Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both g...Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.展开更多
Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does no...Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does not represent an important parameter.However,in critical applications,this parameter represents a crucial aspect.One important sensing device used in IoT designs is the accelerometer.In most applications,the response time of the embedded driver software handling this device is generally not analysed and not taken into account.In this paper,we present the design and implementation of a predictable real-time driver stack for a popular accelerometer and gyroscope device family.We provide clear justifications for why this response time is extremely important for critical applications in the acquisition process of such data.We present extensive measurements and experimental results that demonstrate the predictability of our solution,making it suitable for critical real-time systems.展开更多
Graphics Processing Units(GPUs)are used to accelerate computing-intensive tasks,such as neural networks,data analysis,high-performance computing,etc.In the past decade or so,researchers have done a lot of work on GPU ...Graphics Processing Units(GPUs)are used to accelerate computing-intensive tasks,such as neural networks,data analysis,high-performance computing,etc.In the past decade or so,researchers have done a lot of work on GPU architecture and proposed a variety of theories and methods to study the microarchitectural characteristics of various GPUs.In this study,the GPU serves as a co-processor and works together with the CPU in an embedded real-time system to handle computationally intensive tasks.It models the architecture of the GPU and further considers it based on some excellent work.The SIMT mechanism and Cache-miss situation provide a more detailed analysis of the GPU architecture.In order to verify the GPU architecture model proposed in this article,10 GPU kernel_task and an Nvidia GPU device were used to perform experiments.The experimental results showed that the minimum error between the kernel task execution time predicted by the GPU architecture model proposed in this article and the actual measured kernel task execution time was 3.80%,and the maximum error was 8.30%.展开更多
The chaotic characteristics and maximum predictable time scale of the observation series of hourly water consumption in Hangzhou were investigated using the advanced algorithm presented here is based on the convention...The chaotic characteristics and maximum predictable time scale of the observation series of hourly water consumption in Hangzhou were investigated using the advanced algorithm presented here is based on the conventional Wolf's algorithm for the largest Lyapunov exponent. For comparison, the largest Lyapunov exponents of water consumption series with one-hour and 24-hour intervals were calculated respectively. The results indicated that chaotic characteristics obviously exist in the hourly water consumption system; and that observation series with 24-hour interval have longer maximum predictable scale than hourly series. These findings could have significant practical application for better prediction of urban hourly water consumption.展开更多
In this paper, the method which can combine different seismic data with the different precision and completeness, even the palaeo-earthquake data, has been applied to estimate the yearly seismic moment rate in the sei...In this paper, the method which can combine different seismic data with the different precision and completeness, even the palaeo-earthquake data, has been applied to estimate the yearly seismic moment rate in the seismic region. Based on this, the predictable model of regional time-magnitude has been used in North China and Southwest China. The normal correlation between the time interval of the events and the magnitude of the last strong earthquake shows that the model is suitable. The value of the parameter c is less than the average value of 0.33 that is obtained from the events occurred in the plate boundary in the world. It is explained that the correlativity between the recurrence interval of the earthquake and the magnitude of the last strong event is not obvious. It is shown that the continental earthquakes in China are different from that occurred in the plate boundary and the recurrence model for the continental events are different from the one for the plate boundary events. Finally the seismic risk analysis based on this model for North China and Southwest China is given in this paper.展开更多
In this paper,the optional and predictable projections of set-valued measurable processes are studied.The existence and uniqueness of optional and predictable projections of set-valued measurable processes are proved ...In this paper,the optional and predictable projections of set-valued measurable processes are studied.The existence and uniqueness of optional and predictable projections of set-valued measurable processes are proved under proper circumstances.展开更多
Making accurate forecast or prediction is a challenging task in the big data era, in particular for those datasets involving high-dimensional variables but short-term time series points,which are generally available f...Making accurate forecast or prediction is a challenging task in the big data era, in particular for those datasets involving high-dimensional variables but short-term time series points,which are generally available from real-world systems.To address this issue, Prof.展开更多
