS in another way so that it becomes compatible with other existing notions.To examine the interrelationship between any numbers of IHFSs,we combined the notions of power averaging(PA)operators and power geometric(PG)operators with IHFSs to present the idea of intuitionistic hesitant fuzzy PA(IHFPA)operators,intuitionistic hesitant fuzzy PG(IHFPG)operators,intuitionistic hesitant fuzzy power weighted average(IHFPWA)operators,intuitionistic hesitant fuzzy power ordered weighted average(IHFPOWA)operators,intuitionistic hesitant fuzzy power ordered weighted geometric(IHFPOWG)operators,intuitionistic hesitant fuzzy power hybrid average(IHFPHA)operators,intuitionistic hesitant fuzzy power hybrid geometric(IHFPHG)operators and examined as well their fundamental properties.Some special cases of the explored work are also discovered.Additionally,the similarity measures based on IHFSs are presented and their advantages are discussed along examples.Furthermore,we initiated a new approach to multiple attribute decision making(MADM)problem applying suggested operators and a mathematical model is solved to develop an approach and to establish its common sense and adequacy.Advantages,comparative analysis,and graphical representation of the presented work are elaborated to show the reliability and effectiveness of the presented works.展开更多
Tbeacrine （1,3,7,9-tetramethyluric acid）, a purine alkaloid similar to caffeine in its chemical structure, is isolated from edible Camellia assamica vat. kucha and has various pharmacological activities including hy...Tbeacrine （1,3,7,9-tetramethyluric acid）, a purine alkaloid similar to caffeine in its chemical structure, is isolated from edible Camellia assamica vat. kucha and has various pharmacological activities including hypnotic effects, anti-depressant effects, anti-inflammatory and analgesic effects, and a protective effect against stress-provoked liver damage. A rapid and simple assay is required to quantify theacrine in biological samples for pharmacokinetic studies in small animals. This study aimed to establish an enzyme-linked immunosorbent assay （ELISA） for theacrine quantification in blood. Herein, we successfully obtained monoclonal antibodies （MAbs） against theacrine, MAbs C11B5, and developed an ELISA method for the fast determination of theacrine in mouse blood. The range for calibration of theacrine by ELISA was 0.156-100 μg mL-1. The half maximum inhibitory concentration （IC50） value was 1.55 μg mL-1. The ELISA method lays a good foundation for the further research.展开更多
Aiming at the kitchen stain and fast growth of dishwasher market in China,the addition of protease and amylase solution in the dishwasher detergents was proposed for the food stains typical in China.A comparison betwe...Aiming at the kitchen stain and fast growth of dishwasher market in China,the addition of protease and amylase solution in the dishwasher detergents was proposed for the food stains typical in China.A comparison between Chinese commercial dishwasher detergents and an EU mainstream detergent was made.The results indicated that the addition of protease and amylase could significantly increase the washing performance,and thus could help close the washing performance gap between our products and the EU mainstream product.展开更多
The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering analysis.To address this issue,this paper introduces ...The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering analysis.To address this issue,this paper introduces a new method named Big Data Tensor Multi-Cluster Distributed Incremental Update(BDTMCDIncreUpdate),which combines distributed computing,storage technology,and incremental update techniques to provide an efficient and effective means for clustering analysis.Firstly,the original dataset is divided into multiple subblocks,and distributed computing resources are utilized to process the sub-blocks in parallel,enhancing efficiency.Then,initial clustering is performed on each sub-block using tensor-based multi-clustering techniques to obtain preliminary results.When new data arrives,incremental update technology is employed to update the core tensor and factor matrix,ensuring that the clustering model can adapt to changes in data.Finally,by combining the updated core tensor and factor matrix with historical computational results,refined clustering results are obtained,achieving real-time adaptation to dynamic data.Through experimental simulation on the Aminer dataset,the BDTMCDIncreUpdate method has demonstrated outstanding performance in terms of accuracy(ACC)and normalized mutual information(NMI)metrics,achieving an accuracy rate of 90%and an NMI score of 0.85,which outperforms existing methods such as TClusInitUpdate and TKLClusUpdate in most scenarios.Therefore,the BDTMCDIncreUpdate method offers an innovative solution to the field of big data analysis,integrating distributed computing,incremental updates,and tensor-based multi-clustering techniques.It not only improves the efficiency and scalability in processing large-scale high-dimensional datasets but also has been validated for its effectiveness and accuracy through experiments.This method shows great potential in real-world applications where dynamic data growth is common,and it is of significant importance for advancing the development of data analysis technology.展开更多
Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the int...Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the intensity of summer precipitation is often largely underestimated in many current dynamic models.This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)method.Using the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model predictions.This study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.展开更多
A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study em...A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.展开更多
Marine heatwaves(MHWs),which can exert devastating socioeconomic and ecological impacts,have attracted much public interest in recent years.In this study,we evaluate the sub-seasonal forecast skill of MHWs based on th...Marine heatwaves(MHWs),which can exert devastating socioeconomic and ecological impacts,have attracted much public interest in recent years.In this study,we evaluate the sub-seasonal forecast skill of MHWs based on the Nanjing University of Information Science&Technology Climate Forecast System version 1.1(NUIST CFS1.1)and analyze the related physical processes.Our results show that the model can accurately forecast the occurrence of MHWs on a global scale out to a lead time of 25 days.Notably,even at lead times of 51–55 days,the forecast skill in most tropical regions,as well as in the northeastern and southeastern Pacific,is superior to both random forecasts and persistence forecasts.Accurate predictions of sea level pressure,zonal currents,and mixed-layer depth are important for MHW forecasting.Furthermore,we also conduct forecast skill assessments for two well-documented MHW events.Due to its ability to correctly forecast the changes in heat flux anomalies at a lead time of 25 days,the model can accurately forecast the strong MHW event that occurred in the South China Sea in May–October 2020.However,the forecasting results were less than optimal for the strong MHW event that occurred along the Australian west coast in January–April 2011.Although the model accurately forecasts its occurrence,the forecast of its intensity is poor.Additionally,when the lead time exceeds 10 days,forecasts of the relevant physical processes of this MHW event are also inaccurate.展开更多
Diatomic metasurfaces designed for interferometric mechanisms possess significant potential for the multidimensional manipulation of electromagnetic waves,including control over amplitude,phase,frequency,and polarizat...Diatomic metasurfaces designed for interferometric mechanisms possess significant potential for the multidimensional manipulation of electromagnetic waves,including control over amplitude,phase,frequency,and polarization.Geometric phase profiles with spin-selective properties are commonly associated with wavefront modulation,allowing the implementation of conjugate strategies within orthogonal circularly polarized channels.Simultaneous control of these characteristics in a single-layered diatomic metasurface will be an apparent technological extension.Here,spin-selective modulation of terahertz(THz)beams is realized by assembling a pair of meta-atoms with birefringent effects.The distinct modulation functions arise from geometric phase profiles characterized by multiple rotational properties,which introduce independent parametric factors that elucidate their physical significance.By arranging the key parameters,the proposed design strategy can be employed to realize independent amplitude and phase manipulation.A series of THz metasurface samples with specific modulation functions are characterized,experimentally demonstrating the accuracy of on-demand manipulation.This research paves the way for all-silicon meta-optics that may have great potential in imaging,sensing and detection.展开更多
基金funded by“The Factors Affecting the Accuracy of Wind Resource Assessment and Comprehensive Post-Evaluation Techniques for Operating Wind Power Projects,”grant number YJ24.002“The Research and Application of Future Medium to Long Term Wind Resource Assessment for Wind Farms Based on Artificial Intelligence Project,”grant number 2023021。
文摘Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.
基金financed by the grants from Dunhuang Medical Literature Compilation and Application Research Center Project of Gansu Provincial Key Research Base for Humanities and Social Sciences(No.DHYXJD2025)National Social Science Fund General Project(No.22BYY038).
