Nuclear heating plays an important aspect in design and deployment of both fission and fusion reactors and experimental devices in terms of cooling requirements. Two experimental campaigns in the framework of a collab...Nuclear heating plays an important aspect in design and deployment of both fission and fusion reactors and experimental devices in terms of cooling requirements. Two experimental campaigns in the framework of a collaboration project between the French Atomic and Alternative Energy Commission(CEA) and Jožef Stefan Institute(JSI), Slovenia, have been performed at the JSI TRIGA reactor for the experimental assessment of nuclear heating in fission and fusion-relevant materials by the differential calorimetry technique, based on the CALMOS and CARMEN differential calorimeters, previously developed at CEA. The results of the first campaign performed at reactor powers between 100 and 250 kW have already been reported, highlighting some measurement difficulties. Therefore, the second campaign was performed at a lower reactor power of 30 kW to overcome these issues. Moreover, a computational analysis of the experiments was performed using the JSIR2S code package to calculate the nuclear heating levels. Both experiments and their reproduction by simulations are described in detail. We present a comparison of the previously reported measured nuclear heating values of the first campaign with the computational results, with consistent underestimation by simulations by 8–35%. We report the experimental and computational results for the second experimental campaign performed at a reactor power of 30 kW. The simulated heating values were in agreement with the measurements within the measured heating uncertainty, with simulated heating 2.7–11.3% lower than the experimental values.展开更多
Hans Zempel1,2 TAU,a microtubule-associated protein,encoded by the microtubule-associated protein tau(MAPT)gene,is a central regulator of microtubule stability and axonal function in the human brain,with its pathologi...Hans Zempel1,2 TAU,a microtubule-associated protein,encoded by the microtubule-associated protein tau(MAPT)gene,is a central regulator of microtubule stability and axonal function in the human brain,with its pathological aggregation representing a hallmark of Alzheimer’s disease and related tauopathies.Despite extensive research into the role of TAU in neurodegeneration,its essentiality for human brain development has remained unclear.This perspective synthesizes recent genetic,molecular,and cellular evidence to demonstrate that the human brain-specific TAU isoform 0N3R is indispensable for proper neurodevelopment,pointing to loss-of-function of this isoform as a novel paradigm for TAU-associated disease.Alternative splicing of MAPT generates six brain-specific TAU isoforms,with 0N3R being exclusively expressed during fetal brain development.Analysis of large-scale human genetic datasets(gnomAD v4.0.0)reveals a high probability of loss-of-function intolerance(pLI=0.96)for the 0N3R isoform.This is in stark contrast to the canonical Matched Annotation from the NCBI and EMBL-EBI(MANE)transcript and peripheral“Big TAU,”both of which are tolerant to loss-of-function mutations.This intolerance is further supported by the scarcity of loss-of-function mutations in 0N3R-encoding exons and high missense constraint scores,suggesting strong evolutionary selection against disruption of this isoform.Functional studies using human induced pluripotent stem cell-derived cortical neurons with CRISPR-Cas9-mediated MAPT knockout reveal that,unlike in murine models where compensation by other microtubule-associated proteins occurs,loss of TAU in human neurons leads to deficits in neurite outgrowth,axon initial segment shortening,and a trend toward hyperexcitability,accompanied by broad transcriptomic changes affecting genes involved in microtubule organization and synaptic structure.Remarkably,re-expression of any of the six human brain-specific TAU isoforms rescues these phenotypes,underscoring their functional redundancy during development.These findings position the 0N3R isoform as essential for human brain development and suggest that loss-of-function mutations affecting this isoform likely result in neurodevelopmental impairment,potentially manifesting as intellectual disability without overt dysmorphic features.This contrasts with the apparent tolerance to MAPT loss-of-function in mice and peripheral tissues,highlighting a critical species-and isoform-specific requirement for TAU in human neurodevelopment.The hypothesis of 0N3R-TAU loss-of-function intolerance opens new avenues for understanding neurodevelopmental disorders and refines the conceptual framework of TAU-associated disease mechanisms beyond toxic gain-of-function.展开更多
