Building dynamic population graph for accurate correspondence detection.

PubMed

Du, Shaoyi; Guo, Yanrong; Sanroma, Gerard; Ni, Dong; Wu, Guorong; Shen, Dinggang

2015-12-01

In medical imaging studies, there is an increasing trend for discovering the intrinsic anatomical difference across individual subjects in a dataset, such as hand images for skeletal bone age estimation. Pair-wise matching is often used to detect correspondences between each individual subject and a pre-selected model image with manually-placed landmarks. However, the large anatomical variability across individual subjects can easily compromise such pair-wise matching step. In this paper, we present a new framework to simultaneously detect correspondences among a population of individual subjects, by propagating all manually-placed landmarks from a small set of model images through a dynamically constructed image graph. Specifically, we first establish graph links between models and individual subjects according to pair-wise shape similarity (called as forward step). Next, we detect correspondences for the individual subjects with direct links to any of model images, which is achieved by a new multi-model correspondence detection approach based on our recently-published sparse point matching method. To correct those inaccurate correspondences, we further apply an error detection mechanism to automatically detect wrong correspondences and then update the image graph accordingly (called as backward step). After that, all subject images with detected correspondences are included into the set of model images, and the above two steps of graph expansion and error correction are repeated until accurate correspondences for all subject images are established. Evaluations on real hand X-ray images demonstrate that our proposed method using a dynamic graph construction approach can achieve much higher accuracy and robustness, when compared with the state-of-the-art pair-wise correspondence detection methods as well as a similar method but using static population graph. Copyright © 2015 Elsevier B.V. All rights reserved.

Dynamic access control model for privacy preserving personalized healthcare in cloud environment.

PubMed

Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

2015-01-01

When sharing and storing healthcare data in a cloud environment, access control is a central issue for preserving data privacy as a patient's personal health data may be accessed without permission from many stakeholders. Specifically, dynamic authorization for the access of data is required because personal health data is stored in cloud storage via wearable devices. Therefore, we propose a dynamic access control model for preserving the privacy of personal healthcare data in a cloud environment. The proposed model considers context information for dynamic access. According to the proposed model, access control can be dynamically determined by changing the context information; this means that even for a subject with the same role in the cloud, access permission is defined differently depending on the context information and access condition. Furthermore, we experiment the ability of the proposed model to provide correct responses by representing a dynamic access decision with real-life personalized healthcare system scenarios.

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

PubMed

Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

2011-09-01

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.

PubMed

Benoussaad, Mourad; Poignet, Philippe; Hayashibe, Mitsuhiro; Azevedo-Coste, Christine; Fattal, Charles; Guiraud, David

2013-06-01

We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject. The identification protocol included initial identification steps, which are adaptations of existing identification techniques to estimate most of the parameters of our model. Then we applied an original and safer identification protocol in dynamic conditions, which required resolution of a nonlinear programming (NLP) problem to identify the serial element stiffness of quadriceps. Each identification step and cross validation of the estimated model in dynamic condition were evaluated through a quadratic error criterion. The results highlighted good accuracy, the efficiency of the identification protocol and the ability of the estimated model to predict the subject-specific behavior of the musculoskeletal system. From the comparison of parameter values between subjects, we discussed and explored the inter-subject variability of parameters in order to select parameters that have to be identified in each patient.

Neuromusculoskeletal model self-calibration for on-line sequential bayesian moment estimation

NASA Astrophysics Data System (ADS)

Bueno, Diana R.; Montano, L.

2017-04-01

Objective. Neuromusculoskeletal models involve many subject-specific physiological parameters that need to be adjusted to adequately represent muscle properties. Traditionally, neuromusculoskeletal models have been calibrated with a forward-inverse dynamic optimization which is time-consuming and unfeasible for rehabilitation therapy. Non self-calibration algorithms have been applied to these models. To the best of our knowledge, the algorithm proposed in this work is the first on-line calibration algorithm for muscle models that allows a generic model to be adjusted to different subjects in a few steps. Approach. In this paper we propose a reformulation of the traditional muscle models that is able to sequentially estimate the kinetics (net joint moments), and also its full self-calibration (subject-specific internal parameters of the muscle from a set of arbitrary uncalibrated data), based on the unscented Kalman filter. The nonlinearity of the model as well as its calibration problem have obliged us to adopt the sum of Gaussians filter suitable for nonlinear systems. Main results. This sequential Bayesian self-calibration algorithm achieves a complete muscle model calibration using as input only a dataset of uncalibrated sEMG and kinematics data. The approach is validated experimentally using data from the upper limbs of 21 subjects. Significance. The results show the feasibility of neuromusculoskeletal model self-calibration. This study will contribute to a better understanding of the generalization of muscle models for subject-specific rehabilitation therapies. Moreover, this work is very promising for rehabilitation devices such as electromyography-driven exoskeletons or prostheses.

A Pilot Study of Individual Muscle Force Prediction during Elbow Flexion and Extension in the Neurorehabilitation Field

PubMed Central

Hou, Jiateng; Sun, Yingfei; Sun, Lixin; Pan, Bingyu; Huang, Zhipei; Wu, Jiankang; Zhang, Zhiqiang

2016-01-01

This paper proposes a neuromusculoskeletal (NMS) model to predict individual muscle force during elbow flexion and extension. Four male subjects were asked to do voluntary elbow flexion and extension. An inertial sensor and surface electromyography (sEMG) sensors were attached to subject's forearm. Joint angle calculated by fusion of acceleration and angular rate using an extended Kalman filter (EKF) and muscle activations obtained from the sEMG signals were taken as the inputs of the proposed NMS model to determine individual muscle force. The result shows that our NMS model can predict individual muscle force accurately, with the ability to reflect subject-specific joint dynamics and neural control solutions. Our method incorporates sEMG and motion data, making it possible to get a deeper understanding of neurological, physiological, and anatomical characteristics of human dynamic movement. We demonstrate the potential of the proposed NMS model for evaluating the function of upper limb movements in the field of neurorehabilitation. PMID:27916853

Causal tapestries for psychology and physics.

PubMed

Sulis, William H

2012-04-01

Archetypal dynamics is a formal approach to the modeling of information flow in complex systems used to study emergence. It is grounded in the Fundamental Triad of realisation (system), interpretation (archetype) and representation (formal model). Tapestries play a fundamental role in the framework of archetypal dynamics as a formal representational system. They represent information flow by means of multi layered, recursive, interlinked graphical structures that express both geometry (form or sign) and logic (semantics). This paper presents a detailed mathematical description of a specific tapestry model, the causal tapestry, selected for use in describing behaving systems such as appear in psychology and physics from the standpoint of Process Theory. Causal tapestries express an explicit Lorentz invariant transient now generated by means of a reality game. Observables are represented by tapestry informons while subjective or hidden components (for example intellectual and emotional processes) are incorporated into the reality game that determines the tapestry dynamics. As a specific example, we formulate a random graphical dynamical system using causal tapestries.

Universality of human microbial dynamics

NASA Astrophysics Data System (ADS)

Bashan, Amir; Gibson, Travis E.; Friedman, Jonathan; Carey, Vincent J.; Weiss, Scott T.; Hohmann, Elizabeth L.; Liu, Yang-Yu

2016-06-01

Human-associated microbial communities have a crucial role in determining our health and well-being, and this has led to the continuing development of microbiome-based therapies such as faecal microbiota transplantation. These microbial communities are very complex, dynamic and highly personalized ecosystems, exhibiting a high degree of inter-individual variability in both species assemblages and abundance profiles. It is not known whether the underlying ecological dynamics of these communities, which can be parameterized by growth rates, and intra- and inter-species interactions in population dynamics models, are largely host-independent (that is, universal) or host-specific. If the inter-individual variability reflects host-specific dynamics due to differences in host lifestyle, physiology or genetics, then generic microbiome manipulations may have unintended consequences, rendering them ineffective or even detrimental. Alternatively, microbial ecosystems of different subjects may exhibit universal dynamics, with the inter-individual variability mainly originating from differences in the sets of colonizing species. Here we develop a new computational method to characterize human microbial dynamics. By applying this method to cross-sectional data from two large-scale metagenomic studies—the Human Microbiome Project and the Student Microbiome Project—we show that gut and mouth microbiomes display pronounced universal dynamics, whereas communities associated with certain skin sites are probably shaped by differences in the host environment. Notably, the universality of gut microbial dynamics is not observed in subjects with recurrent Clostridium difficile infection but is observed in the same set of subjects after faecal microbiota transplantation. These results fundamentally improve our understanding of the processes that shape human microbial ecosystems, and pave the way to designing general microbiome-based therapies.

Muscle Synergies May Improve Optimization Prediction of Knee Contact Forces During Walking

PubMed Central

Walter, Jonathan P.; Kinney, Allison L.; Banks, Scott A.; D'Lima, Darryl D.; Besier, Thor F.; Lloyd, David G.; Fregly, Benjamin J.

2014-01-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values. PMID:24402438

Muscle synergies may improve optimization prediction of knee contact forces during walking.

PubMed

Walter, Jonathan P; Kinney, Allison L; Banks, Scott A; D'Lima, Darryl D; Besier, Thor F; Lloyd, David G; Fregly, Benjamin J

2014-02-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values.

IMMEDIATE EFFECTS OF A DYNAMIC ROTATION-SPECIFIC WARM-UP ON X-FACTOR AND X-FACTOR STRETCH IN THE AMATEUR GOLFER.

PubMed

Henry, Elizabeth; Berglund, Kathy; Millar, Lynn; Locke, Frederick

2015-12-01

Recent evidence suggests performing a warm-up prior to golf can improve performance and reduce injuries. While some characteristics of effective golf warm-ups have been determined, no studies have explored the immediate effects of a rotational-specific warm-up with elements of motor control on the biomechanical aspects of the full X-Factor and X-Factor Stretch during the golf swing. Thirty-six amateur golfers (mean ± SD age: 64 ± 8 years old; 75% male) were randomized into a Dynamic Rotation-Specific Warm-up group (n=20), or a Sham Warm-up group (n=16). X-Factor and X-Factor Stretch were measured at baseline and immediately following the warm-up. Mixed model ANCOVAs were used to determine if a Group*Time interaction existed for each variable with group as the between-subjects variable and time as the within-subjects variable. The mixed model ANCOVAs did not reveal a statistically significant group*time interaction for X-Factor or X-Factor Stretch. There was not a significant main effect for time for X-Factor but there was for X-Factor Stretch. These results indicate that neither group had a significant effect on improving X-Factor, however performing either warm-up increased X-Factor Stretch without significant difference between the two. The results of this study suggest that performing the Dynamic Rotation-Specific Warm-up did not increase X-Factor or X-Factor Stretch when controlled for age compared to the Sham Warm-up. Further study is needed to determine the long-term effects of the Dynamic Rotation-Specific Warm-up on performance factors of the golf swing while examining across all ages. 2b.

Qualitative analysis of a discrete thermostatted kinetic framework modeling complex adaptive systems

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Mogno, Caterina

2018-01-01

This paper deals with the derivation of a new discrete thermostatted kinetic framework for the modeling of complex adaptive systems subjected to external force fields (nonequilibrium system). Specifically, in order to model nonequilibrium stationary states of the system, the external force field is coupled to a dissipative term (thermostat). The well-posedness of the related Cauchy problem is investigated thus allowing the new discrete thermostatted framework to be suitable for the derivation of specific models and the related computational analysis. Applications to crowd dynamics and future research directions are also discussed within the paper.

A Robot-Driven Computational Model for Estimating Passive Ankle Torque With Subject-Specific Adaptation.

PubMed

Zhang, Mingming; Meng, Wei; Davies, T Claire; Zhang, Yanxin; Xie, Sheng Q

2016-04-01

Robot-assisted ankle assessment could potentially be conducted using sensor-based and model-based methods. Existing ankle rehabilitation robots usually use torquemeters and multiaxis load cells for measuring joint dynamics. These measurements are accurate, but the contribution as a result of muscles and ligaments is not taken into account. Some computational ankle models have been developed to evaluate ligament strain and joint torque. These models do not include muscles and, thus, are not suitable for an overall ankle assessment in robot-assisted therapy. This study proposed a computational ankle model for use in robot-assisted therapy with three rotational degrees of freedom, 12 muscles, and seven ligaments. This model is driven by robotics, uses three independent position variables as inputs, and outputs an overall ankle assessment. Subject-specific adaptations by geometric and strength scaling were also made to allow for a universal model. This model was evaluated using published results and experimental data from 11 participants. Results show a high accuracy in the evaluation of ligament neutral length and passive joint torque. The subject-specific adaptation performance is high, with each normalized root-mean-square deviation value less than 10%. This model could be used for ankle assessment, especially in evaluating passive ankle torque, for a specific individual. The characteristic that is unique to this model is the use of three independent position variables that can be measured in real time as inputs, which makes it advantageous over other models when combined with robot-assisted therapy.

Gender-specific automatic valence recognition of affective olfactory stimulation through the analysis of the electrodermal activity.

PubMed

Greco, Alberto; Lanata, Antonio; Valenza, Gaetano; Di Francesco, Fabio; Scilingo, Enzo Pasquale

2016-08-01

This study reports on the development of a gender-specific classification system able to discern between two valence levels of smell, through information gathered from electrodermal activity (EDA) dynamics. Specifically, two odorants were administered to 32 healthy volunteers (16 males) while monitoring EDA. CvxEDA model was used to process the EDA signal and extract features from both tonic and phasic components. The feature set was used as input to a K-NN classifier implementing a leave-one-subject-out procedure. Results show strong differences in the accuracy of valence recognition between men (62.5%) and women (78%). We can conclude that affective olfactory stimulation significantly affect EDA dynamics with a highly specific gender dependency.

Nonequilibrium Green's functions and atom-surface dynamics: Simple views from a simple model system

NASA Astrophysics Data System (ADS)

Boström, E.; Hopjan, M.; Kartsev, A.; Verdozzi, C.; Almbladh, C.-O.

2016-03-01

We employ Non-equilibrium Green's functions (NEGF) to describe the real-time dynamics of an adsorbate-surface model system exposed to ultrafast laser pulses. For a finite number of electronic orbitals, the system is solved exactly and within different levels of approximation. Specifically i) the full exact quantum mechanical solution for electron and nuclear degrees of freedom is used to benchmark ii) the Ehrenfest approximation (EA) for the nuclei, with the electron dynamics still treated exactly. Then, using the EA, electronic correlations are treated with NEGF within iii) 2nd Born and with iv) a recently introduced hybrid scheme, which mixes 2nd Born self-energies with non-perturbative, local exchange- correlation potentials of Density Functional Theory (DFT). Finally, the effect of a semi-infinite substrate is considered: we observe that a macroscopic number of de-excitation channels can hinder desorption. While very preliminary in character and based on a simple and rather specific model system, our results clearly illustrate the large potential of NEGF to investigate atomic desorption, and more generally, the non equilibrium dynamics of material surfaces subject to ultrafast laser fields.

Spatial variation of fixed charge density in knee joint cartilage from sodium MRI - Implication on knee joint mechanics under static loading.

PubMed

Räsänen, Lasse P; Tanska, Petri; Mononen, Mika E; Lammentausta, Eveliina; Zbýň, Štefan; Venäläinen, Mikko S; Szomolanyi, Pavol; van Donkelaar, Corrinus C; Jurvelin, Jukka S; Trattnig, Siegfried; Nieminen, Miika T; Korhonen, Rami K

2016-10-03

The effects of fixed charge density (FCD) and cartilage swelling have not been demonstrated on cartilage mechanics on knee joint level before. In this study, we present how the spatial and local variations of FCD affects the mechanical response of the knee joint cartilage during standing (half of the body weight, 13 minutes) using finite element (FE) modeling. The FCD distribution of tibial cartilage of an asymptomatic subject was determined using sodium ( 23 Na) MRI at 7T and implemented into a 3-D FE-model of the knee joint (Subject-specific model, FCD: 0.18±0.08 mEq/ml). Tissue deformation in the Subject-specific model was validated against experimental, in vivo loading of the joint conducted with a MR-compatible compression device. For comparison, models with homogeneous FCD distribution (homogeneous model) and FCD distribution obtained from literature (literature model) were created. Immediately after application of the load (dynamic response), the variations in FCD had minor effects on cartilage stresses and strains. After 13 minutes of standing, the spatial and local variations in FCD had most influence on axial strains. In the superficial tibial cartilage in the Subject-specific model, axial strains were increased up to +13% due to smaller FCD (mean -11%), as compared to the homogeneous model. Compared to the literature model, those were decreased up to -18% due to greater FCD (mean +7%). The findings demonstrate that the spatial and local FCD variations in cartilage modulates strains in knee joint cartilage. Thereby, the results highlight the mechanical importance of site-specific content of proteoglycans in cartilage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of shear wave propagation derived from MR elastography in 3D thigh skeletal muscle using subject specific finite element model.

