海南岛土壤质量的指标与量化表达研究

在海南岛SOTER数据库基础上,结合联合国有关原则与规定,选择表征土壤质量的若干指标项目组成体系,在GIS环境中对图斑的土壤质量进行评价,并将评价等级指数与空间数据库相连,根据用户需求将土壤质量的评价结构输出,结果得到当地有关专家的认可,建议通过当地实践结果,对模型进行了必要的修订（适当修改评价指标及量化标准）,使之更趋完善。     

Structural Patterns under X-Rays: Is SNOMED CT Growing Straight?

Unprincipled modeling decisions in large-domain ontologies, such as SNOMED CT, are problematic and might act as a barrier for their quality assurance and successful use in electronic health records. Most previous work has focused on clustering problematic concepts, which is helpful for quality control but faces difficulties in pinpointing the origin of those modeling problems. In this study, we examined the underlying structural patterns in SNOMED CT’s data model as such patterns directly reflect the modeling strategies of editors. Our results showed that 92% of all structural patterns found accumulated in the Procedure and Clinical finding sub-hierarchies, and pattern reuse was low; over 30% of patterns were only used once. A qualitative analysis of a sample of 50 such singleton patterns revealed modeling problems, including redundancy, omission, and inconsistency. The problems detected in the sample suggest that the analysis of structural patterns is a valuable technique for revealing problematic areas of SNOMED CT and modeling the styles of terminology editors. Furthermore, the patterns that describe the modeling of a large number of concepts could provide insights for template creation and refinement in SNOMED CT.     

基于地面调查的植被生态质量综合评估指标体系构建

植被是陆地生态系统的主体,是保障生态质量的基础,也是基于自然的生态系统增汇、实现“碳中和”的重要利器。植被是生态质量评价的核心要素,但目前的生态质量评价研究中所用到的植被指标多是通过遥感反演或者气象指数模型计算得到的,而基于典型生态系统尺度地面调查的植被观测数据更直接、更准确,数据也很丰富,却很少用于生态质量评价,也缺乏系统的评价指标体系。通过文献研究、专家研讨和问卷调查,并借鉴群落退化演替和生态系统长期监测研究的理论基础,构建基于地面调查的植被生态质量综合评估指标体系。该指标体系整体分为三级,一级综合指数由群落结构指数、物质生产指数、生物多样性指数、群落发展或者演替趋势4个二级分项指标构成,二级分项指标由12—14个三级指标组成,不同植被类型各有其特征指标。该体系将完善我国多尺度陆地生态系统的生态质量评价指标体系,为新时期国家生态质量评价提供科学建议,为我国生态文明建设提供技术支撑。     

Automatic registration of microarray images. II. Hexagonal grid

MOTIVATION: In the first part of this paper the author presented an efficient, robust and completely automated algorithm for spot and block indexing in microarray images with rectangular grids. Although the rectangular grid is currently the most common type of grouping the probes on microarray slides, there is another microarray technology based on bundles of optical fibers where the probes are packed in hexagonal grids. The hexagonal grid provides both advantages and drawbacks over the standard rectangular packing and of course requires adaptation and/or modification of the algorithm of spot indexing presented in the first part of the paper. RESULTS: In the second part of the paper the author presents a version of the spot indexing algorithm adapted for microarray images with spots packed in hexagonal structures. The algorithm is completely automated, works with hexagonal grids of different types and with different parameters of grid spacing and rotation as well as spot sizes. It can successfully trace the local and global distortions of the grid, including non-orthogonal transformations. Similar to the algorithm from part I, it scales linearly with the grid size, the time complexity is O(M), where M is total number of grid points in hexagonal grid. The algorithm has been tested both on CCD and scanned images with spot expression rates as low as 2%. The processing time of an image with about 50 000 hex grid points was less than a second. For images with high expression rates ( approximately 90%) the registration time is even smaller, around a quarter of a second. Supplementary information: http://fleece.ucsd.edu/~vit/Registration_Supplement.pdf     

An Automated System for Skeletal Maturity Assessment by Extreme Learning Machines

Assessing skeletal age is a subjective and tedious examination process. Hence, automated assessment methods have been developed to replace manual evaluation in medical applications. In this study, a new fully automated method based on content-based image retrieval and using extreme learning machines (ELM) is designed and adapted to assess skeletal maturity. The main novelty of this approach is it overcomes the segmentation problem as suffered by existing systems. The estimation results of ELM models are compared with those of genetic programming (GP) and artificial neural networks (ANNs) models. The experimental results signify improvement in assessment accuracy over GP and ANN, while generalization capability is possible with the ELM approach. Moreover, the results are indicated that the ELM model developed can be used confidently in further work on formulating novel models of skeletal age assessment strategies. According to the experimental results, the new presented method has the capacity to learn many hundreds of times faster than traditional learning methods and it has sufficient overall performance in many aspects. It has conclusively been found that applying ELM is particularly promising as an alternative method for evaluating skeletal age.     