文摘Dunhuang medicine is an important part of Dunhuang studies,boasting rich and comprehensive connotations.It records more than 1,000 Dunhuang medical prescriptions,involving internal,external,gynecological,pediatric,Buddhist,and Daoist medicine,and has demonstrated good clinical effects.However,the mechanism of action of relevant Dunhuang medical prescriptions is still unclear,existing research lacks systematic review and summarization,which has limited their further development.At the same time,the inheritance,innovation,and transformation of Dunhuang medicine are critical issues for the development of Dunhuang medicine,which has important guiding significance for the future development of Dunhuang medicine.Therefore,this study systematically summarizes the experimental research progress of Dunhuang medical prescriptions[except for those contained in Fu Xing Jue Zang Fu Yong Yao Fa Yao(《辅行诀脏腑用药法要》The Guideline to Use Medicines for Zang-fu)],and seven such prescriptions were selected based on three criteria:well-preserved texts,no prior transmission to the outside world,and having extensive research and clinical application over the past decade.The findings indicate that this type of prescription is applicable to a broad spectrum of diseases and has a promising application prospect in health preservation and disease prevention,as it exerts therapeutic effects through multiple targets and pathways.Based on this,specific strategies for the transformation of Dunhuang characteristic prescriptions were proposed from three aspects:inheritance,innovative development,and transformation strategies,aiming to provide insights for the future development of Dunhuang medical prescriptions.
基金supported by the Fundamental Research Program of Shanxi Province(Nos.202303021212159 and 202303021222190)the National Natural Science Foundation of China(No.62222403)+2 种基金the Higher Education Institutions Science and Technology Innovation Program of Shanxi Province(No.2023L160)the Scientific Research Fund of Hunan Provincial Education Department(No.23B0842)the Natural Science Foundation of Shanxi Normal University(Nos.JCYJ2024017 and JCYJ2023015)。
文摘Doping plays a pivotal role in enhancing the performance of organic semiconductors(OSCs)for advanced optoelectronic and thermoelectric applications.In this study,we systematically investigated the doping performance and applicability of the ionic dopant 4-isopropyl-4′-methyldiphenyliodonium tetrakis(penta-fluorophenyl-borate)(DPI-TPFB)as a p-dopant for OSCs.Using the p-type OSC PBBT-2T as a model system,we demonstrated that DPI-TPFB shows significant doping effect,as confirmed by ESR spectra,ultraviolet-visible-near-infrared(UV-vis-NIR)absorption,and work function analysis,and enhances the electronic conductivity of PBBT-2T films by over four orders of magnitude.Furthermore,DPI-TPFB exhibited broad doping applicability,effectively doping various p-type OSCs and even imparting p-type characteristics to the n-type OSC N2200,transforming its intrinsic n-type behavior into p-type.The application of DPI-TPFB-doped PBBT-2T films in organic thermoelectric devices(OTEs)was also explored,achieving a power factor of approximately 10μW·m^(-1)·K^(-2).These findings highlight the potential of DPI-TPFB as a versatile and efficient dopant for integration into organic optoelectronic and thermoelectric devices.
基金supported by the National Key R&D Program of China[2022YFF0902703]the State Administration for Market Regulation Science and Technology Plan Project(2024MK033).
文摘Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.
基金supported by the National Natural Science Foundation of China(Grant No.82274442)the Key Research Project in Traditional Chinese Medicine of Tianjin Municipal Health Commission(Grant No.202007)the Integrated Traditional Chinese and Western Medicine Research Project of Tianjin Municipal Health Commission(Grant No.2023134).
