According to China's Customs' statistics,from January to May 2008,the import and export volume of foreign- invested enterprises totaled US$563.612 billion,an increase of 21.28 percent over the same period of l...According to China's Customs' statistics,from January to May 2008,the import and export volume of foreign- invested enterprises totaled US$563.612 billion,an increase of 21.28 percent over the same period of last year,5.02 percent lower than the growth rate of the country (26.30 percent) in the same period,accounting for 55.69 percent of the total import and export of the country.(See Chart 1)展开更多
The neutron capture resonance parameters for 159Tb are crucial for validating nuclear models,nucleosynthesis during the neutron capture process,and nuclear technology applications.In this study,resonance analyses were...The neutron capture resonance parameters for 159Tb are crucial for validating nuclear models,nucleosynthesis during the neutron capture process,and nuclear technology applications.In this study,resonance analyses were performed for the neutron capture cross sections of 159Tb measured at the China Spallation Neutron Source(CSNS)backscattering white neutron beamline(Back-n)facility.The resonance parameters were extracted from the R-Matrix code SAMMY and fitted to the experimental capture yield up to the 1.2 keV resolved resonance region(RRR).The average resonance parameters were determined by performing statistical analysis on the set of the resonance parameters in the RRR.These results were used to fit the measured average capture cross sections using the FITACS code in the unresolved resonance region from 2 keV to 1 MeV.The contributions of partial waves l=0,1,2 to the average capture cross sections are reported.展开更多
BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using...BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using ChatGPT to streamline and enhance the meta-analysis process.AIM To investigate the potential of ChatGPT to conduct meta-analyses in interventional cardiology by comparing the results of ChatGPT-generated analyses with those of randomly selected,human-conducted meta-analyses on the same topic.METHODS We systematically searched PubMed for meta-analyses on interventional cardiology published in 2024.Five metaanalyses were randomly chosen.ChatGPT 4.0 was used to perform meta-analyses on the extracted data.We compared the results from ChatGPT with the original meta-analyses,focusing on key effect sizes,such as risk ratios(RR),hazard ratios,and odds ratios,along with their confidence intervals(CI)and P values.RESULTS The ChatGPT results showed high concordance with those of the original meta-analyses.For most outcomes,the effect measures and P values generated by ChatGPT closely matched those of the original studies,except for the RR of stent thrombosis in the Sreenivasan et al study,where ChatGPT reported a non-significant effect size,while the original study found it to be statistically significant.While minor discrepancies were observed in specific CI and P values,these differences did not alter the overall conclusions drawn from the analyses.CONCLUSION Our findings suggest the potential of ChatGPT in conducting meta-analyses in interventional cardiology.However,further research is needed to address the limitations of transparency and potential data quality issues,ensuring that AI-generated analyses are robust and trustworthy for clinical decision-making.展开更多
The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and co...The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).展开更多
Cryo-electron microscopy(cryo-EM) provides a powerful tool to resolve the structure of biological macromolecules in natural state. One advantage of cryo-EM technology is that different conformation states of a protein...Cryo-electron microscopy(cryo-EM) provides a powerful tool to resolve the structure of biological macromolecules in natural state. One advantage of cryo-EM technology is that different conformation states of a protein complex structure can be simultaneously built, and the distribution of different states can be measured. This provides a tool to push cryo-EM technology beyond just to resolve protein structures, but to obtain the thermodynamic properties of protein machines. Here, we used a deep manifold learning framework to get the conformational landscape of Kai C proteins, and further obtained the thermodynamic properties of this central oscillator component in the circadian clock by means of statistical physics.展开更多
Population growth and expanding urbanization have caused persistent shortages and contamination of groundwater resources in Mali,Africa.The increase in groundwater salinity makes it more difficult for residents to obt...Population growth and expanding urbanization have caused persistent shortages and contamination of groundwater resources in Mali,Africa.The increase in groundwater salinity makes it more difficult for residents to obtain drinking water,it is necessary to clarify the causes and control factors of groundwater mineralization in Gao region,northern Mali.Based on the analysis of the hydrochemical composition of groundwater in 24 boreholes,Piper and Sch?eller diagrams,principal component analysis(PCA)and hierarchical cluster analysis(HCA)are used to carry out multivariate statistical analysis on the main ions.The results show that the groundwater samples are weakly alkaline,with pH values ranging from 5.83 to 8.40,and the average values of boreholes are 7.50,respectively.The average electrical conductivity(EC)value is 354.4(μS/cm),and the extreme value is between 124.0 and 1247(μS/cm).Water is usually mineralized and presents nine types of water phase.The three principal components explain 84.42%of the total variance for 13 parameters.The factor F1(58.85%),the factor F2(16.88%)and the factor F3(8.69%)present for the majority of the total data set.In addition,multivariate statistical analysis confirmed the genetic relationship among aquifers and identified three main clusters.Clustering related to groundwater mineralization(F1),clustering related to oxide reduction and iron enrichment(F2),and clustering of groundwater pollution caused by nitrate and magnesium(F3).We found that agriculture,weathering activities and dissolution of geological materials promote the mineralization of groundwater.Groundwater quality in the Gao region is becoming less and less potable because of increasing salinity.展开更多
