Teniendo en consideración que la formación integral de un profesor de Física implica que éste tenga un dominio de su campo disciplinar, una concepción crítica sobre la ciencia que enseña y su enseñanza; presentamos en este trabajo el diseño de una propuesta didáctica que tiene como principal propósito considerar los principios de la Teoría del Aprendizaje Significativo Crítico de Moreira en el aula de clase, a partir de la implementación de actividades de modelación computacional. Estas actividades están apoyadas en el uso del diagrama AVM (Adaptación de la V de Gowin a la Modelación Computacional) y tienen como propósito favorecer el aprendizaje significativo de conceptos físicos y la formación de futuros profesores de Física con visiones más críticas y reflexivas en relación con el conocimiento científico, la modelación científica y la enseñanza de las Ciencias.; This paper presents a didactical proposal that aims to help the mastery of Physics contents and the developing of critical thinking on Physics and its learning by pre-service teachers. The proposal was designed to embed the principles of Moreira’s Critical Meaningful Learning Theory into computational modeling activities through the use of a heuristic instrument known as AVM diagram (Adaptation of Gowin’s V for Computational Modeling). A detailed description of the proposal and some of its possible implications for Physics teaching are discussed.

The purpose of this research was to investigate the learning of students who worked with computational modeling and simulation using the software Modellus in the study of simple electric circuits. The theoretical framework was based on Ausubel’s theory of meaningful learning and Halloun’s schematic modeling approach. The quantitative results show that there were statistically significant differences in the performance of students who worked with the computational activities (experimental group), when compared to the one in which students were just exposed to a traditional method of teaching (control group). The qualitative results suggest that many students from the experimental group seemed to have achieved meaningful learning, and the students’ interaction among themselves and with the teacher as well during the computational activities has strongly contributed for that.

El propósito de este trabajo fue realizar un estudio exploratorio sobre el proceso de aprendizaje de algunos conceptos básicos de dinámica newtoniana, a través de la implementación de actividades de modelación computacional haciendo uso del diagrama AVM (Adaptación del diagrama V de Gowin a la Modelación Computacional). La fundamentación teórica está soportada en la Teoría del aprendizaje significativo de Ausubel, en la modelación esquemática de Halloun y en la modelación computacional con diagrama AVM. Los resultados de esta investigación indican un desempeño satisfactorio de los estudiantes en la realización de estas actividades que se traduce no solo en la gran contribución de éstas para el aprendizaje de conceptos de dinámica newtoniana, sino también en su influencia positiva en la predisposición de los estudiantes para aprender conceptos físicos. Tales actividades fueron implementadas en un curso inicial de física con 23 estudiantes de Licenciatura en Ciencias Naturales y Educación Ambiental de la Universidad de Antioquia, Colombia.; The purpose of this work was to conduct an exploratory study on the learning process of some basic concepts of Newtonian dynamics, through computational modeling activities using the AVM diagram (Adaptation of the Gowin’s V diagram to Computational Modeling). The theoretical framework is based on Ausubel’s meaningful learning theory...

Neste trabalho apresentamos a modelagem computacional de uma válvula de expansão eletrônica a partir de dados experimentais de entradas e saídas através de modelos no espaço de estado, usando técnicas de subespaços, com objetivo de ter um sistema de refrigeração e ar condicionado eficiente, combinando eletrônica de potência e computação de modo a fornecer uma melhor solução para conservação de energia. A modelagem e a validação são feitas usando uma implementação computacional dos algoritmos de subespaços do espaço de estado. Os resultados apresentados mostram a validade e vantagens da técnica de modelagem realizada; This research shows the computational modeling of a electronic expansion valve based on input and output experimental data using Models in State Space and subspace methods. The aim of this work was to obtain an efficient Cooling and Air Conditioning system by the combination of power electronics and computation, as a result, a better solution for energy conservation was obtained. Modeling and validation are made using a computational implementation of subspace methods algorithms in state space. Achieved results show the validity and advantages of the modeling technique implemented

