A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

Health problems among detainees in Switzerland: a study using the ICPC-2 classification.

BACKGROUND: Little is known about the health status of prisoners in Switzerland. The aim of this study was to provide a detailed description of the health problems presented by detainees in Switzerland's largest remand prison. METHODS: In this retrospective cross-sectional study we reviewed the health records of all detainees leaving Switzerland's largest remand prison in 2007. The health problems were coded using the International Classification for Primary Care (ICPC-2). Analyses were descriptive, stratified by gender. RESULTS: A total of 2195 health records were reviewed. Mean age was 29.5 years (SD 9.5); 95% were male; 87.8% were migrants. Mean length of stay was 80 days (SD 160). Illicit drug use (40.2%) and mental health problems (32.6%) were frequent, but most of these detainees (57.6%) had more generic primary care problems, such as skin (27.0%), infectious diseases (23.5%), musculoskeletal (19.2%), injury related (18.3%), digestive (15.0%) or respiratory problems (14.0%). Furthermore, 7.9% reported exposure to violence during arrest by the police. CONCLUSION: Morbidity is high in this young, predominantly male population of detainees, in particular in relation to substance abuse. Other health problems more commonly seen in general practice are also frequent. These findings support the further development of coordinated primary care and mental health services within detention centers.

Pathophysiology and classification of the vibration white finger.

Skin, arteries and nerves of the upper extremities can be affected by vibration exposure. Recent advances in skin and vascular biology as well as new investigative methods, have shown that neurovascular symptoms may be due to different vascular and neurological disorders which should be differentiated if proper management is to be evaluated. Three types of vascular disorder can be observed in the vibration white finger: digital organic microangiopathy, a digital vasospastic phenomenon and arterial thrombosis in the upper extremities. An imbalance between endothelin-1 and calcitonin-gene-related peptide is probably responsible for the vasospastic phenomenon. Moreover, paresthesiae can be due to either a diffuse vibration neuropathy or a carpal tunnel syndrome. A precise diagnosis is then necessary to adapt the treatment to individual cases. A classification describing the type and severity of the vascular lesions is presented. Asymptomatic lesions are included for adequate epidemiological studies and risk assessment of vibrating tools. Monitoring of vibration exposed workers should include not only a questionnaire about symptoms, but also a clinical evaluation including diagnostic tests for the screening of early asymptomatic neurovascular injuries.

Cluster kernels for semisupervised classification of VHR urban images

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Is the ability of biocontrol fluorescent pseudomonads to produce the antifungal metabolite 2,4-diacetylphloroglucinol really synonymous with higher plant protection?

The antifungal compound 2,4-diacetylphloroglucinol (Phl) contributes to biocontrol in pseudomonads, but whether or not Phl(+) biocontrol pseudomonads display higher plant-protecting activity than Phl(-) biocontrol pseudomonads remains to be demonstrated. This issue was addressed by assessing 230 biocontrol fluorescent pseudomonads selected from a collection of 3132 bacterial isolates obtained from 63 soils worldwide. One-third of the biocontrol pseudomonads were Phl(+) and almost all Phl(+) isolates also produced hydrogen cyanide (HCN). The only Phl(+) HCN(-) strain did harbor hcn genes, but with the deletion of a 134 bp hcnC fragment corresponding to an ADP-binding motif. Statistical analysis of biocontrol isolate distributions indicated that Phl production ability was associated with superior disease suppression activity in the Pythium-cucumber and Fusarium-tomato pathosystems, but this was also the case with HCN production ability. However, HCN significance was not as strong, as indicated both by the comparison of Phl(-) HCN(+) and Phl(-) HCN(-) strains and by correlation analyses. This is the first population-level demonstration of the higher plant-protecting activity of Phl(+) biocontrol pseudomonads in comparison with Phl(-) biocontrol pseudomonads.

Breast cancer prognostic classification in the molecular era: the role of histological grade.

Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers.

The ability of haemolysins expressed by atypical enteropathogenic Escherichia coli to bind to extracellular matrix components

Typical and atypical enteropathogenic Escherichia coli (EPEC) are considered important bacterial causes of diarrhoea. Considering the repertoire of virulence genes, atypical EPEC (aEPEC) is a heterogeneous group, harbouring genes that are found in other diarrheagenic E. coli pathotypes, such as those encoding haemolysins. Haemolysins are cytolytic toxins that lyse host cells disrupting the function of the plasma membrane. In addition, these cytolysins mediate a connection to vascular tissue and/or blood components, such as plasma and cellular fibronectin. Therefore, we investigated the haemolytic activity of 72 aEPEC isolates and determined the correlation of this phenotype with the presence of genes encoding enterohaemolysins (Ehly) and cytolysin A (ClyA). In addition, the correlation between the expression of haemolysins and the ability of these secreted proteins to adhere to extracellular matrix (ECM) components was also assessed in this study. Our findings demonstrate that a subset of aEPEC presents haemolytic activity due to the expression of Ehlys and/or ClyA and that this activity is closely related to the ability of these isolates to bind to ECM components.