Promoter Sequences Prediction Using Relational Association Rule Mining

In this paper we are approaching, from a computational perspective, the problem of promoter sequences prediction, an important problem within the field of bioinformatics. As the conditions for a DNA sequence to function as a promoter are not known, machine learning based classification models are still developed to approach the problem of promoter identification in the DNA. We are proposing a classification model based on relational association rules mining. Relational association rules are a particular type of association rules and describe numerical orderings between attributes that commonly occur over a data set. Our classifier is based on the discovery of relational association rules for predicting if a DNA sequence contains or not a promoter region. An experimental evaluation of the proposed model and comparison with similar existing approaches is provided. The obtained results show that our classifier overperforms the existing techniques for identifying promoter sequences, confirming the potential of our proposal

Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Background: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. Methods: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. Results: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. Conclusions: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy

Plant functional and taxonomic diversity in European grasslands along climatic gradients

Aim: European grassland communities are highly diverse, but patterns and drivers of their continental-scale diversity remain elusive. This study analyses taxonomic and functional richness in European grasslands along continental-scale temperature and precipitation gradients. Location: Europe. Methods: We quantified functional and taxonomic richness of 55,748 vegetation plots. Six plant traits, related to resource acquisition and conservation, were analysed to describe plant community functional composition. Using a null-model approach we derived functional richness effect sizes that indicate higher or lower diversity than expected given the taxonomic richness. We assessed the variation in absolute functional and taxonomic richness and in functional richness effect sizes along gradients of minimum temperature, temperature range, annual precipitation, and precipitation seasonality using a multiple general additive modelling approach. Results: Functional and taxonomic richness was high at intermediate minimum temperatures and wide temperature ranges. Functional and taxonomic richness was low in correspondence with low minimum temperatures or narrow temperature ranges. Functional richness increased and taxonomic richness decreased at higher minimum temperatures and wide annual temperature ranges. Both functional and taxonomic richness decreased with increasing precipitation seasonality and showed a small increase at intermediate annual precipitation. Overall, effect sizes of functional richness were small. However, effect sizes indicated trait divergence at extremely low minimum temperatures and at low annual precipitation with extreme precipitation seasonality. Conclusions: Functional and taxonomic richness of European grassland communities vary considerably over temperature and precipitation gradients. Overall, they follow similar patterns over the climate gradients, except at high minimum temperatures and wide temperature ranges, where functional richness increases and taxonomic richness decreases. This contrasting pattern may trigger new ideas for studies that target specific hypotheses focused on community assembly processes. And though effect sizes were small, they indicate that it may be important to consider climate seasonality in plant diversity studies

Electron energy-loss near-edge shape as a probe to investigate the stabilization of yttria-stabilized zirconia

The electron energy-loss near-edge structure (ELNES) at the O K edge has been studied in yttria-stabilized zirconia (YSZ). The electronic structure of YSZ for compositions between 3 and 15 mol % Y2O3 has been computed using a pseudopotential-based technique to calculate the local relaxations near the O vacancies. The results showed phase transition from the tetragonal to cubic YSZ at 10 mol % of Y2O3, reproducing experimental observations. Using the relaxed defect geometry, calculation of the ELNES was carried out using the full-potential linear muffin-tin orbital method. The results show very good agreement with the experimental O K-edge signal, demonstrating the power of using ELNES to probe the stabilization mechanism in doped metal oxides

Effect of relaxation on the oxygen K-edge electron energy-loss near-edge structure in yttria-stabilized zirconia

The electron energy-loss near-edge structure (ELNES) at the oxygen K-edge has been investigated in a range of yttria-stabilized zirconia (YSZ) materials. The electronic structure of the three polymorphs of pure ZrO/sub 2/ and of the doped YSZ structure close to the 33 mol%Y/sub 2/O/sub 3/ composition have been calculated using a full-potential linear muffin-tin orbital method (NFP-LMTO) as well as a pseudopotential based technique. Calculations of the ELNES dipole transition matrix elements in the framework of the NFP-LMTO scheme and inclusion of core hole screening within Slater's transition state theory enable the ELNES to be computed. Good agreement between the experimental and calculated ELNES is obtained for pure monoclinic ZrO/sub 2/. The agreement is less good with the ideal tetragonal and cubic structures. This is because the inclusion of defects is essential in the calculation of the YSZ ELNES. If the model used contains ordered defects such as vacancies and metal Y planes, agreement between the calculated and experimental O K-edges is significantly improved. The calculations show how the five different O environments of Zr/sub 2/Y/sub 2/O/sub 7/ are connected with the features observed in the experimental spectra and demonstrate clearly the power of using ELNES to probe the stabilization mechanism in doped metal oxides

Functional Data Analysis for Optimizing Strategies of Cash-Flow Management

The cash management deals with problem of automating and managing cash-flow processes. Optimization of the management processes greatly reduces overall cash handling costs. The present analysis is an empirical study of cash flows, from and to bank branches, deriving an underlying theoretical framework, which can in a reasonable way be connected with the optimal strategy. Functional data analysis is considered an appropriate framework to analyze the dynamics of the time series behavior of cash flows: since the observations are not equally spaced in time and their number is different for each series, they are converted into a collection of random curves in a space spanned by finite dimensional functional bases. A central issue in the analysis is describing specific patterns of the curves, taking into account the temporal dependence, and the dependence between curves. The analysis provides a dynamic cash management model that is applied with alternative strategies for programming a cash in transit for the difference between cash inflows and cash outflows in a fixed interval of time. As the strategies are affected by changes in the behavior of the cash flows, the dynamic model outperforms more traditional approaches in identifying the optimal strategy

Neutral Detergent Fibre (NDF) and Non Structural Carbohydrate (NSC) requirements in the nutrition of dairy ewes

<p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">The aim of this review was to contribute to the knowledge of neutral detergent fibre (NDF) and non structural carbo-<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">hydrate (NSC) requirements in the nutrition of dairy ewes. NDF and NSC requirements were evaluated by analysing a<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">dataset that involved 30 experimental trials carried out from 1985 to 2003. The dataset included chemical composition<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">of the experimental diets, individual milk yield, body weight, milk protein and fat content. These selected papers regard<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">10 different dairy ewe breeds (Valle del Belice, Bergamasca, Comisana, Delle Langhe, Massese, Sarda, Chios,<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">Manchega, Lacaune and Friesian) and lactating ewes in mid lactation, kept under non homogeneous environmental and<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">feeding conditions. Results substantially confirmed that which was recently reported in literature: NDF requirements are<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">higher in late lactation than during early lactation and they vary between 33-38% on DM, while NSC requirements are<span style="font: 12.0px Helvetica;">&nbsp;</span></p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 8.0px Verdana;">higher during early lactation than in late lactation when the energy from NSC promotes an increase in fat deposits.<span style="font: 12.0px Helvetica;">&nbsp;</span></p><div><span style="font-family: Helvetica, Arial, Helvetica, sans-serif; font-size: small;"><span style="font-size: 12px;"><br /></span></span></div