Lack of CD117 and rare bcl-2 expression in stomach cancer by immunohistochemistry. An immunohistochemical study with review of the literature

Aims

To develop and implement an automated virtual slide screening system that distinguishes normal histological findings and several tissue – based crude (texture – based) diagnoses.

Theoretical considerations

Virtual slide technology has to handle and transfer images of GB Bytes in size. The performance of tissue based diagnosis can be separated into a) a sampling procedure to allocate the slide area containing the most significant diagnostic information, and b) the evaluation of the diagnosis obtained from the information present in the selected area. Nyquist's theorem that is broadly applied in acoustics, can also serve for quality assurance in image information analysis, especially to preset the accuracy of sampling. Texture – based diagnosis can be performed with recursive formulas that do not require a detailed segmentation procedure. The obtained results will then be transferred into a "self-learning" discrimination system that adjusts itself to changes of image parameters such as brightness, shading, or contrast.

Methods

Non-overlapping compartments of the original virtual slide (image) will be chosen at random and according to Nyquist's theorem (predefined error-rate). The compartments will be standardized by local filter operations, and are subject for texture analysis. The texture analysis is performed on the basis of a recursive formula that computes the median gray value and the local noise distribution. The computations will be performed at different magnifications that are adjusted to the most frequently used objectives (*2, *4.5, *10, *20, *40). The obtained data are statistically analyzed in a hierarchical sequence, and in relation to the clinical significance of the diagnosis.

Results

The system has been tested with a total of 896 lung cancer cases that include the diagnoses groups: cohort (1) normal lung – cancer; cancer subdivided: cohort (2) small cell lung cancer – non small cell lung cancer; non small cell lung cancer subdivided: cohort (3) squamous cell carcinoma – adenocarcinoma – large cell carcinoma. The system can classify all diagnoses of the cohorts (1) and (2) correctly in 100%, those of cohort (3) in more than 95%. The percentage of the selected area can be limited to only 10% of the original image without any increased error rate.

Conclusion

The developed system is a fast and reliable procedure to fulfill all requirements for an automated "pre-screening" of virtual slides in lung pathology.     

PROuST: a comparison method of three-dimensional structures of proteins using indexing techniques.

We present a new method for protein structure comparison that combines indexing and dynamic programming (DP). The method is based on simple geometric features of triplets of secondary structures of proteins. These features provide indexes to a hash table that allows fast retrieval of similarity information for a query protein. After the query protein is matched with all proteins in the hash table producing a list of putative similarities, the dynamic programming algorithm is used to align the query protein with each protein of this list. Since the pairwise comparison with DP is applied only to a small subset of proteins and, furthermore, DP re-uses information that is already computed and stored in the hash table, the approach is very fast even when searching the entire PDB. We have done extensive experimentation showing that our approach achieves results of quality comparable to that of other existing approaches but is generally faster.     

Metric-space indexes as a basis for scalable biological databases

Biochemical databases will be best served by the development of new specialized database management systems whose storage managers are based on metric-space indexing techniques and the development a database query languages that embody semantics derived from biochemical models of similarity and evolution. Important biochemical data types cannot be effectively mapped to low dimensional coordinate systems on which O(log n) indexing methods rely. It is clear from an abundance of bioinformatic discoveries that biochemical data is not random and exhibits interesting structure with respect to clustering. Metric-space indexing exploits a data set's intrinsic clustering to speed the execution of similarity queries, even when the data cannot be mapped to a coordinate system. Database management systems that seamlessly integrate semantically rich query languages with a metric-storage and retrieval mechanism will allow biologists to simply and concisely develop informatic studies that have traditionally been large and labor intensive.     

Evaluation of contextual analysis for computer classification of cervical smears

A procedure for automated analysis of cervical smears has been implemented in an image cytometry system. Smears are described exclusively in terms of global and contextual information extracted by pattern-recognition algorithms and represented by a vector of proportions of cellular object types. Linear discriminant functions, based on a Fisher criterion, are derived to classify smears with a cross-section of diagnoses into two broad categories, normal and abnormal. Results obtained from 83 smears indicate 78% correct classification. In contrast to most automated systems, good classification results were obtained in normal smears with benign changes caused by inflammation and with postmenopausal atrophia and in abnormals with mild dysplasia. These findings suggest that contextual analysis may be sensitive to subtle changes in cellular morphology and to progressive patterns of dysplasia. When used with standard isolated cell analysis, contextual analysis may provide additional complementary information for automated cervical prescreening.     