Three-point bending fatigue experiments were conducted on a typical Zr-based bulk metallic glass(BMG)at ambient temperature to investigate the fatigue behavior under cyclic loading conditions.Results show that the str...Three-point bending fatigue experiments were conducted on a typical Zr-based bulk metallic glass(BMG)at ambient temperature to investigate the fatigue behavior under cyclic loading conditions.Results show that the stress amplitude-cycles to failure(S-N)curve of the Zr-based BMG is determined,and the fatigue endurance limit is 442 MPa(stress amplitude).To evaluate the probability-stress amplitude-cycles to failure(P-S-N)curve,an estimation method based on maximum likelihood was proposed,which relies on statistical principles to estimate the fatigue life of the material and allows for a reduction in the number of samples required,offering a cost-effective and efficient alternative to traditional testing methods.The experimental results align with the American Society for Testing and Materials(ASTM)standard,indicating the reliability and accuracy of this estimation method in evaluating the fatigue behavior of Zr-based BMG.展开更多
Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NV...Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).展开更多
Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information abou...Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.展开更多
This study focuses on designing a solution to the perennial issue of clothing fit in Fashion Industry using tools offered by digital technology and statistical analysis, in particular, the data gathered on Asian women...This study focuses on designing a solution to the perennial issue of clothing fit in Fashion Industry using tools offered by digital technology and statistical analysis, in particular, the data gathered on Asian women (Bangladeshi and Chinese). The study reveals that managing information can significantly enhance the capability of the industry to cater to the needs of its consumers and increase diversity. It centers on the effectiveness of turning dressmaking patterns into digital ones, thus transecting from traditional cutting and stitching to remote techniques. This entails the requirement to have correct self-measures and probable errors, which can arise in the process. Thus, with the help of regression analysis, the study identifies, which measurements are incorrect and influence the fit of the clothes, and, therefore, digital pattern creation is more accurate. Altogether, it can be observed how digitalization and statistical methods are crucial to transforming the way clothes are created to approach an ideal standard of measurements that fulfill every customer’s needs to make operational and efficient the clothing sector.展开更多
To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA）...To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA） is proposed to analyze vibro-acoustics responses with uncertainties at middle frequencies. The mid-frequency dynamic response of the framework-plate structure with uncertainties is studied based on the hybrid FE-SEA method and the Monte Carlo（MC）simulation is performed so as to provide a benchmark comparison with the hybrid method. The energy response of the framework-plate structure matches well with the MC simulation results, which validates the effectiveness of the hybrid FE-SEA method considering both the complexity of the vibro-acoustic structure and the uncertainties in mid-frequency vibro-acousitc analysis. Based on the hybrid method, a vibroacoustic model of a construction machinery cab with random properties is established, and the excitations of the model are measured by experiments. The responses of the sound pressure level of the cab and the vibration power spectrum density of the front windscreen are calculated and compared with those of the experiment. At middle frequencies, the results have a good consistency with the tests and the prediction error is less than 3. 5dB.展开更多
[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was ...[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was analyzed by three models respectively： Finlay and Wilkinson model： the additive main effects and multiplicative interaction （AMMI） model and linear regression-principal components analysis （LR- PCA） model, so as to compare the models. [Result] The Finlay and Wilkinson model was easier, but the analysis of the other two models was more comprehensive, and there was a bit difference between the additive main effects and multiplicative inter- action （AMMI） model and linear regression-principal components analysis （LR-PCA） model. [Conclusion] In practice, while the proper statistical method was usually con- sidered according to the different data, it should be also considered that the same data should be analyzed with different statistical methods in order to get a more reasonable result by comparison.展开更多
Based on the real-time wind direction and speed data from an automatic meteorological monitoring network in Shenzhen, the wind characteristics of Jue Diao Sha maritime area are analyzed. As indicated in the results, t...Based on the real-time wind direction and speed data from an automatic meteorological monitoring network in Shenzhen, the wind characteristics of Jue Diao Sha maritime area are analyzed. As indicated in the results, the wind speed of this area is higher than that over the land, the average wind speed is above 3 m/s and the probability for the maximum wind speed to drop below 20 m/s is above 90%. Moreover, the probability for the hourly swing angle of wind direction to become less than 50o is above 80%, suggesting that the wind conditions in the Jue Diao Sha area could meet the requirements of the sporting events. According to the numerical simulation, this area is the best selected site among three candidates. Furthermore, the characteristics of daily land and sea breezes are such that it is suggested the game will be best carried out from 1000 to 1700 Beijing Standard Time.展开更多