The use of computational modeling to predict arrhythmia and arrhythmogensis is a relatively new field, but has nonetheless dramatically enhanced our understanding of the physiological and pathophysiological mechanisms that lead to arrhythmia. This review summarizes recent advances in the field of computational modeling approaches with a brief review of the evolution of cellular action potential models, and the incorporation of genetic mutations to understand fundamental arrhythmia mechanisms, including how simulations have revealed situation specific mechanisms leading to multiple phenotypes for the same genotype. The review then focuses on modeling drug blockade to understand how the less-than-intuitive effects some drugs have to either ameliorate or paradoxically exacerbate arrhythmia. Quantification of specific arrhythmia indicies are discussed at each spatial scale, from channel to tissue. The utility of hERG modeling to assess altered repolarization in response to drug blockade is also briefly discussed. Finally, insights gained from Ca2+ dynamical modeling and EC coupling, neurohumoral regulation of cardiac dynamics, and cell signaling pathways are also reviewed.

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamoring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensorimotor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialog between two fictional characters: Ernest, the “experimenter,” and Mary, the “computational modeler.” The dialog consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and...

One of the major obstacles in computational modeling of a biological system is to determine a large number of parameters in the mathematical equations representing biological properties of the system. To tackle this problem, we have developed a global optimization method, called Discrete Selection Levenberg-Marquardt (DSLM), for parameter estimation. For fast computational convergence, DSLM suggests a new approach for the selection of optimal parameters in the discrete spaces, while other global optimization methods such as genetic algorithm and simulated annealing use heuristic approaches that do not guarantee the convergence. As a specific application example, we have targeted understanding phagocyte transmigration which is involved in the fibrosis process for biomedical device implantation. The goal of computational modeling is to construct an analyzer to understand the nature of the system. Also, the simulation by computational modeling for phagocyte transmigration provides critical clues to recognize current knowledge of the system and to predict yet-to-be observed biological phenomenon.

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis.

Although computational modeling is common in many areas of science and engineering, only recently have advances in experimental techniques and medical imaging allowed this tool to be applied in cardiac surgery. Despite its infancy in cardiac surgery, computational modeling has been useful in calculating the effects of clinical devices and surgical procedures. In this review, we present several examples that demonstrate the capabilities of computational cardiac modeling in cardiac surgery. Specifically, we demonstrate its ability to simulate surgery, predict myofiber stress and pump function, and quantify changes to regional myocardial material properties. In addition, issues that would need to be resolved in order for computational modeling to play a greater role in cardiac surgery are discussed.

Objective: Dysregulated muscle metabolism is a cardinal feature of human insulin resistance (IR) and associated diseases, including type 2 diabetes (T2D). However, specific reactions contributing to abnormal energetics and metabolic inflexibility in IR are unknown. Methods: We utilize flux balance computational modeling to develop the first systems-level analysis of IR metabolism in fasted and fed states, and varying nutrient conditions. We systematically perturb the metabolic network to identify reactions that reproduce key features of IR-linked metabolism. Results: While reduced glucose uptake is a major hallmark of IR, model-based reductions in either extracellular glucose availability or uptake do not alter metabolic flexibility, and thus are not sufficient to fully recapitulate IR-linked metabolism. Moreover, experimentally-reduced flux through single reactions does not reproduce key features of IR-linked metabolism. However, dual knockdowns of pyruvate dehydrogenase (PDH), in combination with reduced lipid uptake or lipid/amino acid oxidation (ETFDH), does reduce ATP synthesis, TCA cycle flux, and metabolic flexibility. Experimental validation demonstrates robust impact of dual knockdowns in PDH/ETFDH on cellular energetics and TCA cycle flux in cultured myocytes. Parallel analysis of transcriptomic and metabolomics data in humans with IR and T2D demonstrates downregulation of PDH subunits and upregulation of its inhibitory kinase PDK4...

