Is there a difference between narrowing of the spinal canal and neurological deficits comparing Denis and Magerl classifications?

We have read with great interest the retrospective study by Caffaro and Avanzi1 evaluating the relation between narrowing of the spinal canal and neurological deficits in patients with burst-type fractures of the spine. The authors are to be commended for obtaining detailed neurological and radiological data in a large cohort of 227 patients. The authors conclude: “The percentage of narrowing of the spinal canal proved to be a pre-disposing factor for the severity of the neurological status in thoracolumbar and lumbar burst-type fractures according to the classifications of Denis and Magerl.” Although this conclusion is mainly in accordance with previous findings, we would like to comment on the methodological approach applied in the current study.

Conceptualising business models : definitions, frameworks and classifications

The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in terms of how it creates and captures customer value. This abstract and generic definition is made more specific and operational by the compositional elements that need to address the customer, value proposition, organizational architecture (firm and network level) and economics dimensions. Business model archetypes complement the definition and elements by providing a more concrete and empirical understanding of the business model concept. The main contributions of this paper are (1) explicitly including the customer value concept in the business model definition and focussing on value creation, (2) presenting four core dimensions that business model elements need to cover, (3) arguing for flexibility by adapting and extending business model elements to cater for different purposes and contexts (e.g. technology, innovation, strategy),(4) stressing a more systematic approach to business model archetypes by using business model elements for their description, and (5) suggesting to use business model archetype research for the empirical exploration and testing of business model elements and their relationships.

A two-stage SVM method to predict membrane protein types by incorporating amino acid classifications and physicochemical properties into a general form of Chou's PseAAC

Membrane proteins play important roles in many biochemical processes and are also attractive targets of drug discovery for various diseases. The elucidation of membrane protein types provides clues for understanding the structure and function of proteins. Recently we developed a novel system for predicting protein subnuclear localizations. In this paper, we propose a simplified version of our system for predicting membrane protein types directly from primary protein structures, which incorporates amino acid classifications and physicochemical properties into a general form of pseudo-amino acid composition. In this simplified system, we will design a two-stage multi-class support vector machine combined with a two-step optimal feature selection process, which proves very effective in our experiments. The performance of the present method is evaluated on two benchmark datasets consisting of five types of membrane proteins. The overall accuracies of prediction for five types are 93.25% and 96.61% via the jackknife test and independent dataset test, respectively. These results indicate that our method is effective and valuable for predicting membrane protein types. A web server for the proposed method is available at http://www.juemengt.com/jcc/memty_page.php

Assessing police classifications of sexual assault reports: A meta-analysis of false reporting rates

The objective of the study was to determine, through meta-analysis, the rate of confirmed false reports of sexual assault to police. The meta-analysis initially involved a search for relevant articles. The search revealed seven studies where researchers or their trained helpers evaluated reported sexual assault cases to determine the rate of confirmed false reports. The meta-analysis calculated an overall rate and tested for possible moderators of effect size. The meta-analytic rate of false reports of sexual assault was .052 (95% CIs .030, .089). The rates for the individual studies were heterogeneous, suggesting the possibility of moderators of rate. However, the four possible moderators examined, year of publication, whether the data set used had information in addition to police reports, whether the study was completed in the U.S. or elsewhere, and whether inter-rater reliabilities were reported, were all not significant. The meta-analysis of seven relevant studies shows that confirmed false allegations of sexual assault made to police occur at a significant rate. The total false reporting rate, including both confirmed and equivocal cases, would be greater than the 5 percent rate found here.

Cost733cat: a database of weather and circulation type classifications

A new database of weather and circulation type catalogs is presented comprising 17 automated classification methods and five subjective classifications. It was compiled within COST Action 733 "Harmonisation and Applications of Weather Type Classifications for European regions" in order to evaluate different methods for weather and circulation type classification. This paper gives a technical description of the included methods using a new conceptual categorization for classification methods reflecting the strategy for the definition of types. Methods using predefined types include manual and threshold based classifications while methods producing types derived from the input data include those based on eigenvector techniques, leader algorithms and optimization algorithms. In order to allow direct comparisons between the methods, the circulation input data and the methods' configuration were harmonized for producing a subset of standard catalogs of the automated methods. The harmonization includes the data source, the climatic parameters used, the classification period as well as the spatial domain and the number of types. Frequency based characteristics of the resulting catalogs are presented, including variation of class sizes, persistence, seasonal and inter-annual variability as well as trends of the annual frequency time series. The methodological concept of the classifications is partly reflected by these properties of the resulting catalogs. It is shown that the types of subjective classifications compared to automated methods show higher persistence, inter-annual variation and long-term trends. Among the automated classifications optimization methods show a tendency for longer persistence and higher seasonal variation. However, it is also concluded that the distance metric used and the data preprocessing play at least an equally important role for the properties of the resulting classification compared to the algorithm used for type definition and assignment.