PubMed

Dao, Tien Tuan; Pouletaut, Philippe; Charleux, Fabrice; Tho, Marie-Christine Ho Ba; Bensamoun, Sabine

2014-01-01

The purpose of this study was to develop a subject specific finite element model derived from MRI images to numerically analyze the MRE (magnetic resonance elastography) shear wave propagation within skeletal thigh muscles. A sagittal T2 CUBE MRI sequence was performed on the 20-cm thigh segment of a healthy male subject. Skin, adipose tissue, femoral bone and 11 muscles were manually segmented in order to have 3D smoothed solid and meshed models. These tissues were modeled with different constitutive laws. A transient modal dynamics analysis was applied to simulate the shear wave propagation within the thigh tissues. The effects of MRE experimental parameters (frequency, force) and the muscle material properties (shear modulus: C10) were analyzed through the simulated shear wave displacement within the vastus medialis muscle. The results showed a plausible range of frequencies (from 90Hz to 120 Hz), which could be used for MRE muscle protocol. The wave amplitude increased with the level of the force, revealing the importance of the boundary condition. Moreover, different shear displacement patterns were obtained as a function of the muscle mechanical properties. The present study is the first to analyze the shear wave propagation in skeletal muscles using a 3D subject specific finite element model. This study could be of great value to assist the experimenters in the set-up of MRE protocols.

The case for an internal dynamics model versus equilibrium point control in human movement.

PubMed

Hinder, Mark R; Milner, Theodore E

2003-06-15

The equilibrium point hypothesis (EPH) was conceived as a means whereby the central nervous system could control limb movements by a relatively simple shift in equilibrium position without the need to explicitly compensate for task dynamics. Many recent studies have questioned this view with results that suggest the formation of an internal dynamics model of the specific task. However, supporters of the EPH have argued that these results are not incompatible with the EPH and that there is no reason to abandon it. In this study, we have tested one of the fundamental predictions of the EPH, namely, equifinality. Subjects learned to perform goal-directed wrist flexion movements while a motor provided assistance in proportion to the instantaneous velocity. It was found that the subjects stopped short of the target on the trials where the magnitude of the assistance was randomly decreased, compared to the preceding control trials (P = 0.003), i.e. equifinality was not achieved. This is contrary to the EPH, which predicts that final position should not be affected by external loads that depend purely on velocity. However, such effects are entirely consistent with predictions based on the formation of an internal dynamics model.

Computational knee ligament modeling using experimentally determined zero-load lengths.

PubMed

Bloemker, Katherine H; Guess, Trent M; Maletsky, Lorin; Dodd, Kevin

2012-01-01

This study presents a subject-specific method of determining the zero-load lengths of the cruciate and collateral ligaments in computational knee modeling. Three cadaver knees were tested in a dynamic knee simulator. The cadaver knees also underwent manual envelope of motion testing to find their passive range of motion in order to determine the zero-load lengths for each ligament bundle. Computational multibody knee models were created for each knee and model kinematics were compared to experimental kinematics for a simulated walk cycle. One-dimensional non-linear spring damper elements were used to represent cruciate and collateral ligament bundles in the knee models. This study found that knee kinematics were highly sensitive to altering of the zero-load length. The results also suggest optimal methods for defining each of the ligament bundle zero-load lengths, regardless of the subject. These results verify the importance of the zero-load length when modeling the knee joint and verify that manual envelope of motion measurements can be used to determine the passive range of motion of the knee joint. It is also believed that the method described here for determining zero-load length can be used for in vitro or in vivo subject-specific computational models.

Intra-Articular Knee Contact Force Estimation During Walking Using Force-Reaction Elements and Subject-Specific Joint Model.

PubMed

Jung, Yihwan; Phan, Cong-Bo; Koo, Seungbum

2016-02-01

Joint contact forces measured with instrumented knee implants have not only revealed general patterns of joint loading but also showed individual variations that could be due to differences in anatomy and joint kinematics. Musculoskeletal human models for dynamic simulation have been utilized to understand body kinetics including joint moments, muscle tension, and knee contact forces. The objectives of this study were to develop a knee contact model which can predict knee contact forces using an inverse dynamics-based optimization solver and to investigate the effect of joint constraints on knee contact force prediction. A knee contact model was developed to include 32 reaction force elements on the surface of a tibial insert of a total knee replacement (TKR), which was embedded in a full-body musculoskeletal model. Various external measurements including motion data and external force data during walking trials of a subject with an instrumented knee implant were provided from the Sixth Grand Challenge Competition to Predict in vivo Knee Loads. Knee contact forces in the medial and lateral portions of the instrumented knee implant were also provided for the same walking trials. A knee contact model with a hinge joint and normal alignment could predict knee contact forces with root mean square errors (RMSEs) of 165 N and 288 N for the medial and lateral portions of the knee, respectively, and coefficients of determination (R2) of 0.70 and -0.63. When the degrees-of-freedom (DOF) of the knee and locations of leg markers were adjusted to account for the valgus lower-limb alignment of the subject, RMSE values improved to 144 N and 179 N, and R2 values improved to 0.77 and 0.37, respectively. The proposed knee contact model with subject-specific joint model could predict in vivo knee contact forces with reasonable accuracy. This model may contribute to the development and improvement of knee arthroplasty.

Environmental noise spectroscopy with qubits subjected to dynamical decoupling

NASA Astrophysics Data System (ADS)

Szańkowski, P.; Ramon, G.; Krzywda, J.; Kwiatkowski, D.; Cywiński, Ł.

2017-08-01

A qubit subjected to pure dephasing due to classical Gaussian noise can be turned into a spectrometer of this noise by utilizing its readout under properly chosen dynamical decoupling (DD) sequences to reconstruct the power spectral density of the noise. We review the theory behind this DD-based noise spectroscopy technique, paying special attention to issues that arise when the environmental noise is non-Gaussian and/or it has truly quantum properties. While we focus on the theoretical basis of the method, we connect the discussed concepts with specific experiments, and provide an overview of environmental noise models relevant for solid-state based qubits, including quantum-dot based spin qubits, superconducting qubits, and NV centers in diamond.

Dynamic magnetic hysteresis and nonlinear susceptibility of antiferromagnetic nanoparticles

NASA Astrophysics Data System (ADS)

Kalmykov, Yuri P.; Ouari, Bachir; Titov, Serguey V.

2016-08-01

The nonlinear ac stationary response of antiferromagnetic nanoparticles subjected to both external ac and dc fields of arbitrary strength and orientation is investigated using Brown's continuous diffusion model. The nonlinear complex susceptibility and dynamic magnetic hysteresis (DMH) loops of an individual antiferromagnetic nanoparticle are evaluated and compared with the linear regime for extensive ranges of the anisotropy, the ac and dc magnetic fields, damping, and the specific antiferromagnetic parameter. It is shown that the shape and area of the DMH loops of antiferromagnetic particles are substantially altered by applying a dc field that permits tuning of the specific magnetic power loss in the nanoparticles.

Modal Damping Ratio and Optimal Elastic Moduli of Human Body Segments for Anthropometric Vibratory Model of Standing Subjects.

PubMed

Gupta, Manoj; Gupta, T C

2017-10-01

The present study aims to accurately estimate inertial, physical, and dynamic parameters of human body vibratory model consistent with physical structure of the human body that also replicates its dynamic response. A 13 degree-of-freedom (DOF) lumped parameter model for standing person subjected to support excitation is established. Model parameters are determined from anthropometric measurements, uniform mass density, elastic modulus of individual body segments, and modal damping ratios. Elastic moduli of ellipsoidal body segments are initially estimated by comparing stiffness of spring elements, calculated from a detailed scheme, and values available in literature for same. These values are further optimized by minimizing difference between theoretically calculated platform-to-head transmissibility ratio (TR) and experimental measurements. Modal damping ratios are estimated from experimental transmissibility response using two dominant peaks in the frequency range of 0-25 Hz. From comparison between dynamic response determined form modal analysis and experimental results, a set of elastic moduli for different segments of human body and a novel scheme to determine modal damping ratios from TR plots, are established. Acceptable match between transmissibility values calculated from the vibratory model and experimental measurements for 50th percentile U.S. male, except at very low frequencies, establishes the human body model developed. Also, reasonable agreement obtained between theoretical response curve and experimental response envelop for average Indian male, affirms the technique used for constructing vibratory model of a standing person. Present work attempts to develop effective technique for constructing subject specific damped vibratory model based on its physical measurements.

A Formal Approach to Empirical Dynamic Model Optimization and Validation

NASA Technical Reports Server (NTRS)

Crespo, Luis G; Morelli, Eugene A.; Kenny, Sean P.; Giesy, Daniel P.

2014-01-01

A framework was developed for the optimization and validation of empirical dynamic models subject to an arbitrary set of validation criteria. The validation requirements imposed upon the model, which may involve several sets of input-output data and arbitrary specifications in time and frequency domains, are used to determine if model predictions are within admissible error limits. The parameters of the empirical model are estimated by finding the parameter realization for which the smallest of the margins of requirement compliance is as large as possible. The uncertainty in the value of this estimate is characterized by studying the set of model parameters yielding predictions that comply with all the requirements. Strategies are presented for bounding this set, studying its dependence on admissible prediction error set by the analyst, and evaluating the sensitivity of the model predictions to parameter variations. This information is instrumental in characterizing uncertainty models used for evaluating the dynamic model at operating conditions differing from those used for its identification and validation. A practical example based on the short period dynamics of the F-16 is used for illustration.

Comparison of four specific dynamic office chairs with a conventional office chair: impact upon muscle activation, physical activity and posture.

PubMed

Ellegast, Rolf P; Kraft, Kathrin; Groenesteijn, Liesbeth; Krause, Frank; Berger, Helmut; Vink, Peter

2012-03-01

Prolonged and static sitting postures provoke physical inactivity at VDU workplaces and are therefore discussed as risk factors for the musculoskeletal system. Manufacturers have designed specific dynamic office chairs featuring structural elements which promote dynamic sitting and therefore physical activity. The aim of the present study was to evaluate the effects of four specific dynamic chairs on erector spinae and trapezius EMG, postures/joint angles and physical activity intensity (PAI) compared to those of a conventional standard office chair. All chairs were fitted with sensors for measurement of the chair parameters (backrest inclination, forward and sideward seat pan inclination), and tested in the laboratory by 10 subjects performing 7 standardized office tasks and by another 12 subjects in the field during their normal office work. Muscle activation revealed no significant differences between the specific dynamic chairs and the reference chair. Analysis of postures/joint angles and PAI revealed only a few differences between the chairs, whereas the tasks performed strongly affected the measured muscle activation, postures and kinematics. The characteristic dynamic elements of each specific chair yielded significant differences in the measured chair parameters, but these characteristics did not appear to affect the sitting dynamics of the subjects performing their office tasks. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Density dependence in group dynamics of a highly social mongoose, Suricata suricatta.

PubMed

Bateman, Andrew W; Ozgul, Arpat; Coulson, Tim; Clutton-Brock, Tim H

2012-05-01

1. For social species, the link between individual behaviour and population dynamics is mediated by group-level demography. 2. Populations of obligate cooperative breeders are structured into social groups, which may be subject to inverse density dependence (Allee effects) that result from a dependence on conspecific helpers, but evidence for population-wide Allee effects is rare. 3. We use field data from a long-term study of cooperative meerkats (Suricata suricatta; Schreber, 1776) - a species for which local Allee effects are not reflected in population-level dynamics - to empirically model interannual group dynamics. 4. Using phenomenological population models, modified to incorporate environmental conditions and potential Allee effects, we first investigate overall patterns of group dynamics and find support only for conventional density dependence that increases after years of low rainfall. 5. To explain the observed patterns, we examine specific demographic rates and assess their contributions to overall group dynamics. Although per-capita meerkat mortality is subject to a component Allee effect, it contributes relatively little to observed variation in group dynamics, and other (conventionally density dependent) demographic rates - especially emigration - govern group dynamics. 6. Our findings highlight the need to consider demographic processes and density dependence in subpopulations before drawing conclusions about how behaviour affects population processes in socially complex systems. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.

Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration.

PubMed

Ehrhardt, Jan; Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz

2011-02-01

Modeling of respiratory motion has become increasingly important in various applications of medical imaging (e.g., radiation therapy of lung cancer). Current modeling approaches are usually confined to intra-patient registration of 3D image data representing the individual patient's anatomy at different breathing phases. We propose an approach to generate a mean motion model of the lung based on thoracic 4D computed tomography (CT) data of different patients to extend the motion modeling capabilities. Our modeling process consists of three steps: an intra-subject registration to generate subject-specific motion models, the generation of an average shape and intensity atlas of the lung as anatomical reference frame, and the registration of the subject-specific motion models to the atlas in order to build a statistical 4D mean motion model (4D-MMM). Furthermore, we present methods to adapt the 4D mean motion model to a patient-specific lung geometry. In all steps, a symmetric diffeomorphic nonlinear intensity-based registration method was employed. The Log-Euclidean framework was used to compute statistics on the diffeomorphic transformations. The presented methods are then used to build a mean motion model of respiratory lung motion using thoracic 4D CT data sets of 17 patients. We evaluate the model by applying it for estimating respiratory motion of ten lung cancer patients. The prediction is evaluated with respect to landmark and tumor motion, and the quantitative analysis results in a mean target registration error (TRE) of 3.3 ±1.6 mm if lung dynamics are not impaired by large lung tumors or other lung disorders (e.g., emphysema). With regard to lung tumor motion, we show that prediction accuracy is independent of tumor size and tumor motion amplitude in the considered data set. However, tumors adhering to non-lung structures degrade local lung dynamics significantly and the model-based prediction accuracy is lower in these cases. The statistical respiratory motion model is capable of providing valuable prior knowledge in many fields of applications. We present two examples of possible applications in radiation therapy and image guided diagnosis.

Are Subject-Specific Musculoskeletal Models Robust to the Uncertainties in Parameter Identification?

PubMed Central

Valente, Giordano; Pitto, Lorenzo; Testi, Debora; Seth, Ajay; Delp, Scott L.; Stagni, Rita; Viceconti, Marco; Taddei, Fulvia

2014-01-01

Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be affected by an uncertainty in the same order of magnitude of its value, although this condition has low probability to occur. PMID:25390896

Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface

PubMed Central

Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Wenzel, Sally E.; Lin, Ching-Long

2016-01-01

We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11% of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches. PMID:27704229

Assessing Peer Leader Skill Acquisition and Group Dynamics in a First-Year Calculus Course

ERIC Educational Resources Information Center

Glover, Rebecca; Hammond, Nicholas B.; Smith, Justin; Guerra, Dalyana

2018-01-01

Peer-led team learning (PLTL), specifically the model known as 'Workshops', has been shown to contribute positively and significantly to student success in STEM courses across subjects (Gosser et al., 2001). Our research adds to the SOTL literature describing the effectiveness of Workshops by reporting on the changes in student leaders. We examine…

A closed-loop multi-level model of glucose homeostasis

PubMed Central

Uluseker, Cansu; Simoni, Giulia; Dauriz, Marco; Matone, Alice

2018-01-01

Background The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes. Methodology/Principal findings The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal in silico subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context. Conclusions/Significance The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism. PMID:29420588

Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.