文摘Background:The development of gastric cancer(GC)encompasses precancerous conditions like chronic atrophic gastritis(CAG)and premalignant lesions of gastric cancer(PLGC).In these situations,abnormal Notch signaling results in mucosal impairment and the initiation of cancer.Banxia Xiexin Decoction(BXD),a well-known formula in traditional Chinese medicine(TCM),shows promise in treating gastric disorders,but its mechanisms in gastric restoration remain unclear.Methods:Using MNNG-induced CAG and PLGC rat models,BXD was administered for 12 weeks.Gastric mucosal pathology was assessed via hematoxylin-eosin staining.Proliferation(Ki-67)and angiogenesis(VEGFA)markers were evaluated by immunohistochemistry.Network pharmacology identified BXD’s targets and pathways.Notch pathway components(Notch1,Jagged1,Dll4,Hes1)were analyzed via qPCR,Western blot,and immunohistochemistry.Results:BXD significantly ameliorated mucosal atrophy,glandular structural disorder,and dysplasia in CAG and PLGC rats.Network pharmacology revealed 323 overlapping targets between BXD and PLGC,with Notch signaling as a central pathway.BXD downregulated Notch1,Jagged1,Dll4,and Hes1 expression at transcriptional and protein levels,suppressed Ki-67(proliferation)and VEGFA(angiogenesis)overexpression,and restored gastric mucosal integrity.Conclusion:BXD inhibits Notch signaling,reduces aberrant proliferation and angiogenesis,and interrupts Correa’s gastric carcinogenesis cascade.This study provides mechanistic evidence supporting BXD as a TCM-based intervention for gastric precancerous lesions.
基金financially supported by The Scientific and Technological Research Council of Türkiye(T??B1TAK)with the project number 121C420。
文摘Rockfall hazards pose significant risks to both cultural heritage and populated areas,necessitating comprehensive assessment methodologies.Despite extensive research on rockfalls,only a small number of studies have directly compared empirical methods with modelling approaches.This study investigated rockfalls in five settlements within the Cappadocia region of Türkiye,employing both empirical methods and advanced three-dimensional(3D)probabilistic modeling.The energy line angle approach was applied to identify rockfall propagation zones,while high-resolution digital surface models derived from unmanned aerial vehicle(UAV)imagery facilitated detailed 3D rockfall simulations.Cappadocia’s unique geological setting—comprising alternating layers of ignimbrites and weaker fluviolacustrine deposits—renders it highly susceptible to rockfalls intensified by wetting-drying and freeze-thaw cycles.Results indicate that rockfall propagation characteristics vary markedly between settlements:Göre and Tatlarin exhibit shorter runout distances due to basalt-dominated slopes,whereas Akköy,SoğanlıandŞahinefendi display longer trajectories associated with welded ignimbrites.Empirical cone propagation analyses correspond broadly with field observations,but variations in energy line angles(23°-33°)highlight the necessity for site-specific calibration.Comparative evaluations demonstrate that 3D probabilistic modeling better captures local-scale block dynamics and identifies high-risk areas affected by topographic and structural features such as rockfall ditches.These findings emphasize the importance of integrating empirical and 3D approaches to improve hazard zoning,optimize mitigation structures and guide the protection of Cappadocia’s unique cultural heritage landscape.
基金the Scientific and Technological Research Council of Türkiye(TÜBİTAK)Under the International Postdoctoral Research Fellowship Program(2219),No.1059B192400980the National Postdoctoral Research Fellowship Program(2218),No.122C158.
文摘Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal cells(MSCs)exhibited greater therapeutic efficacy than CD146-MSCs.These cells enhance epithelial repair through nuclear factor kappa B/cyclooxygenase-2-associated paracrine signaling and secretion of pro-angiogenic factors.We concur that MSCs hold significant promise for ARDS treatment;however,the heterogeneity of cell products is a translational barrier.Phenotype-aware strategies,such as CD146 enrichment,standardized potency assays,and extracellular vesicle profiling,are essential for improving the consistency of these studies.Further-more,advanced preclinical models,such as lung-on-a-chip systems,may provide more predictive insights into the therapeutic mechanisms.This article underscores the importance of CD146+MSCs in ARDS,emphasizes the need for precision in defining cell products,and discusses how integrating subset selection into translational pipelines could enhance the clinical impact of MSC-based therapies.
