Iron, folic acid and vitamin B12 deficiencies related to anemia in adolescents from a region with a high incidence of congenital malformations in Venezuela

Since in recent years for certain age groups, the main cause of anemia is not iron deficiency, we intended to study the effect of iron, folic acid and vitamin B12 deficiencies on anemia prevalence in adolescents from Venezuela. One hundred adolescents aged between 12 and 19 years participated in the study. Each subject was interviewed about antecedents and habits and a physical examination and a 24-hour food recall questionnaire were performed. From a blood sample, hemoglobin and hematocrit concentrations were determined and serum was separated for quantification of ferritin, folic acid and vitamin B12 concentrations. Prevalence of anemia was 78% and for iron, folic acid and vitamin B12 deficiencies were 34.66, 90.9 and 18.18%, respectively. From anemic cases, 35.89% presented iron deficiency, while 91.02% presented folic acid deficiency. Only 19.23% of adolescents with anemia presented also vitamin B12 deficiency, but all the cases with vitamin B12 deficiency, were anemic. Simultaneous iron and folic acid deficiencies affected 30.76% of anemic cases. The high prevalence of deficiencies found in this work could be explained by insufficient intake and inadequate food habits. The prevalence of anemia was associated to folic acid deficiency rather than to iron deficiency, due to the high prevalence of folic acid deficiency. The high prevalence of nutritional deficiencies found in this work, especially regarding folic acid deficiency, require immediate interventions.     

A color image watermarking framework for copyright protection of stereo images based on binocular just noticeable difference and LU decomposition

Multimedia Tools and Applications - The copyright protection of three-dimensional (3D) content is a matter of interest in artistic and creative works due to the rights of the holder for the...     

Development and implementation of a hybrid scale up model for a batch high shear wet granulation operation

The high shear wet granulation (HSWG) operation consists of several rate processes influenced by the raw material properties, process operational parameters, and equipment design. Their combined effect determines the granule attributes. In literature, these rate processes have been modeled using different dimensionless numbers and their correlations. Each of these dimensionless numbers represent only certain rate processes. Since many of these rate processes occur at the same time, it is necessary to simultaneously model them to account for all the important degrees of freedom. Most of the HSWG scale up approaches in literature calculate scale up conditions based on a single rate process or operating parameter of interest that can lead to sub-optimal process design. We present the development of a hybrid HSWG scale up model accounting simultaneously for all the rate processes. The approach was successfully implemented to scale up the HSWG operation across laboratory, pilot, and commercial scales.     

Biofilm Responses to Flow Regulation by Dams in Mediterranean Rivers

Dams regulate downstream hydrology and modify water quality, which in turn can impinge on the biota, especially in rivers naturally subject to large hydrological variability, such as those under Mediterranean climate. The effect of dams on biofilms was analysed in three tributaries (Cinca, Siurana and Montsant) of the Ebro River (NE Spain). We hypothesized that flow regulation would lead to lower spatial variability of biofilms on the streambed and to a decrease in their metabolic rate per unit biomass, especially during low flow periods. Biofilm characteristics were studied in five transects evenly spaced along river reaches upstream (control) and downstream (impact) of dams in each river, along with riverbed granulometry, hydraulics and water chemistry. Chlorophyll‐a, respiratory activity, photosynthetic capacity and efficiency, and extracellular enzymatic activities (β‐d ‐glucosidase, alkaline phosphatase and leucine‐amino‐peptidase) of epilithic biofilms were measured in different seasons. Spatial variability of chemical and biological variables was reduced downstream of the dams. Chlorophyll‐a concentration, photosynthetic efficiency and respiration capacity were higher in impact than in control reaches, but generally, low inorganic phosphorus concentrations resulted in comparable phosphatase activities downstream and upstream of dams. On the other hand, β‐d ‐glucosidase and leucine‐amino‐peptidase activities were higher at impact reaches. Biofilms were thicker and metabolically more active at the impact reaches, with higher ability to transform dissolved organic matter. Overall, results from this study provide evidence that dams can largely affect the structure and activity of river biofilms, with foreseeable important consequences for river ecosystem functioning. Copyright © 2014 John Wiley & Sons, Ltd.     

Landmark-based music recognition system optimisation using genetic algorithms

Audio fingerprinting allows us to label an unidentified music fragment within a previously generated database. The use of spectral landmarks aims to obtain a robustness that lets a certain level of noise be present in the audio query. This group of audio identification algorithms holds several configuration parameters whose values are usually chosen based upon the researcher’s knowledge, previous published experimentation or just trial and error methods. In this paper we describe the whole optimisation process of a Landmark-based Music Recognition System using genetic algorithms. We define the actual structure of the algorithm as a chromosome by transforming its high relevant parameters into various genes and building up an appropriate fitness evaluation method. The optimised output parameters are used to set up a complete system that is compared with a non-optimised one by designing an unbiased evaluation model.     

Socio-Cultural Connections and Ruptures: Social Roles of Older Adults in Chile

This research focused on determining the sociocultural factors that build the social perception of the social roles of senior citizens in Chile in the 2002–2012 period. For this purpose, public opinion was studied in newspapers El Mercurio and La Cuarta. Specialized opinion included the Senior Citizen Program of Pontificia Universidad Católica de Chile, the National Service for Senior Citizens, the Social Observatory for Aging and Old Age of Universidad de Chile, and the Society of Geriatrics and Gerontology of Chile. A comprehensive methodology was used, along with a bibliographical four-stage design. The following ten sociocultural factors were identified: Health and Quality of Life, Studies and Data, Social Images of Aging, Gerontological Concepts and Sociopolitical Participation, Gerontological Policies, Plans and Principles, Aging, Production and Gender, Institutionalization, Demographic Growth, Gerontological Training, and Exclusion and Old Age. This work suggests modifying the conceptual premise that emphasizes the inexistence of a social role for elderly people with a vision centered on the heterogeneity of social roles under permanent sociocultural construction.     

Multi-objective optimization with an adaptive resonance theory-based estimation of distribution algorithm

The introduction of learning to the search mechanisms of optimization algorithms has been nominated as one of the viable approaches when dealing with complex optimization problems, in particular with multi-objective ones. One of the forms of carrying out this hybridization process is by using multi-objective optimization estimation of distribution algorithms (MOEDAs). However, it has been pointed out that current MOEDAs have an intrinsic shortcoming in their model-building algorithms that hamper their performance. In this work, we put forward the argument that error-based learning, the class of learning most commonly used in MOEDAs is responsible for current MOEDA underachievement. We present adaptive resonance theory (ART) as a suitable learning paradigm alternative and present a novel algorithm called multi-objective ART-based EDA (MARTEDA) that uses a Gaussian ART neural network for model-building and a hypervolume-based selector as described for the HypE algorithm. In order to assert the improvement obtained by combining two cutting-edge approaches to optimization an extensive set of experiments are carried out. These experiments also test the scalability of MARTEDA as the number of objective functions increases.