Risk patterns and correlated brain activities. Multidimensional statistical analysis of FMRI data in economic decision making study.

PubMed

van Bömmel, Alena; Song, Song; Majer, Piotr; Mohr, Peter N C; Heekeren, Hauke R; Härdle, Wolfgang K

2014-07-01

Decision making usually involves uncertainty and risk. Understanding which parts of the human brain are activated during decisions under risk and which neural processes underly (risky) investment decisions are important goals in neuroeconomics. Here, we analyze functional magnetic resonance imaging (fMRI) data on 17 subjects who were exposed to an investment decision task from Mohr, Biele, Krugel, Li, and Heekeren (in NeuroImage 49, 2556-2563, 2010b). We obtain a time series of three-dimensional images of the blood-oxygen-level dependent (BOLD) fMRI signals. We apply a panel version of the dynamic semiparametric factor model (DSFM) presented in Park, Mammen, Wolfgang, and Borak (in Journal of the American Statistical Association 104(485), 284-298, 2009) and identify task-related activations in space and dynamics in time. With the panel DSFM (PDSFM) we can capture the dynamic behavior of the specific brain regions common for all subjects and represent the high-dimensional time-series data in easily interpretable low-dimensional dynamic factors without large loss of variability. Further, we classify the risk attitudes of all subjects based on the estimated low-dimensional time series. Our classification analysis successfully confirms the estimated risk attitudes derived directly from subjects' decision behavior.

In Silico, Experimental, Mechanistic Model for Extended-Release Felodipine Disposition Exhibiting Complex Absorption and a Highly Variable Food Interaction

PubMed Central

Kim, Sean H. J.; Jackson, Andre J.; Hunt, C. Anthony

2014-01-01

The objective of this study was to develop and explore new, in silico experimental methods for deciphering complex, highly variable absorption and food interaction pharmacokinetics observed for a modified-release drug product. Toward that aim, we constructed an executable software analog of study participants to whom product was administered orally. The analog is an object- and agent-oriented, discrete event system, which consists of grid spaces and event mechanisms that map abstractly to different physiological features and processes. Analog mechanisms were made sufficiently complicated to achieve prespecified similarity criteria. An equation-based gastrointestinal transit model with nonlinear mixed effects analysis provided a standard for comparison. Subject-specific parameterizations enabled each executed analog’s plasma profile to mimic features of the corresponding six individual pairs of subject plasma profiles. All achieved prespecified, quantitative similarity criteria, and outperformed the gastrointestinal transit model estimations. We observed important subject-specific interactions within the simulation and mechanistic differences between the two models. We hypothesize that mechanisms, events, and their causes occurring during simulations had counterparts within the food interaction study: they are working, evolvable, concrete theories of dynamic interactions occurring within individual subjects. The approach presented provides new, experimental strategies for unraveling the mechanistic basis of complex pharmacological interactions and observed variability. PMID:25268237

Computational Knee Ligament Modeling Using Experimentally Determined Zero-Load Lengths

PubMed Central

Bloemker, Katherine H; Guess, Trent M; Maletsky, Lorin; Dodd, Kevin

2012-01-01

This study presents a subject-specific method of determining the zero-load lengths of the cruciate and collateral ligaments in computational knee modeling. Three cadaver knees were tested in a dynamic knee simulator. The cadaver knees also underwent manual envelope of motion testing to find their passive range of motion in order to determine the zero-load lengths for each ligament bundle. Computational multibody knee models were created for each knee and model kinematics were compared to experimental kinematics for a simulated walk cycle. One-dimensional non-linear spring damper elements were used to represent cruciate and collateral ligament bundles in the knee models. This study found that knee kinematics were highly sensitive to altering of the zero-load length. The results also suggest optimal methods for defining each of the ligament bundle zero-load lengths, regardless of the subject. These results verify the importance of the zero-load length when modeling the knee joint and verify that manual envelope of motion measurements can be used to determine the passive range of motion of the knee joint. It is also believed that the method described here for determining zero-load length can be used for in vitro or in vivo subject-specific computational models. PMID:22523522

Hydrodynamic and Longitudinal Impedance Analysis of Cerebrospinal Fluid Dynamics at the Craniovertebral Junction in Type I Chiari Malformation

PubMed Central

Martin, Bryn A.; Kalata, Wojciech; Shaffer, Nicholas; Fischer, Paul; Luciano, Mark; Loth, Francis

2013-01-01

Elevated or reduced velocity of cerebrospinal fluid (CSF) at the craniovertebral junction (CVJ) has been associated with type I Chiari malformation (CMI). Thus, quantification of hydrodynamic parameters that describe the CSF dynamics could help assess disease severity and surgical outcome. In this study, we describe the methodology to quantify CSF hydrodynamic parameters near the CVJ and upper cervical spine utilizing subject-specific computational fluid dynamics (CFD) simulations based on in vivo MRI measurements of flow and geometry. Hydrodynamic parameters were computed for a healthy subject and two CMI patients both pre- and post-decompression surgery to determine the differences between cases. For the first time, we present the methods to quantify longitudinal impedance (LI) to CSF motion, a subject-specific hydrodynamic parameter that may have value to help quantify the CSF flow blockage severity in CMI. In addition, the following hydrodynamic parameters were quantified for each case: maximum velocity in systole and diastole, Reynolds and Womersley number, and peak pressure drop during the CSF cardiac flow cycle. The following geometric parameters were quantified: cross-sectional area and hydraulic diameter of the spinal subarachnoid space (SAS). The mean values of the geometric parameters increased post-surgically for the CMI models, but remained smaller than the healthy volunteer. All hydrodynamic parameters, except pressure drop, decreased post-surgically for the CMI patients, but remained greater than in the healthy case. Peak pressure drop alterations were mixed. To our knowledge this study represents the first subject-specific CFD simulation of CMI decompression surgery and quantification of LI in the CSF space. Further study in a larger patient and control group is needed to determine if the presented geometric and/or hydrodynamic parameters are helpful for surgical planning. PMID:24130704

Perception of the dynamic visual vertical during sinusoidal linear motion.

PubMed

Pomante, A; Selen, L P J; Medendorp, W P

2017-10-01

The vestibular system provides information for spatial orientation. However, this information is ambiguous: because the otoliths sense the gravitoinertial force, they cannot distinguish gravitational and inertial components. As a consequence, prolonged linear acceleration of the head can be interpreted as tilt, referred to as the somatogravic effect. Previous modeling work suggests that the brain disambiguates the otolith signal according to the rules of Bayesian inference, combining noisy canal cues with the a priori assumption that prolonged linear accelerations are unlikely. Within this modeling framework the noise of the vestibular signals affects the dynamic characteristics of the tilt percept during linear whole-body motion. To test this prediction, we devised a novel paradigm to psychometrically characterize the dynamic visual vertical-as a proxy for the tilt percept-during passive sinusoidal linear motion along the interaural axis (0.33 Hz motion frequency, 1.75 m/s 2 peak acceleration, 80 cm displacement). While subjects ( n =10) kept fixation on a central body-fixed light, a line was briefly flashed (5 ms) at different phases of the motion, the orientation of which had to be judged relative to gravity. Consistent with the model's prediction, subjects showed a phase-dependent modulation of the dynamic visual vertical, with a subject-specific phase shift with respect to the imposed acceleration signal. The magnitude of this modulation was smaller than predicted, suggesting a contribution of nonvestibular signals to the dynamic visual vertical. Despite their dampening effect, our findings may point to a link between the noise components in the vestibular system and the characteristics of dynamic visual vertical. NEW & NOTEWORTHY A fundamental question in neuroscience is how the brain processes vestibular signals to infer the orientation of the body and objects in space. We show that, under sinusoidal linear motion, systematic error patterns appear in the disambiguation of linear acceleration and spatial orientation. We discuss the dynamics of these illusory percepts in terms of a dynamic Bayesian model that combines uncertainty in the vestibular signals with priors based on the natural statistics of head motion. Copyright © 2017 the American Physiological Society.

Coherent exciton-vibrational dynamics and energy transfer in conjugated organics

DOE PAGES

Nelson, Tammie R.; Ondarse-Alvarez, Dianelys; Oldani, Nicolas; ...

2018-06-13

Coherence, signifying concurrent electron-vibrational dynamics in complex natural and man-made systems, is currently a subject of intense study. Understanding this phenomenon is important when designing carrier transport in optoelectronic materials. Here, excited state dynamics simulations reveal a ubiquitous pattern in the evolution of photoexcitations for a broad range of molecular systems. Symmetries of the wavefunctions define a specific form of the non-adiabatic coupling that drives quantum transitions between excited states, leading to a collective asymmetric vibrational excitation coupled to the electronic system. This promotes periodic oscillatory evolution of the wavefunctions, preserving specific phase and amplitude relations across the ensemble ofmore » trajectories. The simple model proposed here explains the appearance of coherent exciton-vibrational dynamics due to non-adiabatic transitions, which is universal across multiple molecular systems. The observed relationships between electronic wavefunctions and the resulting functionalities allows us to understand, and potentially manipulate, excited state dynamics and energy transfer in molecular materials.« less

Coherent exciton-vibrational dynamics and energy transfer in conjugated organics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, Tammie R.; Ondarse-Alvarez, Dianelys; Oldani, Nicolas

Coherence, signifying concurrent electron-vibrational dynamics in complex natural and man-made systems, is currently a subject of intense study. Understanding this phenomenon is important when designing carrier transport in optoelectronic materials. Here, excited state dynamics simulations reveal a ubiquitous pattern in the evolution of photoexcitations for a broad range of molecular systems. Symmetries of the wavefunctions define a specific form of the non-adiabatic coupling that drives quantum transitions between excited states, leading to a collective asymmetric vibrational excitation coupled to the electronic system. This promotes periodic oscillatory evolution of the wavefunctions, preserving specific phase and amplitude relations across the ensemble ofmore » trajectories. The simple model proposed here explains the appearance of coherent exciton-vibrational dynamics due to non-adiabatic transitions, which is universal across multiple molecular systems. The observed relationships between electronic wavefunctions and the resulting functionalities allows us to understand, and potentially manipulate, excited state dynamics and energy transfer in molecular materials.« less

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

PubMed

Veksler, Vladislav D; Buchler, Norbou; Hoffman, Blaine E; Cassenti, Daniel N; Sample, Char; Sugrim, Shridat

2018-01-01

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.

Computational fluid dynamics endpoints to characterize obstructive sleep apnea syndrome in children

PubMed Central

Luo, Haiyan; Persak, Steven C.; Sin, Sanghun; McDonough, Joseph M.; Isasi, Carmen R.; Arens, Raanan

2013-01-01

Computational fluid dynamics (CFD) analysis may quantify the severity of anatomical airway restriction in obstructive sleep apnea syndrome (OSAS) better than anatomical measurements alone. However, optimal CFD model endpoints to characterize or assess OSAS have not been determined. To model upper airway fluid dynamics using CFD and investigate the strength of correlation between various CFD endpoints, anatomical endpoints, and OSAS severity, in obese children with OSAS and controls. CFD models derived from magnetic resonance images were solved at subject-specific peak tidal inspiratory flow; pressure at the choanae was set by nasal resistance. Model endpoints included airway wall minimum pressure (Pmin), flow resistance in the pharynx (Rpharynx), and pressure drop from choanae to a minimum cross section where tonsils and adenoids constrict the pharynx (dPTAmax). Significance of endpoints was analyzed using paired comparisons (t-test or Wilcoxon signed rank test) and Spearman correlation. Fifteen subject pairs were analyzed. Rpharynx and dPTAmax were higher in OSAS than control and most significantly correlated to obstructive apnea-hypopnea index (oAHI), r = 0.48 and r = 0.49, respectively (P < 0.01). Airway minimum cross-sectional correlation to oAHI was weaker (r = −0.39); Pmin was not significantly correlated. CFD model endpoints based on pressure drops in the pharynx were more closely associated with the presence and severity of OSAS than pressures including nasal resistance, or anatomical endpoints. This study supports the usefulness of CFD to characterize anatomical restriction of the pharynx and as an additional tool to evaluate subjects with OSAS. PMID:24265282

Endophysical Models Based on Empirical Data

NASA Astrophysics Data System (ADS)

Jahn, Robert G.; Dunne, Brenda J.

2005-10-01

Any proposed endophysical models need to acknowledge a number of subjective correlates that have been well established in such objectively quantifiable experimental contexts as anomalous human/machine interactions and remote perception information acquisition. Most notable of these factors are conscious and unconscious intention; gender disparities; serial position effects; intrinsic uncertainties; elusive replicability; and emotional resonance between the participants and the devices, process, and tasks. Perhaps even more pertinent are the insensitivities of the anomalous effects to spatial and temporal separations of the participants from the physical targets. Inclusion of subjective coordinates in the models, and exclusion of physical distance and time, raise formidable issues of specification, quantification, and dynamical formulation from both the physical and psychological perspectives. A few primitive examples of possible approaches are presented.

Molecular modeling of nucleic Acid structure: electrostatics and solvation.

PubMed

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E

2014-12-19

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand its structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as a way of sampling conformational space for a better understanding of the relevance of a given model. This discussion highlighted the major limitations with modeling in general. When sampling conformational space effectively, difficult issues are encountered, such as multiple minima or conformational sampling problems, and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These subjects are discussed in detail in this unit. Copyright © 2014 John Wiley & Sons, Inc.

3D finite element model of the diabetic neuropathic foot: a gait analysis driven approach.

PubMed

Guiotto, Annamaria; Sawacha, Zimi; Guarneri, Gabriella; Avogaro, Angelo; Cobelli, Claudio

2014-09-22

Diabetic foot is an invalidating complication of diabetes that can lead to foot ulcers. Three-dimensional (3D) finite element analysis (FEA) allows characterizing the loads developed in the different anatomical structures of the foot in dynamic conditions. The aim of this study was to develop a subject specific 3D foot FE model (FEM) of a diabetic neuropathic (DNS) and a healthy (HS) subject, whose subject specificity can be found in term of foot geometry and boundary conditions. Kinematics, kinetics and plantar pressure (PP) data were extracted from the gait analysis trials of the two subjects with this purpose. The FEM were developed segmenting bones, cartilage and skin from MRI and drawing a horizontal plate as ground support. Materials properties were adopted from previous literature. FE simulations were run with the kinematics and kinetics data of four different phases of the stance phase of gait (heel strike, loading response, midstance and push off). FEMs were then driven by group gait data of 10 neuropathic and 10 healthy subjects. Model validation focused on agreement between FEM-simulated and experimental PP. The peak values and the total distribution of the pressures were compared for this purpose. Results showed that the models were less robust when driven from group data and underestimated the PP in each foot subarea. In particular in the case of the neuropathic subject's model the mean errors between experimental and simulated data were around the 20% of the peak values. This knowledge is crucial in understanding the aetiology of diabetic foot. Copyright © 2014 Elsevier Ltd. All rights reserved.

Diagnostic accuracy of metronome-paced tachypnea to detect dynamic hyperinflation.

PubMed

Lahaije, Anke J M C; Willems, Laura M; van Hees, Hieronymus W H; Dekhuijzen, P N Richard; van Helvoort, Hanneke A C; Heijdra, Yvonne F

2013-01-01

This prospective study was carried out to investigate if metronome-paced tachypnea (MPT) can serve as an accurate diagnostic tool to identify patients with chronic obstructive pulmonary disease (COPD) who are susceptible to develop dynamic hyperinflation during exercise. Commonly, this is assessed by measuring change in inspiratory capacity (IC) during cardiopulmonary exercise testing (CPET), which, however, is complex and laborious. Fifty-three patients with COPD (FEV(1) 58 ± 22%pred) and 20 age-matched healthy subjects were characterized by lung function testing and performed CPET (reference standard) and MPT. The repeatability coefficient of IC (10·2%) was used as cut-off to classify subjects as hyperinflators during CPET. Subsequently, dynamic hyperinflation was measured after MPT. With receiver operating characteristic analysis, the optimal cut-off for MPT-induced dynamic hyperinflation was determined and sensitivity and specificity of MPT to identify hyperinflators were evaluated. With 10·2% decrease in IC as cut-off for CPET-induced dynamic hyperinflation, the optimal cut-off for MPT was 11·1% decrease in IC. Using these cut-offs, MPT had a sensitivity of 85% and specificity of 85% to identify the subjects who hyperinflated during CPET. The MPT test shows good overall accuracy to identify subjects who are susceptible to develop dynamic hyperinflation during CPET. Before considering the use of MPT as a screening tool for dynamic hyperinflation in COPD, sensitivity and specificity need further evaluation. © 2012 The Authors Clinical Physiology and Functional Imaging © 2012 Scandinavian Society of Clinical Physiology and Nuclear Medicine.