基金supported by the National Natural Science Foundation of China(No.81974553)the High Level Key Disciplines of Traditional Chinese Medicine:Basic Theory of Traditional Chinese Medicine,National Administration of Traditional Chinese Medicine(No.zyyzdxk-2023118)+3 种基金the Special Funding for the Taishan Scholars Project(Nos.tsqn202211137,tsqn201909186,and tsqn202211355)the Natural Science Foundation of Shandong Province(Nos.ZR2020ZD17 and ZR2021LZY018)the City-School Integration Development Strategy Project of Jinan City(No.JNSX2023056)the Chinese Medicine and Brain Science Youth Scientific Research Innovation Team,Shandong University of Traditional Chinese Medicine(No.22202101),China.
文摘Premenstrual dysphoric disorder(PMDD),a subtype of premenstrual syndrome(PMS),involves physical and emotional symptoms that impact patients'daily lives and productivity.A reliable,side-effect-free clinical intervention is needed.Shuyu capsule is an effective traditional Chinese medicine preparation for PMDD used in the clinics,but its therapeutic mechanism remains unclear.Previous research has suggested that theγ-aminobutyric acidergic(GABAergic)system in the periaqueductal gray(PAG)may play a role in treating PMDD with traditional Chinese medicine,but there is a lack of functional verification.This study aims to reveal the potential mechanism of the Shuyu capsule in treating PMDD.The study employed an experimental design using female C57BL/6J and Vgat-Cre mice to assess the effects of Shuyu capsules on PMDD,with a focus on the GABAergic system in the dorsal PAG(dPAG).Assessments were conducted using the forced swimming test(FST)to gauge depression-like behaviors and western blot(WB)and immunofluorescence(IF)to measure the numbers of active GABAergic neurons and theγ-aminobutyric acid type A receptor(GABA,R)δsubunit(GABRD)expression.Chemogenetic techniques and adeno-associated virus were specifically used to activate GABAergic neurons and knock down the expression of subunits,respectively,providing insights into the neurobiological mechanisms underpinning the therapeutic effects of Shuyu capsules in treating PMDD.After being stressed by FST,the immobility duration of PMDD mice in the late dioestrus(LD)phase decreased after the Shuyu capsule intervention,implying that it can improve the estrous cycle-dependent depression-like phenotype in PMDD mice.Additionally,the application of Shuyu capsule can downregulate the expression of GABRD and reverse the downtrend of activated GABAergic neurons in the dPAG of PMDD model mice.We also found that single-target manipulation was enough to improve the depressionlike behavior of PMDD model mice.Transgenic mice with GABRD knockout were established,and their behaviors were tested,revealing changes in their exploratory behaviors,indicating that the GABRD may be closely related to anxiety disorders.Shuyu capsule plays an anti-PMDD role by activating GABAergic neurons and downregulating the expression of GABRD in the dPAG.This provides a theoretical basis for the clinical treatment of PMDD with traditional Chinese medicine and promotes the development of drugs for treating PMDD.
文摘Remote sensing technology has long been used to detect and map crop diseases.Airborne and satellite imagery acquired during growing seasons can be used not only for early detection and within-season management of some crop diseases,but also for the control of recurring diseases in future seasons.With variable rate technology in precision agriculture,site-specific fungicide application can be made to infested areas if the disease is stable,although traditional uniform application is more appropriate for diseases that can spread rapidly across the field.This article provides a brief overview of remote sensing and precision agriculture technologies that have been used for crop disease detection and management.Specifically,the article illustrates how airborne and satellite imagery and variable rate technology have been used for detecting and mapping cotton root rot,a destructive soilborne fungal disease,in cotton fields and how site-specific fungicide application has been implemented using prescription maps derived from the imagery for effective control of the disease.The overview and methodologies presented in this article should provide researchers,extension personnel,growers,crop consultants,and farm equipment and chemical dealers with practical guidelines for remote sensing detection and effective management of some crop diseases.