BACKGROUND The rising incidence of inflammatory bowel disease(IBD)globally has increased disease burden and economic impact.Gaps remain in understanding the IBD burden between Asian and Western populations.AIM To esti...BACKGROUND The rising incidence of inflammatory bowel disease(IBD)globally has increased disease burden and economic impact.Gaps remain in understanding the IBD burden between Asian and Western populations.AIM To estimate the current and following 10-year prevalence and incidence of IBD in Hong Kong,Japan,and the United States.METHODS Patients diagnosed with IBD were identified from a territory-wide electronic medical records database in Hong Kong(2003-2022,including all ages)and two large employment-based healthcare claims databases in Japan and the United States(2010-2022,including<65 age).We used Autoregressive Integrated Moving Average models to predict prevalence and incidence from 2023 to 2032,stratified by disease subtype[ulcerative colitis(UC);Crohn’s disease(CD)],sex,and age,with 95%prediction intervals(PIs).The forecasted annual average percentage change(AAPC)with 95%confidence intervals was calculated.RESULTS The age-standardized prevalence of IBD for 2032 is forecasted at 105.88 per 100000 in Hong Kong(95%PI:83.01-128.75,AAPC:5.85%),645.79 in Japan(95%PI:562.51-741.39,AAPC:5.78%),and 629.85 in the United States(95%PI:569.09-690.63,AAPC:2.85%).Prevalence is estimated to rise most significantly among those under 18 in Japan and the United States.Over the next decade,the incidence of IBD is estimated to increase annually by 3.3%in Hong Kong with forecasted increases across all age groups(although the AAPC for each group is not statistically significant);by 2.88%in Japan with a significant rise in those under 18 and stability in 18-65;and remaining stable in the United States.By 2032,the prevalence of CD is estimated to surpass UC in Hong Kong and the United States,whereas UC will continue to be more prevalent in Japan.A higher prevalence and incidence of IBD is forecast for males in Hong Kong and Japan,whereas rates will be similar for both males and females in the United States.CONCLUSION The prevalence of IBD is forecasted to increase in Hong Kong,Japan,and the United States,while estimates of incidence vary.The forecasts show distinct patterns across disease subtype,sex,and age groups.Health systems will need to plan for the predicted increasing prevalence among different demographics.展开更多
An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation sin...An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China＇s seas has been updated to（1/24）° from the global model with（1/2）°resolution. Besides, daily remote sensing sea surface temperature（SST） data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth（MLD） and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores（SS） is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value（more than 0.90）. Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.展开更多
In this paper, the Holt’s exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2...In this paper, the Holt’s exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2010 to May 2014. Results show that the ARIMA ((12), 1, 0) is an adequate model which best fits the CPI time series data and is therefore suitable for forecasting CPI and subsequently the inflation rate. However, the choice of the Holt’s exponential smoothing is as good as an ARIMA model considering the smaller deviations in the mean absolute percentage error and mean square error. Moreover, the Holt’s exponential smoothing model is less complicated since you do not require specialised software to implement it as is the case for ARIMA models. The forecasted inflation rate for April and May, 2015 is 7.0 and 6.6 respectively.展开更多
In this work an algorithm to predict short times series with missing data by means energy associated of series using artificial neural networks (ANN) is presented. In order to give the prediction one step ahead, a com...In this work an algorithm to predict short times series with missing data by means energy associated of series using artificial neural networks (ANN) is presented. In order to give the prediction one step ahead, a comparison between this and previous work that involves a similar approach to test short time series with uncertainties on their data, indicates that a linear smoothing is a well approximation in order to employ a method for uncompleted datasets. Moreover, in function of the long- or short-term stochastic dependence of the short time series considered, the training process modifies the number of patterns and iterations in the topology according to a heuristic law, where the Hurst parameter H is related with the short times series, of which they are considered as a path of the fractional Brownian motion. The results are evaluated on high roughness time series from solutions of the Mackey-Glass Equation (MG) and cumulative monthly historical rainfall data from San Agustin, Cordoba. A comparison with ANN nonlinear filters is shown in order to see a better performance of the outcomes when the information is taken from geographical point observation.展开更多