Opinion dynamics within a virtual small group: the stubbornness effect

NASA Astrophysics Data System (ADS)

Guazzini, Andrea; Cini, Alessandro; Bagnoli, Franco; Ramasco, José

2015-09-01

The modeling of opinion dynamics is social systems has attracted a good deal of attention in the last decade. Even though based on intuition and observation, the mechanisms behind many of these models need solid empirical grounding. In this work, we investigate the relation among subjective variables (such as the personality), the dynamics of the affinity network dynamics, the communication patterns emerging throughout the social interactions and the opinions dynamics in a series of experiments with five small groups of ten people each. In order to ignite the discussion, the polemic topic of animal experimentation was proposed. The groups essentially polarized in two factions with a set of stubborn individuals (those not changing their opinions in time) playing the role of anchors. Our results suggest that the different layers present in the group dynamics (i.e., individual level, group dynamics and meso-communication) are deeply intermingled, specifically the stubbornness effect appears to be related to the dynamical features of the network topologies, and only in an undirected way to the personality of the participants.

Dynamic analysis of clamp band joint system subjected to axial vibration

NASA Astrophysics Data System (ADS)

Qin, Z. Y.; Yan, S. Z.; Chu, F. L.

2010-10-01

Clamp band joints are commonly used for connecting circular components together in industry. Some of the systems jointed by clamp band are subjected to dynamic load. However, very little research on the dynamic characteristics for this kind of joint can be found in the literature. In this paper, a dynamic model for clamp band joint system is developed. Contact and frictional slip between the components are accommodated in this model. Nonlinear finite element analysis is conducted to identify the model parameters. Then static experiments are carried out on a scaled model of the clamp band joint to validate the joint model. Finally, the model is adopted to study the dynamic characteristics of the clamp band joint system subjected to axial harmonic excitation and the effects of the wedge angle of the clamp band joint and the preload on the response. The model proposed in this paper can represent the nonlinearity of the clamp band joint and be used conveniently to investigate the effects of the structural and loading parameters on the dynamic characteristics of this type of joint system.

Learning-based subject-specific estimation of dynamic maps of cortical morphology at missing time points in longitudinal infant studies.

PubMed

Meng, Yu; Li, Gang; Gao, Yaozong; Lin, Weili; Shen, Dinggang

2016-11-01

Longitudinal neuroimaging analysis of the dynamic brain development in infants has received increasing attention recently. Many studies expect a complete longitudinal dataset in order to accurately chart the brain developmental trajectories. However, in practice, a large portion of subjects in longitudinal studies often have missing data at certain time points, due to various reasons such as the absence of scan or poor image quality. To make better use of these incomplete longitudinal data, in this paper, we propose a novel machine learning-based method to estimate the subject-specific, vertex-wise cortical morphological attributes at the missing time points in longitudinal infant studies. Specifically, we develop a customized regression forest, named dynamically assembled regression forest (DARF), as the core regression tool. DARF ensures the spatial smoothness of the estimated maps for vertex-wise cortical morphological attributes and also greatly reduces the computational cost. By employing a pairwise estimation followed by a joint refinement, our method is able to fully exploit the available information from both subjects with complete scans and subjects with missing scans for estimation of the missing cortical attribute maps. The proposed method has been applied to estimating the dynamic cortical thickness maps at missing time points in an incomplete longitudinal infant dataset, which includes 31 healthy infant subjects, each having up to five time points in the first postnatal year. The experimental results indicate that our proposed framework can accurately estimate the subject-specific vertex-wise cortical thickness maps at missing time points, with the average error less than 0.23 mm. Hum Brain Mapp 37:4129-4147, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dynamic models for estimating the effect of HAART on CD4 in observational studies: Application to the Aquitaine Cohort and the Swiss HIV Cohort Study.

PubMed

Prague, Mélanie; Commenges, Daniel; Gran, Jon Michael; Ledergerber, Bruno; Young, Jim; Furrer, Hansjakob; Thiébaut, Rodolphe

2017-03-01

Highly active antiretroviral therapy (HAART) has proved efficient in increasing CD4 counts in many randomized clinical trials. Because randomized trials have some limitations (e.g., short duration, highly selected subjects), it is interesting to assess the effect of treatments using observational studies. This is challenging because treatment is started preferentially in subjects with severe conditions. This general problem had been treated using Marginal Structural Models (MSM) relying on the counterfactual formulation. Another approach to causality is based on dynamical models. We present three discrete-time dynamic models based on linear increments models (LIM): the first one based on one difference equation for CD4 counts, the second with an equilibrium point, and the third based on a system of two difference equations, which allows jointly modeling CD4 counts and viral load. We also consider continuous-time models based on ordinary differential equations with non-linear mixed effects (ODE-NLME). These mechanistic models allow incorporating biological knowledge when available, which leads to increased statistical evidence for detecting treatment effect. Because inference in ODE-NLME is numerically challenging and requires specific methods and softwares, LIM are a valuable intermediary option in terms of consistency, precision, and complexity. We compare the different approaches in simulation and in illustration on the ANRS CO3 Aquitaine Cohort and the Swiss HIV Cohort Study. © 2016, The International Biometric Society.

Dynamic brain connectivity is a better predictor of PTSD than static connectivity.

PubMed

Jin, Changfeng; Jia, Hao; Lanka, Pradyumna; Rangaprakash, D; Li, Lingjiang; Liu, Tianming; Hu, Xiaoping; Deshpande, Gopikrishna

2017-09-01

Using resting-state functional magnetic resonance imaging, we test the hypothesis that subjects with post-traumatic stress disorder (PTSD) are characterized by reduced temporal variability of brain connectivity compared to matched healthy controls. Specifically, we test whether PTSD is characterized by elevated static connectivity, coupled with decreased temporal variability of those connections, with the latter providing greater sensitivity toward the pathology than the former. Static functional connectivity (FC; nondirectional zero-lag correlation) and static effective connectivity (EC; directional time-lagged relationships) were obtained over the entire brain using conventional models. Dynamic FC and dynamic EC were estimated by letting the conventional models to vary as a function of time. Statistical separation and discriminability of these metrics between the groups and their ability to accurately predict the diagnostic label of a novel subject were ascertained using separate support vector machine classifiers. Our findings support our hypothesis that PTSD subjects have stronger static connectivity, but reduced temporal variability of connectivity. Further, machine learning classification accuracy obtained with dynamic FC and dynamic EC was significantly higher than that obtained with static FC and static EC, respectively. Furthermore, results also indicate that the ease with which brain regions engage or disengage with other regions may be more sensitive to underlying pathology than the strength with which they are engaged. Future studies must examine whether this is true only in the case of PTSD or is a general organizing principle in the human brain. Hum Brain Mapp 38:4479-4496, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The importance of accurate muscle modelling for biomechanical analyses: a case study with a lizard skull

PubMed Central

Gröning, Flora; Jones, Marc E. H.; Curtis, Neil; Herrel, Anthony; O'Higgins, Paul; Evans, Susan E.; Fagan, Michael J.

2013-01-01

Computer-based simulation techniques such as multi-body dynamics analysis are becoming increasingly popular in the field of skull mechanics. Multi-body models can be used for studying the relationships between skull architecture, muscle morphology and feeding performance. However, to be confident in the modelling results, models need to be validated against experimental data, and the effects of uncertainties or inaccuracies in the chosen model attributes need to be assessed with sensitivity analyses. Here, we compare the bite forces predicted by a multi-body model of a lizard (Tupinambis merianae) with in vivo measurements, using anatomical data collected from the same specimen. This subject-specific model predicts bite forces that are very close to the in vivo measurements and also shows a consistent increase in bite force as the bite position is moved posteriorly on the jaw. However, the model is very sensitive to changes in muscle attributes such as fibre length, intrinsic muscle strength and force orientation, with bite force predictions varying considerably when these three variables are altered. We conclude that accurate muscle measurements are crucial to building realistic multi-body models and that subject-specific data should be used whenever possible. PMID:23614944

Analysis of visual quality improvements provided by known tools for HDR content

NASA Astrophysics Data System (ADS)

Kim, Jaehwan; Alshina, Elena; Lee, JongSeok; Park, Youngo; Choi, Kwang Pyo

2016-09-01

In this paper, the visual quality of different solutions for high dynamic range (HDR) compression using MPEG test contents is analyzed. We also simulate the method for an efficient HDR compression which is based on statistical property of the signal. The method is compliant with HEVC specification and also easily compatible with other alternative methods which might require HEVC specification changes. It was subjectively tested on commercial TVs and compared with alternative solutions for HDR coding. Subjective visual quality tests were performed using SUHD TVs model which is SAMSUNG JS9500 with maximum luminance up to 1000nit in test. The solution that is based on statistical property shows not only improvement of objective performance but improvement of visual quality compared to other HDR solutions, while it is compatible with HEVC specification.

A biodynamic feedthrough model based on neuromuscular principles.

PubMed

Venrooij, Joost; Abbink, David A; Mulder, Mark; van Paassen, Marinus M; Mulder, Max; van der Helm, Frans C T; Bulthoff, Heinrich H

2014-07-01

A biodynamic feedthrough (BDFT) model is proposed that describes how vehicle accelerations feed through the human body, causing involuntary limb motions and so involuntary control inputs. BDFT dynamics strongly depend on limb dynamics, which can vary between persons (between-subject variability), but also within one person over time, e.g., due to the control task performed (within-subject variability). The proposed BDFT model is based on physical neuromuscular principles and is derived from an established admittance model-describing limb dynamics-which was extended to include control device dynamics and account for acceleration effects. The resulting BDFT model serves primarily the purpose of increasing the understanding of the relationship between neuromuscular admittance and biodynamic feedthrough. An added advantage of the proposed model is that its parameters can be estimated using a two-stage approach, making the parameter estimation more robust, as the procedure is largely based on the well documented procedure required for the admittance model. To estimate the parameter values of the BDFT model, data are used from an experiment in which both neuromuscular admittance and biodynamic feedthrough are measured. The quality of the BDFT model is evaluated in the frequency and time domain. Results provide strong evidence that the BDFT model and the proposed method of parameter estimation put forward in this paper allows for accurate BDFT modeling across different subjects (accounting for between-subject variability) and across control tasks (accounting for within-subject variability).

Hybrid grammar-based approach to nonlinear dynamical system identification from biological time series

NASA Astrophysics Data System (ADS)

McKinney, B. A.; Crowe, J. E., Jr.; Voss, H. U.; Crooke, P. S.; Barney, N.; Moore, J. H.

2006-02-01

We introduce a grammar-based hybrid approach to reverse engineering nonlinear ordinary differential equation models from observed time series. This hybrid approach combines a genetic algorithm to search the space of model architectures with a Kalman filter to estimate the model parameters. Domain-specific knowledge is used in a context-free grammar to restrict the search space for the functional form of the target model. We find that the hybrid approach outperforms a pure evolutionary algorithm method, and we observe features in the evolution of the dynamical models that correspond with the emergence of favorable model components. We apply the hybrid method to both artificially generated time series and experimentally observed protein levels from subjects who received the smallpox vaccine. From the observed data, we infer a cytokine protein interaction network for an individual’s response to the smallpox vaccine.

Hunting statistics: what data for what use? An account of an international workshop

USGS Publications Warehouse

Nichols, J.D.; Lancia, R.A.; Lebreton, J.D.

2001-01-01

Hunting interacts with the underlying dynamics of game species in several different ways and is, at the same time, a source of valuable information not easily obtained from populations that are not subjected to hunting. Specific questions, including the sustainability of hunting activities, can be addressed using hunting statistics. Such investigations will frequently require that hunting statistics be combined with data from other sources of population-level information. Such reflections served as a basis for the meeting, ?Hunting Statistics: What Data for What Use,? held on January 15-18, 2001 in Saint-Benoist, France. We review here the 20 talks held during the workshop and the contribution of hunting statistics to our knowledge of the population dynamics of game species. Three specific topics (adaptive management, catch-effort models, and dynamics of exploited populations) were highlighted as important themes and are more extensively presented as boxes.

Influence of the model's degree of freedom on human body dynamics identification.

PubMed

Maita, Daichi; Venture, Gentiane

2013-01-01

In fields of sports and rehabilitation, opportunities of using motion analysis of the human body have dramatically increased. To analyze the motion dynamics, a number of subject specific parameters and measurements are required. For example the contact forces measurement and the inertial parameters of each segment of the human body are necessary to compute the joint torques. In this study, in order to perform accurate dynamic analysis we propose to identify the inertial parameters of the human body and to evaluate the influence of the model's number of degrees of freedom (DoF) on the results. We use a method to estimate the inertial parameters without torque sensor, using generalized coordinates of the base link, joint angles and external forces information. We consider a 34DoF model, a 58DoF model, as well as the case when the human is manipulating a tool (here a tennis racket). We compare the obtained in results in terms of contact force estimation.

A one-dimensional model to describe flow localization in viscoplastic slender bars subjected to super critical impact velocities

NASA Astrophysics Data System (ADS)

Vaz-Romero, A.; Rodríguez-Martínez, J. A.

2018-01-01

In this paper we investigate flow localization in viscoplastic slender bars subjected to dynamic tension. We explore loading rates above the critical impact velocity: the wave initiated in the impacted end by the applied velocity is the trigger for the localization of plastic deformation. The problem has been addressed using two kinds of numerical simulations: (1) one-dimensional finite difference calculations and (2) axisymmetric finite element computations. The latter calculations have been used to validate the capacity of the finite difference model to describe plastic flow localization at high impact velocities. The finite difference model, which highlights due to its simplicity, allows to obtain insights into the role played by the strain rate and temperature sensitivities of the material in the process of dynamic flow localization. Specifically, we have shown that viscosity can stabilize the material behavior to the point of preventing the appearance of the critical impact velocity. This is a key outcome of our investigation, which, to the best of the authors' knowledge, has not been previously reported in the literature.

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users

PubMed Central

Veksler, Vladislav D.; Buchler, Norbou; Hoffman, Blaine E.; Cassenti, Daniel N.; Sample, Char; Sugrim, Shridat

2018-01-01

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting. PMID:29867661

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-10-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-01-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e., internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature. PMID:27054199

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing.

Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing. ?? 2006, The International Biometric Society.

A generic analytical foot rollover model for predicting translational ankle kinematics in gait simulation studies.

PubMed

Ren, Lei; Howard, David; Ren, Luquan; Nester, Chris; Tian, Limei

2010-01-19

The objective of this paper is to develop an analytical framework to representing the ankle-foot kinematics by modelling the foot as a rollover rocker, which cannot only be used as a generic tool for general gait simulation but also allows for case-specific modelling if required. Previously, the rollover models used in gait simulation have often been based on specific functions that have usually been of a simple form. In contrast, the analytical model described here is in a general form that the effective foot rollover shape can be represented by any polar function rho=rho(phi). Furthermore, a normalized generic foot rollover model has been established based on a normative foot rollover shape dataset of 12 normal healthy subjects. To evaluate model accuracy, the predicted ankle motions and the centre of pressure (CoP) were compared with measurement data for both subject-specific and general cases. The results demonstrated that the ankle joint motions in both vertical and horizontal directions (relative RMSE approximately 10%) and CoP (relative RMSE approximately 15% for most of the subjects) are accurately predicted over most of the stance phase (from 10% to 90% of stance). However, we found that the foot cannot be very accurately represented by a rollover model just after heel strike (HS) and just before toe off (TO), probably due to shear deformation of foot plantar tissues (ankle motion can occur without any foot rotation). The proposed foot rollover model can be used in both inverse and forward dynamics gait simulation studies and may also find applications in rehabilitation engineering. Copyright 2009 Elsevier Ltd. All rights reserved.

