The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities...The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.展开更多
High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging ...High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).展开更多
Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including ...Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.展开更多
Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced tech...Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.展开更多
Named Data Networking(NDN)improves the data delivery efficiency by caching contents in routers. To prevent corrupted and faked contents be spread in the network,NDN routers should verify the digital signature of each ...Named Data Networking(NDN)improves the data delivery efficiency by caching contents in routers. To prevent corrupted and faked contents be spread in the network,NDN routers should verify the digital signature of each published content. Since the verification scheme in NDN applies the asymmetric encryption algorithm to sign contents,the content verification overhead is too high to satisfy wire-speed packet forwarding. In this paper, we propose two schemes to improve the verification performance of NDN routers to prevent content poisoning. The first content verification scheme, called "user-assisted",leads to the best performance, but can be bypassed if the clients and the content producer collude. A second scheme, named ``RouterCooperation ‘', prevents the aforementioned collusion attack by making edge routers verify the contents independently without the assistance of users and the core routers no longer verify the contents. The Router-Cooperation verification scheme reduces the computing complexity of cryptographic operation by replacing the asymmetric encryption algorithm with symmetric encryption algorithm.The simulation results demonstrate that this Router-Cooperation scheme can speed up18.85 times of the original content verification scheme with merely extra 80 Bytes transmission overhead.展开更多
Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperatur...Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperature, and precipitation will affect grain protein contents and these factors usually cannot be monitored accurately by remote sensing data from single image. In this research, the relationships between wheat protein content at maturity and wheat agronomic parameters at different growing stages were analyzed and multi-temporal images of Landsat TM were used to estimate grain protein content by partial least squares regression. Experiment data were acquired in the suburb of Beijing during a 2-yr experiment in the period from 2003 to 2004. Determination coefficient, average deviation of self-modeling, and deviation of cross- validation were employed to assess the estimation accuracy of wheat grain protein content. Their values were 0.88, 1.30%, 3.81% and 0.72, 5.22%, 12.36% for 2003 and 2004, respectively. The research laid an agronomic foundation for GPC （grain protein content） estimation by multi-temporal remote sensing. The results showed that it is feasible to estimate GPC of wheat from multi-temporal remote sensing data in large area.展开更多
Spatial and temporal resolution of water vapor content is useful in improving the accuracy of short_term weather prediction.Dense and continuously tracking regional GPS arrays will play an important role in remote sen...Spatial and temporal resolution of water vapor content is useful in improving the accuracy of short_term weather prediction.Dense and continuously tracking regional GPS arrays will play an important role in remote sensing atmospheric water vapor content.In this study,a piecewise linear solution method was proposed to estimate the precipitable water vapor (PWV) content from ground_based GPS observations in Hong Kong.To evaluate the solution accuracy of the water vapor content sensed by GPS,the upper air sounding data (radiosonde) that are collected locally was used to calculate the precipitable water vapor during the same period.One_month results of PWV from both ground_based GPS sensing technique and radiosonde method are in agreement within 1～2 mm.This encouraging result will motivate the GPS meteorology application based on the establishment of a dense GPS array in Hong Kong.展开更多
Cryogenian Datangpo Formation was deposited during the interglacial time between the Sturtian and Marinoan ice ages. We studied nitrogen isotope compositions and contents of Mo of the black shales from the basal Datan...Cryogenian Datangpo Formation was deposited during the interglacial time between the Sturtian and Marinoan ice ages. We studied nitrogen isotope compositions and contents of Mo of the black shales from the basal Datangpo Formation in northeastern Guizhou, South China, for an attempt to reconstruct the marine redox change and nitrogen cycle during the interglacial time. Based on lithostratigraphy as well as geochemical profiles, the basal black shales can be divided into four intervals： Interval 1 has the lowest δ^（15）N value（＋5.0‰）; in interval 2, δ^（15）N values vary between ＋6.4‰ and ＋7.4‰（the first peak）; interval 3 records stable values of δ^（15）N around ＋6‰; and interval 4 is characterized by its higher δ^（15）N values, between ＋6.7‰ and ＋7.8‰（the second peak）. The values of enrichment factor of Mo decrease from 56.8 to 2.6 with the ascending stratigraphic trend. It indicated that immediately after the Sturtian glaciations, the marine seawater above the transitional zone between the shelf to slope of the southern margin of the Yangtze Platform was stratified, with shallow seawater being oxic but deep water being sulfidic. Subsequently, high denitrification rates prevailed in expanded suboxic areas in spite of a short emergence of an oxic condition in the surface seawater, and the deep seawaters were still anoxic or even euxinic.展开更多