基金the National Natural Science Foundation of China(No.41807498)the National Key Research and Development Program of China(No.2018YFC1505501)the Humanities and Social Sciences Foundation of the Ministry of Education of China(No.20XJAZH002)。
文摘Numerous researches have been published on the application of landslide susceptibility assessment models;however,they were only applied in the same areas as the models were originated,the effect of applying the models to other areas than the origin of the models has not been explored.This study is purposed to develop an optimized random forest(RF)model with best ratios of positive-to-negative cells and 10-fold cross-validation for landslide susceptibility mapping(LSM),and then explore its generalization ability not only in the area where the model is originated but also in area other than the origin of the model.Two typical counties(Fengjie County and Wushan County)in the Three Gorges Reservoir area,China,which have the same terrain and geological conditions,were selected as an example.To begin with,landslide inventory was prepared based on field investigations,satellite images,and historical records,and 1522 landslides were then identified in Fengjie County.22 landslide-conditioning factors under the influence of topography,geology,environmental conditions,and human activities were prepared.Then,combined with 10-fold cross-validation,three typical ratios of positive-to-negative cells,i.e.,1:1,1:5,and 1:10,were adopted for comparative analyses.An optimized RF model(Fengjie-based model)with the best ratios of positive-to-negative cells and 10-fold cross-validation was constructed.Finally,the Fengjie-based model was applied to Fengjie County and Wushan County,and the confusion matrix and area under the receiver operating characteristic(ROC)curve value(AUC)were used to estimate the accuracy.The Fengjie-based model delivered high stability and predictive capability in Fengjie County,indicating a great generalization ability of the model to the area where the model is originated.The LSM in Wushan County generated by the Fengjie-based model had a reasonable reference value,indicating the Fengjiebased model had a great generalization ability in area other than the origin of the model.The Fengjiebased model in this study could be applied in other similar areas/countries with the same terrain and geological conditions,and a LSM may be generated without collecting landslide information for modeling,so as to reduce workload and improve efficiency in practice.
文摘Existing satellite microwave algorithms for retrieving Sea Surface Temperature （SST） and Wind （SSW） are applicable primarily for non-raining cloudy conditions. With the launch of the Earth Observing System （EOS） Aqua satellite in 2002, the Advanced Microwave Scanning Radiometer （AMSRoE） onboard provides some unique measurements at lower frequencies which are sensitive to ocean surface parameters under adverse weather conditions. In this study, a new algorithm is developed to derive SST and SSW for hurricane predictions such as hurricane vortex analysis from the AMSRoE measurements at 6.925 and 10.65 GHz. In the algorithm, the effects of precipitation emission and scattering on the measurements are properly taken into account. The algorithm performances are evaluated with buoy measurements and aircraft dropsonde data. It is found that the root mean square （RMS） errors for SST and SSW are about 1.8 K and 1.9 m s^- 1, respectively, when the results are compared with the buoy data over open oceans under precipitating clouds （e.g., its liquid water path is larger than 0.5 mm）, while they are 1.1 K for SST and 2.0 m s^-1 for SSW, respectively, when the retrievals are validated against the dropsonde measurements over warm oceans. These results indicate that our newly developed algorithm can provide some critical surface information for tropical cycle predictions. Currently, this newly developed algorithm has been implemented into the hybrid variational scheme for the hurricane vortex analysis to provide predictions of SST and SSW fields.
基金supported by“Algebra and Applications Research Unit,Division of Computational Science,Faculty of Science,Prince of Songkla University”.
文摘Intuitionistic hesitant fuzzy set(IHFS)is amixture of two separated notions called intuitionistic fuzzy set(IFS)and hesitant fuzzy set(HFS),as an important technique to cope with uncertain and awkward information in realistic decision issues.IHFS contains the grades of truth and falsity in the formof the subset of the unit interval.The notion of IHFS was defined by many scholars with different conditions,which contain several weaknesses.Here,keeping in view the problems of already defined IHFSs,we will define IHFS in another way so that it becomes compatible with other existing notions.To examine the interrelationship between any numbers of IHFSs,we combined the notions of power averaging(PA)operators and power geometric(PG)operators with IHFSs to present the idea of intuitionistic hesitant fuzzy PA(IHFPA)operators,intuitionistic hesitant fuzzy PG(IHFPG)operators,intuitionistic hesitant fuzzy power weighted average(IHFPWA)operators,intuitionistic hesitant fuzzy power ordered weighted average(IHFPOWA)operators,intuitionistic hesitant fuzzy power ordered weighted geometric(IHFPOWG)operators,intuitionistic hesitant fuzzy power hybrid average(IHFPHA)operators,intuitionistic hesitant fuzzy power hybrid geometric(IHFPHG)operators and examined as well their fundamental properties.Some special cases of the explored work are also discovered.Additionally,the similarity measures based on IHFSs are presented and their advantages are discussed along examples.Furthermore,we initiated a new approach to multiple attribute decision making(MADM)problem applying suggested operators and a mathematical model is solved to develop an approach and to establish its common sense and adequacy.Advantages,comparative analysis,and graphical representation of the presented work are elaborated to show the reliability and effectiveness of the presented works.
