Redundancy, Deduction Schemes, and Minimum-Size Bases for Association Rules

Association rules are among the most widely employed data analysis methods in the field of Data Mining. An association rule is a form of partial implication between two sets of binary variables. In the most common approach, association rules are parameterized by a lower bound on their confidence, which is the empirical conditional probability of their consequent given the antecedent, and/or by some other parameter bounds such as "support" or deviation from independence. We study here notions of redundancy among association rules from a fundamental perspective. We see each transaction in a dataset as an interpretation (or model) in the propositional logic sense, and consider existing notions of redundancy, that is, of logical entailment, among association rules, of the form "any dataset in which this first rule holds must obey also that second rule, therefore the second is redundant". We discuss several existing alternative definitions of redundancy between association rules and provide new characterizations and relationships among them. We show that the main alternatives we discuss correspond actually to just two variants, which differ in the treatment of full-confidence implications. For each of these two notions of redundancy, we provide a sound and complete deduction calculus, and we show how to construct complete bases (that is, axiomatizations) of absolutely minimum size in terms of the number of rules. We explore finally an approach to redundancy with respect to several association rules, and fully characterize its simplest case of two partial premises.Comment: LMCS accepted pape

The molybdenum isotopic composition of the modern ocean

Natural variations in the isotopic composition of molybdenum (Mo) are showing increasing potential as a tool in geochemistry. Although the ocean is an important reservoir of Mo, data on the isotopic composition of Mo in seawater are scarce. We have recently developed a new method for the precise determination of Mo isotope ratios on the basis of preconcentration using a chelating resin and measurement by multiple-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), which allows us to measure every stable Mo isotope. In this study, 172 seawater samples obtained from 9 stations in the Pacific, Atlantic, and Southern Oceans were analyzed, giving global coverage and the first full depth-profiles. The average isotope composition in δA/95Mo (relative to a Johnson Matthey Mo standard solution) was as follows: δ92/95Mo = –2.54 ± 0.16‰ (2SD), δ94/95Mo = –0.73 ± 0.19‰, δ96/95Mo = 0.85 ± 0.07‰, δ97/95Mo = 1.68 ± 0.08‰, δ98/95Mo = 2.48 ± 0.10‰, and δ100/95Mo = 4.07 ± 0.18‰. The δ values showed an excellent linear correlation with atomic mass of AMo (R2 = 0.999). Three-isotope plots for the Mo isotopes were fitted with straight lines whose slopes agreed with theoretical values for mass-dependent isotope fractionation. These results demonstrate that Mo isotopes are both uniformly distributed and follow a mass-dependent fractionation law in the modern oxic ocean. A common Mo standard is urgently required for the precise comparison of Mo isotopic compositions measured in different laboratories. On the other hand, our results strongly support the possibility of seawater as an international reference material for Mo isotopic composition

TLR7-mediated skin inflammation remotely triggers chemokine expression and leukocyte accumulation in the brain

Background: The relationship between the brain and the immune system has become increasingly topical as, although it is immune-specialised, the CNS is not free from the influences of the immune system. Recent data indicate that peripheral immune stimulation can significantly affect the CNS. But the mechanisms underpinning this relationship remain unclear. The standard approach to understanding this relationship has relied on systemic immune activation using bacterial components, finding that immune mediators, such as cytokines, can have a significant effect on brain function and behaviour. More rarely have studies used disease models that are representative of human disorders. Methods: Here we use a well-characterised animal model of psoriasis-like skin inflammation—imiquimod—to investigate the effects of tissue-specific peripheral inflammation on the brain. We used full genome array, flow cytometry analysis of immune cell infiltration, doublecortin staining for neural precursor cells and a behavioural read-out exploiting natural burrowing behaviour. Results: We found that a number of genes are upregulated in the brain following treatment, amongst which is a subset of inflammatory chemokines (CCL3, CCL5, CCL9, CXCL10, CXCL13, CXCL16 and CCR5). Strikingly, this model induced the infiltration of a number of immune cell subsets into the brain parenchyma, including T cells, NK cells and myeloid cells, along with a reduction in neurogenesis and a suppression of burrowing activity. Conclusions: These findings demonstrate that cutaneous, peripheral immune stimulation is associated with significant leukocyte infiltration into the brain and suggest that chemokines may be amongst the key mediators driving this response