Analyses of the correlation between hyperspectral reflectance and pigment content including chlorophyll a, chlorophyll b and carotenoid of leaves in different sites of rice were reported in this paper. The hyperspe...Analyses of the correlation between hyperspectral reflectance and pigment content including chlorophyll a, chlorophyll b and carotenoid of leaves in different sites of rice were reported in this paper. The hyperspectral reflectance of late rice during the whole growing season was measured using a Spectroradiometer with spectral range of 350-1050 nm and resolution of 3 nm. The chlorophyll a, chlorophyll b and carotenoid contents in rice leaves in rice fields to which different levels of nitrogen were applied were measured. The chlorophyll a content of upper leaves was well correlated with the spectral variables. However, the correlation between both chlorophyll b and caroteniod and the spectral variables was far from that of chlorophyll a. The potential of hyperspectral reflectance measurement for estimating chlorophyll a of upper leaves was evaluated using univariate correlation and multivariate regression analysis methods with different types of predictors. This study showed that the most suitable estimated model of chlorophyll a of upper leaves was obtained by using some hyperspectral variables such as SD r, SD b and their integration.展开更多
Leaf chlorophyll content(LCC)is an important physiological indicator of the actual health status of individual plants.An accurate estimation of LCC can therefore provide valuable information for precision field manage...Leaf chlorophyll content(LCC)is an important physiological indicator of the actual health status of individual plants.An accurate estimation of LCC can therefore provide valuable information for precision field management.Red-edge information from hyperspectral data has been widely used to estimate crop LCC.However,after the advent of red-edge bands in satellite imagery,no systematic evaluation of the performance of satellite data has been conducted.Toward this end,we analyze herein the performance of winter wheat LCC retrieval of currant and forthcoming satellites(RapidEye,Sentinel-2 and EnMAP)and their new red-edge bands by using partial least squares regression(PLSR)and a vegetation-indexbased approach.These satellite spectral data were obtained by resampling ground-measured hyperspectral data under various field conditions and according to specific spectral response functions and spectral resolution.The results showed:1)This study confirmed that RapidEye,Sentinel-2 and EnMAP data are suitable for winter wheat LCC retrieval.For the PLSR approach,Sentinel-2 data provided more accurate estimates of LCC(R2=0.755,0.844,0.805 for 2002,2010,and 2002+2010)than do RapidEye data(R2=0.689,0.710,0.707 for 2002,2010,and 2002+2010)and EnMAP data(R2=0.735,0.867,0.771 for 2002,2010,and 2002+2010).For index-based approaches,the MERIS terrestrial chlorophyll index,which is a vegetation index with two red-edge bands,was the most sensitive and robust index for LCC for both the Sentinel-2 and EnMAP data(R2≥0.628),and the indices(NDRE1,SRRE1 and CIRE1)with a single red-edge band were the most sensitive and robust indices for the RapidEye data(R2≥0.420);2)According to the analysis of the effect of the wavelength and number of used red-edge spectral bands on LCC retrieval,the short-wavelength red-edge bands(from 699 to 734 nm)provided more accurate predictions when using the PLSR approach,whereas the long-wavelength red-edge bands(740 to 783 nm)gave more accurate predictions when using the vegetation indice(VI)approach.In addition,the prediction accuracy of RapidEye,Sentinel-2 and EnMAP data was improved gradually because of more number of red-edge bands and higher spectral resolution;VI regression models that contain a single or multiple red-edge bands provided more accurate predictions of LCC than those without red-edge bands,but for normalized difference vegetation index(NDVI)-,simple ratio(SR)-and chlorophyll index(CI)-like index,two red-edge bands index didn’t significantly improve the predictive accuracy of LCC than those indices with a single red-edge band.Although satellite data with higher spectral resolution and a greater number of red-edge bands marginally improve the accuracy of estimates of crop LCC,the level of this improvement remains insufficient because of higher spectral resolution,which results in a worse signal-to-noise ratio.The results of this study are helpful to accurately monitor LCC of winter wheat in large-area and provide some valuable advice for design of red-edge spectral bands of satellite sensor in future.展开更多
In this study, the upper ocean heat content （OHC） variations in the South China Sea （SCS） during 1993- 2006 were investigated by examining ocean temperatures in seven datasets, including World Ocean Atlas 2009 （W...In this study, the upper ocean heat content （OHC） variations in the South China Sea （SCS） during 1993- 2006 were investigated by examining ocean temperatures in seven datasets, including World Ocean Atlas 2009 （WOA09） （climatology）, Ishii datasets, Ocean General Circulation ModeI for the Earth Simulator （OFES）, Simple Ocean Data Assimilation system （SODA）, Global Ocean Data Assimilation System （GODAS）, China Oceanic ReAnalysis system （CORA） , and an ocean reanalysis dataset for the joining area of Asia and Indian-Pacific Ocean （AIPO1.0）. Among these datasets, two were independent of any numerical model, four relied on data assimilation, and one was generated without any data assimilation. The annual cycles revealed by the seven datasets were similar, but the interannual variations were different. Vertical structures of temperatures along the 18~N, 12.75~N, and 120~E sections were compared with data collected during open cruises in 1998 and 2005-08. The results indicated that Ishii, OFES, CORA, and AIPO1.0 were more consistent with the observations. Through systematic shortcomings and advantages in presenting the upper comparisons, we found that each dataset had its own OHC in the SCS.展开更多
Interest in the Moon started to increase at the beginning of the 21st century, and henceforth, more and more attention has been paid to the content and distribution of water ice in the lunar polar regions. The existen...Interest in the Moon started to increase at the beginning of the 21st century, and henceforth, more and more attention has been paid to the content and distribution of water ice in the lunar polar regions. The existence of water or ice in the regolith can apparently change its dielectric features. Therefore, in this article, the Dobson model is adopted and improved according to the Moon＇s environmental features, to construct the relationship between the volumetric water ice content and the di- electric constant. Thereafter, a lunar regolith dielectric distribution map is generated based on the improved Dobson model and the Clementine UVVIS data. The map indicates that the imaginary part of the dielectric constants in the lunar mare is much higher than that in the highlands. However, the maximum dielectric constants occur at the north- and south-pole regions, whose values are apparently bigger than those in the middle and low latitudes. Then, an abnormal map of the dielectric constant is gained if the threshold is put as 0.053 7, which is the highest value in the middle and low latitudes. The statistical results indicate that the number of abnormal pixels is 110 596, and the average is about 0.057 9. Assuming that the mean dielectric constant in the lunar mare is the normal dielectric constant at the south and north poles and ε1=11.58＋i0.057 9 is the abnormal one, the volumetric water ice content can be evaluated using the advanced Dobson model. The results show that the average volumetric water ice content is about 1.64%, and the total area is about 25 294 km^2, where 10 956 km2 belongs to the north pole and the rest is in the south pole.展开更多
