Computational Modeling Methodologies Research Articles

Moving alcohol prevention research forward—Part I: introducing a complex systems paradigm

The drinking environment is a complex system consisting of a number of heterogeneous, evolving and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. A complex systems paradigm, grounded in socio-ecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models can further increase stakeholder buy-in, understanding and policymaking. A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions.

Prediction of Aerodynamic Characteristics of Ram-Air Parachutes

The focus of this work is on the computational methodology for aerodynamic modeling of ram-air parachutes and increasing confidence and understanding in their concept designs including new parachute control methods. The complex geometries of ram-air parachutes are modeled by two-dimensional rigid airfoil geometries with or without trailing-edge deflections and bleed air spoilers. The aerodynamic forces are then calculated from steady or unsteady Reynolds-averaged Navier–Stokes simulations using Cobalt and Kestrel flow solvers. The effects of the grid size and type, the time step, and the choice of solver parameters are investigated. The flow solvers are then used to study the flow around three-dimensional wings with open/closed ram-air inlets by comparing lift and drag coefficients with available experimental data. The results show that computational fluid dynamics simulations are a valuable aid in understanding the flow structure of ram-air parachutes, which resemble a rectangular wing with open inlets. However, the computational solutions of these geometries have initial oscillations of large amplitude and converge slowly compared to closed wings/airfoils. The simulation of open geometry should run unsteady and for a large number of time steps. It is also shown that an open-inlet geometry has smaller lift and larger drag, and it stalls earlier than a closed-inlet geometry. Although the air reaches stagnation conditions inside the cavity present in an open airfoil, the air pressure inside the wing cells is less than the stagnation pressure. The flow investigations show that eddies are formed on the lower surface of the open airfoil and wings; however, the wing eddy size varies in the spanwise direction. Finally, the grid sensitivity results show that the solutions of open geometries are very sensitive to the grid quality.

Structural computational modeling of RNA aptamers

RNA aptamers represent an emerging class of biologics that can be easily adapted for personalized and precision medicine. Several therapeutic aptamers with desirable binding and functional properties have been developed and evaluated in preclinical studies over the past 25years. However, for the majority of these aptamers, their clinical potential has yet to be realized. A significant hurdle to the clinical adoption of this novel class of biologicals is the limited information on their secondary and tertiary structure. Knowledge of the RNA’s structure would greatly facilitate and expedite the post-selection optimization steps required for translation, including truncation (to reduce costs of manufacturing), chemical modification (to enhance stability and improve safety) and chemical conjugation (to improve drug properties for combinatorial therapy). Here we describe a structural computational modeling methodology that when coupled to a standard functional assay, can be used to determine key sequence and structural motifs of an RNA aptamer. We applied this methodology to enable the truncation of an aptamer to prostate specific membrane antigen (PSMA) with great potential for targeted therapy that had failed previous truncation attempts. This methodology can be easily applied to optimize other aptamers with therapeutic potential.

Energy dissipation via acoustic emission in ductile crack initiation

This article presents a modeling approach to estimate the energy release due to ductile crack initiation in conjunction to the energy dissipation associated with the formation and propagation of transient stress waves typically referred to as acoustic emission. To achieve this goal, a ductile fracture problem is investigated computationally using the finite element method based on a compact tension geometry under Mode I loading conditions. To quantify the energy dissipation associated with acoustic emission, a crack increment is produced given a pre-determined notch size in a 3D cohesive-based extended finite element model. The computational modeling methodology consists of defining a damage initiation state from static simulations and linking such state to a dynamic formulation used to evaluate wave propagation and related energy redistribution effects. The model relies on a custom traction separation law constructed using full field deformation measurements obtained experimentally using the digital image correlation method. The amount of energy release due to the investigated first crack increment is evaluated through three different approaches both for verification purposes and to produce an estimate of the portion of the energy that radiates away from the crack source in the form of transient waves. The results presented herein propose an upper bound for the energy dissipation associated to acoustic emission, which could assist the interpretation and implementation of relevant nondestructive evaluation methods and the further enrichment of the understanding of effects associated with fracture.