North Dakota’s oil production has been rapidly increasing during the past several years. The state’s oil production in March 2013 even increased to more than twice the quantity produced in March 2011, and the estima...North Dakota’s oil production has been rapidly increasing during the past several years. The state’s oil production in March 2013 even increased to more than twice the quantity produced in March 2011, and the estimated Bakken Formation reserves were reported very large compared with those of the United Arab Emirates. It eventually makes a question to us of how much oil will be able to be actually extracted with currently available technologies. To answer this question, this paper forecasts future oil development trend in North Dakota using the Seasonal Autoregressive Integrated Moving Average (S-ARIMA) model. Nonstationarity derived from a stochastic trend and the abrupt structural change of oil industry was a big potential problem, but through the Quandt Likelihood Ratio test, we found break points, which allowed us to select a model fitting period suitable for the S-ARIMA method to provide accurate statistical inference for the historical period. The seven major oil producing counties were investigated to determine whether the current oil boom was consistent across all oil fields in North Dakota. Empirical estimates show that North Dakota’s oil production will be more than double in the next five years. What we can predict with great certainty is that North Dakota’s influence over domestic and global oil supply systems will increase in the near future, especially over the next five to six years. This is good news for those who are concerned about domestic energy security in the USA.展开更多
Diabetes has become a concern in the developed and developing countries with its growing number of patients reported to the ministry of health records. This paper discusses the use of the Autoregressive Fractional Mov...Diabetes has become a concern in the developed and developing countries with its growing number of patients reported to the ministry of health records. This paper discusses the use of the Autoregressive Fractional Moving Average (ARFIMA) technique to modeling the diabetes patient’s attendance at Al-Baha hospitals using monthly time series data. The data used in the analysis of this paper are monthly readings of diabetes patients data covered the period January 2006-December 2016. The data were collected from the General Directorate of Health Affairs, Al-Baha region. The autoregressive fractional moving average approach was applied to the data through the model identification, estimation, diagnostic checking and forecasting. Hurst test results and ACF confirmed that there is a long memory behavior in diabetic patient’s data. Also, the fractional difference to diabetes series data revealed that (<em>d</em> = 0.44). Moreover, unit root tests indicated that the fractional difference of diabetes series level is stationary. Furthermore, according to AIC and BIC of model selection criteria ARFIMA (1, 0.44, 0) model shown the smallest values, hence this model was chosen as an adequate represents the data. Also, a diagnostic check confirmed that ARFIMA was appropriate and highly recommended in modeling and forecasting this type of data.展开更多
The Earth’s natural pulse electromagnetic field data consists typically of an underlying variation tendency of intensity and irregularities.The change tendency may be related to the occurrence of earthquake disasters...The Earth’s natural pulse electromagnetic field data consists typically of an underlying variation tendency of intensity and irregularities.The change tendency may be related to the occurrence of earthquake disasters.Forecasting of the underlying intensity trend plays an important role in the analysis of data and disaster monitoring.Combining chaos theory and the radial basis function neural network,this paper proposes a forecasting model of the chaotic radial basis function neural network to conduct underlying intensity trend forecasting by the Earth’s natural pulse electromagnetic field signal.The main strategy of this forecasting model is to obtain parameters as the basis for optimizing the radial basis function neural network and to forecast the reconstructed Earth’s natural pulse electromagnetic field data.In verification experiments,we employ the 3 and 6 days’data of two channels as training samples to forecast the 14 and 21-day Earth’s natural pulse electromagnetic field data respectively.According to the forecasting results and absolute error results,the chaotic radial basis function forecasting model can fit the fluctuation trend of the actual signal strength,effectively reduce the forecasting error compared with the traditional radial basis function model.Hence,this network may be useful for studying the characteristics of the Earth’s natural pulse electromagnetic field signal before a strong earthquake and we hope it can contribute to the electromagnetic anomaly monitoring before the earthquake.展开更多