During the course of the disease,most patients with Crohn's disease(CD) may eventually develop a stricturing or a perforating complication,and a significant number of patients with both CD and ulcerative colitis w...During the course of the disease,most patients with Crohn's disease(CD) may eventually develop a stricturing or a perforating complication,and a significant number of patients with both CD and ulcerative colitis will undergo surgery.In recent years,research has focused on the determination of factors important in the prediction of disease course in inflammatory bowel diseases to improve stratification of patients,identify individual patient profiles,including clinical,laboratory and molecular markers,which hopefully will allow physicians to choose the most appropriate management in terms of therapy and intensity of follow-up.This review summarizes the available evidence on clinical,endoscopic variables and biomarkers in the prediction of short and long-term outcome in patients with inflammatory bowel diseases.展开更多
This paper proposes a performance prediction model for grid computing model ServiceBSP to support developing high quality applications in grid environment. In ServiceBSP model, the agents carrying computing tasks are ...This paper proposes a performance prediction model for grid computing model ServiceBSP to support developing high quality applications in grid environment. In ServiceBSP model, the agents carrying computing tasks are dispatched to the local domain of the selected computation services. By using the IP （integer program） approach, the Service Selection Agent selects the computation services with global optimized QoS （quality of service） consideration. The performance of a ServiceBSP application can be predicted according to the performance prediction model based on the QoS of the selected services. The performance prediction model can help users to analyze their applications and improve them by optimized the factors which affects the performance. The experiment shows that the Service Selection Agent can provide ServiceBSP users with satisfied QoS of applications.展开更多
Carbon dots(CDs)have wide application potentials in optoelectronic devices,biology,medicine,chemical sensors,and quantum techniques due to their excellent fluorescent properties.However,synthesis of CDs with controlla...Carbon dots(CDs)have wide application potentials in optoelectronic devices,biology,medicine,chemical sensors,and quantum techniques due to their excellent fluorescent properties.However,synthesis of CDs with controllable spectrum is challenging because of the diversity of the CD components and structures.In this report,machine learning(ML)algorithms were applied to help the synthesis of CDs with predictable photoluminescence(PL)under the excitation wavelengths of 365 and 532 nm.The combination of precursors was used as the variable.The PL peaks of the strongest intensity(λ_(s))and the longest wavelength(λ_(l))were used as target functions.Among six investigated ML models,the random forest(RF)model showed outstanding)performance in the prediction of the PL peaks.展开更多
In thepast 2decades,synthetic biologists have applied systematic engineering principles to genetic circuit design to devise biological systems with bespoke behaviors,such as Boolean logic gates,signal filters,oscillat...In thepast 2decades,synthetic biologists have applied systematic engineering principles to genetic circuit design to devise biological systems with bespoke behaviors,such as Boolean logic gates,signal filters,oscillators,state machines,perceptrons,and genetic controllers[1,2].Following a bottom-up strategy,the genetic circuits are designed by assembling a set of well-characterized biological components,or genetic parts[3],and optimized through the iterative Design-Build-Test-Learn(DBTL)cycles.展开更多
Definite emission colorfrom rare-earth Eu^(2+)cannot be guaranteed in distinct hosts because its spectrum behavior is strongly dependent on surrounding microenvironment.Herein,we propose a strategy of heterostructure ...Definite emission colorfrom rare-earth Eu^(2+)cannot be guaranteed in distinct hosts because its spectrum behavior is strongly dependent on surrounding microenvironment.Herein,we propose a strategy of heterostructure polyhedron BO3-PO4 substitution that can realize customizable and even predictable Eu^(2+)emission.Taking Sr_(3)La(PO_(4))_(3):Eu^(2+)blue phosphor as host,we prepared a series of BO3-PO4 substitution-designed Sr_(3)La(PO_(4))_(3):Eu^(2+)(SLP_(3-x)B_(x):Eu^(2+))phosphors via solid-state reaction.Structural and spectral analyses demonstrate that substitution of PO_(4)with BO_(3)unit drives Eu^(2+)to migrate from original occupied Sr sites to unoccupied six-coordinated La sites,bringing out a brand-new broadband yellow-emitting peak at 530 nm,enabling an efficient spectrum tailoring from initial blue emission at 420 nm to white-light and then yellow.Strikingly,we find that the resultant Eu^(2+)spectrum behavior in as-prepared SLP_(3-x)B_(x):Eu^(2+)and Eu^(2+)-doped other borophosphate phosphors is highly similar(although they have different microenvironments).Such exciting findings indicate that proposed BO3-PO4 substitution-strategy possesses an ability of predicting emission by modulating Eu^(2+)site-selective occupation.Utilizing SLP_(3-x)B_(x):Eu^(2+)(x=0.1 and 0.4)phosphors,we fabricated optical temperature sensor and white LED prototypes,showcasing remarkable temperature sensitivity of S_(r)=1.1%/K and good color rendering index(CRI)of 83.This work may aid the discovery of novel functional materials with specific,desirablephysicochemical properties.展开更多
