Los diálogos entre el contenido y la lengua: cautelas y retos en la emergencia de un programa de educación bilingüe

This paper presents a set of ideas about the basics for developing interdisciplinary dialogues between content (science) and language (English) in bilingual educational processes, under the premise that a satisfactory relationship between those elements help guarantee successful content-based instruction (CBI) in its form known as sheltered instruction. Additionally, a practical example (based on a science curriculum) is presented to demonstrate some principles that inform approaches to teaching such content. Finally, based on the authors’ interdisciplinary work and pedagogical experiences, some recommendations on teaching content and language in bilingual settings are presented in the form of cautions (a balance of actions) and challenges (prospects).Este artículo presenta un conjunto de ideas fundamentales para llevar a cabo diálogos interdisciplinarios entre contenido (ciencias naturales) y lengua (inglés) en procesos de educación bilingüe, bajo premisa de que un vínculo satisfactorio entre ambos elementos ayuda a garantizar una instrucción basada en contenidos (CBI) exitosa, particularmente, en su forma de instrucción amparada. En adición, un ejemplo práctico (basado en un currículo de ciencias naturales) se presenta para demostrar algunos principios que dan cuenta de algunos enfoques para enseñar dicho contenido. Finalmente, con base en el trabajo interdisciplinario y la experiencia pedagógica de sus autores, se presentan algunas recomendaciones sobre la enseñanza de contenido y lengua en ambientes bilingües, a manera de cautelas (balance de acciones) y retos (prospectivas)

An Efficient Nearest Neighbor Method for Protein Contact Prediction

A variety of approaches for protein inter-residue contact pre diction have been developed in recent years. However, this problem is far from being solved yet. In this article, we present an efficient nearest neigh bor (NN) approach, called PKK-PCP, and an application for the protein inter-residue contact prediction. The great strength of using this approach is its adaptability to that problem. Furthermore, our method improves considerably the efficiency with regard to other NN approaches. Our NN-based method combines parallel execution with k-d tree as search algorithm. The input data used by our algorithm is based on structural features and physico-chemical properties of amino acids besides of evo lutionary information. Results obtained show better efficiency rates, in terms of time and memory consumption, than other similar approaches.Ministerio de Educación y Ciencia TIN2011-28956-C02-0

Prediction of protein distance maps by assembling fragments according to physicochemical similarities

The prediction of protein structures is a current issue of great significance in structural bioinformatics. More specifically, the prediction of the tertiary structure of a protein consists of determining its three-dimensional conformation based solely on its amino acid sequence. This study proposes a method in which protein fragments are assembled according to their physicochemical similarities, using information extracted from known protein structures. Many approaches cited in the literature use the physicochemical properties of amino acids, generally hydrophobicity, polarity and charge, to predict structure. In our method, implemented with parallel multithreading, a set of 30 physicochemical amino acid properties selected from the AAindex database were used. Several protein tertiary structure prediction methods produce a contact map. Our proposed method produces a distance map, which provides more information about the structure of a protein than a contact map. The results of experiments with several non-homologous protein sets demonstrate the generality of this method and its prediction quality using the amino acid properties considered

Evolutionary decision rules for predicting protein contact maps

Protein structure prediction is currently one of the main open challenges in Bioinformatics. The protein contact map is an useful, and commonly used, represen tation for protein 3D structure and represents binary proximities (contact or non-contact) between each pair of amino acids of a protein. In this work, we propose a multi objective evolutionary approach for contact map prediction based on physico-chemical properties of amino acids. The evolutionary algorithm produces a set of decision rules that identifies contacts between amino acids. The rules obtained by the algorithm impose a set of conditions based on amino acid properties to predict contacts. We present results obtained by our approach on four different protein data sets. A statistical study was also performed to extract valid conclusions from the set of prediction rules generated by our algorithm. Results obtained confirm the validity of our proposal

Alpha Helix Prediction Based on Evolutionary Computation

Multiple approaches have been developed in order to predict the protein secondary structure. In this paper, we propose an approach to such a problem based on evolutionary computation. The proposed ap proach considers various amino acids properties in order to predict the secondary structure of a protein. In particular, we will consider the hy drophobicity, the polarity and the charge of amino acids. In this study, we focus on predicting a particular kind of secondary structure: α-helices. The results of our proposal will be a set of rules that will identify the beginning or the end of such a structure.Junta de Andalucía P07-TIC-02611Ministerio de Ciencia y Tecnología TIN2007-68084-C02-0

Evaluation of the Intermediate Values of the TGA Curves as Indicators of the Proximal Analysis of Biomass

