Censors for Boolean Description Logic

Protecting different kinds of information has become an important area of research. One aspect is to provide effective means to avoid that secrets can be deduced from the answers of legitimate queries. In the context of atomic propositional databases several methods have been developed to achieve this goal. However, in those databases it is not possible to formalize structural information. Also they are quite restrictive with respect to the specification of secrets. In this paper we extend those methods to match the much greater expressive power of Boolean description logics. In addition to the formal framework, we provide a discussion of various kinds of censors and establish different levels of security they can provide.

Prognostic and diagnostic value of EEG signal coupling measures in coma.

OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

The Complexity of Non-Iterated Probabilistic Justification Logic

The logic PJ is a probabilistic logic defined by adding (noniterated) probability operators to the basic justification logic J. In this paper we establish upper and lower bounds for the complexity of the derivability problem in the logic PJ. The main result of the paper is that the complexity of the derivability problem in PJ remains the same as the complexity of the derivability problem in the underlying logic J, which is π[p/2] -complete. This implies that the probability operators do not increase the complexity of the logic, although they arguably enrich the expressiveness of the language.

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

A relationship between aerosol transport and compound-specific d13C land plant biomarker and pollen records

We examined near-surface, late Holocene deep-sea sediments at nine sites on a north-south transect from the Congo Fan (4°S) to the Cape Basin (30°S) along the Southwest African continental margin. Contents, distribution patterns and molecular stable carbon isotope signatures of long-chain n-alkanes (C27-C33) and n-alkanols (C22-C32) are indicators of land plant vegetation of different biosynthetic types, which can be correlated with concentrations and distributions of pollen taxa in the same sediments. Calculated clusters of wind trajectories and satellite Aerosol Index imagery afford information on the source areas for the lipids and pollen on land and their transport pathways to the ocean sites. This multidisciplinary approach on an almost continental scale provides clear evidence of latitudinal differences in lipid and pollen composition paralleling the major phytogeographic zonations on the adjacent continent. Dust and smoke aerosols are mainly derived from the western and central South African hinterland dominated by deserts, semi-deserts and savannah regions rich in C4 and CAM plants. The northern sites (Congo Fan area and northern Angola Basin), which get most of their terrestrial material from the Congo Basin and the Angolan highlands, may also receive some material from the Chad region. Very little aerosol from the African continent is transported to the most southerly sites in the Cape Basin. As can be expected from the present position of the phytogeographic zones, the carbon isotopic signatures of the n-alkanes and n-alkanols both become isotopically more enriched in 13C from north to south. The results of the study suggest that this combination of pollen data and compound-specific isotope geochemical proxies can be effectively applied in the reconstruction of past continental phytogeographic developments.

Grain entrainment and transport rates of magnetic minerals of coastal sediment samples from the Bay of Plenty, New Zealand

Heavy (magnetic & non-magnetic) minerals are found concentrated by natural processes in many fluvial, estuarine, coastal and shelf environments with a potential to form economic placer deposits. Understanding the processes of heavy mineral transport and enrichment is prerequisite to interpret sediment magnetic properties in terms of hydro- and sediment dynamics. In this study, we combine rock magnetic and sedimentological laboratory measurements with numerical 3D discrete element models to investigate differential grain entrainment and transport rates of magnetic minerals in a range of coastal environments (riverbed, mouth, estuary, beach and near-shore). We analyzed grain-size distributions of representative bulk samples and their magnetic mineral fractions to relate grain-size modes to respective transport modes (traction, saltation, suspension). Rock magnetic measurements showed that distribution shapes, population sizes and grain-size offsets of bulk and magnetic mineral fractions hold information on the transport conditions and enrichment process in each depositional environment. A downstream decrease in magnetite grain size and an increase in magnetite concentration was observed from riverine source to marine sink environments. Lower flow velocities permit differential settling of light and heavy mineral grains creating heavy mineral enriched zones in estuary settings, while lighter minerals are washed out further into the sea. Numerical model results showed that higher heavy mineral concentrations in the bed increased the erosion rate and enhancing heavy mineral enrichment. In beach environments where sediments contained light and heavy mineral grains of equivalent grain sizes, the bed was found to be more stable with negligible amount of erosion compared to other bed compositions. Heavy mineral transport rates calculated for four different bed compositions showed that increasing heavy mineral content in the bed decreased the transport rate. There is always a lag in transport between light and heavy minerals which increases with higher heavy mineral concentration in all tested bed compositions. The results of laboratory experiments were validated by numerical models and showed good agreement. We demonstrate that the presented approach bears the potential to investigate heavy mineral enrichment processes in a wide range of sedimentary settings.