Convective dynamics - Panel report

NASA Technical Reports Server (NTRS)

Carbone, Richard; Foote, G. Brant; Moncrieff, Mitch; Gal-Chen, Tzvi; Cotton, William; Heymsfield, Gerald

1990-01-01

Aspects of highly organized forms of deep convection at midlatitudes are reviewed. Past emphasis in field work and cloud modeling has been directed toward severe weather as evidenced by research on tornadoes, hail, and strong surface winds. A number of specific issues concerning future thrusts, tactics, and techniques in convective dynamics are presented. These subjects include; convective modes and parameterization, global structure and scale interaction, convective energetics, transport studies, anvils and scale interaction, and scale selection. Also discussed are analysis workshops, four-dimensional data assimilation, matching models with observations, network Doppler analyses, mesoscale variability, and high-resolution/high-performance Doppler. It is also noted, that, classical surface measurements and soundings, flight-level research aircraft data, passive satellite data, and traditional photogrammetric studies are examples of datasets that require assimilation and integration.

The circadian profile of epilepsy improves seizure forecasting.

PubMed

Karoly, Philippa J; Ung, Hoameng; Grayden, David B; Kuhlmann, Levin; Leyde, Kent; Cook, Mark J; Freestone, Dean R

2017-08-01

It is now established that epilepsy is characterized by periodic dynamics that increase seizure likelihood at certain times of day, and which are highly patient-specific. However, these dynamics are not typically incorporated into seizure prediction algorithms due to the difficulty of estimating patient-specific rhythms from relatively short-term or unreliable data sources. This work outlines a novel framework to develop and assess seizure forecasts, and demonstrates that the predictive power of forecasting models is improved by circadian information. The analyses used long-term, continuous electrocorticography from nine subjects, recorded for an average of 320 days each. We used a large amount of out-of-sample data (a total of 900 days for algorithm training, and 2879 days for testing), enabling the most extensive post hoc investigation into seizure forecasting. We compared the results of an electrocorticography-based logistic regression model, a circadian probability, and a combined electrocorticography and circadian model. For all subjects, clinically relevant seizure prediction results were significant, and the addition of circadian information (combined model) maximized performance across a range of outcome measures. These results represent a proof-of-concept for implementing a circadian forecasting framework, and provide insight into new approaches for improving seizure prediction algorithms. The circadian framework adds very little computational complexity to existing prediction algorithms, and can be implemented using current-generation implant devices, or even non-invasively via surface electrodes using a wearable application. The ability to improve seizure prediction algorithms through straightforward, patient-specific modifications provides promise for increased quality of life and improved safety for patients with epilepsy. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Nonholonomic diffusion of a stochastic sled

NASA Astrophysics Data System (ADS)

Jung, Peter; Marchegiani, Giampiero; Marchesoni, Fabio

2016-01-01

A sled is a stylized mechanical model of a system which is constrained to move in space in a specific orientation, i.e., in the direction of the runners of the sled or a blade. The negation of motion transverse to the runners renders the sled a nonholonomic mechanical system. In this paper we report on the unexpected and fascinating richness of the dynamics of such a sled if it is subject to random forces. Specifically we show that the ensuing random dynamics is characterized by relatively smooth sections of motion interspersed by episodes of persistent tumbling (change of orientation) and sharp reversals resembling the random walks of bacterial cells. In the presence of self-propulsion, the diffusivity of the sled can be enhanced and suppressed depending on the directionality and strength of the propulsive force.

Altered predictive capability of the brain network EEG model in schizophrenia during cognition.

PubMed

Gomez-Pilar, Javier; Poza, Jesús; Gómez, Carlos; Northoff, Georg; Lubeiro, Alba; Cea-Cañas, Benjamín B; Molina, Vicente; Hornero, Roberto

2018-05-12

The study of the mechanisms involved in cognition is of paramount importance for the understanding of the neurobiological substrates in psychiatric disorders. Hence, this research is aimed at exploring the brain network dynamics during a cognitive task. Specifically, we analyze the predictive capability of the pre-stimulus theta activity to ascertain the functional brain dynamics during cognition in both healthy and schizophrenia subjects. Firstly, EEG recordings were acquired during a three-tone oddball task from fifty-one healthy subjects and thirty-five schizophrenia patients. Secondly, phase-based coupling measures were used to generate the time-varying functional network for each subject. Finally, pre-stimulus network connections were iteratively modified according to different models of network reorganization. This adjustment was applied by minimizing the prediction error through recurrent iterations, following the predictive coding approach. Both controls and schizophrenia patients follow a reinforcement of the secondary neural pathways (i.e., pathways between cortical brain regions weakly connected during pre-stimulus) for most of the subjects, though the ratio of controls that exhibited this behavior was statistically significant higher than for patients. These findings suggest that schizophrenia is associated with an impaired ability to modify brain network configuration during cognition. Furthermore, we provide direct evidence that the changes in phase-based brain network parameters from pre-stimulus to cognitive response in the theta band are closely related to the performance in important cognitive domains. Our findings not only contribute to the understanding of healthy brain dynamics, but also shed light on the altered predictive neuronal substrates in schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Altered spinal motion in low back pain associated with lumbar strain and spondylosis.

PubMed

Cheng, Joseph S; Carr, Christopher B; Wong, Cyrus; Sharma, Adrija; Mahfouz, Mohamed R; Komistek, Richard D

2013-04-01

Study Design We present a patient-specific computer model created to translate two-dimensional (2D) fluoroscopic motion data into three-dimensional (3D) in vivo biomechanical motion data. Objective The aim of this study is to determine the in vivo biomechanical differences in patients with and without acute low back pain. Current dynamic imaging of the lumbar spine consists of flexion-extension static radiographs, which lack sensitivity to out-of-plane motion and provide incomplete information on the overall spinal motion. Using a novel technique, in-plane and coupled out-of-plane rotational motions are quantified in the lumbar spine. Methods A total of 30 participants-10 healthy asymptomatic subjects, 10 patients with low back pain without spondylosis radiologically, and 10 patients with low back pain with radiological spondylosis-underwent dynamic fluoroscopy with a 3D-to-2D image registration technique to create a 3D, patient-specific bone model to analyze in vivo kinematics using the maximal absolute rotational magnitude and the path of rotation. Results Average overall in-plane rotations (L1-L5) in patients with low back pain were less than those asymptomatic, with the dominant loss of motion during extension. Those with low back pain also had significantly greater out-of-plane rotations, with 5.5 degrees (without spondylosis) and 7.1 degrees (with spondylosis) more out-of-plane rotational motion per level compared with asymptomatic subjects. Conclusions Subjects with low back pain exhibited greater out-of-plane intersegmental motion in their lumbar spine than healthy asymptomatic subjects. Conventional flexion-extension radiographs are inadequate for evaluating motion patterns of lumbar strain, and assessment of 3D in vivo spinal motion may elucidate the association of abnormal vertebral motions and clinically significant low back pain.

Variable friction device for structural control based on duo-servo vehicle brake: Modeling and experimental validation

NASA Astrophysics Data System (ADS)

Cao, Liang; Downey, Austin; Laflamme, Simon; Taylor, Douglas; Ricles, James

2015-07-01

Supplemental damping can be used as a cost-effective method to reduce structural vibrations. In particular, passive systems are now widely accepted and have numerous applications in the field. However, they are typically tuned to specific excitations and their performances are bandwidth-limited. A solution is to use semi-active devices, which have shown to be capable of substantially enhanced mitigation performance. The authors have recently proposed a new type of semi-active device, which consists of a variable friction mechanism based on a vehicle duo-servo drum brake, a mechanically robust and reliable technology. The theoretical performance of the proposed device has been previously demonstrated via numerical simulations. In this paper, we further the understanding of the device, termed Modified Friction Device (MFD) by fabricating a small scale prototype and characterizing its dynamic behavior. While the dynamics of friction is well understood for automotive braking technology, we investigate for the first time the dynamic behavior of this friction mechanism at low displacements and velocities, in both forward and backward directions, under various hydraulic pressures. A modified 3-stage dynamic model is introduced. A LuGre friction model is used to characterize the friction zone (Stage 1), and two pure stiffness regions to characterize the dynamics of the MFD once the rotation is reversed and the braking shoes are sticking to the drum (Stage 2) and the rapid build up of forces once the shoes are held by the anchor pin (Stage 3). The proposed model is identified experimentally by subjecting the prototype to harmonic excitations. It is found that the proposed model can be used to characterize the dynamics of the MFD, and that the largest fitting error arises at low velocity under low pressure input. The model is then verified by subjecting the MFD to two different earthquake excitations under different pressure inputs. The model is capable of tracking the device's response, despite a lower fitting performance under low pressure and small force output, as it was found in the harmonic tests due to the possible nonlinearity in Stage 2 of the model.

Sensitivity of medial and lateral knee contact force predictions to frontal plane alignment and contact locations.

PubMed

Saliba, Christopher M; Brandon, Scott C E; Deluzio, Kevin J

2017-05-24

Musculoskeletal models are increasingly used to estimate medial and lateral knee contact forces, which are difficult to measure in vivo. The sensitivity of contact force predictions to modeling parameters is important to the interpretation and implication of results generated by the model. The purpose of this study was to quantify the sensitivity of knee contact force predictions to simultaneous errors in frontal plane knee alignment and contact locations under different dynamic conditions. We scaled a generic musculoskeletal model for N=23 subjects' stature and radiographic knee alignment, then perturbed frontal plane alignment and mediolateral contact locations within experimentally-possible ranges of 10° to -10° and 10 to -10mm, respectively. The sensitivity of first peak, second peak, and mean medial and lateral knee contact forces to knee adduction angle and contact locations was modeled using linear regression. Medial loads increased, and lateral loads decreased, by between 3% and 6% bodyweight for each degree of varus perturbation. Shifting the medial contact point medially increased medial loads and decreased lateral loads by between 1% and 4% bodyweight per millimeter. This study demonstrates that realistic measurement errors of 5mm (contact distance) or 5° (frontal plane alignment) could result in a combined 50% BW error in subject specific contact force estimates. We also show that model sensitivity varies between subjects as a result of differences in gait dynamics. These results demonstrate that predicted knee joint contact forces should be considered as a range of possible values determined by model uncertainty. Copyright © 2017 Elsevier Ltd. All rights reserved.

Differential Equation Models for Sharp Threshold Dynamics

DTIC Science & Technology

2012-08-01

dynamics, and the Lanchester model of armed conflict, where the loss of a key capability drastically changes dynamics. We derive and demonstrate a step...dynamics using differential equations. 15. SUBJECT TERMS Differential Equations, Markov Population Process, S-I-R Epidemic, Lanchester Model 16...infection, where a detection event drastically changes dynamics, and the Lanchester model of armed conflict, where the loss of a key capability

A Dynamic Finite Element Analysis of Human Foot Complex in the Sagittal Plane during Level Walking

PubMed Central

Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R.; Ren, Luquan

2013-01-01

The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%–33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning. PMID:24244500

A dynamic finite element analysis of human foot complex in the sagittal plane during level walking.

PubMed

Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R; Ren, Luquan

2013-01-01

The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%-33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning.

Piloting Changes to Changing Aircraft Dynamics: What Do Pilots Need to Know?

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2011-01-01

An experiment was conducted to quantify the effects of changing dynamics on a subject s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. The data will be used to identify primary aircraft dynamics variables that influence changes in pilot s response and produce a simplified pilot model that incorporates this relationship. Each run incorporated a different set of second-order aircraft dynamics representing short period transfer function pitch attitude response: damping ratio, frequency, gain, zero location, and time delay. The subject s ability to conduct the tracking task was the greatest source of root mean square error tracking variability. As for the aircraft dynamics, the factors that affected the subjects ability to conduct the tracking were the time delay, frequency, and zero location. In addition to creating a simplified pilot model, the results of the experiment can be utilized in an advisory capacity. A situation awareness/prediction aid based on the pilot behavior and aircraft dynamics may help tailor pilot s inputs more quickly so that PIO or an upset condition can be avoided.

Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake: An Extended Kalman Filter Approach.

PubMed

Wang, Qian; Molenaar, Peter; Harsh, Saurabh; Freeman, Kenneth; Xie, Jinyu; Gold, Carol; Rovine, Mike; Ulbrecht, Jan

2014-03-01

An essential component of any artificial pancreas is on the prediction of blood glucose levels as a function of exogenous and endogenous perturbations such as insulin dose, meal intake, and physical activity and emotional tone under natural living conditions. In this article, we present a new data-driven state-space dynamic model with time-varying coefficients that are used to explicitly quantify the time-varying patient-specific effects of insulin dose and meal intake on blood glucose fluctuations. Using the 3-variate time series of glucose level, insulin dose, and meal intake of an individual type 1 diabetic subject, we apply an extended Kalman filter (EKF) to estimate time-varying coefficients of the patient-specific state-space model. We evaluate our empirical modeling using (1) the FDA-approved UVa/Padova simulator with 30 virtual patients and (2) clinical data of 5 type 1 diabetic patients under natural living conditions. Compared to a forgetting-factor-based recursive ARX model of the same order, the EKF model predictions have higher fit, and significantly better temporal gain and J index and thus are superior in early detection of upward and downward trends in glucose. The EKF based state-space model developed in this article is particularly suitable for model-based state-feedback control designs since the Kalman filter estimates the state variable of the glucose dynamics based on the measured glucose time series. In addition, since the model parameters are estimated in real time, this model is also suitable for adaptive control. © 2014 Diabetes Technology Society.

A low-cost three-dimensional laser surface scanning approach for defining body segment parameters.

PubMed

Pandis, Petros; Bull, Anthony Mj

2017-11-01

Body segment parameters are used in many different applications in ergonomics as well as in dynamic modelling of the musculoskeletal system. Body segment parameters can be defined using different methods, including techniques that involve time-consuming manual measurements of the human body, used in conjunction with models or equations. In this study, a scanning technique for measuring subject-specific body segment parameters in an easy, fast, accurate and low-cost way was developed and validated. The scanner can obtain the body segment parameters in a single scanning operation, which takes between 8 and 10 s. The results obtained with the system show a standard deviation of 2.5% in volumetric measurements of the upper limb of a mannequin and 3.1% difference between scanning volume and actual volume. Finally, the maximum mean error for the moment of inertia by scanning a standard-sized homogeneous object was 2.2%. This study shows that a low-cost system can provide quick and accurate subject-specific body segment parameter estimates.

Granger Causality Testing with Intensive Longitudinal Data.

PubMed

Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

Modeling population dynamics of mitochondria in mammalian cells

NASA Astrophysics Data System (ADS)

Kornick, Kellianne; Das, Moumita

Mitochondria are organelles located inside eukaryotic cells and are essential for several key cellular processes such as energy (ATP) production, cell signaling, differentiation, and apoptosis. All organisms are believed to have low levels of variation in mitochondrial DNA (mtDNA), and alterations in mtDNA are connected to a range of human health conditions, including epilepsy, heart failure, Parkinsons disease, diabetes, and multiple sclerosis. Therefore, understanding how changes in mtDNA accumulate over time and are correlated to changes in mitochondrial function and cell properties can have a profound impact on our understanding of cell physiology and the origins of some diseases. Motivated by this, we develop and study a mathematical model to determine which cellular parameters have the largest impact on mtDNA population dynamics. The model consists of coupled ODEs to describe subpopulations of healthy and dysfunctional mitochondria subject to mitochondrial fission, fusion, autophagy, and mutation. We study the time evolution and stability of each sub-population under specific selection biases and pressures by tuning specific terms in our model. Our results may provide insights into how sub-populations of mitochondria survive and evolve under different selection pressures. This work was supported by a Grant from the Moore Foundation.

Modeling biological pathway dynamics with timed automata.