Myocardial perfusion imaging with 99 mTc - tetrofosmin SPECT in breast cancer patients that received postoperative radiotherapy: a case-control study

<p>Abstract</p> <p>Purpose</p> <p>To evaluate the cardiac toxicity of radiotherapy (RT) in breast cancer (BC) patients employing myocardial perfusion imaging (MPI) with Tc-99 m Tetrofosmin - single photon emission computer tomography (T-SPECT).</p> <p>Materials and methods</p> <p>We studied 46 BC female patients (28 patients with left and 18 patients with right BC) treated with postoperative RT compared to a control group of 85 age-matched females. The median time of RT to SPECT was 40 months (6-263).</p> <p>Results</p> <p>Abnormalities in the summed stress score (SSS) were found in 54% of left BC patients, 44.4% of right BC patients, and 32.9% of controls. In left BC patients there were significantly more SSS abnormalities compared to controls (4.0 ± 3.5 vs 2.6 ± 2.0, p = 0.05) and possible trend of increased abnormalities of right BC patients (3.7 ± 3.0 vs 2.6 ± 2.0, p = 0.14). Multiple regression analysis showed more abnormalities in the MPI of left BC patients compared to controls (SSS, p = 0.0001); Marginal toxicity was also noted in right BC patients (SSS, p = 0.045). No additional toxicity was found in patients that received adjuvant cardiotoxic chemotherapy. All T-SPECT abnormalities were clinically silent.</p> <p>Conclusion</p> <p>The study suggests that radiation therapy to BC patients result in MPI abnormalities but without apparent clinical consequences.</p

A collaborative-interactive model for mental health consultation: Teacher inservice education by psychiatric clinicians

Primary prevention of emotional disorders is often cited as a goal in community mental health consultation. The daily contact with children and parents by the classroom teacher can yield effective prevention, if the teacher is appropriately prepared to act as a resource, and by clinicians given an awareness of emotional difficulties in children and their parents. Though consultation is often described as facilitative of change, typically discussions of such programs emphasize technique rather than content. Presented here is a collaborative model based upon a didactic input of humanistic psychology, upon which educator and clinician draw as they become allies in pursuit of answers to questions raised in current examples from the teacher's classroom experience. Excerpts and results of the model's effectiveness are given.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43964/1/10578_2005_Article_BF01433269.pd

Data on diabetes-specific distress are needed to improve the quality of diabetes care [Correspondence]

no abstract availabl

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data

<p>Abstract</p> <p>Background</p> <p>Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline.</p> <p>Results</p> <p>We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data.</p> <p>Conclusions</p> <p>The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from <url>http://code.google.com/p/speaq/</url>.</p

An enterprise engineering approach for the alignment of business and information technology strategy

Information systems and information technology (IS/IT, hereafter just IT) strategies usually depend on a business strategy. The alignment of both strategies improves their strategic plans. From an external perspective, business and IT alignment is the extent to which the IT strategy enables and drives the business strategy. This article reviews strategic alignment between business and IT, and proposes the use of enterprise engineering (EE) to achieve this alignment. The EE approach facilitates the definition of a formal dialog in the alignment design. In relation to this, new building blocks and life-cycle phases have been defined for their use in an enterprise architecture context. This proposal has been adopted in a critical process of a ceramic tile company for the purpose of aligning a strategic business plan and IT strategy, which are essential to support this process. © 2011 Taylor & Francis.Cuenca, L.; Boza, A.; Ortiz, A. (2011). 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