The growing collection of scientific data in various web repositories is referred to as Scientific Big Data,as it fulfills the four“V’s”of Big Data—volume,variety,velocity,and veracity.This phenomenon has created ...The growing collection of scientific data in various web repositories is referred to as Scientific Big Data,as it fulfills the four“V’s”of Big Data—volume,variety,velocity,and veracity.This phenomenon has created new opportunities for startups;for instance,the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs.Traditionally,the content of the papers are compared to list the relevant papers from a repository.The conventional method results in a long list of papers that is often impossible to interpret productively.Therefore,the need for a novel approach that intelligently utilizes the available data is imminent.Moreover,the primary element of the scientific knowledge base is a research article,which consists of various logical sections such as the Abstract,Introduction,Related Work,Methodology,Results,and Conclusion.Thus,this study utilizes these logical sections of research articles,because they hold significant potential in finding relevant papers.In this study,comprehensive experiments were performed to determine the role of the logical sections-based terms indexing method in improving the quality of results(i.e.,retrieving relevant papers).Therefore,we proposed,implemented,and evaluated the logical sections-based content comparisons method to address the research objective with a standard method of indexing terms.The section-based approach outperformed the standard content-based approach in identifying relevant documents from all classified topics of computer science.Overall,the proposed approach extracted 14%more relevant results from the entire dataset.As the experimental results suggested that employing a finer content similarity technique improved the quality of results,the proposed approach has led the foundation of knowledge-based startups.展开更多
Objective:This study aims to provide the material basis for the molecular mechanism of Yuxingcao(Houttuynia cordata Thunb,HCT)through the method of evidence-based study to summarize the natural constituents isolated f...Objective:This study aims to provide the material basis for the molecular mechanism of Yuxingcao(Houttuynia cordata Thunb,HCT)through the method of evidence-based study to summarize the natural constituents isolated from HCT.Methods:We searched CNKI,Wanfang,VIP,Pubmed and relevant conference compilations.The keywords were'Yuxingcao or Houttuynia cordata Thunb'and'components'or'ingredients'or'constituent'or'volatile oil'or'flavonoids'or'terpene'or'content',both in Chinese and English.According to the inclusion and exclusion criteria,the reported compositions and contents have been summarized,and SPSS software was used to draw the boxplot of contents.Results:A total of 603 natural compounds in 11 categories were obtained from pooled articles.In the diverse components,the number of aliphatic compounds(n=259)and terpenoids(n=158)are more than those of flavonoids(n=26),alkaloids(n=42)and aromatics(n=42).While,in the part of volatile oils of HCT,the largest components are aliphatic compounds(mainly distributed on the ground)and terpenoids(mainly distributed in the underground).Although,methyl n-nonylketone is distributed in the whole herb plant,a large proportion is present in the underground parts.As for non-volatiles,the flavonoid content(mainly distributed on the ground)was the highest,among which quercetin and its glycosyl derivatives were the prominent.Conclusion:The results of this study provide a more comprehensive material basis for the further study of HCT.It is also helpful to explain the mechanisms of anti-oxidant,anti-inflammatory,anti-bacterial,anti-viral and anti-cancer effects from the molecular target and molecular network levels.展开更多
Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun ...Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun coal mine, located in the Mentougou district of Beijing, was chosen as a case study. The ecological damage was analyzed by 3S technology, field investigation and from chemical data. The derivative spectra of the diagnostic absorption bands are derived from the spectra measured in the field and used as characteristic spectral variables. A correlation analysis was conducted for the nitrogen content of the vegetation samples and the fast derivative spectrum and the estimation model of nitrogen content established by a multiple stepwise linear regression method. The spatial distribution of nitrogen content was extracted by a parameter mapping method from the Hyperion data which revealed the distribution of the nitrogen content. In addition, the estimation model was evaluated for two evaluation indicators which are important for the precision of the model. Experimental results indicate that by linear regression and parameter mapping, the estimation model precision was Very high. The coefficient of determination, R2, was 0.795 and the standard deviation of residual （SDR） 0.19. The nitrogen content of most samples was about 1.03% and the nitrogen content in the study site seems inversely proportional to the distance from the piles of coal waste. Therefore, we can conclude that inversely modeling nitrogen content by hyper-spectral remote sensing in exhausted coal mining sites is feasible and our study can be taken as reference in species selection and in subseauent management and maintenance in ecological restoration.展开更多
Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of m...Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.展开更多