Based on tidal data statistical analysis for 20 years of Tanggu Marine Environmental Monitoring Station from 1991 to 2010, we concluded that an average of nearly 10 days of 100 cm above water increase took place at Ti...Based on tidal data statistical analysis for 20 years of Tanggu Marine Environmental Monitoring Station from 1991 to 2010, we concluded that an average of nearly 10 days of 100 cm above water increase took place at Tianjin coast every year. The maximum high tide and average tide of Tianjin coast occurred in summer and autumn, and the maximum water increase also occurred in summer and autumn. Days with water increase more than 100 cm mostly occurred in spring, autumn and winter. Then we summarized the causes of coastal storm surge disaster in Tianjin based on astronomical tide factors, meteorological factors, sea level rise, land subsidence, and geographic factors, et al. Finally, we proposed storm surge disaster prevention measures.展开更多
Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements ...Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements of statistical methods due to the closure effect.In this study,we applied an integrated approach combining compositional data,multifractal,and multivariate statistical analyses to identify the nonlinear complexity of the spatial distributions of elemental concentrations in the Er’renshan ore field.Initially,the raw concentrations were transformed into log-ratios following the principles of composition data theory to alleviate the impact of the closure effect.Multifractal analysis was then conducted to characterise the nonlinear complexity of the concentration distributions.Furthermore,principal component analysis(PCA)and factor analysis(FA)were applied to identify spurious correlations and the potential factors controlling the distribution patterns.The results demonstrate that:a)the raw data are biased,while the log-ratio data are unbiased and more reliable;b)the spatial distributions of elemental concentrations exhibit nonlinear complexity;and c)the elemental distribution in the study area is largely controlled by structural factors.展开更多
Multi-angle statistical analysis of tropical cyclones(TCs)and their distant thermodynamic disturbances over Northwest Pacific from July to September during 2001-2020 was conducted.The results show that TCs could trigg...Multi-angle statistical analysis of tropical cyclones(TCs)and their distant thermodynamic disturbances over Northwest Pacific from July to September during 2001-2020 was conducted.The results show that TCs could trigger distant thermodynamic disturbances,which mainly caused an increase in air pressure and a rise in temperature in northern China.The distant thermodynamic disturbances triggered by TCs differed in spatial distribution and intensity in different months.In the same month,the spatial distribution of such disturbances triggered by high-intensity TCs was consistent with the overall pattern,and there was a significant increase in intensity and area.From the probability of TC activities and the significance test of variance of analysis under different levels of P-J index,it is found that TC activities could stimulate the increase of P-J teleconnection index.There was a significant positive correlation between them,which was accompanied by a step effect.展开更多
The Kumaun Himalaya is well-known as a geologically and tectonically complex region that amplifies mass wasting processes,particularly landslides.This study attempts to investigate the interplay between landslide dist...The Kumaun Himalaya is well-known as a geologically and tectonically complex region that amplifies mass wasting processes,particularly landslides.This study attempts to investigate the interplay between landslide distribution and the lithotectonic regime of Darma Valley,Kumaun Himalaya.A landslide inventory comprising 295 landslides in the area has been prepared and several morphotectonic proxies such as valley floor width to height ratio(Vf),stream length gradient index(SL),and hypsometric integral(HI)have been used to infer tectonic regime.Morphometric analysis,including basic,linear,aerial,and relief aspects,of 59 fourth-order sub-basins,has been carried out to estimate erosion potential in the study area.The result demonstrates that 46.77%of the landslides lie in very high,20.32%in high,21.29%in medium,and 11.61%in low erosion potential zones respectively.In order to determine the key parameters controlling erosion potential,two multivariate statistical methods namely Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC)were utilized.PCA reveals that the Higher Himalayan Zone(HHZ)has the highest erosion potential due to the presence of elongated sub-basins characterized by steep slopes and high relief.The clusters created through AHC exhibit positive PCA values,indicating a robust correlation between PCA and AHC.Furthermore,the landslide density map shows two major landslide hotspots.One of these hotspots lies in the vicinity of highly active Munsiyari Thrust(MT),while the other is in the Pandukeshwar formation within the MT's hanging wall,characterized by a high exhumation rate.High SL and low Vf values along these hotspots further corroborate that the occurrence of landslides in the study area is influenced by tectonic activity.This study,by identifying erosionprone areas and elucidating the implications of tectonic activity on landslide distribution,empowers policymakers and government agencies to develop strategies for hazard assessment and effective landslide risk mitigation,consequently safeguarding lives and communities.展开更多