Automatic assignment of biomedical categories: toward a generic approach

MOTIVATION: We report on the development of a generic text categorization system designed to automatically assign biomedical categories to any input text. Unlike usual automatic text categorization systems, which rely on data-intensive models extracted from large sets of training data, our categorizer is largely data-independent. METHODS: In order to evaluate the robustness of our approach we test the system on two different biomedical terminologies: the Medical Subject Headings (MeSH) and the Gene Ontology (GO). Our lightweight categorizer, based on two ranking modules, combines a pattern matcher and a vector space retrieval engine, and uses both stems and linguistically-motivated indexing units. RESULTS AND CONCLUSION: Results show the effectiveness of phrase indexing for both GO and MeSH categorization, but we observe the categorization power of the tool depends on the controlled vocabulary: precision at high ranks ranges from above 90% for MeSH to <20% for GO, establishing a new baseline for categorizers based on retrieval methods.     

False alarms in a slit-scan flow system: causes and occurrence rates. Implications and potential solutions.

A slit-scan technique was developed as a basis for an automated prescreening system for gynecologic cytology. A flow system based on this technique was fabricated and tested and results indicated that false alarms (misclassification of objects or events from normal specimens as abnormal) are the greatest remaining obstacle to development of an automated prescreening instrument. A dual view correlation system was fabricated to provide exact image-contour correlation in flow and permit precise determination of causes and occurrence rates of false alarms. This paper presents data from correlation analyses of 23 normal cytologic specimens. Major causes of false alarms and their implications to automated prescreening are discussed. A technique that would eliminate the majority of false alarms in flow is presented.     

Countercurrent multistage fluidized bed reactor for immobilized biocatalysts: II. Operation of a laboratory-scale reactor

In Part I of this series,(1) we derived a model and made simulations for a multistage fluidized bed reactor (MFBR). It was concluded that the MFBR can be an attractive alternative for a fixed bed reactor when operated with a deactivating biocatalyst. In Part II of this series, the design of a laboratory-scale MFBR and its evaluation to investigate the practical feasibility of this reactor type, will be described. Experiments with a duration as long as 10 days were carried out successfully using immobilized glucose isomerase as a model reaction system. The results predicted by the model are in good agreement with the measured glucose concentration and biocatalyst activity gradients, indicating perfect mixing of the particles in the reactor compartments.The diameters of the biocatalyst particles used in the experiments showed a large spread, with the largest being 1.7 times the smallest. Therefore, an additional check was carried out, to make sure that the particles were not segregating according to size. Particles withdrawn from the reactor compartments were investigated using an image analyzer. Histograms of particle size distribution do not indicate segregation and it is concluded that the particles used have been mixed completely within the compartments. As a result, transport of biocatalyst is nearly plug flow.     

Localization of caveolin 1 in aortic valve endothelial cells using antigen retrieval.

Ultrastructural analysis of aortic valve endothelial cells subjected to growth arrest revealed many vesicles defined as caveolae by the localization of caveolin. Translocation of caveolin after exposure to oxidized LDL suggests that the localization of caveolin may be a valuable tool to study models of early atherogenesis. In this study, several antigen retrieval protocols were tested in osmium-fixed and Spurr-embedded cells to determine the optimal method of antigen retrieval in our model system. SDS produced the most consistent labeling pattern. A quantitative evaluation revealed that SDS significantly increased the labeling density in Spurr-embedded cells. The labeling pattern appeared as clusters of gold particles, 15-40 nm in diameter, that were associated with membranes of a similar size which may represent the neck region of the caveolae.     

3D HUMAN MOTION RETRIEVAL BASED ON HUMAN HIERARCHICAL INDEX STRUCTURE

With the development and wide application of motion capture technology, the captured motion data sets are becoming larger and larger. For this reason, an efficient retrieval method for the motion database is very important. The retrieval method needs an appropriate indexing scheme and an effective similarity measure that can organize the existing motion data well. In this paper, we represent a human motion hierarchical index structure and adopt a nonlinear method to segment motion sequences. Based on this, we extract motion patterns and then we employ a fast similarity measure algorithm for motion pattern similarity computation to efficiently retrieve motion sequences. The experiment results show that the approach proposed in our paper is effective and efficient.     