Epilepsy is a severe,relapsing,and multifactorial neurological disorder.Studies regarding the accurate diagnosis,prognosis,and in-depth pathogenesis are crucial for the precise and effective treatment of epilepsy.The ...Epilepsy is a severe,relapsing,and multifactorial neurological disorder.Studies regarding the accurate diagnosis,prognosis,and in-depth pathogenesis are crucial for the precise and effective treatment of epilepsy.The pathogenesis of epilepsy is complex and involves alterations in variables such as gene expression,protein expression,ion channel activity,energy metabolites,and gut microbiota composition.Satisfactory results are lacking for conventional treatments for epilepsy.Surgical resection of lesions,drug therapy,and non-drug interventions are mainly used in clinical practice to treat pain associated with epilepsy.Non-pharmacological treatments,such as a ketogenic diet,gene therapy for nerve regeneration,and neural regulation,are currently areas of research focus.This review provides a comprehensive overview of the pathogenesis,diagnostic methods,and treatments of epilepsy.It also elaborates on the theoretical basis,treatment modes,and effects of invasive nerve stimulation in neurotherapy,including percutaneous vagus nerve stimulation,deep brain electrical stimulation,repetitive nerve electrical stimulation,in addition to non-invasive transcranial magnetic stimulation and transcranial direct current stimulation.Numerous studies have shown that electromagnetic stimulation-mediated neuromodulation therapy can markedly improve neurological function and reduce the frequency of epileptic seizures.Additionally,many new technologies for the diagnosis and treatment of epilepsy are being explored.However,current research is mainly focused on analyzing patients’clinical manifestations and exploring relevant diagnostic and treatment methods to study the pathogenesis at a molecular level,which has led to a lack of consensus regarding the mechanisms related to the disease.展开更多
Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley a...Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.展开更多
Although extended-range forecasting has exceeded the limit of daily predictability of weather,there are still partially predictable characteristics of meteorological fields in such forecasts.A targeted forecast scheme...Although extended-range forecasting has exceeded the limit of daily predictability of weather,there are still partially predictable characteristics of meteorological fields in such forecasts.A targeted forecast scheme and strategy for extended-range predictable components is proposed.Based on chaotic characteristics of the atmosphere,predictable components and unpredictable random components are separated by using the standpoint of error growth in a numerical model.The predictable components are defined as those with slow error growth at a given range,which are not sensitive to small errors in initial conditions. A numerical model for predictable components(NMPC)is established,by filtering random components with poor predictability.The aim is to maintain predictable components and avoid the influence of rapidly growing forecast errors on small scales. Meanwhile,the analogue-dynamical approach(ADA)is used to correct forecast errors of predictable components,to decrease model error and statistically take into account the influence of random components.The scheme is applied to operational dynamical extended-range forecast(DERF)model of the National Climate Center of China Meteorological Administration (NCC/CMA).Prediction results show that the scheme can improve forecast skill of predictable components to some extent, especially in high predictability regions.Forecast skill at zonal wave zero is improved more than for ultra-long waves and synoptic-scale waves.Results show good agreement with predictability of spatial scale.As a result,the scheme can reduce forecast errors and improve forecast skill,which favors operational use.展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