The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and...The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and statistical analysis methods.The travel-time corrections for the Pg phase of 72 stations range between-0.25 s and 0.14 s,while the corrections for the Sg phase range between 0.27 s and 0.35 s,and those for the Pn phase are between-0.86 s and 0.07 s.The spatial distribution of travel-time corrections for Pg,Sg,and Pn phases of 72 stations correlates well with the geological structure in this region.This indicates that the travel-time corrections for Pg and Sg phases are mainly caused by the discrepancy between the actual crustal velocity structure beneath the stations and the 1D South China travel-time model.These corrections empirically compensate for systematic travel-time errors arising from such discrepancies.The primary factor contributing to the travel-time corrections for the Pn phase is the Moho undulations or tilt.These corrections are intended to compensate for systematic errors in travel time caused by variations in the actual Moho.By integrating the obtained travel-time corrections into the HYPO-SAT location algorithm,test results showed an obvious improvement in location accuracy and origin time precision for explosion events.The variation of horizontal distance between repeating earthquake pairs has also improved,with 86%of the repeating earthquake pair spacing being more accurately estimated after correction.This suggests the crucial significance of travel-time correction in earthquake location,and the consideration of travel-time correction exerts a notable impact on enhancing earthquake location accuracy.展开更多
Objective To explore the current state of biopharmaceutical innovation in Africa by analyzing patent data related to biopharmaceutical products in African countries.Methods Based on patent data,simple descriptive stat...Objective To explore the current state of biopharmaceutical innovation in Africa by analyzing patent data related to biopharmaceutical products in African countries.Methods Based on patent data,simple descriptive statistical methods were used to analyze the trend of patent applications,the geographical distribution of patents,and the distribution of applicants in the pharmaceutical field in Africa.Besides,Excel software was used to draw charts to visualize statistical information.Results and Conclusion According to the result,a large number of patents has been granted in these countries and the number is steadily rising each year.From the figure below,we can see that the largest number of patents was granted to Morocco in 2014 with a total number of 613 patents followed by Tunisia with 315 patents,the African Intellectual Property Organization(OAPI)with 124 patents,South Africa with 106 and Mozambique with 1 patent based on data availability(IncoPat Global Patent Search Database).It was observed that,as patents were granted,the number of applications filed on this continent increased.The largest number of patents has been recorded by Morocco,Tunisia and South Africa.Patent applications in Morocco increased fast with an average annual growth of 7.3%.The increase in patent applications is due to improved research infrastructure and enhanced research activities,which shows the importance of biopharmaceutical innovation in the continent.展开更多
The unique structure of signed networks,characterized by positive and negative edges,poses significant challenges for analyzing network topology.In recent years,various statistical algorithms have been developed to ad...The unique structure of signed networks,characterized by positive and negative edges,poses significant challenges for analyzing network topology.In recent years,various statistical algorithms have been developed to address this issue.However,there remains a lack of a unified framework to uncover the nontrivial properties inherent in signed network structures.To support developers,researchers,and practitioners in this field,we introduce a Python library named SNSAlib(Signed Network Structure Analysis),specifically designed to meet these analytical requirements.This library encompasses empirical signed network datasets,signed null model algorithms,signed statistics algorithms,and evaluation indicators.The primary objective of SNSAlib is to facilitate the systematic analysis of micro-and meso-structure features within signed networks,including node popularity,clustering,assortativity,embeddedness,and community structure by employing more accurate signed null models.Ultimately,it provides a robust paradigm for structure analysis of signed networks that enhances our understanding and application of signed networks.展开更多
文摘According to China's Customs' statistics,from January to May 2008,the import and export volume of foreign- invested enterprises totaled US$563.612 billion,an increase of 21.28 percent over the same period of last year,5.02 percent lower than the growth rate of the country (26.30 percent) in the same period,accounting for 55.69 percent of the total import and export of the country.(See Chart 1)
基金supported by the National Natural Science Foundation of China(Nos.12365018,U2032146,12465024)Natural Science Foundation of Inner Mongolia(Nos.2023MS01005,2024ZD23,2024FX30)the program of Innovative Research Team and Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(Nos.NMGIRT2217,NJYT23109)。
文摘The neutron capture resonance parameters for 159Tb are crucial for validating nuclear models,nucleosynthesis during the neutron capture process,and nuclear technology applications.In this study,resonance analyses were performed for the neutron capture cross sections of 159Tb measured at the China Spallation Neutron Source(CSNS)backscattering white neutron beamline(Back-n)facility.The resonance parameters were extracted from the R-Matrix code SAMMY and fitted to the experimental capture yield up to the 1.2 keV resolved resonance region(RRR).The average resonance parameters were determined by performing statistical analysis on the set of the resonance parameters in the RRR.These results were used to fit the measured average capture cross sections using the FITACS code in the unresolved resonance region from 2 keV to 1 MeV.The contributions of partial waves l=0,1,2 to the average capture cross sections are reported.