The International GNSS Service(IGS) has been providing reliable Global Ionospheric Maps(GIMs) since 1998. The Ionosphere Associate Analysis Centers(IAACs) model the global ionospheric Total Electron Content(TEC) and g...The International GNSS Service(IGS) has been providing reliable Global Ionospheric Maps(GIMs) since 1998. The Ionosphere Associate Analysis Centers(IAACs) model the global ionospheric Total Electron Content(TEC) and generate the daily GIM products within the context of the IGS. However, the rapid and final daily GIM products have a latency of at least one day and one week or so, respectively. This limits the value of GIM products in real-time GNSS applications.We propose and develop an approach for near real-time modeling of global ionospheric TEC by using the hourly IGS data. We perform an experiment in a real operating environment to generate near real-time GIM(named BUHG) products for more than two years. Final daily GIM products,Precise Point Positioning(PPP) based VTEC resources, and JASON-3 Vertical TEC(VTEC) measurements are collected for testing the performance of BUHG. The results show that the performance of BUHG is very close to that of the daily GIM products. Also, there is good agreement between BUHG and PPP-derived VTEC as well as with JASON-3 VTEC. It is possible that BUHG would be further improved with an increase in available hourly GNSS data.展开更多
Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this...Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this study probes the spatio-temporal variations of global water vapor content in the past decade. It is found that overall the global water vapor content declined from 2003 to 2012(slope b = –0.0149, R = 0.893, P = 0.0005). The decreasing trend over the ocean surface(b = –0.0170, R = 0.908, P = 0.0003) is more explicit than that over terrestrial surface(b = –0.0100, R = 0.782, P = 0.0070), more significant over the Northern Hemisphere(b = –0.0175, R = 0.923, P = 0.0001) than that over the Southern Hemisphere(b = –0.0123, R = 0.826, P = 0.0030). In addition, the analytical results indicate that water vapor content are decreasing obviously between latitude of 36°N and 36°S(b = 0.0224, R = 0.892, P = 0.0005), especially between latitude of 0°N and 36°N(b = 0.0263, R = 0.931, P = 0.0001), while the water vapor concentrations are increasing slightly in the Arctic regions(b = 0.0028, R = 0.612, P = 0.0590). The decreasing and spatial variation of water vapor content regulates the effects of carbon dioxide which is the main reason of the trend in global surface temperatures becoming nearly flat since the late 1990 s. The spatio-temporal variations of water vapor content also affect the growth and spatial distribution of global vegetation which also regulates the global surface temperature change, and the climate change is mainly caused by the earth's orbit position in the solar and galaxy system. A big data model based on gravitational-magmatic change with the solar or the galactic system is proposed to be built for analyzing how the earth's orbit position in the solar and galaxy system affects spatio-temporal variations of global water vapor content, vegetation and temperature at large spatio-temporal scale. This comprehensive examination of water vapor changes promises a holistic understanding of the global climate change and potential underlying mechanisms.展开更多
A database stores data in order to provide the user with information. However, how a database may achieve this is not always clear. The main reason for this seems that we, who are in the database community, have not f...A database stores data in order to provide the user with information. However, how a database may achieve this is not always clear. The main reason for this seems that we, who are in the database community, have not fully understood and therefore clearly defined the notion of “the information that data in a database carry”, in other words, “the information content of data”. As a result, databases’ capability is limited in terms of answering queries, especially, when users explore information beyond the scope of data stored in a database, the database normally cannot provide it. The underlying reason of the problem is that queries are answered based on a direct match between a query and data (up to aggregations of the data). We observe that this is because the information that data carry is seen as exactly the data per se. To tackle this problem, we propose the notion of information content inclusion relation, and show that it formulates the intuitive notion of the “information content of data” and then show how this notion may be used for the derivation of information from data in a database.展开更多
On the basis of the relationship between the carbonate content and the stratal velocity and density, an exercise has been attempted using an artificial neural network on high-resolution seismic data for inversion of c...On the basis of the relationship between the carbonate content and the stratal velocity and density, an exercise has been attempted using an artificial neural network on high-resolution seismic data for inversion of carbonate content with limited well measarements as a control. The method was applied to the slope area of the northern South China Sea near ODP Sites 1146 and 1148, and the results are satisfaetory. Before inversion calculation, a stepwise regression method was applied to obtain six properties related most closely to the carbonate content variations among the various properties on the seismic profiles across or near the wells. These include the average frequency, the integrated absolute amplitude, the dominant frequency, the reflection time, the derivative instantaneous amplitude, and the instantaneous frequency. The results, with carbonate content errors of mostly ±5 % relative to those measured from sediment samples, show a relatively accurate picture of carbonate distribution along the slope profile. This method pioneers a new quantitative model to acquire carbonate content variations directly from high-resolution seismic data. It will provide a new approach toward obtaining substitutive high-resolution sediment data for earth system studies related to basin evolution, especially in discussing the coupling between regional sedimentation and climate change.展开更多
文摘The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.
文摘High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).
基金Supported by Xuhui District Health Commission,No.SHXH202214.