Ever since gene targeting or specific modification of genome sequences in mice was achieved in the early 1980s,the reverse genetic approach of precise editing of any genomic locus has greatly accelerated biomedical re...Ever since gene targeting or specific modification of genome sequences in mice was achieved in the early 1980s,the reverse genetic approach of precise editing of any genomic locus has greatly accelerated biomedical research and biotechnology development.In particular,the recent development of the CRISPR/Cas9 system has greatly expedited genetic dissection of 3D genomes.CRISPR gene-editing outcomes result from targeted genome cleavage by ectopic bacterial Cas9 nuclease followed by presumed random ligations via the host double-strand break repair machineries.Recent studies revealed,however,that the CRISPR genomeediting system is precise and predictable because of cohesive Cas9 cleavage of targeting DNA.Here,we synthesize the current understanding of CRISPR DNA fragment-editing mechanisms and recent progress in predictable outcomes from precise genetic engineering of 3D genomes.Specifically,we first briefly describe historical genetic studies leading to CRISPR and 3D genome engineering.We then summarize different types of chromosomal rearrangements by DNA fragment editing.Finally,we review significant progress from precise ID gene editing toward predictable 3D genome engineering and synthetic biology.The exciting and rapid advances in this emerging field provide new opportunities and challenges to understand or digest 3D genomes.展开更多
We establish existence of Predictable Forward Performance Processes(PFPPs)in conditionally complete markets,which has been previously shown only in the binomial setting.Our market model can be a discrete-time or a con...We establish existence of Predictable Forward Performance Processes(PFPPs)in conditionally complete markets,which has been previously shown only in the binomial setting.Our market model can be a discrete-time or a continuous-time model,and the investment horizon can be finite or infinite.We show that the main step in construction of PFPPs is solving a one-period problem involving an integral equation,which is the counterpart of the functional equation found in the binomial case.Although this integral equation has been partially studied in the existing literature,we provide a new solution method using the Fourier transform for tempered distributions.We also provide closedform solutions for PFPPs with inverse marginal functions that are completely monotonic and establish uniqueness of PFPPs within this class.We apply our results to two special cases.The first one is the binomial market and is included to relate our work to the existing literature.The second example considers a generalized Black–Scholes model which,to the best of our knowledge,is a new result.展开更多
This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scale...This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scales.Model variables are divided into predictable components and unpredictable chaotic components from the angle of model prediction error growth.The predictable components are defined as those with a slow error growth at a given range.A targeted numerical model for predictable components is established based on the operational dynamical extended-range forecast(DERF)model of the National Climate Center.At the same time,useful information in historical data are combined to find the fields for predictable components in the numerical model that are similar to those for the predictable components in historical data,reducing the variable dimensions in a similar judgment process and further correcting prediction errors of predictable components.Historical data is used to obtain the expected value and variance of the chaotic components through the ensemble forecast method.The numerical experiment results show that this method can effectively improve the forecast skill of the atmospheric circulation field in the 10–30 days extended-range numerical model and has good prospects for operational applications.展开更多
AIM:To investigate the value of optical coherence tomography angiography(OCTA)indicators in the diagnosis of diabetic retinopathy(DR),and to provide patients with diabetic nephropathy(DN)with more sensitive OCTA scree...AIM:To investigate the value of optical coherence tomography angiography(OCTA)indicators in the diagnosis of diabetic retinopathy(DR),and to provide patients with diabetic nephropathy(DN)with more sensitive OCTA screening indicators to detect concurrent DR at an early stage.METHODS:A total of 200 patients who treated in the ophthalmology department of the Seventh Affiliated Hospital,Sun Yat-sen University from 2022 to 2023 were included,including 95 first-diagnosed DR patients and 105 patients without DR,and all patients underwent OCTA examination and a collection of demographics and renal function parameters.After a quality check,automated measurements of the foveal avascular zone area,vessel density(VD),and perfusion density(PD)of both 3 mm×3 mm and 6 mm×6 mm windows were obtained.RESULTS:Using random forest and multivariate Logistic regression methods,we developed a diagnostic model for DR based on 12 variables(age,FBG,SBP,DBP,HbA1c,ALT,ALP,urea/Scr,DM duration,HUA,DN,and CMT).Adding specific OCTA parameters enhanced the efficacy of the existing diagnostic model for DR(outer vessel density in 6 mm×6 mm window,AUC=0.837 vs 0.819,P=0.03).In the study of DN patients,the parameters in the 6 mm×6 mm window improved the diagnostic efficacy of DR(inner VD;outer VD;full VD;outer PD;full PD).CONCLUSION:The outer VD in the 6 mm×6 mm window can enhance the efficacy of the traditional DR diagnostic model.Meanwhile,compared with the 3 mm×3 mm window,the microvascular parameters in the 6 mm×6 mm window focusing on DN patients can be more sensitive to diagnosing the occurrence of DR.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.U2342210 and 42275043)the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.J2223806,ZDJ2024-25 and ZDJ2025-34)。
文摘Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.