As the acceleration of aged population tendency, building models to forecast Alzheimer’s Disease (AD) is essential. In this article, we surveyed 1157 interviewees. By analyzing the results using three machine learnin...As the acceleration of aged population tendency, building models to forecast Alzheimer’s Disease (AD) is essential. In this article, we surveyed 1157 interviewees. By analyzing the results using three machine learning methods—BP neural network, SVM and random forest, we can derive the accuracy of them in forecasting AD, so that we can compare the methods in solving AD prediction. Among them, random forest is the most accurate method. Moreover, to combine the advantages of the methods, we build a new combination forecasting model based on the three machine learning models, which is proved more accurate than the models singly. At last, we give the conclusion of the connection between life style and AD, and provide several suggestions for elderly people to help them prevent AD.展开更多
In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(...In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.展开更多
This paper presented the new sanitary and health protocols implemented by cruise companies in order to internationally resuming the industry. The perception of Brazilians regarding these new protocols was identified t...This paper presented the new sanitary and health protocols implemented by cruise companies in order to internationally resuming the industry. The perception of Brazilians regarding these new protocols was identified through a quantitative survey with a sample of 412 Brazilian respondents, carried out between May and June 2021. As main results, sanitary and health protocols that do not affect their experiences on board were identified, as well as those protocols that compromised the experience perceived by the future traveler. The respondents’ propensity to travel on cruise ships and their perceptions about the influence of the ship size, the number of ports of call, nationalities on board, the number of vips, among other aspects, were also analyzed. Finally, in the final section of this paper, we presented an estimation of the expected number of cruisers for the 21/22 cruising season in Brazil, based on a kind Bayesian argument, considering different scenarios for the forthcoming season.展开更多
In this paper, we present a new approach (Kalman Filter Smoothing) to estimate and forecast survival of Diabetic and Non Diabetic Coronary Artery Bypass Graft Surgery (CABG) patients. Survival proportions of the patie...In this paper, we present a new approach (Kalman Filter Smoothing) to estimate and forecast survival of Diabetic and Non Diabetic Coronary Artery Bypass Graft Surgery (CABG) patients. Survival proportions of the patients are obtained from a lifetime representing parametric model (Weibull distribution with Kalman Filter approach). Moreover, an approach of complete population (CP) from its incomplete population (IP) of the patients with 12 years observations/follow-up is used for their survival analysis [1]. The survival proportions of the CP obtained from Kaplan Meier method are used as observed values yt?at time t (input) for Kalman Filter Smoothing process to update time varying parameters. In case of CP, the term representing censored observations may be dropped from likelihood function of the distribution. Maximum likelihood method, in-conjunction with Davidon-Fletcher-Powell (DFP) optimization method [2] and Cubic Interpolation method is used in estimation of the survivor’s proportions. The estimated and forecasted survival proportions of CP of the Diabetic and Non Diabetic CABG patients from the Kalman Filter Smoothing approach are presented in terms of statistics, survival curves, discussion and conclusion.展开更多
This paper deals with a new integrated method of reconstruction and forecasting of climatic changes in future. The method is based on proxy data pollen-spore analysis method, 14C analysis method, nowadays meteorologic...This paper deals with a new integrated method of reconstruction and forecasting of climatic changes in future. The method is based on proxy data pollen-spore analysis method, 14C analysis method, nowadays meteorological data, and data about of solar activity expressed in numbers of W （Wolf）. Here we present the results of investigation of sediments of the 2nd Fomich River terrace, Taymyr Peninsula, Russia. The formation of the peat bog started 10500 ± 140 years BP and continued during the entire Holocene. The pollen analysis of the sediment samples of the 2nd Fomich River terrace and the analysis of surface samples from a larch forest, typical of this region, reveals two phytochrones： both climatically preconditioned--tundra phytochrone （I1-4） and forest phytochrone （Ⅱ1-4）. The techniques of reconstruction and forecasting of basic elements of climate are presented and discussed in details.展开更多
