MiniAnDE: a reduced AnDE ensemble to deal with microarray data

This article focuses on the supervised classification of datasets with a large number of variables and a small number of instances. This is the case, for example, for microarray data sets commonly used in bioinformatics. Complex classifiers that require estimating statistics over many variables are not suitable for this type of data. Probabilistic classifiers with low-order probability tables, e.g. NB and AODE, are good alternatives for dealing with this type of data. AODE usually improves NB in accuracy, but suffers from high spatial complexity since $k$ models, each with $n+1$ variables, are included in the AODE ensemble. In this paper, we propose MiniAnDE, an algorithm that includes only a small number of heterogeneous base classifiers in the ensemble, i.e., each model only includes a different subset of the $k$ predictive variables. Experimental evaluation shows that using MiniAnDE classifiers on microarray data is feasible and outperforms NB and other ensembles such as bagging and random forest

Size-Controlled Water-Soluble Ag Nanoparticles

Ag nanoparticles of two different sizes (1 and 4 nm) were prepared within an apoferritin cavity by using an Ag+-loaded apoferritin as a nanoconfined environment for their construction. The initial amount of Ag' ions injected in the apoferritin cavity dictates the size of the final Ag particles. The protein shell prevents bulk aggregation of the metal particles, which renders them water soluble and extremely stable

Real-World Attainment of Low-Density Lipoprotein Cholesterol Goals in Patients at High Risk of Cardiovascular Disease Treated with High-Intensity Statins: The TERESA Study

Despite steady improvements in cardiovascular disease (CVD) prevention, a scarce proportion of patients achieve the recommended LDL-C goals, even under high-intensity lipid-lowering therapy (LLT). Our study aimed to evaluate the attainment rate of LDL-C targets recommended by the 2019 European guidelines, and to characterize potential factors associated with LDL-C goal achievement and change patterns in LLT. We conducted a retrospective, observational study on patients treated with high-intensity atorvastatin or rosuvastatin +/- ezetimibe at cardiology and internal medicine clinics across Spain. It included 1570 evaluable patients (median age: 62 years; established CVD: 77.5% [myocardial infarction: 34.3%]; and 85.8% at very high cardiovascular risk). Rosuvastatin +/- ezetimibe was the LLT in 52.2% of patients, and atorvastatin +/- ezetimibe in 47.8%. LLT had been modified in 36.8% of patients (side effects: 10%), being the most common switch from atorvastatin- to rosuvastatin-based treatment (77.2%). The risk-based LDL-C goal attainment rate was 31.1%, with 78.2% high-risk and 71.7% very high-risk patients not achieving the recommended LDL-C targets. Established CVD and familial hypercholesterolemia were significantly associated with the non-achievement of LDL-C goals. Although having limitations, this study shows that the guideline-recommended LDL-C goal attainment rate is still suboptimal despite using high-intensity statin therapy in a real-world setting in Spain

Simulación numérica y resultados experimentales del ensayo a tracción de un panel rigidizado de material compuesto

COMATCOMP 09 : Donostia - San Sebastian, 7, 8 y 9 de octubre de 2009Se analiza numérica y experimentalmente un panel rigidizado plano solicitado por una tracción transversal a los rigidizadores. Se han realizado una serie de ensayos hasta rotura en el laboratorio y se cuenta con la lectura de varias bandas extensométricas en función de la carga aplicada. Se han realizado dos modelos de elementos finitos, resueltos con MSC PATRAN-NASTRAN, y se comparan los resultados con las mediciones experimentales. También se incluyen resultados numéricos incluyendo la evolución del daño

Una propuesta para las prácticas de la materia "Teoría de Autómatas y Lenguajes Formales"

En este trabajo presentamos una propuesta para la realización de las prácticas relativas a la materia “Teoría de Autómatas y Lenguajes Formales”, basadas en el uso de distintos programas que permiten no sólo el diseño y prueba de los distintos modelos de autómata y gramática, sino también la interacción con el alumno para la resolución paso a paso de distintos problemas (minimización de autómatas finitos, conversiones entre distintos modelos de autómata y/o gramática, etc...)

Benefits of hippotherapy in elderly people: Scoping review

The study aims to conduct a bibliographic and structured review based on the results found around the terms “Hippotherapy” and “Elderly”. The words were always introduced in English and computerized databases; SCOPUS, WOS and SPORTDiscus. To limit the search, four inclusion criteria were introduced: i) Mention at least some of the characteristics for Hippotherapy for the elderly (minimum 20 words), ii) Only articles, iii) Full text or summary available, and iii) Written in Spanish, English or Portuguese. In conclusion, documents about Hippotherapy in older people address different research topics and shows the main benefits of equestrian therapies on this population

Predicting Systemic Banking Crises using Extreme Gradient Boosting

571-575Considering the great ability of decision trees techniques to extract useful information from large databases and to handle heterogeneous variables, this paper applies Extreme Gradient Boosting for the prediction of systemic banking crises. To this end, prediction models have been constructed for different regions and the whole world. The results obtained show that Extreme Gradient Boosting overcomes the predictive power of existing models in the previous literature and provides more explanatory information on the causes that produce systemic banking crises, being the demand for deposits, the level of domestic credit and banking assets some of the most significant variables

Using Regulatory and Epistatic Networks to Extend the Findings of a Genome Scan: Identifying the Gene Drivers of Pigmentation in Merino Sheep

Extending genome wide association analysis by the inclusion of gene expression data may assist in the dissection of complex traits. We examined piebald, a pigmentation phenotype in both human and Merino sheep, by analysing multiple data types using a systems approach. First, a case control analysis of 49,034 ovine SNP was performed which confirmed a multigenic basis for the condition. We combined these results with gene expression data from five tissue types analysed with a skin-specific microarray. Promoter sequence analysis of differentially expressed genes allowed us to reverse-engineer a regulatory network. Likewise, by testing two-loci models derived from all pair-wise comparisons across piebald-associated SNP, we generated an epistatic network. At the intersection of both networks, we identified thirteen genes with insulin-like growth factor binding protein 7 (IGFBP7), platelet-derived growth factor alpha (PDGFRA) and the tetraspanin platelet activator CD9 at the kernel of the intersection. Further, we report a number of differentially expressed genes in regions containing highly associated SNP including ATRN, DOCK7, FGFR1OP, GLI3, SILV and TBX15. The application of network theory facilitated co-analysis of genetic variation with gene expression, recapitulated aspects of the known molecular biology of skin pigmentation and provided insights into the transcription regulation and epistatic interactions involved in piebald Merino sheep