The use of renewable energy sources to improve the thermal conditions of built environments and hencedecreasing the consumption of conventional energy is an important aspect to design a sustainable build-ing. Within this context, it is possible to harness the solar energy that reaches the Earth’s surface andis stored by the soil as thermal energy. To do so, the Earth-Air Heat Exchanger (EAHE) device can beemployed, consisting of a buried duct through which the external ambient air is insufflated. The flowingair exchanges heat with surround soil, and leaves the device with a milder temperature compared to itsinput temperature. The main goal of this work was to present a new computational modeling to predictthe thermal behavior of EAHE. This new numerical model has the advantage of needing a lower com-putational effort, allowing the study about the influence of operational and constructive parameters, aswell as, the application of geometric optimization methods in EAHE. A case study was developed whereinfluence of the installation depth in the thermal potential of an EAHE was investigated. The results arein agreement with those found in literature; however they were obtained with a reduction in processingtime of almost 45%.

Nowadays, there is a focus on finding sustainable energy sources, as well as, alternatives to rationalize the use of electrical energy. In this sense, the employment of Earth-Air Heat Exchangers (EAHE) is one technique which allows the reduction of energy consumption for climatization of buildings environments. The present study shows the evaluation of a numerical method to estimate the ground thermal potential, allowing its applicability for future thermal design of EAHE. The soil domain is considered two-dimensional and a transient solution for the thermal behavior of the soil is obtained. Moreover, a soil surface temperature distribution equation based on experimental data is employed to define the domain boundary conditions. The simulations are performed with a numerical method based on the finite volume method, more precisely using the software FLUENT®. The results presented an excellent agreement with analytical solutions showing the validity and effectiveness of the computational model for prediction of the soil behavior. The numerical results were also confronted with experimental ones predicted into literature and show a good agreement, with a deviation lower than 14%. The main difference is attributed to the duct presence which is taken into account only for the experimental study.

The objective of this study was to investigate the performance of students when exposed to complementary activities of computational modeling in the learning of Physics and Mathematics taken integrated, using the software Modellus. The difficulties of changing record (algebraic, numeric, graphic and animation), in the work with contents of Kinematics and Functions were the subjects chosen. The study involved first-year students of high school from Agrotécnica Federal de Satuba School - AL and was held in the second half of 2008. For research was adopted a quasi-experimental design, consisting of an experimental group of 18 students who were submitted to computational modeling activities exploratory and of creation for an interval of two weeks (five meetings of two sessions of 50 minutes each) and by a control group of eighteen other students. The results show that there was a statistically significant improvement in the students performance in the experimental group when compared to students in the control group exposed only to the traditional method of teaching. The results of qualitative analysis suggest that many students achieved significant learning. Our observations suggest that the interactions between students and computer activities became a motivating factor in learning.; O objetivo deste trabalho foi o de investigar o desempenho de estudantes quando expostos a atividades complementares de modelagem computacional na aprendizagem de conteúdos de Física e de Matemática tomados de forma integracionista...

19th ICCRTS, Toward Computational Modeling of C2 for Teams of Autonomous Systems and People, Autonomy Track – Paper 116; The technological capabilities of autonomous systems (AS) continue to accelerate. Although AS are replacing people in many skilled mission domains and demanding environmental circumstances, people and machines have complementary capabilities, and integrated performance by AS and people working together can be superior to that of either AS or people working alone. We refer to this increasingly important phenomenon as Teams of Autonomous Systems and People (TASP), and we identify a plethora of open, command and control (C2) research, policy and decision making questions. Computational modeling and simulation offer unmatched yet largely unexplored potential to address C2 questions along these lines. The central problem is, this kind of C2 organization modeling and simulation capability has yet to be developed and demonstrated in the TASP domain. This is where our ongoing research project begins to make an important contribution. In this article, we motivate and introduce such TASP research, and we provide an overview of the computational environment used to model and simulate TASP C2 organizations and phenomena. We follow in turn with an approach to characterizing a matrix of diverse TASP C2 contexts...

The employment of numerical methods to solve engineering problems is a reality, as well as, the worldwide concern about the need of renewable and alternative energy sources. Thus, this work presents a computational model capable of simulating the operating principle of some Wave Energy Converters (WEC). To do so, the device is coupled in a wave tank, where the sea waves are reproduced. The Finite Volume Method (FVM) and the Volume of Fluid (VOF) model are adopted. The results showed that the converter's operating principle can be numerically reproduced, demonstrating the potential of computational modeling to study this subject.