ANALYTICAL REVIEW OF THE METHODOLOGY OF COMPUTER MODELING

The application of computer modeling gives additional incentives of devel???opment to the branches of science, helps to limit intuitive speculative modeling and expands the appendix of rational methods of information technologies. The review of methodology of computer modeling has been offered, the basic concepts of computer modeling have been given, the methodology of algorithms of stage-by-stage and step-by-step modeling has been also given.

B'More Healthy Communities for Kids: design of a multi-level intervention for obesity prevention for low-income African American children.

BackgroundChildhood obesity rates in the U.S. have reached epidemic proportions, and an urgent need remains to identify evidence-based strategies for prevention and treatment. Multi-level, multi-component interventions are needed due to the multi-factorial nature of obesity, and its proven links to both the social and built environment. However, there are huge gaps in the literature related to doing these kinds of interventions among low-income, urban, minority groups.MethodsThe B’More Healthy Communities for Kids (BHCK) intervention is a multi-level, multi-component intervention, targeting low-income African American youth ages 10–14 and their families in Baltimore, Maryland. This intervention prevents childhood obesity by working at multiple levels of the food and social environments to increase access to, demand for, and consumption of healthier foods. BHCK works to create systems-level change by partnering with city policy-makers, multiple levels of the food environment (wholesalers, corner stores, carryout restaurants), and the social environment (peers and families). In addition, extensive evaluation will be conducted at each level of the intervention to assess intervention effectiveness via both process and impact measures.DiscussionThis project is novel in multiple ways, including: the inclusion of stakeholders at multiple levels (policy, institutional, and at multiple levels of the food system); that it uses novel computational modeling methodologies to engage policy makers and guide informed decisions of intervention effectiveness; it emphasizes both the built environment (intervening with food sources) and the social environment (intervening with families and peers). The design of the intervention and the evaluation plan of the BHCK project are documented here.Trial registrationNCT02181010 (July 2, 2014).

Nanoscale wetting and fouling resistance of functionalized surfaces: a computational approach.

A computational modeling methodology has been developed and employed to characterize the nanoscale wettability and antifouling properties of functionalized hard and deformable surfaces, with a specific focus on poly(ethylene glycol) grafted substrates and their resistance to graphitic carbons. Empirical evidence suggests that the antifouling behavior of polyethylene PEG is associated with two main mechanisms: steric repulsions and hydration via formation of a structured water layer. However, there is also little attention paid to the contribution of steric repulsion vs surface hydration. We examine these two mechanisms through a combination of in silico contact angle and force measurements at the nanoscale level. We investigate the properties of the grafted functional chains and the underlying substrate, responsible for resisting surface deposition of graphitic contaminants in aqueous solution. Our results reveal that the fouling-release efficiency is enhanced when PEG chains are grafted onto hard hydrophilic substrates such as silica in contrast to deformable polymer substrates where surface modifications are effectively mitigated during interfacial contact with a hard contaminant. We conclude that the contribution of steric repulsion vs surface hydration to the antifouling ability of surfaces is strongly dependent on the nanoscale structure and deformability of the substrate. This generic method can be applied to examine individual contribution of steric repulsions and surface hydration to antifouling performance of grafted chains.

Book Review: Consciousness and Robot Sentience by Pentti Olavi Antero Haikonen

Given the recent heated debates and controversies regarding machine consciousness, it would seem that writing a book on robot consciousness is a daring act. Expressing almost any view on this controversial, many might say intractable, topic opens the author to a range of criticisms. Addressing machine consciousness seems to present an unpalatable choice. One can take a \high road, and address the ontological status of consciousness, present arguments for or against various types of consciousness, and whether or not one or the other can be su±ciently operationalized to enable an implementation. These treatments often illustrate their perspective with a limited implemented model, and thereby open themselves to criticisms of insu±cient detail, overly-aggregated and unexplainable constructs, and limited or no implementation. Alternatively, one can take a \low road, focus on a single aspect of consciousness, and provide a (necessarily) limited implementation, and invite criticism of too narrow a focus, non-generalizable implementation, and a lack of validation. It is not easy to win in the game of machine consciousness. (Could this, perhaps, indicate that it may be the wrong game to play at this time, with the available neuroscience data and computational modeling methodologies?) Haikonen's book strikes a reasonable middle ground between these two extremes, and positions itself closer to the second of the two alternatives above: the more fruitful of the two, in my opinion. In the rst half of the book, Haikonen adopts a strong stance regarding the nature of, or at least an essential precondition for, consciousness: \qualia based perception [ ] the presence of the phenomenal subjective experience; and internal appearance of the perception-related neural (p. 53) and associated connection to sub-symbolic processing. In fact, he goes much further than this, and claims that: \the one and only real mystery of consciousness is the existence of the inner appearance of the neural activity in the brain (p. 225). He then elaborates this view by discussing the nature of, and evidence for, a variety of qualia, including amodal qualia, in biological agents, and describes the machine International Journal of Machine Consciousness Vol. 6, No. 1 (2014) 29–39 #.c World Scienti c Publishing Company DOI: 10.1142/S1793843014400058

