Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction

This paper introduces and evaluates a new class of knowledge model, the recursive Bayesian multinet (RBMN), which encodes the joint probability distribution of a given database. RBMNs extend Bayesian networks (BNs) as well as partitional clustering systems. Briefly, a RBMN is a decision tree with component BNs at the leaves. A RBMN is learnt using a greedy, heuristic approach akin to that used by many supervised decision tree learners, but where BNs are learnt at leaves using constructive induction. A key idea is to treat expected data as real data. This allows us to complete the database and to take advantage of a closed form for the marginal likelihood of the expected complete data that factorizes into separate marginal likelihoods for each family (a node and its parents). Our approach is evaluated on synthetic and real-world databases.     

Regularized continuous estimation of distribution algorithms

Regularization is a well-known technique in statistics for model estimation which is used to improve the generalization ability of the estimated model. Some of the regularization methods can also be used for variable selection that is especially useful in high-dimensional problems. This paper studies the use of regularized model learning in estimation of distribution algorithms (EDAs) for continuous optimization based on Gaussian distributions. We introduce two approaches to the regularized model estimation and analyze their effect on the accuracy and computational complexity of model learning in EDAs. We then apply the proposed algorithms to a number of continuous optimization functions and compare their results with other Gaussian distribution-based EDAs. The results show that the optimization performance of the proposed RegEDAs is less affected by the increase in the problem size than other EDAs, and they are able to obtain significantly better optimization values for many of the functions in high-dimensional settings.     

Detecting reliable gene interactions by a hierarchy of Bayesian network classifiers

The main purpose of a gene interaction network is to map the relationships of the genes that are out of sight when a genomic study is tackled. DNA microarrays allow the measure of gene expression of thousands of genes at the same time. These data constitute the numeric seed for the induction of the gene networks. In this paper, we propose a new approach to build gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling. The interactions induced by the Bayesian classifiers are based both on the expression levels and on the phenotype information of the supervised variable. Feature selection and bootstrap resampling add reliability and robustness to the overall process removing the false positive findings. The consensus among all the induced models produces a hierarchy of dependences and, thus, of variables. Biologists can define the depth level of the model hierarchy so the set of interactions and genes involved can vary from a sparse to a dense set. Experimental results show how these networks perform well on classification tasks. The biological validation matches previous biological findings and opens new hypothesis for future studies.     

Advances and Perspectives in Dental Pulp Stem Cell Based Neuroregeneration Therapies

Human dental pulp stem cells (hDPSCs) are some of the most promising stem cell types for regenerative therapies given their ability to grow in the absence of serum and their realistic possibility to be used in autologous grafts. In this review, we describe the particular advantages of hDPSCs for neuroregenerative cell therapies. We thoroughly discuss the knowledge about their embryonic origin and characteristics of their postnatal niche, as well as the current status of cell culture protocols to maximize their multilineage differentiation potential, highlighting some common issues when assessing neuronal differentiation fates of hDPSCs. We also review the recent progress on neuroprotective and immunomodulatory capacity of hDPSCs and their secreted extracellular vesicles, as well as their combination with scaffold materials to improve their functional integration on the injured central nervous system (CNS) and peripheral nervous system (PNS). Finally, we offer some perspectives on the current and possible future applications of hDPSCs in neuroregenerative cell therapies.     

Optimization of a slurry dispersion method for minerals and trace elements analysis in infant formulae by ICP OES and FAAS

Infant formula developed by manufacturers requires a rigorous control of composition, particularly those elements added routinely in an attempt to mimic the mineral composition of human milk. A total of 97 different types of powdered infant formulae (preterm, adapted starter, adapted follow-up, toddler, specialised and soy-based formulae) commercially available in Spain were studied. It is noteworthy great differences in mineral (Ca, P, Mg) and trace element (Zn, Fe, Cu, Mn) contents found between analysed and listed in label information. The development of a fast, simple and direct slurry method for the determination of these essential micronutrients in infant formula by inductively coupled plasma optical emission spectrometry (ICP OES) and flame atomic absorption spectrometry (FAAS) was performed in order to help in quality control tasks. Infant formula samples were solubilised using different amounts of several different solvents. An addition of 250 μL of a solution 10% tetramethylammonium hydroxide and 25% ammonium hydroxide were required for the accurate quantification of Ca and P, Mg, Zn, Fe, Cu and Mn, respectively. The standard reference material 1549 non-fat milk powder was solubilised to compare the validity of assayed methodology following slurry nebulisation and traditional microwave-assisted acid digestion method. Good agreement of the analytical results by both ICP OES and FAAS, with the certified values was obtained. Method performance parameters (accuracy, precision and methodological detection limits) were determined for studied elements to check the quality and usefulness of the optimised slurry method. The analytical procedure was applied successfully to the analysis of a representative group of infant formulae. Levels of analysed elements were graphically represented, showing an acceptable comparability between slurry and acid-mineralisation method set by linear correlation coefficients and slopes close to the unit. The described simple and slurry method is appropriate, as an attractive alternative, for routine control analysis of added essential elements in infant formulae regardless of predominant protein type used in manufacture.     