文摘BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using ChatGPT to streamline and enhance the meta-analysis process.AIM To investigate the potential of ChatGPT to conduct meta-analyses in interventional cardiology by comparing the results of ChatGPT-generated analyses with those of randomly selected,human-conducted meta-analyses on the same topic.METHODS We systematically searched PubMed for meta-analyses on interventional cardiology published in 2024.Five metaanalyses were randomly chosen.ChatGPT 4.0 was used to perform meta-analyses on the extracted data.We compared the results from ChatGPT with the original meta-analyses,focusing on key effect sizes,such as risk ratios(RR),hazard ratios,and odds ratios,along with their confidence intervals(CI)and P values.RESULTS The ChatGPT results showed high concordance with those of the original meta-analyses.For most outcomes,the effect measures and P values generated by ChatGPT closely matched those of the original studies,except for the RR of stent thrombosis in the Sreenivasan et al study,where ChatGPT reported a non-significant effect size,while the original study found it to be statistically significant.While minor discrepancies were observed in specific CI and P values,these differences did not alter the overall conclusions drawn from the analyses.CONCLUSION Our findings suggest the potential of ChatGPT in conducting meta-analyses in interventional cardiology.However,further research is needed to address the limitations of transparency and potential data quality issues,ensuring that AI-generated analyses are robust and trustworthy for clinical decision-making.
基金The National Natural Science Foundation of China under contract Nos 41875061 and 41775165.
文摘The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).
基金supported by the National Natural Science Foundation of China (Grant No. 12090054)。
文摘Cryo-electron microscopy(cryo-EM) provides a powerful tool to resolve the structure of biological macromolecules in natural state. One advantage of cryo-EM technology is that different conformation states of a protein complex structure can be simultaneously built, and the distribution of different states can be measured. This provides a tool to push cryo-EM technology beyond just to resolve protein structures, but to obtain the thermodynamic properties of protein machines. Here, we used a deep manifold learning framework to get the conformational landscape of Kai C proteins, and further obtained the thermodynamic properties of this central oscillator component in the circadian clock by means of statistical physics.
基金funded by the China's National Natural Science Foundation(No.41440027)。
文摘Population growth and expanding urbanization have caused persistent shortages and contamination of groundwater resources in Mali,Africa.The increase in groundwater salinity makes it more difficult for residents to obtain drinking water,it is necessary to clarify the causes and control factors of groundwater mineralization in Gao region,northern Mali.Based on the analysis of the hydrochemical composition of groundwater in 24 boreholes,Piper and Sch?eller diagrams,principal component analysis(PCA)and hierarchical cluster analysis(HCA)are used to carry out multivariate statistical analysis on the main ions.The results show that the groundwater samples are weakly alkaline,with pH values ranging from 5.83 to 8.40,and the average values of boreholes are 7.50,respectively.The average electrical conductivity(EC)value is 354.4(μS/cm),and the extreme value is between 124.0 and 1247(μS/cm).Water is usually mineralized and presents nine types of water phase.The three principal components explain 84.42%of the total variance for 13 parameters.The factor F1(58.85%),the factor F2(16.88%)and the factor F3(8.69%)present for the majority of the total data set.In addition,multivariate statistical analysis confirmed the genetic relationship among aquifers and identified three main clusters.Clustering related to groundwater mineralization(F1),clustering related to oxide reduction and iron enrichment(F2),and clustering of groundwater pollution caused by nitrate and magnesium(F3).We found that agriculture,weathering activities and dissolution of geological materials promote the mineralization of groundwater.Groundwater quality in the Gao region is becoming less and less potable because of increasing salinity.