Diagnosis of benign and malignant cervical specimens by multifiberoptic microspectrophometry and by flow cytometry

Two techniques for the automation of mass screening for cervical cancer were studied. Microspectrophotometry was tried first, using a novel multifiberoptic scanning system that measured the nuclear size and DNA content of cells in routine smears restained by the Feulgen technique. Specimen diagnoses were based on the percentages of cell types present, as determined by thresholds set for the two parameters. While this method gave good results in the automated detection of severe dysplasias and carcinomas, with only 3 of 72 cases misdiagnosed as negative (4.2%), it had a 22.9% false-positive rate (misdiagnosing 24 of 105 "benign" cases) and a 30.3% false-negative rate for adenocarcinomas (10 of 33 cases misclassified). The second approach involved flow cytometric measurements of specimens that were double stained for the assessment of both the DNA and RNA content, with the results analyzed by preset windows in a two-dimensional plane. This technique gave a 6.1% false-negative rate in 49 positive specimens and a 32.3% false-positive rate in 102 benign specimens, with an overall correct classification rate of 76.2%, including adenocarcinomas.     

Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.     

基于MCE的饶河流域国土空间生态质量综合评价及其空间分异

开展国土空间生态调查与评价,摸清区域三类空间生态现状与问题所在,是进行区域国土空间生态修复、空间格局优化等工作的必要前提。基于城镇、农业和生态空间自身的结构、功能和效应,构建国土空间生态质量综合评价体系,以饶河流域所涉县市为研究区域,采用多目标综合评价法开展国土空间生态质量综合评价研究并进行分区,探究结果的空间分异特征。结果表明:(1)研究区国土空间生态质量整体水平良好,中等以上区域占比70.6%。(2)Ⅰ级和Ⅱ级分区主要分布于研究区东北部,该区域的生态环境、生态效益与社会经济呈协同发展态势。(3)研究区国土空间生态质量存在较强的空间相关性和聚集性特征,冷点和热点区域面积基本持平。(4)结合综合评估及障碍度诊断结果,建议依据研究区自然优势,调整社会经济结构,推进工业健康转型,改善城镇空间人居环境,整体提高生态效益水平。研究可为研究区国土空间规划、生态修复、生态-经济-社会可持续发展等提供科学依据和参考价值。     

Structural characterization of Salmonella typhimurium YeaZ, an M22 O-sialoglycoprotein endopeptidase homolog

Protein functional sites are key targets for drug design and protein engineering, but their large-scale experimental characterization remains difficult. The evolutionary trace (ET) is a computational approach to this problem that has been useful in a variety of case studies, but its proteomic scale application is partially hindered because automated retrieval of input sequences from databases often includes some with errors that degrade functional site identification. To recognize and purge these sequences, this study introduces a novel and structure-free measure of ET quality called rank information (RI). It is shown that RI decreases in response to errors in sequences, alignments, or functional classifications. Conversely, an automated procedure to increase RI by selectively removing sequences improves functional site identification so as to nearly match manually curated traces in kinases and in a test set of 79 diverse proteins. Thus we conclude that RI partially reflects the evolutionary consistency of sequence, structure, and function. In practice, as the size of the proteome continues to grow exponentially, it provides a novel and structure-free measure of ET quality that increases its accuracy for large-scale automated annotation of protein functional sites.     

Novel Microarrays for Simultaneous Serodiagnosis of Multiple Antiviral Antibodies

We developed an automated diagnostic system for the detection of virus-specific immunoglobulin Gs (IgGs) that was based on a microarray platform. We compared efficacies of our automated system with conventional enzyme immunoassays (EIAs). Viruses were immobilized to microarrays using a radical cross-linking reaction that was induced by photo-irradiation. A new photoreactive polymer containing perfluorophenyl azide (PFPA) and poly(ethylene glycol) methacrylate was prepared and coated on plates. Inactivated measles, rubella, mumps, Varicella-Zoster and recombinant Epstein-Barr viruse antigen were added to coated plates, and irradiated with ultraviolet light to facilitate immobilization. Virus-specific IgGs in healthy human sera were assayed using these prepared microarrays and the results obtained compared with those from conventional EIAs. We observed high correlation (0.79–0.96) in the results between the automated microarray technique and EIAs. The microarray-based assay was more rapid, involved less reagents and sample, and was easier to conduct compared with conventional EIA techniques. The automated microarray system was further improved by introducing reagent storage reservoirs inside the chamber, thereby conserving the use of expensive reagents and antibodies. We considered the microarray format to be suitable for rapid and multiple serological diagnoses of viral diseases that could be developed further for clinical applications.