PubMed

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Solitary pulmonary nodules: Comparison of dynamic first-pass contrast-enhanced perfusion area-detector CT, dynamic first-pass contrast-enhanced MR imaging, and FDG PET/CT.

PubMed

Ohno, Yoshiharu; Nishio, Mizuho; Koyama, Hisanobu; Seki, Shinichiro; Tsubakimoto, Maho; Fujisawa, Yasuko; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Sugimura, Kazuro

2015-02-01

To prospectively compare the capabilities of dynamic perfusion area-detector computed tomography (CT), dynamic magnetic resonance (MR) imaging, and positron emission tomography (PET) combined with CT (PET/CT) with use of fluorine 18 fluorodeoxyglucose (FDG) for the diagnosis of solitary pulmonary nodules. The institutional review board approved this study, and written informed consent was obtained from each subject. A total of 198 consecutive patients with 218 nodules prospectively underwent dynamic perfusion area-detector CT, dynamic MR imaging, FDG PET/CT, and microbacterial and/or pathologic examinations. Nodules were classified into three groups: malignant nodules (n = 133) and benign nodules with low (n = 53) or high (n = 32) biologic activity. Total perfusion was determined with dual-input maximum slope models at area-detector CT, maximum and slope of enhancement ratio at MR imaging, and maximum standardized uptake value (SUVmax) at PET/CT. Next, all indexes for malignant and benign nodules were compared with the Tukey honest significant difference test. Then, receiver operating characteristic analysis was performed for each index. Finally, sensitivity, specificity, and accuracy were compared with the McNemar test. All indexes showed significant differences between malignant nodules and benign nodules with low biologic activity (P < .0001). The area under the receiver operating characteristic curve for total perfusion was significantly larger than that for other indexes (.0006 ≤ P ≤ .04). The specificity and accuracy of total perfusion were significantly higher than those of maximum relative enhancement ratio (specificity, P < .0001; accuracy, P < .0001), slope of enhancement ratio (specificity, P < .0001; accuracy, P < .0001), and SUVmax (specificity, P < .0001; accuracy, P < .0001). Dynamic perfusion area-detector CT is more specific and accurate than dynamic MR imaging and FDG PET/CT in the diagnosis of solitary pulmonary nodules in routine clinical practice. © RSNA, 2014.

The coordination dynamics of social neuromarkers.

PubMed

Tognoli, Emmanuelle; Kelso, J A Scott

2015-01-01

Social behavior is a complex integrative function that entails many aspects of the brain's sensory, cognitive, emotional and movement capacities. Its neural processes are seldom simultaneous but occur according to precise spatiotemporal choreographies, manifested by the coordination of their oscillations within and between brains. Methods with good temporal resolution can help to identify so-called "neuromarkers" of social function and aid in disentangling the dynamical architecture of social brains. In our ongoing research, we have used dual-electroencephalography (EEG) to study neuromarker dynamics during synchronic interactions in which pairs of subjects coordinate behavior spontaneously and intentionally (social coordination) and during diachronic transactions that require subjects to perceive or behave in turn (action observation, delayed imitation). In this paper, after outlining our dynamical approach to the neurophysiological basis of social behavior, we examine commonalities and differences in the neuromarkers that are recruited for both kinds of tasks. We find the neuromarker landscape to be task-specific: synchronic paradigms of social coordination reveal medial mu, alpha and the phi complex as contributing neuromarkers. Diachronic tasks recruit alpha as well, in addition to lateral mu rhythms and the newly discovered nu and kappa rhythms whose functional significance is still unclear. Social coordination, observation, and delayed imitation share commonality of context: in each of our experiments, subjects exchanged information through visual perception and moved in similar ways. Nonetheless, there was little overlap between their neuromarkers, a result that hints strongly of task-specific neural mechanisms for social behavior. The only neuromarker that transcended both synchronic and diachronic social behaviors was the ubiquitous alpha rhythm, which appears to be a key signature of visually-mediated social behaviors. The present paper is both an entry point and a challenge: much work remains to determine the nature and scope of recruitment of other neuromarkers, and to create theoretical models of their within- and between-brain dynamics during social interaction.

The coordination dynamics of social neuromarkers

PubMed Central

Tognoli, Emmanuelle; Kelso, J. A. Scott

2015-01-01

Social behavior is a complex integrative function that entails many aspects of the brain’s sensory, cognitive, emotional and movement capacities. Its neural processes are seldom simultaneous but occur according to precise spatiotemporal choreographies, manifested by the coordination of their oscillations within and between brains. Methods with good temporal resolution can help to identify so-called “neuromarkers” of social function and aid in disentangling the dynamical architecture of social brains. In our ongoing research, we have used dual-electroencephalography (EEG) to study neuromarker dynamics during synchronic interactions in which pairs of subjects coordinate behavior spontaneously and intentionally (social coordination) and during diachronic transactions that require subjects to perceive or behave in turn (action observation, delayed imitation). In this paper, after outlining our dynamical approach to the neurophysiological basis of social behavior, we examine commonalities and differences in the neuromarkers that are recruited for both kinds of tasks. We find the neuromarker landscape to be task-specific: synchronic paradigms of social coordination reveal medial mu, alpha and the phi complex as contributing neuromarkers. Diachronic tasks recruit alpha as well, in addition to lateral mu rhythms and the newly discovered nu and kappa rhythms whose functional significance is still unclear. Social coordination, observation, and delayed imitation share commonality of context: in each of our experiments, subjects exchanged information through visual perception and moved in similar ways. Nonetheless, there was little overlap between their neuromarkers, a result that hints strongly of task-specific neural mechanisms for social behavior. The only neuromarker that transcended both synchronic and diachronic social behaviors was the ubiquitous alpha rhythm, which appears to be a key signature of visually-mediated social behaviors. The present paper is both an entry point and a challenge: much work remains to determine the nature and scope of recruitment of other neuromarkers, and to create theoretical models of their within- and between-brain dynamics during social interaction. PMID:26557067

Buckling of circular cylindrical shells under dynamically applied axial loads

NASA Technical Reports Server (NTRS)

Tulk, J. D.

1972-01-01

A theoretical and experimental study was made of the buckling characteristics of perfect and imperfect circular cylindrical shells subjected to dynamic axial loading. Experimental data included dynamic buckling loads (124 data points), high speed photographs of buckling mode shapes and observations of the dynamic stability of shells subjected to rapidly applied sub-critical loads. A mathematical model was developed to describe the dynamic behavior of perfect and imperfect shells. This model was based on the Donnell-Von Karman compatibility and equilibrium equations and had a wall deflection function incorporating five separate modes of deflection. Close agreement between theory and experiment was found for both dynamic buckling strength and buckling mode shapes.

The effect of subtalar inversion/eversion on the dynamic function of the tibialis anterior, soleus, and gastrocnemius during the stance phase of gait.

PubMed

Wang, Ruoli; Gutierrez-Farewik, Elena M

2011-05-01

The purpose of this study was to determine how gait deviation in one plane (i.e. excessive subtalar inversion/eversion) can affect the dynamic function of the tibialis anterior, gastrocnemius, and soleus to accelerate the subtalar, ankle, knee and hip joints, as well as the body center of mass. Induced acceleration analysis was performed based on a subject-specific three-dimensional linkage model configured by stance phase gait data and driven by one unit of muscle force. Eight healthy adult subjects were examined in gait analysis. The subtalar inversion/eversion was modeled by offsetting up to 20° from the normal subtalar angle while other configurations remained unaltered. This study showed that the gastrocnemius, soleus and tibialis anterior generally functioned as their anatomical definition in normal gait, but counterintuitive function was occasionally found in the bi-articular gastrocnemius. The plantarflexors play important roles in the body support and forward progression. Excessive subtalar eversion was found to enlarge the plantarflexors and tibialis anterior's function. Induced acceleration analysis demonstrated its ability to isolate the contributions of individual muscle to a given factor, and as a means of studying effect of pathological gait on the dynamic muscle functions. Copyright © 2011 Elsevier B.V. All rights reserved.

Influence of foundation mass and surface roughness on dynamic response of beam on dynamic foundation subjected to the moving load

NASA Astrophysics Data System (ADS)

Tran Quoc, Tinh; Khong Trong, Toan; Luong Van, Hai

2018-04-01

In this paper, Improved Moving Element Method (IMEM) is used to analyze the dynamic response of Euler-Bernoulli beam structures on the dynamic foundation model subjected to the moving load. The effects of characteristic foundation model parameters such as Winkler stiffness, shear layer based on the Pasternak model, viscoelastic dashpot and characteristic parameter of mass on foundation. Beams are modeled by moving elements while the load is fixed. Based on the principle of the publicly virtual balancing and the theory of moving element method, the motion differential equation of the system is established and solved by means of the numerical integration based on the Newmark algorithm. The influence of mass on foundation and the roughness of the beam surface on the dynamic response of beam are examined in details.

Pilot modeling and closed-loop analysis of flexible aircraft in the pitch tracking task

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

The issue addressed in the appropriate modeling technique for pilot vehicle analysis of large flexible aircraft, when the frequency separation between the rigid-body mode and the dynamic aeroelastic modes is reduced. This situation was shown to have significant effects on pitch-tracking performance and subjective rating of the task, obtained via fixed base simulation. Further, the dynamics in these cases are not well modeled with a rigid-body-like model obtained by including only 'static elastic' effects, for example. It is shown that pilot/vehicle analysis of this data supports the hypothesis that an appropriate pilot-model structure is an optimal-control pilot model of full order. This is in contrast to the contention that a representative model is of reduced order when the subject is controlling high-order dynamics as in a flexible vehicle. The key appears to be in the correct assessment of the pilot's objective of attempting to control 'rigid-body' vehicle response, a response that must be estimated by the pilot from observations contaminated by aeroelastic dynamics. Finally, a model-based metric is shown to correlate well with the pilot's subjective ratings.

Modeling the Dynamics of Disease States in Depression

PubMed Central

Demic, Selver; Cheng, Sen

2014-01-01

Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidity, disability, and risk for suicide. The disorder is clinically and etiologically heterogeneous. Despite intense research efforts, the response rates of antidepressant treatments are relatively low and the etiology and progression of MDD remain poorly understood. Here we use computational modeling to advance our understanding of MDD. First, we propose a systematic and comprehensive definition of disease states, which is based on a type of mathematical model called a finite-state machine. Second, we propose a dynamical systems model for the progression, or dynamics, of MDD. The model is abstract and combines several major factors (mechanisms) that influence the dynamics of MDD. We study under what conditions the model can account for the occurrence and recurrence of depressive episodes and how we can model the effects of antidepressant treatments and cognitive behavioral therapy within the same dynamical systems model through changing a small subset of parameters. Our computational modeling suggests several predictions about MDD. Patients who suffer from depression can be divided into two sub-populations: a high-risk sub-population that has a high risk of developing chronic depression and a low-risk sub-population, in which patients develop depression stochastically with low probability. The success of antidepressant treatment is stochastic, leading to widely different times-to-remission in otherwise identical patients. While the specific details of our model might be subjected to criticism and revisions, our approach shows the potential power of computationally modeling depression and the need for different type of quantitative data for understanding depression. PMID:25330102

Dual-joint modeling for estimation of total knee replacement contact forces during locomotion.

PubMed

Hast, Michael W; Piazza, Stephen J

2013-02-01

Model-based estimation of in vivo contact forces arising between components of a total knee replacement is challenging because such forces depend upon accurate modeling of muscles, tendons, ligaments, contact, and multibody dynamics. Here we describe an approach to solving this problem with results that are tested by comparison to knee loads measured in vivo for a single subject and made available through the Grand Challenge Competition to Predict in vivo Tibiofemoral Loads. The approach makes use of a "dual-joint" paradigm in which the knee joint is alternately represented by (1) a ball-joint knee for inverse dynamic computation of required muscle controls and (2) a 12 degree-of-freedom (DOF) knee with elastic foundation contact at the tibiofemoral and patellofemoral articulations for forward dynamic integration. Measured external forces and kinematics were applied as a feedback controller and static optimization attempted to track measured knee flexion angles and electromyographic (EMG) activity. The resulting simulations showed excellent tracking of knee flexion (average RMS error of 2.53 deg) and EMG (muscle activations within ±10% envelopes of normalized measured EMG signals). Simulated tibiofemoral contact forces agreed qualitatively with measured contact forces, but their RMS errors were approximately 25% of the peak measured values. These results demonstrate the potential of a dual-joint modeling approach to predict joint contact forces from kinesiological data measured in the motion laboratory. It is anticipated that errors in the estimation of contact force will be reduced as more accurate subject-specific models of muscles and other soft tissues are developed.

Integrated Bayesian models of learning and decision making for saccadic eye movements.

PubMed

Brodersen, Kay H; Penny, Will D; Harrison, Lee M; Daunizeau, Jean; Ruff, Christian C; Duzel, Emrah; Friston, Karl J; Stephan, Klaas E

2008-11-01

The neurophysiology of eye movements has been studied extensively, and several computational models have been proposed for decision-making processes that underlie the generation of eye movements towards a visual stimulus in a situation of uncertainty. One class of models, known as linear rise-to-threshold models, provides an economical, yet broadly applicable, explanation for the observed variability in the latency between the onset of a peripheral visual target and the saccade towards it. So far, however, these models do not account for the dynamics of learning across a sequence of stimuli, and they do not apply to situations in which subjects are exposed to events with conditional probabilities. In this methodological paper, we extend the class of linear rise-to-threshold models to address these limitations. Specifically, we reformulate previous models in terms of a generative, hierarchical model, by combining two separate sub-models that account for the interplay between learning of target locations across trials and the decision-making process within trials. We derive a maximum-likelihood scheme for parameter estimation as well as model comparison on the basis of log likelihood ratios. The utility of the integrated model is demonstrated by applying it to empirical saccade data acquired from three healthy subjects. Model comparison is used (i) to show that eye movements do not only reflect marginal but also conditional probabilities of target locations, and (ii) to reveal subject-specific learning profiles over trials. These individual learning profiles are sufficiently distinct that test samples can be successfully mapped onto the correct subject by a naïve Bayes classifier. Altogether, our approach extends the class of linear rise-to-threshold models of saccadic decision making, overcomes some of their previous limitations, and enables statistical inference both about learning of target locations across trials and the decision-making process within trials.

Keep it simple - A case study of model development in the context of the Dynamic Stocks and Flows (DSF) task

NASA Astrophysics Data System (ADS)

Halbrügge, Marc

2010-12-01

This paper describes the creation of a cognitive model submitted to the ‘Dynamic Stocks and Flows’ (DSF) modeling challenge. This challenge aims at comparing computational cognitive models for human behavior during an open ended control task. Participants in the modeling competition were provided with a simulation environment and training data for benchmarking their models while the actual specification of the competition task was withheld. To meet this challenge, the cognitive model described here was designed and optimized for generalizability. Only two simple assumptions about human problem solving were used to explain the empirical findings of the training data. In-depth analysis of the data set prior to the development of the model led to the dismissal of correlations or other parametric statistics as goodness-of-fit indicators. A new statistical measurement based on rank orders and sequence matching techniques is being proposed instead. This measurement, when being applied to the human sample, also identifies clusters of subjects that use different strategies for the task. The acceptability of the fits achieved by the model is verified using permutation tests.

Musculoskeletal Simulation Model Generation from MRI Data Sets and Motion Capture Data

NASA Astrophysics Data System (ADS)

Schmid, Jérôme; Sandholm, Anders; Chung, François; Thalmann, Daniel; Delingette, Hervé; Magnenat-Thalmann, Nadia

Today computer models and computer simulations of the musculoskeletal system are widely used to study the mechanisms behind human gait and its disorders. The common way of creating musculoskeletal models is to use a generic musculoskeletal model based on data derived from anatomical and biomechanical studies of cadaverous specimens. To adapt this generic model to a specific subject, the usual approach is to scale it. This scaling has been reported to introduce several errors because it does not always account for subject-specific anatomical differences. As a result, a novel semi-automatic workflow is proposed that creates subject-specific musculoskeletal models from magnetic resonance imaging (MRI) data sets and motion capture data. Based on subject-specific medical data and a model-based automatic segmentation approach, an accurate modeling of the anatomy can be produced while avoiding the scaling operation. This anatomical model coupled with motion capture data, joint kinematics information, and muscle-tendon actuators is finally used to create a subject-specific musculoskeletal model.