基金supported by the Slovenian Research Agency(research project NC-0001-Analysis of nuclear heating in a reactor,research core funding Reactor physics No.P2-0073,infrastructure program I0-0005)。
文摘Nuclear heating plays an important aspect in design and deployment of both fission and fusion reactors and experimental devices in terms of cooling requirements. Two experimental campaigns in the framework of a collaboration project between the French Atomic and Alternative Energy Commission(CEA) and Jožef Stefan Institute(JSI), Slovenia, have been performed at the JSI TRIGA reactor for the experimental assessment of nuclear heating in fission and fusion-relevant materials by the differential calorimetry technique, based on the CALMOS and CARMEN differential calorimeters, previously developed at CEA. The results of the first campaign performed at reactor powers between 100 and 250 kW have already been reported, highlighting some measurement difficulties. Therefore, the second campaign was performed at a lower reactor power of 30 kW to overcome these issues. Moreover, a computational analysis of the experiments was performed using the JSIR2S code package to calculate the nuclear heating levels. Both experiments and their reproduction by simulations are described in detail. We present a comparison of the previously reported measured nuclear heating values of the first campaign with the computational results, with consistent underestimation by simulations by 8–35%. We report the experimental and computational results for the second experimental campaign performed at a reactor power of 30 kW. The simulated heating values were in agreement with the measurements within the measured heating uncertainty, with simulated heating 2.7–11.3% lower than the experimental values.
文摘Hans Zempel1,2 TAU,a microtubule-associated protein,encoded by the microtubule-associated protein tau(MAPT)gene,is a central regulator of microtubule stability and axonal function in the human brain,with its pathological aggregation representing a hallmark of Alzheimer’s disease and related tauopathies.Despite extensive research into the role of TAU in neurodegeneration,its essentiality for human brain development has remained unclear.This perspective synthesizes recent genetic,molecular,and cellular evidence to demonstrate that the human brain-specific TAU isoform 0N3R is indispensable for proper neurodevelopment,pointing to loss-of-function of this isoform as a novel paradigm for TAU-associated disease.Alternative splicing of MAPT generates six brain-specific TAU isoforms,with 0N3R being exclusively expressed during fetal brain development.Analysis of large-scale human genetic datasets(gnomAD v4.0.0)reveals a high probability of loss-of-function intolerance(pLI=0.96)for the 0N3R isoform.This is in stark contrast to the canonical Matched Annotation from the NCBI and EMBL-EBI(MANE)transcript and peripheral“Big TAU,”both of which are tolerant to loss-of-function mutations.This intolerance is further supported by the scarcity of loss-of-function mutations in 0N3R-encoding exons and high missense constraint scores,suggesting strong evolutionary selection against disruption of this isoform.Functional studies using human induced pluripotent stem cell-derived cortical neurons with CRISPR-Cas9-mediated MAPT knockout reveal that,unlike in murine models where compensation by other microtubule-associated proteins occurs,loss of TAU in human neurons leads to deficits in neurite outgrowth,axon initial segment shortening,and a trend toward hyperexcitability,accompanied by broad transcriptomic changes affecting genes involved in microtubule organization and synaptic structure.Remarkably,re-expression of any of the six human brain-specific TAU isoforms rescues these phenotypes,underscoring their functional redundancy during development.These findings position the 0N3R isoform as essential for human brain development and suggest that loss-of-function mutations affecting this isoform likely result in neurodevelopmental impairment,potentially manifesting as intellectual disability without overt dysmorphic features.This contrasts with the apparent tolerance to MAPT loss-of-function in mice and peripheral tissues,highlighting a critical species-and isoform-specific requirement for TAU in human neurodevelopment.The hypothesis of 0N3R-TAU loss-of-function intolerance opens new avenues for understanding neurodevelopmental disorders and refines the conceptual framework of TAU-associated disease mechanisms beyond toxic gain-of-function.