基金Guangdong Basic and Applied Basic Research Foundation(2022A1515010207)Shaanxi Key Laboratory of Artificially-Structured Functional Materials and Devices(AFMD-KFJJ-22204)。
文摘Three-point bending fatigue experiments were conducted on a typical Zr-based bulk metallic glass(BMG)at ambient temperature to investigate the fatigue behavior under cyclic loading conditions.Results show that the stress amplitude-cycles to failure(S-N)curve of the Zr-based BMG is determined,and the fatigue endurance limit is 442 MPa(stress amplitude).To evaluate the probability-stress amplitude-cycles to failure(P-S-N)curve,an estimation method based on maximum likelihood was proposed,which relies on statistical principles to estimate the fatigue life of the material and allows for a reduction in the number of samples required,offering a cost-effective and efficient alternative to traditional testing methods.The experimental results align with the American Society for Testing and Materials(ASTM)standard,indicating the reliability and accuracy of this estimation method in evaluating the fatigue behavior of Zr-based BMG.
文摘Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).
文摘Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.
文摘This study focuses on designing a solution to the perennial issue of clothing fit in Fashion Industry using tools offered by digital technology and statistical analysis, in particular, the data gathered on Asian women (Bangladeshi and Chinese). The study reveals that managing information can significantly enhance the capability of the industry to cater to the needs of its consumers and increase diversity. It centers on the effectiveness of turning dressmaking patterns into digital ones, thus transecting from traditional cutting and stitching to remote techniques. This entails the requirement to have correct self-measures and probable errors, which can arise in the process. Thus, with the help of regression analysis, the study identifies, which measurements are incorrect and influence the fit of the clothes, and, therefore, digital pattern creation is more accurate. Altogether, it can be observed how digitalization and statistical methods are crucial to transforming the way clothes are created to approach an ideal standard of measurements that fulfill every customer’s needs to make operational and efficient the clothing sector.
基金Science and Technology Support Planning of Jiangsu Province(No.BE2014133)the Open Foundation of Key Laboratory of Underw ater Acoustic Signal Processing(No.UASP1301)the Prospective Joint Research Project of Jiangsu province(No.BY2014127-01)
文摘To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA） is proposed to analyze vibro-acoustics responses with uncertainties at middle frequencies. The mid-frequency dynamic response of the framework-plate structure with uncertainties is studied based on the hybrid FE-SEA method and the Monte Carlo（MC）simulation is performed so as to provide a benchmark comparison with the hybrid method. The energy response of the framework-plate structure matches well with the MC simulation results, which validates the effectiveness of the hybrid FE-SEA method considering both the complexity of the vibro-acoustic structure and the uncertainties in mid-frequency vibro-acousitc analysis. Based on the hybrid method, a vibroacoustic model of a construction machinery cab with random properties is established, and the excitations of the model are measured by experiments. The responses of the sound pressure level of the cab and the vibration power spectrum density of the front windscreen are calculated and compared with those of the experiment. At middle frequencies, the results have a good consistency with the tests and the prediction error is less than 3. 5dB.
基金Supported by the Guangdong Technological Program (2009B02001002)the Special Funds of National Agricultural Department for Commonweal Trade Research (nyhyzx07-019)the Earmarked Fund for Modern Agro-industry Technology Research System~~
文摘[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was analyzed by three models respectively： Finlay and Wilkinson model： the additive main effects and multiplicative interaction （AMMI） model and linear regression-principal components analysis （LR- PCA） model, so as to compare the models. [Result] The Finlay and Wilkinson model was easier, but the analysis of the other two models was more comprehensive, and there was a bit difference between the additive main effects and multiplicative inter- action （AMMI） model and linear regression-principal components analysis （LR-PCA） model. [Conclusion] In practice, while the proper statistical method was usually con- sidered according to the different data, it should be also considered that the same data should be analyzed with different statistical methods in order to get a more reasonable result by comparison.