The Cognitive Benefit of Dynamic Representations on Procedural Skill Acquisition: A Computational Modeling Approach

Cognitive computational modeling is a viable methodology for further investigation of the hitherto inconclusive findings on the cognitive benefits of dynamic versus static visualization components of instructions. This is more so as contemporary cognitive architectures such as the Adaptive Control of Thought–Rational (ACT–R) 6.0 are increasingly applied to traditional cognitive psychology research problems. The application of this methodology is, however, restricted by the limited capability of existing architectures for implementing detailed atomic motor actions such as those involved in complex skill acquisition and performance. This article presents a 2-component computational modeling methodology for investigating the cognitive processes involved in the acquisition and performance of skilled motor tasks. The approach specifies a novel combination of a sequence-of-point technique with a movement control mechanism to implement variously acquired cognitive mental task representations and their intertwined role in postlearning performance as evident in the atomic control of motor actions. This paradigm is validated for 2 experiments using incrementally developed cognitive models developed in ACT–R 6.0. The model's quantitative outputs correlate significantly with equivalent empirical human data. This has implications for multimedia instructional design, especially where rapid, transferrable skill acquisition is desired on initial exposure.

Temperature Measurement and Finite Element Modeling Methodology for Laser Cutting of Stainless Steel Plate

The article is focused to the temperature measurement and methodology of computer modeling of laser cutting process on stainless steel plate. Microstructure of stainless steel and dimension of the kerf width was obtained. The temperature was measured with two K-type thermocouples by digital convertor NIUSB9211. Obtained temperature dependences were used for simulation 2D and 3D models creation by ANSYS software. The results of the model application with SHELL and SOLID elements are shown. Numerical simulation showed effect of nitrogen gas on heat dissipation and is also one of the reason why isn't total energy received in the material. Author considered 3D model with impinging jet flow whose proposal is in the article as the model closest to reality.

Modeling the generation and propagation of hydrodynamic hull noise near the ocean surface

Hydrodynamic hull noise is an important consideration for determining the detection envelope of SONAR domes mounted to surface vessels. In order to model the generation of this noise by a moving ship, a hybrid computational hydro-acoustic modeling methodology has been developed by combining the Lighthill-Curle acoustic analogy with the Numerical Wind Tunnel computational fluid dynamics code. This model has been shown in previous work to significantly over-predict the experimentally observed far field sound of Canadian Forces Auxiliary Vehicle Quest in at-sea acoustic trials. This deficiency is shown to be due in part to neglecting the Lloyd’s Mirror interference effect of the sea surface in the Lighthill-Curle equations. By utilizing a method of images solution to the acoustic analogy to simulate the Lloyd’s Mirror interference, an average sound pressure level improvement of 25 dB was obtained. This solution is compared and contrasted to a model utilizing the Lloyd’s Mirror interference of a simple source, and a normal mode sound propagation model, and is shown to be superior for transmission ranges up to 2 km.

Modeling the short time-scale dynamics of β-amyloid–neuron interactions

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the formation of senile plaques and neurofibrillary tangles. The primary protein components of these two histopathological features, β-amyloid peptide (Aβ) and tau, respectively, have been implicated in neuronal death. Despite extensive research into the disease etiology, its underlying molecular processes remain unknown. Researchers hypothesize that Aβ interacts with the cell surface preceding neuronal dysfunction and cell death; however, there is no consensus about the functional role of Aβ at the cell surface. Utilizing a mathematical model of a neuron, we compared simulation results under voltage-clamp, current-clamp and high [K+] membrane depolarized conditions of two hypothesized mechanisms of Aβ–neuron interactions: the Aβ blocking of fast-inactivating K+ (IA) channels and the Aβ-induced increase in membrane conductance. Our model predicts that both mechanisms may lead to changes in ion conductances, cell excitability and Ca2+ influx under voltage- and current-clamp conditions. Interestingly, membrane depolarization simulations predict very different correlations in Ca2+ influx between the two mechanisms and may provide data that distinguishes the mechanisms. Our results suggest that our computational modeling methodology may enhance experimental design such that mechanisms of Aβ-induced action on a neuron can be discriminated.