基金funds including the National Natural Science Foundation of China (Nos.81473590,No.81274115,No.81473119)China-Japan Friendship Hospital Youth Science and Technology Excellence Project (No.2014-QNYC-B-10)+1 种基金Program for New Century Excellent Talents in University of the Chinese Ministry of Education (No.NCET-11-0606)Program for Excellent Talents of Beijing Municipal Party Committee Organization Department of the Communist Party of China (No.2013D009999000001)
文摘Tbeacrine （1,3,7,9-tetramethyluric acid）, a purine alkaloid similar to caffeine in its chemical structure, is isolated from edible Camellia assamica vat. kucha and has various pharmacological activities including hypnotic effects, anti-depressant effects, anti-inflammatory and analgesic effects, and a protective effect against stress-provoked liver damage. A rapid and simple assay is required to quantify theacrine in biological samples for pharmacokinetic studies in small animals. This study aimed to establish an enzyme-linked immunosorbent assay （ELISA） for theacrine quantification in blood. Herein, we successfully obtained monoclonal antibodies （MAbs） against theacrine, MAbs C11B5, and developed an ELISA method for the fast determination of theacrine in mouse blood. The range for calibration of theacrine by ELISA was 0.156-100 μg mL-1. The half maximum inhibitory concentration （IC50） value was 1.55 μg mL-1. The ELISA method lays a good foundation for the further research.
文摘Aiming at the kitchen stain and fast growth of dishwasher market in China,the addition of protease and amylase solution in the dishwasher detergents was proposed for the food stains typical in China.A comparison between Chinese commercial dishwasher detergents and an EU mainstream detergent was made.The results indicated that the addition of protease and amylase could significantly increase the washing performance,and thus could help close the washing performance gap between our products and the EU mainstream product.
基金sponsored by the National Natural Science Foundation of China(Nos.61972208,62102194 and 62102196)National Natural Science Foundation of China(Youth Project)(No.62302237)+3 种基金Six Talent Peaks Project of Jiangsu Province(No.RJFW-111),China Postdoctoral Science Foundation Project(No.2018M640509)Postgraduate Research and Practice Innovation Program of Jiangsu Province(Nos.KYCX22_1019,KYCX23_1087,KYCX22_1027,KYCX23_1087,SJCX24_0339 and SJCX24_0346)Innovative Training Program for College Students of Nanjing University of Posts and Telecommunications(No.XZD2019116)Nanjing University of Posts and Telecommunications College Students Innovation Training Program(Nos.XZD2019116,XYB2019331).