Evaluation of Using LaNi0.6Fe0.4O3–δ Contact Layer Between La0.6Sr0.4FeO3 Cathode and Crofer22APU Interconnect for Solid Oxide Fuel Cells

Interconnect‐cathode interfacial adhesion is important for the durability of solid oxide fuel cell (SOFC). Thus, the use of a conductive contact layer between interconnect and cathode could reduce the cell area specific resistance (ASR). The use of La_0.6Sr_0.4FeO₃ (LSF) cathode, LaNi_0.6Fe_0.4O_3–δ (LNF) contact layer and Crofer22APU interconnect was proposed as an alternative cathode side. LNF‐LSF powder mixtures were heated at 800 °C for 1,000 h and at 1,050 °C for 2 h and analyzed by X‐Ray power diffraction (XRD). The results indicated a low reactivity between the materials. The degradation occurring between the components of the half‐cell (LSF/LNF/Crofer22APU) was studied. XRD results indicated the formation of secondary phases, mainly: SrCrO₄, A(B, Cr)O₃ (A = La, Sr; B = Ni, Fe) and SrFe₁₂O₁₉. Scanning electron microscopy with energy dispersive X‐Ray spectroscopy (SEM‐EDX) and the X‐Ray photoelectron spectroscopy (XPS) analyzes confirmed the interaction between LSF/LNF and the metallic interconnect due to the Cr vaporization/migration. An increment of the resistance of ∼0.007 Ω cm² in 1,000 h is observed for (LSF/LNF/Crofer22APU) sample. However, the ASR values of the cell without contact coating, (LSF/Crofer22APU), were higher (0.31(1) Ω cm²) than those of the system with LNF coated interconnect (0.054(7) Ω cm²), which makes the proposed materials combination interesting for SOFC.     

Aromatic DNA adducts in relation to dietary and other lifestyle factors in Spanish adults

The aim of this study was to assess the relationship between bulky DNA adducts in white blood cells (WBC) and lifestyle factors in a sample from the Spanish cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC). 296 subjects aged between 35 and 64 years, from five regions, were included. Food intake was estimated with a computerized version of dietary history questionnaire. Daily intake of polycyclic aromatic hydrocarbons (PAH) was estimated using a database with information on food content of potential carcinogens. Data on lifestyle and health factors were collected and DNA adducts measured using the nuclease P1 ³²P-postlabelling technique. Geometric means of adducts were similar for men and women (4.11/10⁹ and 3.94/10⁹ nucleotides, respectively). Highest levels of adduct were observed in non-smokers and non-occupationally exposed. Meat intake, oils and fats were associated with higher levels of adducts, but all non-statistically significant. Higher intakes of calcium, sodium and phosphorus were associated with lower adducts levels. Summarising, our study shows that bulky adducts measured by ³²P-postlabelling in DNA from WBC do not correlate with the usual diet of healthy Spanish adults. Although it has been proposed that diet be the main source of PAH in nonsmokers without occupational exposure, DNA adducts do not seem to be suitable biomarkers of dietary PAH in general population.     

Melanoblastoma of the rectum

Vroom's (1964) expectancy theory model was used to predict older workers' choices between continued employment or immediate retirement. It was hypothesized that a person's preference for one of the two alternatives would be a function of the differences between the instrumentality of employment and the instrumentality of retirement for the attainment of outcomes, multiplied by the valence of each outcome, summed over outcomes. To test this, 290 Israeli male workers, aged 57 to 64, were interviewed. Measures included: preference for employment or retirement; valences of 35 outcomes; perceived instrumentalities of employment and retirement. The results supported the hypothesis (R = .40; p less than .01). It is suggested that further research along these lines could equip organizations with a tool for assisting older employees in the transition to retirement or for encouraging those who are still capable of making a significant contribution to remain employed.     

Experimental simulation of solar drying of garlic using an adsorbent energy storage bed

Solar drying of garlic with energy storage in silica gel is experimentally simulated in a closed system in which the air is continuously circulated between food and adsorbent. Kinetics of the drying process are studied and equilibrium data are predicted by a mathematical model developed from the experimental results. By comparing the end points of drying with equilibrium values the length of the drying process can be established.From sorption data, a garlic surface area of 63–188 m² g^?1 and a heat of adsorption in the first layer of 2548–2691 kJ kg^?1 have been calculated. A value of 746 kJ kg^?1 has been deduced for the activation energy for water removal.