文摘Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.
基金supported by the International Platform for Dryland Research and Education, Tottori University and the National Key R&D Program of China (2016YFC0500909)
文摘Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.
基金financially supported by Shenzhen Key Fundamental Research Projects(Grant No.:JCYJ20170306091556329).
文摘Named Data Networking(NDN)improves the data delivery efficiency by caching contents in routers. To prevent corrupted and faked contents be spread in the network,NDN routers should verify the digital signature of each published content. Since the verification scheme in NDN applies the asymmetric encryption algorithm to sign contents,the content verification overhead is too high to satisfy wire-speed packet forwarding. In this paper, we propose two schemes to improve the verification performance of NDN routers to prevent content poisoning. The first content verification scheme, called "user-assisted",leads to the best performance, but can be bypassed if the clients and the content producer collude. A second scheme, named ``RouterCooperation ‘', prevents the aforementioned collusion attack by making edge routers verify the contents independently without the assistance of users and the core routers no longer verify the contents. The Router-Cooperation verification scheme reduces the computing complexity of cryptographic operation by replacing the asymmetric encryption algorithm with symmetric encryption algorithm.The simulation results demonstrate that this Router-Cooperation scheme can speed up18.85 times of the original content verification scheme with merely extra 80 Bytes transmission overhead.
基金the National Natural Science Foundation of China (41171281, 40701120)the Beijing Nova Program, China (2008B33)
文摘Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperature, and precipitation will affect grain protein contents and these factors usually cannot be monitored accurately by remote sensing data from single image. In this research, the relationships between wheat protein content at maturity and wheat agronomic parameters at different growing stages were analyzed and multi-temporal images of Landsat TM were used to estimate grain protein content by partial least squares regression. Experiment data were acquired in the suburb of Beijing during a 2-yr experiment in the period from 2003 to 2004. Determination coefficient, average deviation of self-modeling, and deviation of cross- validation were employed to assess the estimation accuracy of wheat grain protein content. Their values were 0.88, 1.30%, 3.81% and 0.72, 5.22%, 12.36% for 2003 and 2004, respectively. The research laid an agronomic foundation for GPC （grain protein content） estimation by multi-temporal remote sensing. The results showed that it is feasible to estimate GPC of wheat from multi-temporal remote sensing data in large area.
文摘Spatial and temporal resolution of water vapor content is useful in improving the accuracy of short_term weather prediction.Dense and continuously tracking regional GPS arrays will play an important role in remote sensing atmospheric water vapor content.In this study,a piecewise linear solution method was proposed to estimate the precipitable water vapor (PWV) content from ground_based GPS observations in Hong Kong.To evaluate the solution accuracy of the water vapor content sensed by GPS,the upper air sounding data (radiosonde) that are collected locally was used to calculate the precipitable water vapor during the same period.One_month results of PWV from both ground_based GPS sensing technique and radiosonde method are in agreement within 1～2 mm.This encouraging result will motivate the GPS meteorology application based on the establishment of a dense GPS array in Hong Kong.
基金supported by the National Basic Research Program of China (No. 2013CB835004)NSFC programs (Nos. 41102018, 41230102)
文摘Cryogenian Datangpo Formation was deposited during the interglacial time between the Sturtian and Marinoan ice ages. We studied nitrogen isotope compositions and contents of Mo of the black shales from the basal Datangpo Formation in northeastern Guizhou, South China, for an attempt to reconstruct the marine redox change and nitrogen cycle during the interglacial time. Based on lithostratigraphy as well as geochemical profiles, the basal black shales can be divided into four intervals： Interval 1 has the lowest δ^（15）N value（＋5.0‰）; in interval 2, δ^（15）N values vary between ＋6.4‰ and ＋7.4‰（the first peak）; interval 3 records stable values of δ^（15）N around ＋6‰; and interval 4 is characterized by its higher δ^（15）N values, between ＋6.7‰ and ＋7.8‰（the second peak）. The values of enrichment factor of Mo decrease from 56.8 to 2.6 with the ascending stratigraphic trend. It indicated that immediately after the Sturtian glaciations, the marine seawater above the transitional zone between the shelf to slope of the southern margin of the Yangtze Platform was stratified, with shallow seawater being oxic but deep water being sulfidic. Subsequently, high denitrification rates prevailed in expanded suboxic areas in spite of a short emergence of an oxic condition in the surface seawater, and the deep seawaters were still anoxic or even euxinic.