Global solutions to a class of multi-species reaction-diffusion systems with cross-diffusions arising in population dynamics

NASA Astrophysics Data System (ADS)

Wen, Zijuan; Fu, Shengmao

2009-08-01

In this paper, an n-species strongly coupled cooperating diffusive system is considered in a bounded smooth domain, subject to homogeneous Neumann boundary conditions. Employing the method of energy estimates, we obtain some conditions on the diffusion matrix and inter-specific cooperatives to ensure the global existence and uniform boundedness of a nonnegative solution. The globally asymptotical stability of the constant positive steady state is also discussed. As a consequence, all the results hold true for multi-species Lotka-Volterra type competition model and prey-predator model.

The dynamic failure behavior of tungsten heavy alloys subjected to transverse loads

NASA Astrophysics Data System (ADS)

Tarcza, Kenneth Robert

Tungsten heavy alloys (WHA), a category of particulate composites used in defense applications as kinetic energy penetrators, have been studied for many years. Even so, their dynamic failure behavior is not fully understood and cannot be predicted by numerical models presently in use. In this experimental investigation, a comprehensive understanding of the high-rate transverse-loading fracture behavior of WHA has been developed. Dynamic fracture events spanning a range of strain rates and loading conditions were created via mechanical testing and used to determine the influence of surface condition and microstructure on damage initiation, accumulation, and sample failure under different loading conditions. Using standard scanning electron microscopy metallographic and fractographic techniques, sample surface condition is shown to be extremely influential to the manner in which WHA fails, causing a fundamental change from externally to internally nucleated failures as surface condition is improved. Surface condition is characterized using electron microscopy and surface profilometry. Fracture surface analysis is conducted using electron microscopy, and linear elastic fracture mechanics is used to understand the influence of surface condition, specifically initial flaw size, on sample failure behavior. Loading conditions leading to failure are deduced from numerical modeling and experimental observation. The results highlight parameters and considerations critical to the understanding of dynamic WHA fracture and the development of dynamic WHA failure models.

EEG-Based Quantification of Cortical Current Density and Dynamic Causal Connectivity Generalized across Subjects Performing BCI-Monitored Cognitive Tasks

PubMed Central

Courellis, Hristos; Mullen, Tim; Poizner, Howard; Cauwenberghs, Gert; Iversen, John R.

2017-01-01

Quantification of dynamic causal interactions among brain regions constitutes an important component of conducting research and developing applications in experimental and translational neuroscience. Furthermore, cortical networks with dynamic causal connectivity in brain-computer interface (BCI) applications offer a more comprehensive view of brain states implicated in behavior than do individual brain regions. However, models of cortical network dynamics are difficult to generalize across subjects because current electroencephalography (EEG) signal analysis techniques are limited in their ability to reliably localize sources across subjects. We propose an algorithmic and computational framework for identifying cortical networks across subjects in which dynamic causal connectivity is modeled among user-selected cortical regions of interest (ROIs). We demonstrate the strength of the proposed framework using a “reach/saccade to spatial target” cognitive task performed by 10 right-handed individuals. Modeling of causal cortical interactions was accomplished through measurement of cortical activity using (EEG), application of independent component clustering to identify cortical ROIs as network nodes, estimation of cortical current density using cortically constrained low resolution electromagnetic brain tomography (cLORETA), multivariate autoregressive (MVAR) modeling of representative cortical activity signals from each ROI, and quantification of the dynamic causal interaction among the identified ROIs using the Short-time direct Directed Transfer function (SdDTF). The resulting cortical network and the computed causal dynamics among its nodes exhibited physiologically plausible behavior, consistent with past results reported in the literature. This physiological plausibility of the results strengthens the framework's applicability in reliably capturing complex brain functionality, which is required by applications, such as diagnostics and BCI. PMID:28566997

Modeling and Identification of a Realistic Spiking Neural Network and Musculoskeletal Model of the Human Arm, and an Application to the Stretch Reflex.

PubMed

Sreenivasa, Manish; Ayusawa, Ko; Nakamura, Yoshihiko

2016-05-01

This study develops a multi-level neuromuscular model consisting of topological pools of spiking motor, sensory and interneurons controlling a bi-muscular model of the human arm. The spiking output of motor neuron pools were used to drive muscle actions and skeletal movement via neuromuscular junctions. Feedback information from muscle spindles were relayed via monosynaptic excitatory and disynaptic inhibitory connections, to simulate spinal afferent pathways. Subject-specific model parameters were identified from human experiments by using inverse dynamics computations and optimization methods. The identified neuromuscular model was used to simulate the biceps stretch reflex and the results were compared to an independent dataset. The proposed model was able to track the recorded data and produce dynamically consistent neural spiking patterns, muscle forces and movement kinematics under varying conditions of external forces and co-contraction levels. This additional layer of detail in neuromuscular models has important relevance to the research communities of rehabilitation and clinical movement analysis by providing a mathematical approach to studying neuromuscular pathology.

Gender dimorphic ACL strain in response to combined dynamic 3D knee joint loading: implications for ACL injury risk.

PubMed

Mizuno, Kiyonori; Andrish, Jack T; van den Bogert, Antonie J; McLean, Scott G

2009-12-01

While gender-based differences in knee joint anatomies/laxities are well documented, the potential for them to precipitate gender-dimorphic ACL loading and resultant injury risk has not been considered. To this end, we generated gender-specific models of ACL strain as a function of any six degrees of freedom (6DOF) knee joint load state via a combined cadaveric and analytical approach. Continuously varying joint forces and torques were applied to five male and five female cadaveric specimens and recorded along with synchronous knee flexion and ACL strain data. All data (approximately 10,000 samples) were submitted to specimen-specific regression analyses, affording ACL strain predictions as a function of the combined 6 DOF knee loads. Following individual model verifications, generalized gender-specific models were generated and subjected to 6 DOF external load scenarios consistent with both a clinical examination and a dynamic sports maneuver. The ensuing model-based strain predictions were subsequently examined for gender-based discrepancies. Male and female specimen-specific models predicted ACL strain within 0.51%+/-0.10% and 0.52%+/-0.07% of the measured data respectively, and explained more than 75% of the associated variance in each case. Predicted female ACL strains were also significantly larger than respective male values for both simulated 6 DOF load scenarios. Outcomes suggest that the female ACL will rupture in response to comparatively smaller external load applications. Future work must address the underlying anatomical/laxity contributions to knee joint mechanical and resultant ACL loading, ultimately affording prevention strategies that may cater to individual joint vulnerabilities.

Sensitivity of a juvenile subject-specific musculoskeletal model of the ankle joint to the variability of operator-dependent input

PubMed Central

Hannah, Iain; Montefiori, Erica; Modenese, Luca; Prinold, Joe; Viceconti, Marco; Mazzà, Claudia

2017-01-01

Subject-specific musculoskeletal modelling is especially useful in the study of juvenile and pathological subjects. However, such methodologies typically require a human operator to identify key landmarks from medical imaging data and are thus affected by unavoidable variability in the parameters defined and subsequent model predictions. The aim of this study was to thus quantify the inter- and intra-operator repeatability of a subject-specific modelling methodology developed for the analysis of subjects with juvenile idiopathic arthritis. Three operators each created subject-specific musculoskeletal foot and ankle models via palpation of bony landmarks, adjustment of geometrical muscle points and definition of joint coordinate systems. These models were then fused to a generic Arnold lower limb model for each of three modelled patients. The repeatability of each modelling operation was found to be comparable to those previously reported for the modelling of healthy, adult subjects. However, the inter-operator repeatability of muscle point definition was significantly greater than intra-operator repeatability (p < 0.05) and predicted ankle joint contact forces ranged by up to 24% and 10% of the peak force for the inter- and intra-operator analyses, respectively. Similarly, the maximum inter- and intra-operator variations in muscle force output were 64% and 23% of peak force, respectively. Our results suggest that subject-specific modelling is operator dependent at the foot and ankle, with the definition of muscle geometry the most significant source of output uncertainty. The development of automated procedures to prevent the misplacement of crucial muscle points should therefore be considered a particular priority for those developing subject-specific models. PMID:28427313

Sensitivity of a juvenile subject-specific musculoskeletal model of the ankle joint to the variability of operator-dependent input.

PubMed

Hannah, Iain; Montefiori, Erica; Modenese, Luca; Prinold, Joe; Viceconti, Marco; Mazzà, Claudia

2017-05-01

Subject-specific musculoskeletal modelling is especially useful in the study of juvenile and pathological subjects. However, such methodologies typically require a human operator to identify key landmarks from medical imaging data and are thus affected by unavoidable variability in the parameters defined and subsequent model predictions. The aim of this study was to thus quantify the inter- and intra-operator repeatability of a subject-specific modelling methodology developed for the analysis of subjects with juvenile idiopathic arthritis. Three operators each created subject-specific musculoskeletal foot and ankle models via palpation of bony landmarks, adjustment of geometrical muscle points and definition of joint coordinate systems. These models were then fused to a generic Arnold lower limb model for each of three modelled patients. The repeatability of each modelling operation was found to be comparable to those previously reported for the modelling of healthy, adult subjects. However, the inter-operator repeatability of muscle point definition was significantly greater than intra-operator repeatability ( p < 0.05) and predicted ankle joint contact forces ranged by up to 24% and 10% of the peak force for the inter- and intra-operator analyses, respectively. Similarly, the maximum inter- and intra-operator variations in muscle force output were 64% and 23% of peak force, respectively. Our results suggest that subject-specific modelling is operator dependent at the foot and ankle, with the definition of muscle geometry the most significant source of output uncertainty. The development of automated procedures to prevent the misplacement of crucial muscle points should therefore be considered a particular priority for those developing subject-specific models.

Parameterized Linear Longitudinal Airship Model

NASA Technical Reports Server (NTRS)

Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph

2010-01-01

A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics

Estimation of Quasi-Stiffness and Propulsive Work of the Human Ankle in the Stance Phase of Walking

PubMed Central

Shamaei, Kamran; Sawicki, Gregory S.; Dollar, Aaron M.

2013-01-01

Characterizing the quasi-stiffness and work of lower extremity joints is critical for evaluating human locomotion and designing assistive devices such as prostheses and orthoses intended to emulate the biological behavior of human legs. This work aims to establish statistical models that allow us to predict the ankle quasi-stiffness and net mechanical work for adults walking on level ground. During the stance phase of walking, the ankle joint propels the body through three distinctive phases of nearly constant stiffness known as the quasi-stiffness of each phase. Using a generic equation for the ankle moment obtained through an inverse dynamics analysis, we identify key independent parameters needed to predict ankle quasi-stiffness and propulsive work and also the functional form of each correlation. These parameters include gait speed, ankle excursion, and subject height and weight. Based on the identified form of the correlation and key variables, we applied linear regression on experimental walking data for 216 gait trials across 26 subjects (speeds from 0.75–2.63 m/s) to obtain statistical models of varying complexity. The most general forms of the statistical models include all the key parameters and have an R2 of 75% to 81% in the prediction of the ankle quasi-stiffnesses and propulsive work. The most specific models include only subject height and weight and could predict the ankle quasi-stiffnesses and work for optimal walking speed with average error of 13% to 30%. We discuss how these models provide a useful framework and foundation for designing subject- and gait-specific prosthetic and exoskeletal devices designed to emulate biological ankle function during level ground walking. PMID:23555839

Estimation of left ventricular blood flow parameters: clinical application of patient-specific CFD simulations from 4D echocardiography

NASA Astrophysics Data System (ADS)

Larsson, David; Spühler, Jeannette H.; Günyeli, Elif; Weinkauf, Tino; Hoffman, Johan; Colarieti-Tosti, Massimiliano; Winter, Reidar; Larsson, Matilda

2017-03-01

Echocardiography is the most commonly used image modality in cardiology, assessing several aspects of cardiac viability. The importance of cardiac hemodynamics and 4D blood flow motion has recently been highlighted, however such assessment is still difficult using routine echo-imaging. Instead, combining imaging with computational fluid dynamics (CFD)-simulations has proven valuable, but only a few models have been applied clinically. In the following, patient-specific CFD-simulations from transthoracic dobutamin stress echocardiography have been used to analyze the left ventricular 4D blood flow in three subjects: two with normal and one with reduced left ventricular function. At each stress level, 4D-images were acquired using a GE Vivid E9 (4VD, 1.7MHz/3.3MHz) and velocity fields simulated using a presented pathway involving endocardial segmentation, valve position identification, and solution of the incompressible Navier-Stokes equation. Flow components defined as direct flow, delayed ejection flow, retained inflow, and residual volume were calculated by particle tracing using 4th-order Runge-Kutta integration. Additionally, systolic and diastolic average velocity fields were generated. Results indicated no major changes in average velocity fields for any of the subjects. For the two subjects with normal left ventricular function, increased direct flow, decreased delayed ejection flow, constant retained inflow, and a considerable drop in residual volume was seen at increasing stress. Contrary, for the subject with reduced left ventricular function, the delayed ejection flow increased whilst the retained inflow decreased at increasing stress levels. This feasibility study represents one of the first clinical applications of an echo-based patient-specific CFD-model at elevated stress levels, and highlights the potential of using echo-based models to capture highly transient flow events, as well as the ability of using simulation tools to study clinically complex phenomena. With larger patient studies planned for the future, and with the possibility of adding more anatomical features into the model framework, the current work demonstrates the potential of patient-specific CFD-models as a tool for quantifying 4D blood flow in the heart.

Estimation of skeletal movement of human locomotion from body surface shapes using dynamic spatial video camera (DSVC) and 4D human model.

PubMed

Saito, Toshikuni; Suzuki, Naoki; Hattori, Asaki; Suzuki, Shigeyuki; Hayashibe, Mitsuhiro; Otake, Yoshito

2006-01-01

We have been developing a DSVC (Dynamic Spatial Video Camera) system to measure and observe human locomotion quantitatively and freely. A 4D (four-dimensional) human model with detailed skeletal structure, joint, muscle, and motor functionality has been built. The purpose of our research was to estimate skeletal movements from body surface shapes using DSVC and the 4D human model. For this purpose, we constructed a body surface model of a subject and resized the standard 4D human model to match with geometrical features of the subject's body surface model. Software that integrates the DSVC system and the 4D human model, and allows dynamic skeletal state analysis from body surface movement data was also developed. We practically applied the developed system in dynamic skeletal state analysis of a lower limb in motion and were able to visualize the motion using geometrically resized standard 4D human model.

Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition.

PubMed

Moghadam, Saeed Montazeri; Seyyedsalehi, Seyyed Ali

2018-05-31

Nonlinear components extracted from deep structures of bottleneck neural networks exhibit a great ability to express input space in a low-dimensional manifold. Sharing and combining the components boost the capability of the neural networks to synthesize and interpolate new and imaginary data. This synthesis is possibly a simple model of imaginations in human brain where the components are expressed in a nonlinear low dimensional manifold. The current paper introduces a novel Dynamic Deep Bottleneck Neural Network to analyze and extract three main features of videos regarding the expression of emotions on the face. These main features are identity, emotion and expression intensity that are laid in three different sub-manifolds of one nonlinear general manifold. The proposed model enjoying the advantages of recurrent networks was used to analyze the sequence and dynamics of information in videos. It is noteworthy to mention that this model also has also the potential to synthesize new videos showing variations of one specific emotion on the face of unknown subjects. Experiments on discrimination and recognition ability of extracted components showed that the proposed model has an average of 97.77% accuracy in recognition of six prominent emotions (Fear, Surprise, Sadness, Anger, Disgust, and Happiness), and 78.17% accuracy in the recognition of intensity. The produced videos revealed variations from neutral to the apex of an emotion on the face of the unfamiliar test subject which is on average 0.8 similar to reference videos in the scale of the SSIM method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Stochastic Dynamics Underlying Cognitive Stability and Flexibility

PubMed Central

Ueltzhöffer, Kai; Armbruster-Genç, Diana J. N.; Fiebach, Christian J.