This work presents the computational modeling of a converter of wave energy in electrical energy. The converter is Oscillating Water Column (OWC) type, submitted to the wave climate of Rio Grande city. The numerical simulation was performed using FLUE)T® package and employing the multiphase Volume of Fluid (VOF) model in the wave generation and in the interaction between the wave and the converter device. The computational domain was represented by a wave tank coupled with the OWC device. This domain allows the behavior analysis to be performed when the device is subjected to the incidence of regular waves. The waves were molded to represent the characteristics of the Rio Grande coastclimate. Results demonstrate that the OWC converter can be successfully used to convert the Rio Grande's coast wave energy in useful electrical energy.

Background: Accurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs). Correctly and consistently quantifying what cells “see,” during an in vitro exposure requires standardized preparation of stable ENM suspensions, accurate characterizatoin of agglomerate sizes and effective densities, and predictive modeling of mass transport. Earlier transport models provided a marked improvement over administered concentration or total mass, but included assumptions that could produce sizable inaccuracies, most notably that all particles at the bottom of the well are adsorbed or taken up by cells, which would drive transport downward, resulting in overestimation of deposition. Methods: Here we present development, validation and results of two robust computational transport models. Both three-dimensional computational fluid dynamics (CFD) and a newly-developed one-dimensional Distorted Grid (DG) model were used to estimate delivered dose metrics for industry-relevant metal oxide ENMs suspended in culture media. Both models allow simultaneous modeling of full size distributions for polydisperse ENM suspensions, and provide deposition metrics as well as concentration metrics over the extent of the well. The DG model also emulates the biokinetics at the particle-cell interface using a Langmuir isotherm...

In this paper, we survey five different computational modeling methods. For comparison, we use the activation cycle of G-proteins that regulate cellular signaling events downstream of G-protein-coupled receptors (GPCRs) as a driving example. Starting from an existing Ordinary Differential Equations (ODEs) model, we implement the G-protein cycle in the stochastic Pi-calculus using SPiM, as Petri-nets using Cell Illustrator, in the Kappa Language using Cellucidate, and in Bio-PEPA using the Bio-PEPA eclipse plug in. We also provide a high-level notation to abstract away from communication primitives that may be unfamiliar to the average biologist, and we show how to translate high-level programs into stochastic Pi-calculus processes and chemical reactions.; Comment: In Proceedings MeCBIC 2010, arXiv:1011.0051

Students taking introductory physics are rarely exposed to computational modeling. In a one-semester large lecture introductory calculus-based mechanics course at Georgia Tech, students learned to solve physics problems using the VPython programming environment. During the term 1357 students in this course solved a suite of fourteen computational modeling homework questions delivered using an online commercial course management system. Their proficiency with computational modeling was evaluated in a proctored environment using a novel central force problem. The majority of students (60.4%) successfully completed the evaluation. Analysis of erroneous student-submitted programs indicated that a small set of student errors explained why most programs failed. We discuss the design and implementation of the computational modeling homework and evaluation, the results from the evaluation and the implications for instruction in computational modeling in introductory STEM courses.; Comment: 14 pages, 1 figure, 6 tables, submitted to PRST-PER

7 pages.-- PMID: 17220082 [PubMed].; It has been accepted that aryl hydrocarbon receptor (AhR) ligands are compounds with two or more aromatic rings in a coplanar conformation. Although general agreement exists that carbaryl is able to activate the AhR, it has been proposed that such activation could occur through alternative pathways without ligand binding. This idea was supported by studies showing a planar conformation of carbaryl as unlikely. The objective of the present work was to clarify the process of AhR activation by carbaryl. In rat H4IIE cells permanently transfected with a luciferase gene under the indirect control of AhR, incubation with carbaryl led to an increase of luminescence. Ligand binding to the AhR was studied by means of a cell-free in vitro system in which the activation of AhR can occur only by ligand binding. In this system, exposure to carbaryl also led to activation of AhR. These results were similar to those obtained with the AhR model ligand β-naphthoflavone, although this compound exhibited higher potency than carbaryl in both assays. By means of computational modeling (molecular mechanics and quantum chemical calculations), the structural characteristics and electrostatic properties of carbaryl were described in detail...