基金Supported by the Research Grant Council,Research Impact Fund,No.R7007-22.
文摘BACKGROUND The rising incidence of inflammatory bowel disease(IBD)globally has increased disease burden and economic impact.Gaps remain in understanding the IBD burden between Asian and Western populations.AIM To estimate the current and following 10-year prevalence and incidence of IBD in Hong Kong,Japan,and the United States.METHODS Patients diagnosed with IBD were identified from a territory-wide electronic medical records database in Hong Kong(2003-2022,including all ages)and two large employment-based healthcare claims databases in Japan and the United States(2010-2022,including<65 age).We used Autoregressive Integrated Moving Average models to predict prevalence and incidence from 2023 to 2032,stratified by disease subtype[ulcerative colitis(UC);Crohn’s disease(CD)],sex,and age,with 95%prediction intervals(PIs).The forecasted annual average percentage change(AAPC)with 95%confidence intervals was calculated.RESULTS The age-standardized prevalence of IBD for 2032 is forecasted at 105.88 per 100000 in Hong Kong(95%PI:83.01-128.75,AAPC:5.85%),645.79 in Japan(95%PI:562.51-741.39,AAPC:5.78%),and 629.85 in the United States(95%PI:569.09-690.63,AAPC:2.85%).Prevalence is estimated to rise most significantly among those under 18 in Japan and the United States.Over the next decade,the incidence of IBD is estimated to increase annually by 3.3%in Hong Kong with forecasted increases across all age groups(although the AAPC for each group is not statistically significant);by 2.88%in Japan with a significant rise in those under 18 and stability in 18-65;and remaining stable in the United States.By 2032,the prevalence of CD is estimated to surpass UC in Hong Kong and the United States,whereas UC will continue to be more prevalent in Japan.A higher prevalence and incidence of IBD is forecast for males in Hong Kong and Japan,whereas rates will be similar for both males and females in the United States.CONCLUSION The prevalence of IBD is forecasted to increase in Hong Kong,Japan,and the United States,while estimates of incidence vary.The forecasts show distinct patterns across disease subtype,sex,and age groups.Health systems will need to plan for the predicted increasing prevalence among different demographics.
基金China-Korea Cooperation Project on the development of oceanic monitoring and prediction system on nuclear safetythe Project of the National Programme on Global Change and Air-sea Interaction under contract No.GASI-03-IPOVAI-05
文摘An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China＇s seas has been updated to（1/24）° from the global model with（1/2）°resolution. Besides, daily remote sensing sea surface temperature（SST） data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth（MLD） and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores（SS） is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value（more than 0.90）. Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.
文摘In this paper, the Holt’s exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2010 to May 2014. Results show that the ARIMA ((12), 1, 0) is an adequate model which best fits the CPI time series data and is therefore suitable for forecasting CPI and subsequently the inflation rate. However, the choice of the Holt’s exponential smoothing is as good as an ARIMA model considering the smaller deviations in the mean absolute percentage error and mean square error. Moreover, the Holt’s exponential smoothing model is less complicated since you do not require specialised software to implement it as is the case for ARIMA models. The forecasted inflation rate for April and May, 2015 is 7.0 and 6.6 respectively.
基金supported by Universidad Nacional de Córdoba(UNC),FONCYT-PDFT PRH No.3(UNC Program RRHH03),SECYT UNC,Universidad Nacional de San Juan—Institute of Automatics(INAUT),National Agency for Scientific and Technological Promotion(ANPCyT)and Departments of Electronics—Electrical and Electronic Engineering—Universidad Nacional of Cordoba.