Discordance of international adiposity classifications in Australian boys and girls - The LOOK study

Background: Various charts based on body mass index (BMI) and per cent body fat (%BF) are used to classify childhood body composition but outcomes may vary.

Aim: The study investigated variation in incidences of childhood obesity as depicted by four classification charts.

Subjects and methods: BMI and DXA-derived %BF were assessed in 741 children. Incidences of overweight and obesity were compared between two BMI charts and two bioelectrical impedance (BIA)-based %BF charts.

Results: The International Obesity Task Force (IOTF)-adopted BMI chart designated 21%, 6% (boys), and 26%, 9% (girls) as overweight and obese, respectively. Corresponding figures using the USA CDC BMI chart were 27%, 11% (boys) and 27%, 12% (girls). Using a USA-derived %BF chart incidences were 17%, 2% (boys) and 21%, 8% (girls) and using a UK-derived %BF chart 51%, 24% (boys) and 53%, 36% (girls). Sensitivity of BMI varied according to the %BF reference chart.

Conclusions: In contrast to the BMI-based charts, there were considerable variations in depicted incidences of obesity between the %BF-based charts. These discordances were considered to result from previously reported variation within and between BIA and DXA %BF assessments underlying the charts. The present study highlights the need for valid, reliable, unchanging BIA and DXA procedures.

Improving classifications for cardiac autonomic neuropathy using multi-level ensemble classifiers and feature selection based on random forest

This paper is devoted to empirical investigation of novel multi-level ensemble meta classifiers for the detection and monitoring of progression of cardiac autonomic neuropathy, CAN, in diabetes patients. Our experiments relied on an extensive database and concentrated on ensembles of ensembles, or multi-level meta classifiers, for the classification of cardiac autonomic neuropathy progression. First, we carried out a thorough investigation comparing the performance of various base classifiers for several known sets of the most essential features in this database and determined that Random Forest significantly and consistently outperforms all other base classifiers in this new application. Second, we used feature selection and ranking implemented in Random Forest. It was able to identify a new set of features, which has turned out better than all other sets considered for this large and well-known database previously. Random Forest remained the very best classier for the new set of features too. Third, we investigated meta classifiers and new multi-level meta classifiers based on Random Forest, which have improved its performance. The results obtained show that novel multi-level meta classifiers achieved further improvement and obtained new outcomes that are significantly better compared with the outcomes published in the literature previously for cardiac autonomic neuropathy.

A comparison of different study load classifications and their association to student performance: an exploratory study

Purpose – The purpose of this paper is to investigate the alternative study load measures (dichotomous full-time/part-time classification and the number of units enrolled) and their association to student performance by using student data from a final year accounting unit in a large Australian university.

Design/methodology/approach – Using regression analysis, the authors compare the two measures to ascertain the explanatory power of the two approaches in explaining student performance.

Findings – A positive association is found between study loads and student performance when using the “number of units enrolled” measure. This relationship was not found when the dichotomous measure (full-time vs part-time) was used. The results suggest that a scaled measure of study loads is a better measure compared to a binary (dichotomous) measure.

Research limitations/implications – The study will assist future researchers to better control for study loads, and also to gain a better understanding of the association between study loads and student performance. This may possibly assist educational institutions and academics to use a more appropriate pedagogical design in the structure of courses when determining study load allocations across the different cohorts.

Practical implications – This study will help in methodology of future researchers controlling for study loads and student performance.
Originality/value – The study adds to existing literature by providing an alternate study load measure in methodology for controlling for student performance.

Findings of the survey on international classifications in Latin America

Spanish document available at the Library