文摘Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does not represent an important parameter.However,in critical applications,this parameter represents a crucial aspect.One important sensing device used in IoT designs is the accelerometer.In most applications,the response time of the embedded driver software handling this device is generally not analysed and not taken into account.In this paper,we present the design and implementation of a predictable real-time driver stack for a popular accelerometer and gyroscope device family.We provide clear justifications for why this response time is extremely important for critical applications in the acquisition process of such data.We present extensive measurements and experimental results that demonstrate the predictability of our solution,making it suitable for critical real-time systems.
文摘Graphics Processing Units(GPUs)are used to accelerate computing-intensive tasks,such as neural networks,data analysis,high-performance computing,etc.In the past decade or so,researchers have done a lot of work on GPU architecture and proposed a variety of theories and methods to study the microarchitectural characteristics of various GPUs.In this study,the GPU serves as a co-processor and works together with the CPU in an embedded real-time system to handle computationally intensive tasks.It models the architecture of the GPU and further considers it based on some excellent work.The SIMT mechanism and Cache-miss situation provide a more detailed analysis of the GPU architecture.In order to verify the GPU architecture model proposed in this article,10 GPU kernel_task and an Nvidia GPU device were used to perform experiments.The experimental results showed that the minimum error between the kernel task execution time predicted by the GPU architecture model proposed in this article and the actual measured kernel task execution time was 3.80%,and the maximum error was 8.30%.
基金Project (No. 50078048) supported by the National Natural Science Foundation of China
文摘The chaotic characteristics and maximum predictable time scale of the observation series of hourly water consumption in Hangzhou were investigated using the advanced algorithm presented here is based on the conventional Wolf's algorithm for the largest Lyapunov exponent. For comparison, the largest Lyapunov exponents of water consumption series with one-hour and 24-hour intervals were calculated respectively. The results indicated that chaotic characteristics obviously exist in the hourly water consumption system; and that observation series with 24-hour interval have longer maximum predictable scale than hourly series. These findings could have significant practical application for better prediction of urban hourly water consumption.
文摘In this paper, the method which can combine different seismic data with the different precision and completeness, even the palaeo-earthquake data, has been applied to estimate the yearly seismic moment rate in the seismic region. Based on this, the predictable model of regional time-magnitude has been used in North China and Southwest China. The normal correlation between the time interval of the events and the magnitude of the last strong earthquake shows that the model is suitable. The value of the parameter c is less than the average value of 0.33 that is obtained from the events occurred in the plate boundary in the world. It is explained that the correlativity between the recurrence interval of the earthquake and the magnitude of the last strong event is not obvious. It is shown that the continental earthquakes in China are different from that occurred in the plate boundary and the recurrence model for the continental events are different from the one for the plate boundary events. Finally the seismic risk analysis based on this model for North China and Southwest China is given in this paper.
基金National Natural Science Foundation of China(1 9971 0 72 )
文摘In this paper,the optional and predictable projections of set-valued measurable processes are studied.The existence and uniqueness of optional and predictable projections of set-valued measurable processes are proved under proper circumstances.
基金supported by the grants from CASthe National Key R&D Program of Chinathe National Natural Science Foundation of China
文摘Making accurate forecast or prediction is a challenging task in the big data era, in particular for those datasets involving high-dimensional variables but short-term time series points,which are generally available from real-world systems.To address this issue, Prof.
文摘During the course of the disease,most patients with Crohn's disease(CD) may eventually develop a stricturing or a perforating complication,and a significant number of patients with both CD and ulcerative colitis will undergo surgery.In recent years,research has focused on the determination of factors important in the prediction of disease course in inflammatory bowel diseases to improve stratification of patients,identify individual patient profiles,including clinical,laboratory and molecular markers,which hopefully will allow physicians to choose the most appropriate management in terms of therapy and intensity of follow-up.This review summarizes the available evidence on clinical,endoscopic variables and biomarkers in the prediction of short and long-term outcome in patients with inflammatory bowel diseases.