BEM Numerical Modeling and Experimental Verification of Cathodic Protection for Offshore Structures

The progresses and theoretical methodology of computer modeling of cathodic protection using the boundary element method (BEM) are outlined. To test the effectiveness and accuracy of BEM numerical modeling of cathodic protection for offshore structures, a miniature model offshore jacket with a sacrificial anode was built and put in a test pool full of seawater. Cathodic protection potentials on different positions were measured and compared with the values obtained from computer modeling. The results show good agreement between measured value and numerical simulated value. The factors that led to discrepancy in the two groups of data were discussed.

Elucidating glycosaminoglycan–protein–protein interactions using carbohydrate microarray and computational approaches

Glycosaminoglycan polysaccharides play critical roles in many cellular processes, ranging from viral invasion and angiogenesis to spinal cord injury. Their diverse biological activities are derived from an ability to regulate a remarkable number of proteins. However, few methods exist for the rapid identification of glycosaminoglycan-protein interactions and for studying the potential of glycosaminoglycans to assemble multimeric protein complexes. Here, we report a multidisciplinary approach that combines new carbohydrate microarray and computational modeling methodologies to elucidate glycosaminoglycan-protein interactions. The approach was validated through the study of known protein partners for heparan and chondroitin sulfate, including fibroblast growth factor 2 (FGF2) and its receptor FGFR1, the malarial protein VAR2CSA, and tumor necrosis factor-α (TNF-α). We also applied the approach to identify previously undescribed interactions between a specific sulfated epitope on chondroitin sulfate, CS-E, and the neurotrophins, a critical family of growth factors involved in the development, maintenance, and survival of the vertebrate nervous system. Our studies show for the first time that CS is capable of assembling multimeric signaling complexes and modulating neurotrophin signaling pathways. In addition, we identify a contiguous CS-E-binding site by computational modeling that suggests a potential mechanism to explain how CS may promote neurotrophin-tyrosine receptor kinase (Trk) complex formation and neurotrophin signaling. Together, our combined microarray and computational modeling methodologies provide a general, facile means to identify new glycosaminoglycan-protein-protein interactions, as well as a molecular-level understanding of those complexes.

Best Practices for QSAR Model Development, Validation, and Exploitation.

After nearly five decades "in the making", QSAR modeling has established itself as one of the major computational molecular modeling methodologies. As any mature research discipline, QSAR modeling can be characterized by a collection of well defined protocols and procedures that enable the expert application of the method for exploring and exploiting ever growing collections of biologically active chemical compounds. This review examines most critical QSAR modeling routines that we regard as best practices in the field. We discuss these procedures in the context of integrative predictive QSAR modeling workflow that is focused on achieving models of the highest statistical rigor and external predictive power. Specific elements of the workflow consist of data preparation including chemical structure (and when possible, associated biological data) curation, outlier detection, dataset balancing, and model validation. We especially emphasize procedures used to validate models, both internally and externally, as well as the need to define model applicability domains that should be used when models are employed for the prediction of external compounds or compound libraries. Finally, we present several examples of successful applications of QSAR models for virtual screening to identify experimentally confirmed hits.

Dendritic vulnerability in neurodegenerative disease: insights from analyses of cortical pyramidal neurons in transgenic mouse models