文摘In this work an algorithm to predict short times series with missing data by means energy associated of series using artificial neural networks (ANN) is presented. In order to give the prediction one step ahead, a comparison between this and previous work that involves a similar approach to test short time series with uncertainties on their data, indicates that a linear smoothing is a well approximation in order to employ a method for uncompleted datasets. Moreover, in function of the long- or short-term stochastic dependence of the short time series considered, the training process modifies the number of patterns and iterations in the topology according to a heuristic law, where the Hurst parameter H is related with the short times series, of which they are considered as a path of the fractional Brownian motion. The results are evaluated on high roughness time series from solutions of the Mackey-Glass Equation (MG) and cumulative monthly historical rainfall data from San Agustin, Cordoba. A comparison with ANN nonlinear filters is shown in order to see a better performance of the outcomes when the information is taken from geographical point observation.
文摘North Dakota’s oil production has been rapidly increasing during the past several years. The state’s oil production in March 2013 even increased to more than twice the quantity produced in March 2011, and the estimated Bakken Formation reserves were reported very large compared with those of the United Arab Emirates. It eventually makes a question to us of how much oil will be able to be actually extracted with currently available technologies. To answer this question, this paper forecasts future oil development trend in North Dakota using the Seasonal Autoregressive Integrated Moving Average (S-ARIMA) model. Nonstationarity derived from a stochastic trend and the abrupt structural change of oil industry was a big potential problem, but through the Quandt Likelihood Ratio test, we found break points, which allowed us to select a model fitting period suitable for the S-ARIMA method to provide accurate statistical inference for the historical period. The seven major oil producing counties were investigated to determine whether the current oil boom was consistent across all oil fields in North Dakota. Empirical estimates show that North Dakota’s oil production will be more than double in the next five years. What we can predict with great certainty is that North Dakota’s influence over domestic and global oil supply systems will increase in the near future, especially over the next five to six years. This is good news for those who are concerned about domestic energy security in the USA.
文摘Diabetes has become a concern in the developed and developing countries with its growing number of patients reported to the ministry of health records. This paper discusses the use of the Autoregressive Fractional Moving Average (ARFIMA) technique to modeling the diabetes patient’s attendance at Al-Baha hospitals using monthly time series data. The data used in the analysis of this paper are monthly readings of diabetes patients data covered the period January 2006-December 2016. The data were collected from the General Directorate of Health Affairs, Al-Baha region. The autoregressive fractional moving average approach was applied to the data through the model identification, estimation, diagnostic checking and forecasting. Hurst test results and ACF confirmed that there is a long memory behavior in diabetic patient’s data. Also, the fractional difference to diabetes series data revealed that (<em>d</em> = 0.44). Moreover, unit root tests indicated that the fractional difference of diabetes series level is stationary. Furthermore, according to AIC and BIC of model selection criteria ARFIMA (1, 0.44, 0) model shown the smallest values, hence this model was chosen as an adequate represents the data. Also, a diagnostic check confirmed that ARFIMA was appropriate and highly recommended in modeling and forecasting this type of data.
基金sponsored by the National Natural Science Foundation of China(61333002)Open Research Foundation of the State Key Laboratory of Geodesy and Earth’s Dynamics(SKLGED2018-5-4-E)+5 种基金Foundation of the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems(ACIA2017002)111 projects under Grant(B17040)Open Research Project of the Hubei Key Laboratory of Intelligent Geo-Information Processing(KLIGIP-2017A02)supported by the Three Gorges Research Center for geo-hazardMinistry of Education cooperation agreements of Krasnoyarsk Science Center and Technology BureauRussian Academy of Sciences。
文摘The Earth’s natural pulse electromagnetic field data consists typically of an underlying variation tendency of intensity and irregularities.The change tendency may be related to the occurrence of earthquake disasters.Forecasting of the underlying intensity trend plays an important role in the analysis of data and disaster monitoring.Combining chaos theory and the radial basis function neural network,this paper proposes a forecasting model of the chaotic radial basis function neural network to conduct underlying intensity trend forecasting by the Earth’s natural pulse electromagnetic field signal.The main strategy of this forecasting model is to obtain parameters as the basis for optimizing the radial basis function neural network and to forecast the reconstructed Earth’s natural pulse electromagnetic field data.In verification experiments,we employ the 3 and 6 days’data of two channels as training samples to forecast the 14 and 21-day Earth’s natural pulse electromagnetic field data respectively.According to the forecasting results and absolute error results,the chaotic radial basis function forecasting model can fit the fluctuation trend of the actual signal strength,effectively reduce the forecasting error compared with the traditional radial basis function model.Hence,this network may be useful for studying the characteristics of the Earth’s natural pulse electromagnetic field signal before a strong earthquake and we hope it can contribute to the electromagnetic anomaly monitoring before the earthquake.
