Data Independence in the Multi-dimensional Numbered Information Spaces

The concept of data independence designates the techniques that allow data to be changed without affecting the applications that process it. The different structures of the information bases require corresponded tools for supporting data independence. A kind of information bases (the Multi-dimensional Numbered Information Spaces) are pointed in the paper. The data independence in such information bases is discussed.

Improved functional ability and independence in activities of daily living for older adults at high risk of hospital readmission : a randomised controlled trial

Objective: During hospitalisation older people often experience functional decline which impacts on their future independence. The objective of this study was to evaluate a multifaceted transitional care intervention including home-based exercise strategies for at-risk older people on functional status, independence in activities of daily living, and walking ability. Methods: A randomised controlled trial was undertaken in a metropolitan hospital in Australia with 128 patients (64 intervention, 64 control) aged over 65 years with an acute medical admission and at least one risk factor for hospital readmission. The intervention group received an individually tailored program for exercise and follow-up care which was commenced in hospital and included regular visits in hospital by a physiotherapist and a Registered Nurse, a home visit following discharge, and regular telephone follow-up for 24 weeks following discharge. The program was designed to improve health promoting behaviours, strength, stability, endurance and mobility. Data were collected at baseline, then 4, 12 and 24 weeks following discharge using the Index of Activities of Daily Living (ADL), Instrumental Index of Activities of Daily Living (IADL), and the Walking Impairment Questionnaire (Modified). Results: Significant improvements were found in the intervention group in IADL scores (p<.001), ADL scores (p<.001), and WIQ scale scores (p<.001) in comparison to the control group. The greatest improvements were found in the first four weeks following discharge. Conclusions: Early introduction of a transitional model of care incorporating a tailored exercise program and regular telephone follow-up for hospitalised at-risk older adults can improve independence and functional ability.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.

Functional independence following subacute inpatient rehabilitation was not affected by age among older patients recovering from cardiac-related hospital admissions

Introduction Older people recovering from cardiac events requiring an acute hospital admission may experience a decline in physical function limiting their ability to return home to their previous accommodation. Subacute inpatient rehabilitation therapies have potential to assist recovery of physical functioning. However, it is unknown whether age influences the length of stay or physical functioning at discharge from subacute inpatient rehabilitation for this population. Objectives This study examined the outcomes of a cohort of older patients recovering from a cardiac event requiring hospitalisation to investigate the association between age and physical function at discharge, as well as age and length of rehabilitation stay. Methods Participants included 145 consecutive inpatient admissions to a subacute geriatric assessment and rehabilitation unit with a cardiac condition as their primary reason for hospital admission. Participants were required to complete a multi-disciplinary physical functioning assessment within 72 hours of admission to the unit, and again within 72 hours prior to discharge from the unit. The primary outcome measure was the Functional Independence Measure motor score. Demographic and clinical information, including length of stay and discharge destination, were also recorded. Results A total n=126 (87%) participants, with a mean (standard deviation) age of 79 (10) years, had both assessments completed and were included in analyses. Participants who had passed away (n=4, 3%), or did not have both assessments completed per protocol were excluded from analyses. Discharge destinations included home (n=101, 80%), residential aged care (n=17, 13%) and another hospital (n=8, 6%). The (median, interquartile range) Functional Independence Measure motor score was higher at discharge (79, 71 to 84) than admission (61, 48 to 71); z=7.75 p<0.001. Age was not associated with Functional Independence Measure motor score at discharge (t= -0.18, p=0.86), or length of stay in the rehabilitation unit (t= -0.52, 0.60). Conclusion Any perception that age may be associated with longer lengths of stay and reduced physical function outcomes among patients with cardiac conditions admitted for subacute inpatient rehabilitation for older adults is not supported data from this investigation. Older age should not be considered a disincentive when considering the suitability of patients with cardiac diagnoses for this type of inpatient rehabilitation or their potential physical functioning outcome.

Quantile regression for longitudinal data with a working correlation model

This paper proposes a linear quantile regression analysis method for longitudinal data that combines the between- and within-subject estimating functions, which incorporates the correlations between repeated measurements. Therefore, the proposed method results in more efficient parameter estimation relative to the estimating functions based on an independence working model. To reduce computational burdens, the induced smoothing method is introduced to obtain parameter estimates and their variances. Under some regularity conditions, the estimators derived by the induced smoothing method are consistent and have asymptotically normal distributions. A number of simulation studies are carried out to evaluate the performance of the proposed method. The results indicate that the efficiency gain for the proposed method is substantial especially when strong within correlations exist. Finally, a dataset from the audiology growth research is used to illustrate the proposed methodology.