基金Supported by the National Natural Science Foundation of China (60573109)Shanghai Municipal Committee of Science and Tech-nology (05dz15005)Shanghai High Institution Grid Project
文摘This paper proposes a performance prediction model for grid computing model ServiceBSP to support developing high quality applications in grid environment. In ServiceBSP model, the agents carrying computing tasks are dispatched to the local domain of the selected computation services. By using the IP （integer program） approach, the Service Selection Agent selects the computation services with global optimized QoS （quality of service） consideration. The performance of a ServiceBSP application can be predicted according to the performance prediction model based on the QoS of the selected services. The performance prediction model can help users to analyze their applications and improve them by optimized the factors which affects the performance. The experiment shows that the Service Selection Agent can provide ServiceBSP users with satisfied QoS of applications.
基金supported by the National Natural Science Foundation of China(No.22175095).
文摘Carbon dots(CDs)have wide application potentials in optoelectronic devices,biology,medicine,chemical sensors,and quantum techniques due to their excellent fluorescent properties.However,synthesis of CDs with controllable spectrum is challenging because of the diversity of the CD components and structures.In this report,machine learning(ML)algorithms were applied to help the synthesis of CDs with predictable photoluminescence(PL)under the excitation wavelengths of 365 and 532 nm.The combination of precursors was used as the variable.The PL peaks of the strongest intensity(λ_(s))and the longest wavelength(λ_(l))were used as target functions.Among six investigated ML models,the random forest(RF)model showed outstanding)performance in the prediction of the PL peaks.
基金Fundamental Research Funds for the Central Universities,Grant/Award Number:226-2022-00214National Key R&D Program of China,Grant/Award Number:2023YFF1204500+1 种基金“Pioneer”and“Leading Goose”R&D Program of Zhejiang,Grant/Award Number:2024C03011National Natural Science Foundation of China,Grant/AwardNumbers:32271475,32320103001。
文摘In thepast 2decades,synthetic biologists have applied systematic engineering principles to genetic circuit design to devise biological systems with bespoke behaviors,such as Boolean logic gates,signal filters,oscillators,state machines,perceptrons,and genetic controllers[1,2].Following a bottom-up strategy,the genetic circuits are designed by assembling a set of well-characterized biological components,or genetic parts[3],and optimized through the iterative Design-Build-Test-Learn(DBTL)cycles.
基金the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2021D01E19,2022TSYCXC0016)the Project of youth science and technology innovation talent project of Xinjiang Normal University(XJNUQB2022-15)+1 种基金the National Natural Science Foundations of China(52262029,51762040)Postgraduate Research and the Research Fund of Xinjiang Normal University Research Platform Student Project(XSY202201013).
文摘Definite emission colorfrom rare-earth Eu^(2+)cannot be guaranteed in distinct hosts because its spectrum behavior is strongly dependent on surrounding microenvironment.Herein,we propose a strategy of heterostructure polyhedron BO3-PO4 substitution that can realize customizable and even predictable Eu^(2+)emission.Taking Sr_(3)La(PO_(4))_(3):Eu^(2+)blue phosphor as host,we prepared a series of BO3-PO4 substitution-designed Sr_(3)La(PO_(4))_(3):Eu^(2+)(SLP_(3-x)B_(x):Eu^(2+))phosphors via solid-state reaction.Structural and spectral analyses demonstrate that substitution of PO_(4)with BO_(3)unit drives Eu^(2+)to migrate from original occupied Sr sites to unoccupied six-coordinated La sites,bringing out a brand-new broadband yellow-emitting peak at 530 nm,enabling an efficient spectrum tailoring from initial blue emission at 420 nm to white-light and then yellow.Strikingly,we find that the resultant Eu^(2+)spectrum behavior in as-prepared SLP_(3-x)B_(x):Eu^(2+)and Eu^(2+)-doped other borophosphate phosphors is highly similar(although they have different microenvironments).Such exciting findings indicate that proposed BO3-PO4 substitution-strategy possesses an ability of predicting emission by modulating Eu^(2+)site-selective occupation.Utilizing SLP_(3-x)B_(x):Eu^(2+)(x=0.1 and 0.4)phosphors,we fabricated optical temperature sensor and white LED prototypes,showcasing remarkable temperature sensitivity of S_(r)=1.1%/K and good color rendering index(CRI)of 83.This work may aid the discovery of novel functional materials with specific,desirablephysicochemical properties.