文摘As the acceleration of aged population tendency, building models to forecast Alzheimer’s Disease (AD) is essential. In this article, we surveyed 1157 interviewees. By analyzing the results using three machine learning methods—BP neural network, SVM and random forest, we can derive the accuracy of them in forecasting AD, so that we can compare the methods in solving AD prediction. Among them, random forest is the most accurate method. Moreover, to combine the advantages of the methods, we build a new combination forecasting model based on the three machine learning models, which is proved more accurate than the models singly. At last, we give the conclusion of the connection between life style and AD, and provide several suggestions for elderly people to help them prevent AD.
基金the National Natural Science Foundation of China Study on the Theory and Methods of Deterministic-Probabilistic(No.U2039207)the National Key Research and Development Program of China‘CSEP China in the Context of China Seismic Experimental Site’(No.2018YFE0109700).
文摘In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.
文摘This paper presented the new sanitary and health protocols implemented by cruise companies in order to internationally resuming the industry. The perception of Brazilians regarding these new protocols was identified through a quantitative survey with a sample of 412 Brazilian respondents, carried out between May and June 2021. As main results, sanitary and health protocols that do not affect their experiences on board were identified, as well as those protocols that compromised the experience perceived by the future traveler. The respondents’ propensity to travel on cruise ships and their perceptions about the influence of the ship size, the number of ports of call, nationalities on board, the number of vips, among other aspects, were also analyzed. Finally, in the final section of this paper, we presented an estimation of the expected number of cruisers for the 21/22 cruising season in Brazil, based on a kind Bayesian argument, considering different scenarios for the forthcoming season.
文摘In this paper, we present a new approach (Kalman Filter Smoothing) to estimate and forecast survival of Diabetic and Non Diabetic Coronary Artery Bypass Graft Surgery (CABG) patients. Survival proportions of the patients are obtained from a lifetime representing parametric model (Weibull distribution with Kalman Filter approach). Moreover, an approach of complete population (CP) from its incomplete population (IP) of the patients with 12 years observations/follow-up is used for their survival analysis [1]. The survival proportions of the CP obtained from Kaplan Meier method are used as observed values yt?at time t (input) for Kalman Filter Smoothing process to update time varying parameters. In case of CP, the term representing censored observations may be dropped from likelihood function of the distribution. Maximum likelihood method, in-conjunction with Davidon-Fletcher-Powell (DFP) optimization method [2] and Cubic Interpolation method is used in estimation of the survivor’s proportions. The estimated and forecasted survival proportions of CP of the Diabetic and Non Diabetic CABG patients from the Kalman Filter Smoothing approach are presented in terms of statistics, survival curves, discussion and conclusion.
文摘This paper deals with a new integrated method of reconstruction and forecasting of climatic changes in future. The method is based on proxy data pollen-spore analysis method, 14C analysis method, nowadays meteorological data, and data about of solar activity expressed in numbers of W （Wolf）. Here we present the results of investigation of sediments of the 2nd Fomich River terrace, Taymyr Peninsula, Russia. The formation of the peat bog started 10500 ± 140 years BP and continued during the entire Holocene. The pollen analysis of the sediment samples of the 2nd Fomich River terrace and the analysis of surface samples from a larch forest, typical of this region, reveals two phytochrones： both climatically preconditioned--tundra phytochrone （I1-4） and forest phytochrone （Ⅱ1-4）. The techniques of reconstruction and forecasting of basic elements of climate are presented and discussed in details.