文摘The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering analysis.To address this issue,this paper introduces a new method named Big Data Tensor Multi-Cluster Distributed Incremental Update(BDTMCDIncreUpdate),which combines distributed computing,storage technology,and incremental update techniques to provide an efficient and effective means for clustering analysis.Firstly,the original dataset is divided into multiple subblocks,and distributed computing resources are utilized to process the sub-blocks in parallel,enhancing efficiency.Then,initial clustering is performed on each sub-block using tensor-based multi-clustering techniques to obtain preliminary results.When new data arrives,incremental update technology is employed to update the core tensor and factor matrix,ensuring that the clustering model can adapt to changes in data.Finally,by combining the updated core tensor and factor matrix with historical computational results,refined clustering results are obtained,achieving real-time adaptation to dynamic data.Through experimental simulation on the Aminer dataset,the BDTMCDIncreUpdate method has demonstrated outstanding performance in terms of accuracy(ACC)and normalized mutual information(NMI)metrics,achieving an accuracy rate of 90%and an NMI score of 0.85,which outperforms existing methods such as TClusInitUpdate and TKLClusUpdate in most scenarios.Therefore,the BDTMCDIncreUpdate method offers an innovative solution to the field of big data analysis,integrating distributed computing,incremental updates,and tensor-based multi-clustering techniques.It not only improves the efficiency and scalability in processing large-scale high-dimensional datasets but also has been validated for its effectiveness and accuracy through experiments.This method shows great potential in real-world applications where dynamic data growth is common,and it is of significant importance for advancing the development of data analysis technology.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608000)the National Natural Science Foundation of China(Grant No.42030605)+1 种基金CAAI-MindSpore Academic Fund Research Projects(CAAIXSJLJJ2023MindSpore11)the program of China Scholarships Council(No.CXXM2101180001)。
文摘Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the intensity of summer precipitation is often largely underestimated in many current dynamic models.This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)method.Using the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model predictions.This study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.
基金supported by the National Natural Science Foundation of China [grant number 42030605]the National Key R&D Program of China [grant number 2020YFA0608004]。
文摘A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.
基金supported by National Natural Science Foundation of China(Grant Nos.42030605 and 42088101)National Key R&D Program of China(Grant No.2020YFA0608004)High Performance Computing of Nanjing University of Information Science&Technology for their support of this work。
文摘Marine heatwaves(MHWs),which can exert devastating socioeconomic and ecological impacts,have attracted much public interest in recent years.In this study,we evaluate the sub-seasonal forecast skill of MHWs based on the Nanjing University of Information Science&Technology Climate Forecast System version 1.1(NUIST CFS1.1)and analyze the related physical processes.Our results show that the model can accurately forecast the occurrence of MHWs on a global scale out to a lead time of 25 days.Notably,even at lead times of 51–55 days,the forecast skill in most tropical regions,as well as in the northeastern and southeastern Pacific,is superior to both random forecasts and persistence forecasts.Accurate predictions of sea level pressure,zonal currents,and mixed-layer depth are important for MHW forecasting.Furthermore,we also conduct forecast skill assessments for two well-documented MHW events.Due to its ability to correctly forecast the changes in heat flux anomalies at a lead time of 25 days,the model can accurately forecast the strong MHW event that occurred in the South China Sea in May–October 2020.However,the forecasting results were less than optimal for the strong MHW event that occurred along the Australian west coast in January–April 2011.Although the model accurately forecasts its occurrence,the forecast of its intensity is poor.Additionally,when the lead time exceeds 10 days,forecasts of the relevant physical processes of this MHW event are also inaccurate.
基金supports from National Key Research and Development Program of China(2021YFB2800703)Sichuan Province Science and Technology Support Program(25QNJJ2419)+1 种基金National Natural Science Foundation of China(U22A2008,12404484)Laoshan Laboratory Science and Technology Innovation Project(LSKJ202200801).
文摘Diatomic metasurfaces designed for interferometric mechanisms possess significant potential for the multidimensional manipulation of electromagnetic waves,including control over amplitude,phase,frequency,and polarization.Geometric phase profiles with spin-selective properties are commonly associated with wavefront modulation,allowing the implementation of conjugate strategies within orthogonal circularly polarized channels.Simultaneous control of these characteristics in a single-layered diatomic metasurface will be an apparent technological extension.Here,spin-selective modulation of terahertz(THz)beams is realized by assembling a pair of meta-atoms with birefringent effects.The distinct modulation functions arise from geometric phase profiles characterized by multiple rotational properties,which introduce independent parametric factors that elucidate their physical significance.By arranging the key parameters,the proposed design strategy can be employed to realize independent amplitude and phase manipulation.A series of THz metasurface samples with specific modulation functions are characterized,experimentally demonstrating the accuracy of on-demand manipulation.This research paves the way for all-silicon meta-optics that may have great potential in imaging,sensing and detection.