The carbon dioxide hydration activity of the sulfonamide-resistant carbonic anhydrase from the liver of male rat: pH independence of the steady-state kinetics

The steady-state kinetic constants for the catalysis of CO2 hydration by the sulfonamide-resistant and testosterone-induced carbonic anhydrase from the liver of the male rat has been determined by stopped-flow spectrophotometry. The turnover number was 2.6 ± 0.6 × 103 s− at 25 °C, and was invariant with pH ranging from 6.2 to 8.2 within experimental error. The Km at 25 °C was 5 ± 1 mImage , and was also pH independent. These data are in quantitative agreement with earlier findings of pH-independent CO2 hydration activity for the mammalian skeletal muscle carbonic anhydrase isozyme III. The turnover numbers for higher-activity isozymes I and II are strongly pH dependent in this pH range. Thus, the kinetic status of the male rat liver enzyme is that of carbonic anhydrase III. This finding is consistent with preliminary structural and immunologic data from other laboratories.

A modified pseudolikelihood approach for analysis of longitudinal data

We consider the analysis of longitudinal data when the covariance function is modeled by additional parameters to the mean parameters. In general, inconsistent estimators of the covariance (variance/correlation) parameters will be produced when the "working" correlation matrix is misspecified, which may result in great loss of efficiency of the mean parameter estimators (albeit the consistency is preserved). We consider using different "Working" correlation models for the variance and the mean parameters. In particular, we find that an independence working model should be used for estimating the variance parameters to ensure their consistency in case the correlation structure is misspecified. The designated "working" correlation matrices should be used for estimating the mean and the correlation parameters to attain high efficiency for estimating the mean parameters. Simulation studies indicate that the proposed algorithm performs very well. We also applied different estimation procedures to a data set from a clinical trial for illustration.

Learning Bayesian networks from data: An information-theory based approach

This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop efficient algorithms that can effectively learn Bayesian networks, requiring only polynomial numbers of conditional independence (CI) tests in typical cases. We provide precise conditions that specify when these algorithms are guaranteed to be correct as well as empirical evidence (from real world applications and simulation tests) that demonstrates that these systems work efficiently and reliably in practice.

Inference and Declaration of Independence in Task-Parallel Programs

The inherent difficulty of thread-based shared-memory programming has recently motivated research in high-level, task-parallel programming models. Recent advances of Task-Parallel models add implicit synchronization, where the system automatically detects and satisfies data dependencies among spawned tasks. However, dynamic dependence analysis incurs significant runtime overheads, because the runtime must track task resources and use this information to schedule tasks while avoiding conflicts and races.
We present SCOOP, a compiler that effectively integrates static and dynamic analysis in code generation. SCOOP combines context-sensitive points-to, control-flow, escape, and effect analyses to remove redundant dependence checks at runtime. Our static analysis can work in combination with existing dynamic analyses and task-parallel runtimes that use annotations to specify tasks and their memory footprints. We use our static dependence analysis to detect non-conflicting tasks and an existing dynamic analysis to handle the remaining dependencies. We evaluate the resulting hybrid dependence analysis on a set of task-parallel programs.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

DNA mismatch repair and the transition to hormone independence in breast and prostate cancer

The molecular basis for the progression of breast and prostate cancer from hormone dependent to hormone independent disease remains a critical issue in the management of these two cancers. The DNA mismatch repair system is integral to the maintenance of genomic stability and suppression of tumorigenesis. No firm consensus exists regarding the implications of mismatch repair (MMR) deficiencies in the development of breast or prostate cancer. However, recent studies have reported an association between mismatch repair deficiency and loss of specific hormone receptors, inferring a potential role for mismatch repair deficiency in this transition. An updated review of the experimental data supporting or contradicting the involvement of MMR defects in the development and progression of breast and prostate cancer will be provided with particular emphasis on their implications in the transition to hormone independence.