基金supported by the National Natural Science Foundation of China,No.32130060(to XG).
文摘Epilepsy is a severe,relapsing,and multifactorial neurological disorder.Studies regarding the accurate diagnosis,prognosis,and in-depth pathogenesis are crucial for the precise and effective treatment of epilepsy.The pathogenesis of epilepsy is complex and involves alterations in variables such as gene expression,protein expression,ion channel activity,energy metabolites,and gut microbiota composition.Satisfactory results are lacking for conventional treatments for epilepsy.Surgical resection of lesions,drug therapy,and non-drug interventions are mainly used in clinical practice to treat pain associated with epilepsy.Non-pharmacological treatments,such as a ketogenic diet,gene therapy for nerve regeneration,and neural regulation,are currently areas of research focus.This review provides a comprehensive overview of the pathogenesis,diagnostic methods,and treatments of epilepsy.It also elaborates on the theoretical basis,treatment modes,and effects of invasive nerve stimulation in neurotherapy,including percutaneous vagus nerve stimulation,deep brain electrical stimulation,repetitive nerve electrical stimulation,in addition to non-invasive transcranial magnetic stimulation and transcranial direct current stimulation.Numerous studies have shown that electromagnetic stimulation-mediated neuromodulation therapy can markedly improve neurological function and reduce the frequency of epileptic seizures.Additionally,many new technologies for the diagnosis and treatment of epilepsy are being explored.However,current research is mainly focused on analyzing patients’clinical manifestations and exploring relevant diagnostic and treatment methods to study the pathogenesis at a molecular level,which has led to a lack of consensus regarding the mechanisms related to the disease.
基金supported by the General Program of the National Natural Science Foundation of China(No.52274326)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202109)the Seventh Batch of Ten Thousand Talents Plan of China(No.ZX20220553).
文摘Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.
基金supported by National Natural Science Foundation of China (Grant Nos.41105070,40930952 and 41005041)State Key Program of Science and Technology of China(Grant No.2009BAC51B04)Meteorological Special Project of China(Grant No.GYHY 201106016)
文摘Although extended-range forecasting has exceeded the limit of daily predictability of weather,there are still partially predictable characteristics of meteorological fields in such forecasts.A targeted forecast scheme and strategy for extended-range predictable components is proposed.Based on chaotic characteristics of the atmosphere,predictable components and unpredictable random components are separated by using the standpoint of error growth in a numerical model.The predictable components are defined as those with slow error growth at a given range,which are not sensitive to small errors in initial conditions. A numerical model for predictable components(NMPC)is established,by filtering random components with poor predictability.The aim is to maintain predictable components and avoid the influence of rapidly growing forecast errors on small scales. Meanwhile,the analogue-dynamical approach(ADA)is used to correct forecast errors of predictable components,to decrease model error and statistically take into account the influence of random components.The scheme is applied to operational dynamical extended-range forecast(DERF)model of the National Climate Center of China Meteorological Administration (NCC/CMA).Prediction results show that the scheme can improve forecast skill of predictable components to some extent, especially in high predictability regions.Forecast skill at zonal wave zero is improved more than for ultra-long waves and synoptic-scale waves.Results show good agreement with predictability of spatial scale.As a result,the scheme can reduce forecast errors and improve forecast skill,which favors operational use.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
基金This work was supported by grants from the National Natural Science Foundation of China(31630039 and 32000425)the Ministry of Science and Technology of China(2017YFA0504203 and 2018YFC1004504)the Science and Technology Commission of Shanghai Municipality(19JC1412500).