In neurodegenerative disorders, such as Alzheimer's disease, neuronal dendrites and dendritic spines undergo significant pathological changes. Because of the determinant role of these highly dynamic structures in signaling by individual neurons and ultimately in the functionality of neuronal networks that mediate cognitive functions, a detailed understanding of these changes is of paramount importance. Mutant murine models, such as the Tg2576 APP mutant mouse and the rTg4510 tau mutant mouse have been developed to provide insight into pathogenesis involving the abnormal production and aggregation of amyloid and tau proteins, because of the key role that these proteins play in neurodegenerative disease. This review showcases the multidimensional approach taken by our collaborative group to increase understanding of pathological mechanisms in neurodegenerative disease using these mouse models. This approach includes analyses of empirical 3D morphological and electrophysiological data acquired from frontal cortical pyramidal neurons using confocal laser scanning microscopy and whole-cell patch-clamp recording techniques, combined with computational modeling methodologies. These collaborative studies are designed to shed insight on the repercussions of dystrophic changes in neocortical neurons, define the cellular phenotype of differential neuronal vulnerability in relevant models of neurodegenerative disease, and provide a basis upon which to develop meaningful therapeutic strategies aimed at preventing, reversing, or compensating for neurodegenerative changes in dementia.

Simulation of planar flexible multibody systems with clearance and lubricated revolute joints

Modeling of clearance joints plays an important role in the analysis and design of multibody mechanical systems. Based on the absolute nodal coordinate formulation (ANCF), a new computational methodology for modeling and analysis of planar flexible multibody systems with clearance and lubricated revolute joints is presented. A planar absolute nodal coordinate formulation based on the locking-free shear deformable beam element is implemented to discretize the flexible bodies. A continuous contact-impact model is used to evaluate the contact force, in which energy dissipation in the form of hysteresis damping is considered. A force transition model from hydrodynamic lubrication forces to dry contact forces is introduced to ensure continuity in the joint reaction force. A comprehensive study with different lubrication force models has also been carried out. The generalized-α method is used to solve the equations of motion and several efficient methods are incorporated in the proposed model. Finally, the methodology is validated by two numerical examples.

New Computational and Mathematical Methods for Archaeological Fieldwork at the Extreme South of the Populated World

We present the methodology of computer modeling of an archaeological excavation. The method allows the study of archaeological formation, modification and transformation processes. Our main goal has been to build a computer model of middensite formation processes. The main purpose of these models is converting excavation data to visual elements (lines, surfaces, and solids) which can be used as a representation of that data. Furthermore, geostatistics and other quantitative spatial analysis methods are also discussed to characterize the processes having generated the spatial distribution of archaeological data.

A non-conforming computational methodology for modeling coupled problems

A variety of engineering applications that involve coupling different physical phenomena, often require detailed finite element analysis to be carried out over complex domains. Often such analysis may be accomplished by dividing the global domain into several local subdomains over each of which a local model can be analyzed independently. The global solution can then be constructed by suitably piecing together local solutions from these individually modeled subdomains. However, during the assembly, it is often too cumbersome, or even infeasible, to coordinate the meshes over separate subdomains. One must therefore, employ non-conforming techniques to accomplish such modeling. In this paper, we develop a non-conforming computational methodology via the mortar finite element method to solve a coupled problem where we are interested in determining the effects of temperature variations on a given flow or the transfer of heat within the flow. Using this method the solution over different subdomains with different multigrid levels is efficiently computed. Our numerical results clearly suggest that the proposed methodology is robust and stable.

Large-scale simulation of polymer electrolyte fuel cells by parallel computing

A three-dimensional, electrochemical–transport fully coupled numerical model of polymer electrolyte fuel cells (PEFC) is introduced. A complete set of conservation equations of mass, momentum, species, and charge are numerically solved with proper account of electrochemical kinetics and water management. Such a multi-physics model combined with the need for a large numerical mesh results in very intense computations that require parallel computing in order to reduce simulation time. In this study, we explore a massively parallel computational methodology for PEFC modeling, for the first time. The physical model is validated against experimental data under both fully and low-humidified feed conditions. Detailed results of hydrogen, oxygen, water, and current distributions in a PEFC of 5-channel serpentine flow-field are discussed. Under the fully humidified condition, current distribution is determined by the oxygen concentration distribution. Cell performance decreases in low-humidity inlet conditions, but good cell performance can still be achieved with proper water management. Under low-humidity conditions, current distribution is dominated by the water distribution at high cell voltages. When the cell voltage is low, the local current density initially increases along the flow path as the water concentration rises, but then starts to decrease due to oxygen consumption. Under both fully and low-humidified conditions, numerical results reveal that the ohmic losses due to proton transport in anode and cathode catalyst layers are comparable to that in the membrane, indicating that the catalyst layers cannot be neglected in PEFC modeling.