Combination Strategies for Semantic Role Labeling

This paper introduces and analyzes a battery of inference models for the problem of semantic role labeling: one based on constraint satisfaction, and several strategies that model the inference as a meta-learning problem using discriminative classifiers. These classifiers are developed with a rich set of novel features that encode proposition and sentence-level information. To our knowledge, this is the first work that: (a) performs a thorough analysis of learning-based inference models for semantic role labeling, and (b) compares several inference strategies in this context. We evaluate the proposed inference strategies in the framework of the CoNLL-2005 shared task using only automatically-generated syntactic information. The extensive experimental evaluation and analysis indicates that all the proposed inference strategies are successful -they all outperform the current best results reported in the CoNLL-2005 evaluation exercise- but each of the proposed approaches has its advantages and disadvantages. Several important traits of a state-of-the-art SRL combination strategy emerge from this analysis: (i) individual models should be combined at the granularity of candidate arguments rather than at the granularity of complete solutions; (ii) the best combination strategy uses an inference model based in learning; and (iii) the learning-based inference benefits from max-margin classifiers and global feedback

Performance Degradation and Cost Impact Evaluation of Privacy Preserving Mechanisms in Big Data Systems

Big Data is an emerging area and concerns managing datasets whose size is beyond commonly used software tools ability to capture, process, and perform analyses in a timely way. The Big Data software market is growing at 32% compound annual rate, almost four times more than the whole ICT market, and the quantity of data to be analyzed is expected to double every two years. Security and privacy are becoming very urgent Big Data aspects that need to be tackled. Indeed, users share more and more personal data and user-generated content through their mobile devices and computers to social networks and cloud services, losing data and content control with a serious impact on their own privacy. Privacy is one area that had a serious debate recently, and many governments require data providers and companies to protect users’ sensitive data. To mitigate these problems, many solutions have been developed to provide data privacy but, unfortunately, they introduce some computational overhead when data is processed. The goal of this paper is to quantitatively evaluate the performance and cost impact of multiple privacy protection mechanisms. A real industry case study concerning tax fraud detection has been considered. Many experiments have been performed to analyze the performance degradation and additional cost (required to provide a given service level) for running applications in a cloud system

Is late-life dependency increasing or not? A comparison of the Cognitive Function and Ageing Studies (CFAS)

Background: Little is known about how dependency levels have changed between generational cohorts of older people. We estimated years lived in different care states at age 65 in 1991 and 2011 and new projections of future demand for care. Methods: Two population-based studies of older people in defined geographical areas conducted two decades apart (the Cognitive Function and Ageing Studies) provided prevalence estimates of dependency in four states: high (24-hour care); medium (daily care); low (less than daily); independent. Years in each dependency state were calculated by Sullivan’s method. To project future demand, the proportions in each dependency state (by age group and sex) were applied to the 2014 England population projections. Findings: Between 1991 and 2011 there were significant increases in years lived from age 65 with low (men:1·7 years, 95%CI 1·0-2·4; women:2·4 years, 95%CI 1·8-3·1) and high dependency (men:0·9 years, 95%CI 0·2-1·7; women:1·3 years, 95%CI 0·5-2·1). The majority of men’s extra years of life were independent (36%) or with low dependency (36%) whilst for women the majority were spent with low dependency (58%), only 5% being independent. There were substantial reductions in the proportions with medium and high dependency who lived in care homes, although, if these dependency and care home proportions remain constant in the future, further population ageing will require an extra 71,000 care home places by 2025. Interpretation: On average older men now spend 2.4 years and women 3.0 years with substantial care needs (medium or high dependency), and most will live in the community. These findings have considerable implications for older people’s families who provide the majority of unpaid care, but the findings also supply valuable new information for governments and care providers planning the resources and funding required for the care of their future ageing populations

Polar optical phonons in wurtzite spheroidal quantum dots: Theory and application to ZnO and ZnO/MgZnO nanostructures

Polar optical-phonon modes are derived analytically for spheroidal quantum dots with wurtzite crystal structure. The developed theory is applied to a freestanding spheroidal ZnO quantum dot and to a spheroidal ZnO quantum dot embedded into a MgZnO crystal. The wurtzite (anisotropic) quantum dots are shown to have strongly different polar optical-phonon modes in comparison with zincblende (isotropic) quantum dots. The obtained results allow one to explain and accurately predict phonon peaks in the Raman spectra of wurtzite nanocrystals, nanorods (prolate spheroids), and epitaxial quantum dots (oblate spheroids).Comment: 11 page