[EN] Thermogravimetric analysis (TGA) is becoming popular for the evaluation of biomass to determine the content of ashes, volatiles, and fixed carbon and to simulate pyrolysis, gasification, and combustion processes. This analysis consists of heating a sample recording the weight variation as the temperature increases over time. The final temperature of the analyzes is usually set at 550 degrees C or 900 degrees C. The aim of this paper is to use the intermediate weight values obtained in short times from heating process in TGA to calculate the percentage of volatile, ash, or the residual mass remaining at the end of the experiment. Under the hypothesis that the curve does not vary when the analysis is carried out under certain conditions for the same type of biomass, these values must be similar and are related to the searched values. Nevertheless, given that the behavior of the thermogravimetric curves can be influenced by different factors, such as the species, temperature variation with time, final temperature reached, and presence of leaves, these factors are analyzed in this article. The results show models developed for the ash and volatiles determination from TGA time reduced to 75 s when a temperature increase of 200 degrees C per minute is used (CR-200 and VR-200 models). The curves obtained have R2 coefficients of between 0.75 and 0.95, being validated through independent samples. It is shown that the plot of the curve is influenced by the composition, the rate of heating and the percentage of leaves. This variability makes it necessary to select an analytical method that is efficient and as brief as possible. In this article, rapid analyses combined with the application of the equations obtained are proposed.This work was carried out within the framework of a study examining the analysis of the implementation of biomass exploitation chains in rural communities in the province of Bolívar (Ecuador) as part of the ADSIEO-COOPERATION program of the Polytechnic University of Valencia (UPV). The Ecuadorian Energy Exploitation Research Network of Biomass (ECUMASA) and the IBEROMASA Network of the Ibero-American Program of Science and Technology for Development (CYTED) participated in this program.Velázquez Martí, B.; Gaibor-Chavez, J.; López- Cortés, I.; Olivares Aguilar, LE. (2023). Evaluation of the Intermediate Values of the TGA Curves as Indicators of the Proximal Analysis of Biomass. Agronomy. 13(10). https://doi.org/10.3390/agronomy13102552131

An Evolutionary Approach for Protein Contact Map Prediction

In this study, we present a residue-residue contact prediction approach based on evolutionary computation. Some amino acid properties are employed according to their importance in the folding process: hydrophobicity, polarity, charge and residue size. Our evolutionary algorithm provides a set of rules which determine different cases where two amino acids are in contact. A rule represents two windows of three amino acids. Each amino acid is characterized by these four properties. We also include a statistical study for the propensities of contacts between each pair of amino acids, according to their types, hydrophobicity and polarity. Different experiments were also performed to determine the best selection of properties for the structure prediction among the cited properties.Junta de Andalucía P07-TIC-02611Ministerio de Ciencia y Tecnología TIN2007-68084-C02-0

Short-Range Interactions and Decision Tree-Based Protein Contact Map Predictor

In this paper, we focus on protein contact map prediction, one of the most important intermediate steps of the protein folding prob lem. The objective of this research is to know how short-range interac tions can contribute to a system based on decision trees to learn about the correlation among the covalent structures of a protein residues. We propose a solution to predict protein contact maps that combines the use of decision trees with a new input codification for short-range in teractions. The method’s performance was very satisfactory, improving the accuracy instead using all information of the protein sequence. For a globulin data set the method can predict contacts with a maximal accu racy of 43%. The presented predictive model illustrates that short-range interactions play the predominant role in determining protein structur

A decision tree-based method for protein contact map prediction

In this paper, we focus on protein contact map prediction. We describe a method where contact maps are predicted using decision tree-based model. The algorithm includes the subsequence information between the couple of analyzed amino acids. In order to evaluate the method generalization capabilities, we carry out an experiment using 173 non-homologous proteins of known structures. Our results indicate that the method can assign protein contacts with an average accuracy of 0.34, superior to the 0.25 obtained by the FNETCSS method. This shows that our algorithm improves the accuracy with respect to the methods compared, especially with the increase of protein lengt

Detection, counting, and classification of visual ganglia columns of drosophila pupae

Many neurobiologists use the fruit fly (Drosophila) as a model to study neuron interaction and neuron organization and then extrapolate this knowledge to the nature of human neurological disorders. Recently, the fluorescence microscopy images of fruit-fly neurons are commonly used, because of the high contrast. However, the detection of the neurons or cells is compromised by background signals, generating fuzzy boundaries. As a result, it is still common that in many laboratories, the detection, counting, and analysis of this microscope imagery is still a manual task. An automated detection, counting, and morphological analysis of these images can provide faster data processing and easier access to new information. The main objective of this work is to present a semi-automatic detection-counting system and give the main characteristics of images of the visual ganglia columns in Drosophila. We present the semi-automatic detection, count, segmentation and we concluded that it is possible to obtain an accuracy of 75% (with a Kappa statistic of 0.50) in the shape classification. Additionally, we develop python GUI CC Analyzer which can be used by neurobiology laboratories whose research interests are focused on this topic.Peer ReviewedPostprint (published version