文摘Analyses of the correlation between hyperspectral reflectance and pigment content including chlorophyll a, chlorophyll b and carotenoid of leaves in different sites of rice were reported in this paper. The hyperspectral reflectance of late rice during the whole growing season was measured using a Spectroradiometer with spectral range of 350-1050 nm and resolution of 3 nm. The chlorophyll a, chlorophyll b and carotenoid contents in rice leaves in rice fields to which different levels of nitrogen were applied were measured. The chlorophyll a content of upper leaves was well correlated with the spectral variables. However, the correlation between both chlorophyll b and caroteniod and the spectral variables was far from that of chlorophyll a. The potential of hyperspectral reflectance measurement for estimating chlorophyll a of upper leaves was evaluated using univariate correlation and multivariate regression analysis methods with different types of predictors. This study showed that the most suitable estimated model of chlorophyll a of upper leaves was obtained by using some hyperspectral variables such as SD r, SD b and their integration.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19080304)the Agricultural Science and Technology Innovation of Sanya, China (2015KJ04)+4 种基金the Natural Science Foundation of Hainan Province, China (20164179, 2016CXTD015)the Technology Research, Development and Promotion Program of Hainan Province, China (ZDXM2015102)the Hainan Provincial Department of Science and Technology, China (ZDKJ2016021)the National Natural Science Foundation of China (41601466)the Youth Innovation Promotion Association of Chinese Academy of Sciences (CAS) (2017085)
文摘Leaf chlorophyll content(LCC)is an important physiological indicator of the actual health status of individual plants.An accurate estimation of LCC can therefore provide valuable information for precision field management.Red-edge information from hyperspectral data has been widely used to estimate crop LCC.However,after the advent of red-edge bands in satellite imagery,no systematic evaluation of the performance of satellite data has been conducted.Toward this end,we analyze herein the performance of winter wheat LCC retrieval of currant and forthcoming satellites(RapidEye,Sentinel-2 and EnMAP)and their new red-edge bands by using partial least squares regression(PLSR)and a vegetation-indexbased approach.These satellite spectral data were obtained by resampling ground-measured hyperspectral data under various field conditions and according to specific spectral response functions and spectral resolution.The results showed:1)This study confirmed that RapidEye,Sentinel-2 and EnMAP data are suitable for winter wheat LCC retrieval.For the PLSR approach,Sentinel-2 data provided more accurate estimates of LCC(R2=0.755,0.844,0.805 for 2002,2010,and 2002+2010)than do RapidEye data(R2=0.689,0.710,0.707 for 2002,2010,and 2002+2010)and EnMAP data(R2=0.735,0.867,0.771 for 2002,2010,and 2002+2010).For index-based approaches,the MERIS terrestrial chlorophyll index,which is a vegetation index with two red-edge bands,was the most sensitive and robust index for LCC for both the Sentinel-2 and EnMAP data(R2≥0.628),and the indices(NDRE1,SRRE1 and CIRE1)with a single red-edge band were the most sensitive and robust indices for the RapidEye data(R2≥0.420);2)According to the analysis of the effect of the wavelength and number of used red-edge spectral bands on LCC retrieval,the short-wavelength red-edge bands(from 699 to 734 nm)provided more accurate predictions when using the PLSR approach,whereas the long-wavelength red-edge bands(740 to 783 nm)gave more accurate predictions when using the vegetation indice(VI)approach.In addition,the prediction accuracy of RapidEye,Sentinel-2 and EnMAP data was improved gradually because of more number of red-edge bands and higher spectral resolution;VI regression models that contain a single or multiple red-edge bands provided more accurate predictions of LCC than those without red-edge bands,but for normalized difference vegetation index(NDVI)-,simple ratio(SR)-and chlorophyll index(CI)-like index,two red-edge bands index didn’t significantly improve the predictive accuracy of LCC than those indices with a single red-edge band.Although satellite data with higher spectral resolution and a greater number of red-edge bands marginally improve the accuracy of estimates of crop LCC,the level of this improvement remains insufficient because of higher spectral resolution,which results in a worse signal-to-noise ratio.The results of this study are helpful to accurately monitor LCC of winter wheat in large-area and provide some valuable advice for design of red-edge spectral bands of satellite sensor in future.
基金supported by the National Basic Research Program of China (Grant Nos. 2010CB950400 and 2013CB430301)the National Natural Science Foundation of China (Grant Nos. 41276025 and 41176023)+2 种基金the R&D Special Fund for Public Welfare Industry (Meteorology) (Grant No. GYHY201106036)The OFES simulation was conducted on the Earth Simulator under the support of JAMSTECsupported by the Data Sharing Infrastructure of Earth System Science-Data Sharing Service Center of the South China Sea and adjacent regions
文摘In this study, the upper ocean heat content （OHC） variations in the South China Sea （SCS） during 1993- 2006 were investigated by examining ocean temperatures in seven datasets, including World Ocean Atlas 2009 （WOA09） （climatology）, Ishii datasets, Ocean General Circulation ModeI for the Earth Simulator （OFES）, Simple Ocean Data Assimilation system （SODA）, Global Ocean Data Assimilation System （GODAS）, China Oceanic ReAnalysis system （CORA） , and an ocean reanalysis dataset for the joining area of Asia and Indian-Pacific Ocean （AIPO1.0）. Among these datasets, two were independent of any numerical model, four relied on data assimilation, and one was generated without any data assimilation. The annual cycles revealed by the seven datasets were similar, but the interannual variations were different. Vertical structures of temperatures along the 18~N, 12.75~N, and 120~E sections were compared with data collected during open cruises in 1998 and 2005-08. The results indicated that Ishii, OFES, CORA, and AIPO1.0 were more consistent with the observations. Through systematic shortcomings and advantages in presenting the upper comparisons, we found that each dataset had its own OHC in the SCS.