基金Project on Meteorological Conditions for Selection of Site of Maritime Sporting Base for 26th Summer Universiade 2011
文摘Based on the real-time wind direction and speed data from an automatic meteorological monitoring network in Shenzhen, the wind characteristics of Jue Diao Sha maritime area are analyzed. As indicated in the results, the wind speed of this area is higher than that over the land, the average wind speed is above 3 m/s and the probability for the maximum wind speed to drop below 20 m/s is above 90%. Moreover, the probability for the hourly swing angle of wind direction to become less than 50o is above 80%, suggesting that the wind conditions in the Jue Diao Sha area could meet the requirements of the sporting events. According to the numerical simulation, this area is the best selected site among three candidates. Furthermore, the characteristics of daily land and sea breezes are such that it is suggested the game will be best carried out from 1000 to 1700 Beijing Standard Time.
文摘Based on tidal data statistical analysis for 20 years of Tanggu Marine Environmental Monitoring Station from 1991 to 2010, we concluded that an average of nearly 10 days of 100 cm above water increase took place at Tianjin coast every year. The maximum high tide and average tide of Tianjin coast occurred in summer and autumn, and the maximum water increase also occurred in summer and autumn. Days with water increase more than 100 cm mostly occurred in spring, autumn and winter. Then we summarized the causes of coastal storm surge disaster in Tianjin based on astronomical tide factors, meteorological factors, sea level rise, land subsidence, and geographic factors, et al. Finally, we proposed storm surge disaster prevention measures.
基金supported by the Doctoral Research Start-up Fund,East China University of Technology(DHBK2019313)the Open Research Fund Program of Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring(Central South University),the Ministry of Education(2020YSJS10)+1 种基金the Open Research Fund Program of Shandong Provincial Engineering Laboratory of Application and Development of Big Data for Deep Gold Exploration(SDK202224)the Basic Scientific Research Fund of the Institute of Geophysical and Geochemical Exploration,Chinese Academy of Geological Sciences(AS2022P03).
文摘Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements of statistical methods due to the closure effect.In this study,we applied an integrated approach combining compositional data,multifractal,and multivariate statistical analyses to identify the nonlinear complexity of the spatial distributions of elemental concentrations in the Er’renshan ore field.Initially,the raw concentrations were transformed into log-ratios following the principles of composition data theory to alleviate the impact of the closure effect.Multifractal analysis was then conducted to characterise the nonlinear complexity of the concentration distributions.Furthermore,principal component analysis(PCA)and factor analysis(FA)were applied to identify spurious correlations and the potential factors controlling the distribution patterns.The results demonstrate that:a)the raw data are biased,while the log-ratio data are unbiased and more reliable;b)the spatial distributions of elemental concentrations exhibit nonlinear complexity;and c)the elemental distribution in the study area is largely controlled by structural factors.
基金the National Natural Science Foundation of China(42305011).
文摘Multi-angle statistical analysis of tropical cyclones(TCs)and their distant thermodynamic disturbances over Northwest Pacific from July to September during 2001-2020 was conducted.The results show that TCs could trigger distant thermodynamic disturbances,which mainly caused an increase in air pressure and a rise in temperature in northern China.The distant thermodynamic disturbances triggered by TCs differed in spatial distribution and intensity in different months.In the same month,the spatial distribution of such disturbances triggered by high-intensity TCs was consistent with the overall pattern,and there was a significant increase in intensity and area.From the probability of TC activities and the significance test of variance of analysis under different levels of P-J index,it is found that TC activities could stimulate the increase of P-J teleconnection index.There was a significant positive correlation between them,which was accompanied by a step effect.
基金CSIR for providing financial assistance(09/0420(11800)/2021EMR-I)。
文摘The Kumaun Himalaya is well-known as a geologically and tectonically complex region that amplifies mass wasting processes,particularly landslides.This study attempts to investigate the interplay between landslide distribution and the lithotectonic regime of Darma Valley,Kumaun Himalaya.A landslide inventory comprising 295 landslides in the area has been prepared and several morphotectonic proxies such as valley floor width to height ratio(Vf),stream length gradient index(SL),and hypsometric integral(HI)have been used to infer tectonic regime.Morphometric analysis,including basic,linear,aerial,and relief aspects,of 59 fourth-order sub-basins,has been carried out to estimate erosion potential in the study area.The result demonstrates that 46.77%of the landslides lie in very high,20.32%in high,21.29%in medium,and 11.61%in low erosion potential zones respectively.In order to determine the key parameters controlling erosion potential,two multivariate statistical methods namely Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC)were utilized.PCA reveals that the Higher Himalayan Zone(HHZ)has the highest erosion potential due to the presence of elongated sub-basins characterized by steep slopes and high relief.The clusters created through AHC exhibit positive PCA values,indicating a robust correlation between PCA and AHC.Furthermore,the landslide density map shows two major landslide hotspots.One of these hotspots lies in the vicinity of highly active Munsiyari Thrust(MT),while the other is in the Pandukeshwar formation within the MT's hanging wall,characterized by a high exhumation rate.High SL and low Vf values along these hotspots further corroborate that the occurrence of landslides in the study area is influenced by tectonic activity.This study,by identifying erosionprone areas and elucidating the implications of tectonic activity on landslide distribution,empowers policymakers and government agencies to develop strategies for hazard assessment and effective landslide risk mitigation,consequently safeguarding lives and communities.
