On Weakly Singular Versions of Discrete Nonlinear Inequalities and Applications

Some new weakly singular versions of discrete nonlinear inequalities are established, which generalize some existing weakly singular inequalities and can be used in the analysis of nonlinear Volterra type difference equations with weakly singular kernels. A few applications to the upper bound and the uniqueness of solutions of nonlinear difference equations are also involved

An Integrated Land Cover Mapping Method Suitable for Low-Accuracy Areas in Global Land Cover Maps

In land cover mapping, an area with complex topography or heterogeneous land covers is usually poorly classified and therefore defined as a low-accuracy area. The low-accuracy areas are important because they restrict the overall accuracy (OA) of global land cover classification (LCC) data generated. In this paper, low-accuracy areas in China (extracted from the MODIS global LCC maps) were taken as examples, identified as the regions having lower accuracy than the average OA of China. An integrated land cover mapping method targeting low-accuracy regions was developed and tested in eight representative low-accuracy regions of China. The method optimized procedures of image choosing and sample selection based on an existent visually-interpreted regional LCC dataset with high accuracies. Five algorithms and 16 groups of classification features were compared to achieve the highest OA. The support vector machine (SVM) achieved the highest mean OA (81.5%) when only spectral bands were classified. Aspect tended to attenuate OA as a classification feature. The optimal classification features for different regions largely depends on the topographic feature of vegetation. The mean OA for eight low-accuracy regions was 84.4% by the proposed method in this study, which exceeded the mean OA of most precedent global land cover datasets. The new method can be applied worldwide to improve land cover mapping of low-accuracy areas in global land cover maps

Enriching the international clinical nomenclature with Chinese daily used synonyms and concept recognition in physician notes

Abstract Background It has been shown that the entities in everyday clinical text are often expressed in a way that varies from how they are expressed in the nomenclature. Owing to lots of synonyms, abbreviations, medical jargons or even misspellings in the daily used physician notes in clinical information system (CIS), the terminology without enough synonyms may not be adequately suitable for the task of Chinese clinical term recognition. Methods This paper demonstrates a validated system to retrieve the Chinese term of clinical finding (CTCF) from CIS and map them to the corresponding concepts of international clinical nomenclature, such as SNOMED CT. The system focuses on the SNOMED CT with Chinese synonyms enrichment (SCCSE). The literal similarity and the diagnosis-related similarity metrics were used for concept mapping. Two CTCF recognition methods, the rule- and terminology-based approach (RTBA) and the conditional random field machine learner (CRF), were adopted to identify the concepts in physician notes. The system was validated against the history of present illness annotated by clinical experts. The RTBA and CRF could be combined to predict new CTCFs besides SCCSE persistently. Results Around 59,000 CTCF candidates were accepted as valid and 39,000 of them occurred at least once in the history of present illness. 3,729 of them were accordant with the description in referenced Chinese clinical nomenclature, which could cross map to other international nomenclature such as SNOMED CT. With the hybrid similarity metrics, another 7,454 valid CTCFs (synonyms) were succeeded in concept mapping. For CTCF recognition in physician notes, a series of experiments were performed to find out the best CRF feature set, which gained an F-score of 0.887. The RTBA achieved a better F-score of 0.919 by the CTCF dictionary created in this research. Conclusions This research demonstrated that it is feasible to help the SNOMED CT with Chinese synonyms enrichment based on physician notes in CIS. With continuous maintenance of SCCSE, the CTCFs could be precisely retrieved from free text, and the CTCFs arranged in semantic hierarchy of SNOMED CT could greatly improve the meaningful use of electronic health record in China. The methodology is also useful for clinical synonyms enrichment in other languages

Selective and Cleavable Extraction of Sialo-glycoproteins by Disulfide-Linked Amino-oxy-Functionalized Fe₃O₄ Magnetic Nanoparticles

The low abundance of sialo-glycoprotein hampered the separation, enrichment, and analysis of sialo-glycoproteins, which are critical for studying their functions. Here, we designed cleavable amino-oxy functionalized magnetic materials and employed to fast and selective isolate sialo-glycoproteins. This includes the ligation of disulfide-linked amino-oxy-functionalized magnetic nanoparticles with periodate-treated glycoproteins or cells, followed by magnetic separation. A reductive reagent could release the sialo-glycoproteins with small molecular fragments on the terminal of glycan chains, and the sialo-glycoproteins were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis. On-bead digestion of the peptides were analyzed by tandem mass spectrometry. The results indicated that this method could selectively separate the majority of cell-surface sialo-glycoproteins

Selective and Cleavable Extraction of Sialo-glycoproteins by Disulfide-Linked Amino-oxy-Functionalized Fe₃O₄ Magnetic Nanoparticles

The low abundance of sialo-glycoprotein hampered the separation, enrichment, and analysis of sialo-glycoproteins, which are critical for studying their functions. Here, we designed cleavable amino-oxy functionalized magnetic materials and employed to fast and selective isolate sialo-glycoproteins. This includes the ligation of disulfide-linked amino-oxy-functionalized magnetic nanoparticles with periodate-treated glycoproteins or cells, followed by magnetic separation. A reductive reagent could release the sialo-glycoproteins with small molecular fragments on the terminal of glycan chains, and the sialo-glycoproteins were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis. On-bead digestion of the peptides were analyzed by tandem mass spectrometry. The results indicated that this method could selectively separate the majority of cell-surface sialo-glycoproteins