基金supported by the National Natural Science Foundation of China (Nos. 40901159, 40901187)the Doctoral Fund of Ministry of Education of China (No. 20090061120055)+1 种基金the Fundamental Research Funds for the Central Universities (No. 200903047)the National High Technology Research and Development Program of China (No. 2010AA122203)
文摘Interest in the Moon started to increase at the beginning of the 21st century, and henceforth, more and more attention has been paid to the content and distribution of water ice in the lunar polar regions. The existence of water or ice in the regolith can apparently change its dielectric features. Therefore, in this article, the Dobson model is adopted and improved according to the Moon＇s environmental features, to construct the relationship between the volumetric water ice content and the di- electric constant. Thereafter, a lunar regolith dielectric distribution map is generated based on the improved Dobson model and the Clementine UVVIS data. The map indicates that the imaginary part of the dielectric constants in the lunar mare is much higher than that in the highlands. However, the maximum dielectric constants occur at the north- and south-pole regions, whose values are apparently bigger than those in the middle and low latitudes. Then, an abnormal map of the dielectric constant is gained if the threshold is put as 0.053 7, which is the highest value in the middle and low latitudes. The statistical results indicate that the number of abnormal pixels is 110 596, and the average is about 0.057 9. Assuming that the mean dielectric constant in the lunar mare is the normal dielectric constant at the south and north poles and ε1=11.58＋i0.057 9 is the abnormal one, the volumetric water ice content can be evaluated using the advanced Dobson model. The results show that the average volumetric water ice content is about 1.64%, and the total area is about 25 294 km^2, where 10 956 km2 belongs to the north pole and the rest is in the south pole.
基金supported by Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(2020-0-01592)Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2019R1F1A1058548).
文摘The growing collection of scientific data in various web repositories is referred to as Scientific Big Data,as it fulfills the four“V’s”of Big Data—volume,variety,velocity,and veracity.This phenomenon has created new opportunities for startups;for instance,the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs.Traditionally,the content of the papers are compared to list the relevant papers from a repository.The conventional method results in a long list of papers that is often impossible to interpret productively.Therefore,the need for a novel approach that intelligently utilizes the available data is imminent.Moreover,the primary element of the scientific knowledge base is a research article,which consists of various logical sections such as the Abstract,Introduction,Related Work,Methodology,Results,and Conclusion.Thus,this study utilizes these logical sections of research articles,because they hold significant potential in finding relevant papers.In this study,comprehensive experiments were performed to determine the role of the logical sections-based terms indexing method in improving the quality of results(i.e.,retrieving relevant papers).Therefore,we proposed,implemented,and evaluated the logical sections-based content comparisons method to address the research objective with a standard method of indexing terms.The section-based approach outperformed the standard content-based approach in identifying relevant documents from all classified topics of computer science.Overall,the proposed approach extracted 14%more relevant results from the entire dataset.As the experimental results suggested that employing a finer content similarity technique improved the quality of results,the proposed approach has led the foundation of knowledge-based startups.
文摘Objective:This study aims to provide the material basis for the molecular mechanism of Yuxingcao(Houttuynia cordata Thunb,HCT)through the method of evidence-based study to summarize the natural constituents isolated from HCT.Methods:We searched CNKI,Wanfang,VIP,Pubmed and relevant conference compilations.The keywords were'Yuxingcao or Houttuynia cordata Thunb'and'components'or'ingredients'or'constituent'or'volatile oil'or'flavonoids'or'terpene'or'content',both in Chinese and English.According to the inclusion and exclusion criteria,the reported compositions and contents have been summarized,and SPSS software was used to draw the boxplot of contents.Results:A total of 603 natural compounds in 11 categories were obtained from pooled articles.In the diverse components,the number of aliphatic compounds(n=259)and terpenoids(n=158)are more than those of flavonoids(n=26),alkaloids(n=42)and aromatics(n=42).While,in the part of volatile oils of HCT,the largest components are aliphatic compounds(mainly distributed on the ground)and terpenoids(mainly distributed in the underground).Although,methyl n-nonylketone is distributed in the whole herb plant,a large proportion is present in the underground parts.As for non-volatiles,the flavonoid content(mainly distributed on the ground)was the highest,among which quercetin and its glycosyl derivatives were the prominent.Conclusion:The results of this study provide a more comprehensive material basis for the further study of HCT.It is also helpful to explain the mechanisms of anti-oxidant,anti-inflammatory,anti-bacterial,anti-viral and anti-cancer effects from the molecular target and molecular network levels.
文摘Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun coal mine, located in the Mentougou district of Beijing, was chosen as a case study. The ecological damage was analyzed by 3S technology, field investigation and from chemical data. The derivative spectra of the diagnostic absorption bands are derived from the spectra measured in the field and used as characteristic spectral variables. A correlation analysis was conducted for the nitrogen content of the vegetation samples and the fast derivative spectrum and the estimation model of nitrogen content established by a multiple stepwise linear regression method. The spatial distribution of nitrogen content was extracted by a parameter mapping method from the Hyperion data which revealed the distribution of the nitrogen content. In addition, the estimation model was evaluated for two evaluation indicators which are important for the precision of the model. Experimental results indicate that by linear regression and parameter mapping, the estimation model precision was Very high. The coefficient of determination, R2, was 0.795 and the standard deviation of residual （SDR） 0.19. The nitrogen content of most samples was about 1.03% and the nitrogen content in the study site seems inversely proportional to the distance from the piles of coal waste. Therefore, we can conclude that inversely modeling nitrogen content by hyper-spectral remote sensing in exhausted coal mining sites is feasible and our study can be taken as reference in species selection and in subseauent management and maintenance in ecological restoration.