基金supported by the National Key Research and Development Program of China(2023YFC3008605)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021002)the Seismological Research Foundation for Youths of Guangdong Earthquake Agency(Open Funding Project of Key Laboratory of Earthquake Monitoring and Disaster Mitigation Technology,China Earthquake Administration)(GDDZY202309)。
文摘The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and statistical analysis methods.The travel-time corrections for the Pg phase of 72 stations range between-0.25 s and 0.14 s,while the corrections for the Sg phase range between 0.27 s and 0.35 s,and those for the Pn phase are between-0.86 s and 0.07 s.The spatial distribution of travel-time corrections for Pg,Sg,and Pn phases of 72 stations correlates well with the geological structure in this region.This indicates that the travel-time corrections for Pg and Sg phases are mainly caused by the discrepancy between the actual crustal velocity structure beneath the stations and the 1D South China travel-time model.These corrections empirically compensate for systematic travel-time errors arising from such discrepancies.The primary factor contributing to the travel-time corrections for the Pn phase is the Moho undulations or tilt.These corrections are intended to compensate for systematic errors in travel time caused by variations in the actual Moho.By integrating the obtained travel-time corrections into the HYPO-SAT location algorithm,test results showed an obvious improvement in location accuracy and origin time precision for explosion events.The variation of horizontal distance between repeating earthquake pairs has also improved,with 86%of the repeating earthquake pair spacing being more accurately estimated after correction.This suggests the crucial significance of travel-time correction in earthquake location,and the consideration of travel-time correction exerts a notable impact on enhancing earthquake location accuracy.
文摘Objective To explore the current state of biopharmaceutical innovation in Africa by analyzing patent data related to biopharmaceutical products in African countries.Methods Based on patent data,simple descriptive statistical methods were used to analyze the trend of patent applications,the geographical distribution of patents,and the distribution of applicants in the pharmaceutical field in Africa.Besides,Excel software was used to draw charts to visualize statistical information.Results and Conclusion According to the result,a large number of patents has been granted in these countries and the number is steadily rising each year.From the figure below,we can see that the largest number of patents was granted to Morocco in 2014 with a total number of 613 patents followed by Tunisia with 315 patents,the African Intellectual Property Organization(OAPI)with 124 patents,South Africa with 106 and Mozambique with 1 patent based on data availability(IncoPat Global Patent Search Database).It was observed that,as patents were granted,the number of applications filed on this continent increased.The largest number of patents has been recorded by Morocco,Tunisia and South Africa.Patent applications in Morocco increased fast with an average annual growth of 7.3%.The increase in patent applications is due to improved research infrastructure and enhanced research activities,which shows the importance of biopharmaceutical innovation in the continent.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.72371031,62173065,62476045)Fundamental Research Funds for the Central Universities(Grant No.124330008)。
文摘The unique structure of signed networks,characterized by positive and negative edges,poses significant challenges for analyzing network topology.In recent years,various statistical algorithms have been developed to address this issue.However,there remains a lack of a unified framework to uncover the nontrivial properties inherent in signed network structures.To support developers,researchers,and practitioners in this field,we introduce a Python library named SNSAlib(Signed Network Structure Analysis),specifically designed to meet these analytical requirements.This library encompasses empirical signed network datasets,signed null model algorithms,signed statistics algorithms,and evaluation indicators.The primary objective of SNSAlib is to facilitate the systematic analysis of micro-and meso-structure features within signed networks,including node popularity,clustering,assortativity,embeddedness,and community structure by employing more accurate signed null models.Ultimately,it provides a robust paradigm for structure analysis of signed networks that enhances our understanding and application of signed networks.