A structured review of long-term care demand modelling

Long-term care (LTC) represents a significant and substantial proportion of healthcare spends across the globe. Its main aim is to assist individuals suffering with more or more chronic illnesses, disabilities or cognitive impairments, to carry out activities associated with daily living. Shifts in several economic, demographic and social factors have raised concerns surrounding the sustainability of current systems of LTC. Substantial effort has been put into modelling the LTC demand process itself so as to increase understanding of the factors driving demand for LTC and its related services. Furthermore, such modeling efforts have also been used to plan the operation and future composition of the LTC system itself. The main aim of this paper is to provide a structured review of the literature surrounding LTC demand modeling and any such industrial application, whilst highlighting any potential direction for future researchers

Two new rapid SNP-typing methods for classifying Mycobacterium tuberculosis complex into the main phylogenetic lineages

There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the 'Beijing' sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae. Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive

A robust SNP barcode for typing Mycobacterium tuberculosis complex strains

Strain-specific genomic diversity in the Mycobacterium tuberculosis complex (MTBC) is an important factor in pathogenesis that may affect virulence, transmissibility, host response and emergence of drug resistance. Several systems have been proposed to classify MTBC strains into distinct lineages and families. Here, we investigate single-nucleotide polymorphisms (SNPs) as robust (stable) markers of genetic variation for phylogenetic analysis. We identify ~92k SNP across a global collection of 1,601 genomes. The SNP-based phylogeny is consistent with the gold-standard regions of difference (RD) classification system. Of the ~7k strain-specific SNPs identified, 62 markers are proposed to discriminate known circulating strains. This SNP-based barcode is the first to cover all main lineages, and classifies a greater number of sublineages than current alternatives. It may be used to classify clinical isolates to evaluate tools to control the disease, including therapeutics and vaccines whose effectiveness may vary by strain type

High Resolution Discrimination of Clinical Mycobacterium tuberculosis Complex Strains Based on Single Nucleotide Polymorphisms

Recently, the diversity of the Mycobacterium tuberculosis complex (MTBC) population structure has been described in detail. Based on geographical separation and specific host pathogen co-evolution shaping MTBC virulence traits, at least 20 major lineages/genotypes have evolved finally leading to a clear influence of strain genetic background on transmissibility, clinical presentation/outcome, and resistance development. Therefore, high resolution genotyping for characterization of strains in larger studies is mandatory for understanding mechanisms of host-pathogen-interaction and to improve tuberculosis (TB) control. Single nucleotide polymorphisms (SNPs) represent the most reliable markers for lineage classification of clinical isolates due to the low levels of homoplasy, however their use is hampered either by low discriminatory power or by the need to analyze a large number of genes to achieve higher resolution. Therefore, we carried out de novo sequencing of 26 genes (approx. 20000 bp per strain) in a reference collection of MTBC strains including all major genotypes to define a highly discriminatory gene set. Overall, 161 polymorphisms were detected of which 59 are genotype-specific, while 13 define deeper branches such as the Euro-American lineage. Unbiased investigation of the most variable set of 11 genes in a population based strain collection (one year, city of Hamburg, Germany) confirmed the validity of SNP analysis as all strains were classified with high accuracy. Taken together, we defined a diagnostic algorithm which allows the identification of 17 MTBC phylogenetic lineages with high confidence for the first time by sequencing analysis of just five genes. In conclusion, the diagnostic algorithm developed in our study is likely to open the door for a low cost high resolution sequence/SNP based differentiation of the MTBC with a very high specificity. High throughput assays can be established which will be needed for large association studies that are mandatory for detailed investigation of host-pathogen-interaction during TB infection

The frequency of transforming growth factor-TGF-B gene polymorphisms in a normal southern Iranian population

Several single nucleotide polymorphisms (SNPs) of the transforming growth factor-β1 gene (TGFB1) have been reported. Determination of TGFB1 SNPs allele frequencies in different ethnic groups is useful for both population genetic analyses and association studies with immunological diseases. In this study, five SNPs of TGFB1 were determined in 325 individuals from a normal southern Iranian population using polymerase chain reaction-restriction fragment length polymorphism method. This population was in Hardy-Weinberg equilibrium for these SNPs. Of the 12 constructed haplotypes, GTCGC and GCTGC were the most frequent in the normal southern Iranian population. Comparison of genotype and allele frequencies of TGFB SNPs between Iranian and other populations (meta-analysis) showed significant differences, and in this case the southern Iranian population seems genetically similar to Caucasoid populations. However, neighbour-joining tree using Nei's genetic distances based on TGF-β1 allele frequencies showed that southern Iranians are genetically far from people from the USA, Germany, UK, Denmark and the Czech Republic. In conclusion, this is the first report of the distribution of TGFB1 SNPs in an Iranian population and the results of this investigation may provide useful information for both population genetic and disease studies. © 2008 The Authors