Compositional Data Analysis in Forensic Geoscience

Statistics are regularly used to make some form of comparison between trace evidence or deploy the exclusionary principle (Morgan and Bull, 2007) in forensic investigations. Trace evidence are routinely the results of particle size, chemical or modal analyses and as such constitute compositional data. The issue is that compositional data including percentages, parts per million etc. only carry relative information. This may be problematic where a comparison of percentages and other constraint/closed data is deemed a statistically valid and appropriate way to present trace evidence in a court of law. Notwithstanding an awareness of the existence of the constant sum problem since the seminal works of Pearson (1896) and Chayes (1960) and the introduction of the application of log-ratio techniques (Aitchison, 1986; Pawlowsky-Glahn and Egozcue, 2001; Pawlowsky-Glahn and Buccianti, 2011; Tolosana-Delgado and van den Boogaart, 2013) the problem that a constant sum destroys the potential independence of variances and covariances required for correlation regression analysis and empirical multivariate methods (principal component analysis, cluster analysis, discriminant analysis, canonical correlation) is all too often not acknowledged in the statistical treatment of trace evidence. Yet the need for a robust treatment of forensic trace evidence analyses is obvious. This research examines the issues and potential pitfalls for forensic investigators if the constant sum constraint is ignored in the analysis and presentation of forensic trace evidence. Forensic case studies involving particle size and mineral analyses as trace evidence are used to demonstrate the use of a compositional data approach using a centred log-ratio (clr) transformation and multivariate statistical analyses.

'Anyone But England‘, Glasgow 2014 and the Independence Referendum: Exploring the Role of Narratives in the Sociological Study of Scottish Sport.

Drawing upon the findings of my MSc dissertation and the proposed methodology for my current PhD thesis, this paper will critically reflect upon the potential uses of narrative analysis within the sociological study of sport. The majority of this paper will consider the expression of anti-English sentiment by Scots in relation to both sporting and wider social contexts. Drawing upon the conceptual framework of ‘narrative identity’ proposed by Somers (1994), data was generated through semi-structured interviews focusing upon the ‘ontological’ and ‘public’ narratives of Scottish identity as expressed by Scots living in England. The relationship between Scotland and England is argued to be heavily influenced by the existence of an ‘underdog mentality’ grand ‘public narrative’ for Scots in relation to their English neighbours, based on perceived differences in economic and sporting resources. This ‘underdog mentality’ is argued to act as a legitimating force for the expression of anti-English sentiment within an individual’s ‘ontological narrative’ in both a sporting and wider social context. The paper concludes by reflecting upon the benefits of adopting a narrative analysis approach, and outlining the proposed use of similar methods within my PhD research on the 2014 Glasgow Commonwealth Games and the Scottish independence referendum.

Political Discourse Analysis, Sport and Scottish Independence: Provisional Reflections upon Fairclough and Fairclough's (2012) Analytical Framework.

This paper aims to reflect upon the potential analytical utility of the political discourse analysis framework proposed by Isabela Fairclough and Norman Fairclough (2012). This framework represents the most recent substantive development upon Norman Fairclough's past work situated within the wider school of Critical Discourse Analysis, building upon his influential position this methodological tradition. Central to this development is the additional emphasis placed upon the necessity to conceptualise all political discourse as 'argumentative' in nature, given that political actors are ultimately proposing or refuting particular courses of concrete future action. This paper will therefore apply Fairclough and Fairclough's model to provisional data derived from an ongoing doctoral thesis which considers the nature of political discourse relating to sport, the Glasgow 2014 Commonwealth Games and Scottish independence, with an ultimate aim of critically considering the benefits and limitations of applying this analytical framework as a methodological tool within this ongoing study.

A tale of two logits, compositional data analysis and zero observations

The application of compositional data analysis through log ratio trans- formations corresponds to a multinomial logit model for the shares themselves. This model is characterized by the property of Independence of Irrelevant Alter- natives (IIA). IIA states that the odds ratio in this case the ratio of shares is invariant to the addition or deletion of outcomes to the problem. It is exactly this invariance of the ratio that underlies the commonly used zero replacement procedure in compositional data analysis. In this paper we investigate using the nested logit model that does not embody IIA and an associated zero replacement procedure and compare its performance with that of the more usual approach of using the multinomial logit model. Our comparisons exploit a data set that com- bines voting data by electoral division with corresponding census data for each division for the 2001 Federal election in Australia