基金Under the auspices of National Natural Science Foundation of China(No.41230751,41101547)Scientific Research Foundation of Graduate School of Nanjing University(No.2012CL14)
文摘Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.
基金funded by the National Natural Science Foundation of China (Nos. 41804026, 41804024 and 41931075)。
文摘The International GNSS Service(IGS) has been providing reliable Global Ionospheric Maps(GIMs) since 1998. The Ionosphere Associate Analysis Centers(IAACs) model the global ionospheric Total Electron Content(TEC) and generate the daily GIM products within the context of the IGS. However, the rapid and final daily GIM products have a latency of at least one day and one week or so, respectively. This limits the value of GIM products in real-time GNSS applications.We propose and develop an approach for near real-time modeling of global ionospheric TEC by using the hourly IGS data. We perform an experiment in a real operating environment to generate near real-time GIM(named BUHG) products for more than two years. Final daily GIM products,Precise Point Positioning(PPP) based VTEC resources, and JASON-3 Vertical TEC(VTEC) measurements are collected for testing the performance of BUHG. The results show that the performance of BUHG is very close to that of the daily GIM products. Also, there is good agreement between BUHG and PPP-derived VTEC as well as with JASON-3 VTEC. It is possible that BUHG would be further improved with an increase in available hourly GNSS data.
基金Under the auspices of National Key Research and Development Program(No.2016YFC0500203)National Natural Science Foundation of China(No.41571427)
文摘Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this study probes the spatio-temporal variations of global water vapor content in the past decade. It is found that overall the global water vapor content declined from 2003 to 2012(slope b = –0.0149, R = 0.893, P = 0.0005). The decreasing trend over the ocean surface(b = –0.0170, R = 0.908, P = 0.0003) is more explicit than that over terrestrial surface(b = –0.0100, R = 0.782, P = 0.0070), more significant over the Northern Hemisphere(b = –0.0175, R = 0.923, P = 0.0001) than that over the Southern Hemisphere(b = –0.0123, R = 0.826, P = 0.0030). In addition, the analytical results indicate that water vapor content are decreasing obviously between latitude of 36°N and 36°S(b = 0.0224, R = 0.892, P = 0.0005), especially between latitude of 0°N and 36°N(b = 0.0263, R = 0.931, P = 0.0001), while the water vapor concentrations are increasing slightly in the Arctic regions(b = 0.0028, R = 0.612, P = 0.0590). The decreasing and spatial variation of water vapor content regulates the effects of carbon dioxide which is the main reason of the trend in global surface temperatures becoming nearly flat since the late 1990 s. The spatio-temporal variations of water vapor content also affect the growth and spatial distribution of global vegetation which also regulates the global surface temperature change, and the climate change is mainly caused by the earth's orbit position in the solar and galaxy system. A big data model based on gravitational-magmatic change with the solar or the galactic system is proposed to be built for analyzing how the earth's orbit position in the solar and galaxy system affects spatio-temporal variations of global water vapor content, vegetation and temperature at large spatio-temporal scale. This comprehensive examination of water vapor changes promises a holistic understanding of the global climate change and potential underlying mechanisms.
文摘A database stores data in order to provide the user with information. However, how a database may achieve this is not always clear. The main reason for this seems that we, who are in the database community, have not fully understood and therefore clearly defined the notion of “the information that data in a database carry”, in other words, “the information content of data”. As a result, databases’ capability is limited in terms of answering queries, especially, when users explore information beyond the scope of data stored in a database, the database normally cannot provide it. The underlying reason of the problem is that queries are answered based on a direct match between a query and data (up to aggregations of the data). We observe that this is because the information that data carry is seen as exactly the data per se. To tackle this problem, we propose the notion of information content inclusion relation, and show that it formulates the intuitive notion of the “information content of data” and then show how this notion may be used for the derivation of information from data in a database.
基金This paper is supported by the National Natural Science Foundation ofChina(Nos.40476030,40576031)andthe National Key Basic ResearchSpecial Foundation Project of China(No.G2000078501).
文摘On the basis of the relationship between the carbonate content and the stratal velocity and density, an exercise has been attempted using an artificial neural network on high-resolution seismic data for inversion of carbonate content with limited well measarements as a control. The method was applied to the slope area of the northern South China Sea near ODP Sites 1146 and 1148, and the results are satisfaetory. Before inversion calculation, a stepwise regression method was applied to obtain six properties related most closely to the carbonate content variations among the various properties on the seismic profiles across or near the wells. These include the average frequency, the integrated absolute amplitude, the dominant frequency, the reflection time, the derivative instantaneous amplitude, and the instantaneous frequency. The results, with carbonate content errors of mostly ±5 % relative to those measured from sediment samples, show a relatively accurate picture of carbonate distribution along the slope profile. This method pioneers a new quantitative model to acquire carbonate content variations directly from high-resolution seismic data. It will provide a new approach toward obtaining substitutive high-resolution sediment data for earth system studies related to basin evolution, especially in discussing the coupling between regional sedimentation and climate change.