文摘Ever since gene targeting or specific modification of genome sequences in mice was achieved in the early 1980s,the reverse genetic approach of precise editing of any genomic locus has greatly accelerated biomedical research and biotechnology development.In particular,the recent development of the CRISPR/Cas9 system has greatly expedited genetic dissection of 3D genomes.CRISPR gene-editing outcomes result from targeted genome cleavage by ectopic bacterial Cas9 nuclease followed by presumed random ligations via the host double-strand break repair machineries.Recent studies revealed,however,that the CRISPR genomeediting system is precise and predictable because of cohesive Cas9 cleavage of targeting DNA.Here,we synthesize the current understanding of CRISPR DNA fragment-editing mechanisms and recent progress in predictable outcomes from precise genetic engineering of 3D genomes.Specifically,we first briefly describe historical genetic studies leading to CRISPR and 3D genome engineering.We then summarize different types of chromosomal rearrangements by DNA fragment editing.Finally,we review significant progress from precise ID gene editing toward predictable 3D genome engineering and synthetic biology.The exciting and rapid advances in this emerging field provide new opportunities and challenges to understand or digest 3D genomes.
基金supported by the National Science Foundation(Grant No.DMS-1929348).
文摘We establish existence of Predictable Forward Performance Processes(PFPPs)in conditionally complete markets,which has been previously shown only in the binomial setting.Our market model can be a discrete-time or a continuous-time model,and the investment horizon can be finite or infinite.We show that the main step in construction of PFPPs is solving a one-period problem involving an integral equation,which is the counterpart of the functional equation found in the binomial case.Although this integral equation has been partially studied in the existing literature,we provide a new solution method using the Fourier transform for tempered distributions.We also provide closedform solutions for PFPPs with inverse marginal functions that are completely monotonic and establish uniqueness of PFPPs within this class.We apply our results to two special cases.The first one is the binomial market and is included to relate our work to the existing literature.The second example considers a generalized Black–Scholes model which,to the best of our knowledge,is a new result.
基金supported by the National Natural Science Foundation of China (Grant Nos. 40930952, 41105055)Global Change Study of Major National Scientific Research Plan of China (Grant No. 2012CB955902)Meteorological Special Project of China (Grant Nos. GYHY201106016, GYHY201106015)
文摘This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scales.Model variables are divided into predictable components and unpredictable chaotic components from the angle of model prediction error growth.The predictable components are defined as those with a slow error growth at a given range.A targeted numerical model for predictable components is established based on the operational dynamical extended-range forecast(DERF)model of the National Climate Center.At the same time,useful information in historical data are combined to find the fields for predictable components in the numerical model that are similar to those for the predictable components in historical data,reducing the variable dimensions in a similar judgment process and further correcting prediction errors of predictable components.Historical data is used to obtain the expected value and variance of the chaotic components through the ensemble forecast method.The numerical experiment results show that this method can effectively improve the forecast skill of the atmospheric circulation field in the 10–30 days extended-range numerical model and has good prospects for operational applications.
文摘AIM:To investigate the value of optical coherence tomography angiography(OCTA)indicators in the diagnosis of diabetic retinopathy(DR),and to provide patients with diabetic nephropathy(DN)with more sensitive OCTA screening indicators to detect concurrent DR at an early stage.METHODS:A total of 200 patients who treated in the ophthalmology department of the Seventh Affiliated Hospital,Sun Yat-sen University from 2022 to 2023 were included,including 95 first-diagnosed DR patients and 105 patients without DR,and all patients underwent OCTA examination and a collection of demographics and renal function parameters.After a quality check,automated measurements of the foveal avascular zone area,vessel density(VD),and perfusion density(PD)of both 3 mm×3 mm and 6 mm×6 mm windows were obtained.RESULTS:Using random forest and multivariate Logistic regression methods,we developed a diagnostic model for DR based on 12 variables(age,FBG,SBP,DBP,HbA1c,ALT,ALP,urea/Scr,DM duration,HUA,DN,and CMT).Adding specific OCTA parameters enhanced the efficacy of the existing diagnostic model for DR(outer vessel density in 6 mm×6 mm window,AUC=0.837 vs 0.819,P=0.03).In the study of DN patients,the parameters in the 6 mm×6 mm window improved the diagnostic efficacy of DR(inner VD;outer VD;full VD;outer PD;full PD).CONCLUSION:The outer VD in the 6 mm×6 mm window can enhance the efficacy of the traditional DR diagnostic model.Meanwhile,compared with the 3 mm×3 mm window,the microvascular parameters in the 6 mm×6 mm window focusing on DN patients can be more sensitive to diagnosing the occurrence of DR.