2015-01-01

Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences. PMID:26068119

Resting state networks in empirical and simulated dynamic functional connectivity.

PubMed

Glomb, Katharina; Ponce-Alvarez, Adrián; Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

2017-10-01

It is well-established that patterns of functional connectivity (FC) - measures of correlated activity between pairs of voxels or regions observed in the human brain using neuroimaging - are robustly expressed in spontaneous activity during rest. These patterns are not static, but exhibit complex spatio-temporal dynamics. Over the last years, a multitude of methods have been proposed to reveal these dynamics on the level of the whole brain. One finding is that the brain transitions through different FC configurations over time, and substantial effort has been put into characterizing these configurations. However, the dynamics governing these transitions are more elusive, specifically, the contribution of stationary vs. non-stationary dynamics is an active field of inquiry. In this study, we use a whole-brain approach, considering FC dynamics between 66 ROIs covering the entire cortex. We combine an innovative dimensionality reduction technique, tensor decomposition, with a mean field model which possesses stationary dynamics. It has been shown to explain resting state FC averaged over time and multiple subjects, however, this average FC summarizes the spatial distribution of correlations while hiding their temporal dynamics. First, we apply tensor decomposition to resting state scans from 24 healthy controls in order to characterize spatio-temporal dynamics present in the data. We simultaneously utilize temporal and spatial information by creating tensors that are subsequently decomposed into sets of brain regions ("communities") that share similar temporal dynamics, and their associated time courses. The tensors contain pairwise FC computed inside of overlapping sliding windows. Communities are discovered by clustering features pooled from all subjects, thereby ensuring that they generalize. We find that, on the group level, the data give rise to four distinct communities that resemble known resting state networks (RSNs): default mode network, visual network, control networks, and somatomotor network. Second, we simulate data with our stationary mean field model whose nodes are connected according to results from DTI and fiber tracking. In this model, all spatio-temporal structure is due to noisy fluctuations around the average FC. We analyze the simulated data in the same way as the empirical data in order to determine whether stationary dynamics can explain the emergence of distinct FC patterns (RSNs) which have their own time courses. We find that this is the case for all four networks using the spatio-temporal information revealed by tensor decomposition if nodes in the simulation are connected according to model-based effective connectivity. Furthermore, we find that these results require only a small part of the FC values, namely the highest values that occur across time and ROI pair. Our findings show that stationary dynamics can account for the emergence of RSNs. We provide an innovative method that does not make strong assumptions about the underlying data and is generally applicable to resting state or task data from different subject populations. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of thermal noise on the transitional dynamics of an inextensible elastic filament in stagnation flow.

PubMed

Deng, Mingge; Grinberg, Leopold; Caswell, Bruce; Karniadakis, George Em

2015-06-28

We investigate the dynamics of a single inextensible elastic filament subject to anisotropic friction in a viscous stagnation-point flow, by employing both a continuum model represented by Langevin type stochastic partial differential equations (SPDEs) and a dissipative particle dynamics (DPD) method. Unlike previous works, the filament is free to rotate and the tension along the filament is determined by the local inextensible constraint. The kinematics of the filament is recorded and studied with normal modes analysis. The results show that the filament displays an instability induced by negative tension, which is analogous to Euler buckling of a beam. Symmetry breaking of normal modes dynamics and stretch-coil transitions are observed above the threshold of the buckling instability point. Furthermore, both temporal and spatial noise are amplified resulting from the interaction of thermal fluctuations and nonlinear filament dynamics. Specifically, the spatial noise is amplified with even normal modes being excited due to symmetry breaking, while the temporal noise is amplified with increasing time correlation length and variance.

Shared internal models for feedforward and feedback control.

PubMed

Wagner, Mark J; Smith, Maurice A

2008-10-15

A child often learns to ride a bicycle in the driveway, free of unforeseen obstacles. Yet when she first rides in the street, we hope that if a car suddenly pulls out in front of her, she will combine her innate goal of avoiding an accident with her learned knowledge of the bicycle, and steer away or brake. In general, when we train to perform a new motor task, our learning is most robust if it updates the rules of online error correction to reflect the rules and goals of the new task. Here we provide direct evidence that, after a new feedforward motor adaptation, motor feedback responses to unanticipated errors become precisely task appropriate, even when such errors were never experienced during training. To study this ability, we asked how, if at all, do online responses to occasional, unanticipated force pulses during reaching arm movements change after adapting to altered arm dynamics? Specifically, do they change in a task-appropriate manner? In our task, subjects learned novel velocity-dependent dynamics. However, occasional force-pulse perturbations produced unanticipated changes in velocity. Therefore, after adaptation, task-appropriate responses to unanticipated pulses should compensate corresponding changes in velocity-dependent dynamics. We found that after adaptation, pulse responses precisely compensated these changes, although they were never trained to do so. These results provide evidence for a smart feedback controller which automatically produces responses specific to the learned dynamics of the current task. To accomplish this, the neural processes underlying feedback control must (1) be capable of accurate real-time state prediction for velocity via a forward model and (2) have access to recently learned changes in internal models of limb dynamics.

Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics

NASA Astrophysics Data System (ADS)

Valenza, Gaetano; Citi, Luca; Lanatá, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

2014-05-01

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis.

Revealing real-time emotional responses: a personalized assessment based on heartbeat dynamics.

PubMed

Valenza, Gaetano; Citi, Luca; Lanatá, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

2014-05-21

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis.

Generic solar photovoltaic system dynamic simulation model specification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas

This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intendedmore » to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.« less

A closed-loop hybrid physiological model relating to subjects under physical stress.

PubMed

El-Samahy, Emad; Mahfouf, Mahdi; Linkens, Derek A

2006-11-01

The objective of this research study is to derive a comprehensive physiological model relating to subjects under physical stress conditions. The model should describe the behaviour of the cardiovascular system, respiratory system, thermoregulation and brain activity in response to physical workload. An experimental testing rig was built which consists of recumbent high performance bicycle for inducing the physical load and a data acquisition system comprising monitors and PCs. The signals acquired and used within this study are the blood pressure, heart rate, respiration, body temperature, and EEG signals. The proposed model is based on a grey-box based modelling approach which was used because of the sufficient level of details it provides. Cardiovascular and EEG Data relating to 16 healthy subject volunteers (data from 12 subjects were used for training/validation and the data from 4 subjects were used for model testing) were collected using the Finapres and the ProComp+ monitors. For model validation, residual analysis via the computing of the confidence intervals as well as related histograms was performed. Closed-loop simulations for different subjects showed that the model can provide reliable predictions for heart rate, blood pressure, body temperature, respiration, and the EEG signals. These findings were also reinforced by the residual analyses data obtained, which suggested that the residuals were within the 90% confidence bands and that the corresponding histograms were of a normal distribution. A higher intelligent level was added to the model, based on neural networks, to extend the capabilities of the model to predict over a wide range of subjects dynamics. The elicited physiological model describing the effect of physiological stress on several physiological variables can be used to predict performance breakdown of operators in critical environments. Such a model architecture lends itself naturally to exploitation via feedback control in a 'reverse-engineering' fashion to control stress via the specification of a safe operating range for the psycho-physiological variables.

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

PubMed

Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles

2004-07-15

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

PubMed

Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

2016-04-01

Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. Copyright © 2016 Elsevier Inc. All rights reserved.

State-space model with deep learning for functional dynamics estimation in resting-state fMRI

PubMed Central

Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

2017-01-01

Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. PMID:26774612

Modeling BAS Dysregulation in Bipolar Disorder.

PubMed

Hamaker, Ellen L; Grasman, Raoul P P P; Kamphuis, Jan Henk

2016-08-01

Time series analysis is a technique that can be used to analyze the data from a single subject and has great potential to investigate clinically relevant processes like affect regulation. This article uses time series models to investigate the assumed dysregulation of affect that is associated with bipolar disorder. By formulating a number of alternative models that capture different kinds of theoretically predicted dysregulation, and by comparing these in both bipolar patients and controls, we aim to illustrate the heuristic potential this method of analysis has for clinical psychology. We argue that, not only can time series analysis elucidate specific maladaptive dynamics associated with psychopathology, it may also be clinically applied in symptom monitoring and the evaluation of therapeutic interventions.

Biomechanical simulation of vocal fold dynamics in adults based on laryngeal high-speed videoendoscopy

PubMed Central

Gómez, Pablo; Patel, Rita R.; Alexiou, Christoph; Bohr, Christopher; Schützenberger, Anne

2017-01-01

Motivation Human voice is generated in the larynx by the two oscillating vocal folds. Owing to the limited space and accessibility of the larynx, endoscopic investigation of the actual phonatory process in detail is challenging. Hence the biomechanics of the human phonatory process are still not yet fully understood. Therefore, we adapt a mathematical model of the vocal folds towards vocal fold oscillations to quantify gender and age related differences expressed by computed biomechanical model parameters. Methods The vocal fold dynamics are visualized by laryngeal high-speed videoendoscopy (4000 fps). A total of 33 healthy young subjects (16 females, 17 males) and 11 elderly subjects (5 females, 6 males) were recorded. A numerical two-mass model is adapted to the recorded vocal fold oscillations by varying model masses, stiffness and subglottal pressure. For adapting the model towards the recorded vocal fold dynamics, three different optimization algorithms (Nelder–Mead, Particle Swarm Optimization and Simulated Bee Colony) in combination with three cost functions were considered for applicability. Gender differences and age-related kinematic differences reflected by the model parameters were analyzed. Results and conclusion The biomechanical model in combination with numerical optimization techniques allowed phonatory behavior to be simulated and laryngeal parameters involved to be quantified. All three optimization algorithms showed promising results. However, only one cost function seems to be suitable for this optimization task. The gained model parameters reflect the phonatory biomechanics for men and women well and show quantitative age- and gender-specific differences. The model parameters for younger females and males showed lower subglottal pressures, lower stiffness and higher masses than the corresponding elderly groups. Females exhibited higher subglottal pressures, smaller oscillation masses and larger stiffness than the corresponding similar aged male groups. Optimizing numerical models towards vocal fold oscillations is useful to identify underlying laryngeal components controlling the phonatory process. PMID:29121085

A bidimensional finite mixture model for longitudinal data subject to dropout.

PubMed

Spagnoli, Alessandra; Marino, Maria Francesca; Alfò, Marco

2018-06-05

In longitudinal studies, subjects may be lost to follow up and, thus, present incomplete response sequences. When the mechanism underlying the dropout is nonignorable, we need to account for dependence between the longitudinal and the dropout process. We propose to model such a dependence through discrete latent effects, which are outcome-specific and account for heterogeneity in the univariate profiles. Dependence between profiles is introduced by using a probability matrix to describe the corresponding joint distribution. In this way, we separately model dependence within each outcome and dependence between outcomes. The major feature of this proposal, when compared with standard finite mixture models, is that it allows the nonignorable dropout model to properly nest its ignorable counterpart. We also discuss the use of an index of (local) sensitivity to nonignorability to investigate the effects that assumptions about the dropout process may have on model parameter estimates. The proposal is illustrated via the analysis of data from a longitudinal study on the dynamics of cognitive functioning in the elderly. Copyright © 2018 John Wiley & Sons, Ltd.

In vivo Loads in the Lumbar L3-4 Disc during a Weight Lifting Extension

PubMed Central

Wang, Shaobai; Park, Won Man; Kim, Yoon Hyuk; Cha, Thomas; Wood, Kirkham; Li, Guoan

2014-01-01

Background Knowledge of in vivo human lumbar loading is critical for understanding the lumbar function and for improving surgical treatments of lumbar pathology. Although numerous experimental measurements and computational simulations have been reported, non-invasive determination of in vivo spinal disc loads is still a challenge in biomedical engineering. The object of the study is to investigate the in vivo human lumbar disc loads using a subject-specific and kinematic driven finite element approach. Methods Three dimensional (3D) lumbar spine models of three living subjects were created using MR images. A 3D finite element model of the L3-4 disc, including the annulus fibrosus and nucleus pulposus, was built for each subject. The endplate kinematics of the L3-4 segment of each subject during a dynamic weight lifting extension was determined using a dual fluoroscopic imaging technique. The endplate kinematics was used as displacement boundary conditions of the subject specific finite element model of the L3-4 disc to calculate the in-vivo disc forces and moments during the weight lifting activity. Findings During the weight lifting extension, the L3-4 disc experienced maximum shear load of about 230 N or 0.34 bodyweight at the flexion position and maximum compressive load of 1500 N or 2.28 bodyweight at the upright position. The disc experienced a primary flexion-extension moment during the motion which reached a maximum of 4.2 Nm at upright position with stretched arms holding the weight. Interpretation This study provided quantitative data on in vivo disc loading that could help understand intrinsic biomechanics of the spine and improve surgical treatment of pathological discs using fusion or arthroplasty techniques. PMID:24345591

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

PubMed Central

Schöner, Gregor; Gail, Alexander

2012-01-01

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations. PMID:23166483

Sleep-Stage Dynamics in Patients with Chronic Fatigue Syndrome with or without Fibromyalgia

PubMed Central

Kishi, Akifumi; Natelson, Benjamin H.; Togo, Fumiharu; Struzik, Zbigniew R.; Rapoport, David M.; Yamamoto, Yoshiharu

2011-01-01

Study Objectives: Chronic fatigue syndrome (CFS) and fibromyalgia (FM) are medically unexplained conditions that often have overlapping symptoms, including sleep-related complaints. However, differences between the 2 conditions have been reported, and we hypothesized that dynamic aspects of sleep would be different in the 2 groups of patients. Participants: Subjects were 26 healthy control subjects, 14 patients with CFS but without FM (CFS alone), and 12 patients with CFS and FM (CFS+FM)—all women. Measurements and Results: We studied transition probabilities and rates between sleep stages (waking, rapid eye movement [REM] sleep, stage 1 [S1], stage 2 [S2], and slow-wave sleep [SWS]) and duration distributions of each sleep stage. We found that the probability of transition from REM sleep to waking was significantly greater in subjects with CFS alone than in control subjects, which may be the specific sleep problem for people with CFS alone. Probabilities of (a) transitions from waking, REM sleep, and S1 to S2 and (b) those from SWS to waking and S1 were significantly greater in subjects with CFS+FM than in control subjects; in addition, rates of these transitions were also significantly increased in subjects with CFS+FM. Result (a) might indicate increased sleep pressure in subjects with CFS+FM whereas result (b) may be the specific sleep problem of subjects with CFS+FM. We also found that shorter durations of S2 sleep are specific to patients with CFS+FM, not to CFS alone. Conclusions: These results suggest that CFS and FM may be different illnesses associated with different problems of sleep regulation. Citation: Kishi A; Natelson BH; Togo F; Struzik ZR; Rapoport DM; Yamamoto Y. Sleep-stage dynamics in patients with chronic fatigue syndrome with or without fibromyalgia. SLEEP 2011;34(11):1551-1560. PMID:22043126

Disruption to control network function correlates with altered dynamic connectivity in the wider autism spectrum.

PubMed

de Lacy, N; Doherty, D; King, B H; Rachakonda, S; Calhoun, V D

2017-01-01

Autism is a common developmental condition with a wide, variable range of co-occurring neuropsychiatric symptoms. Contrasting with most extant studies, we explored whole-brain functional organization at multiple levels simultaneously in a large subject group reflecting autism's clinical diversity, and present the first network-based analysis of transient brain states, or dynamic connectivity , in autism. Disruption to inter-network and inter-system connectivity, rather than within individual networks, predominated. We identified coupling disruption in the anterior-posterior default mode axis, and among specific control networks specialized for task start cues and the maintenance of domain-independent task positive status, specifically between the right fronto-parietal and cingulo-opercular networks and default mode network subsystems. These appear to propagate downstream in autism, with significantly dampened subject oscillations between brain states, and dynamic connectivity configuration differences. Our account proposes specific motifs that may provide candidates for neuroimaging biomarkers within heterogeneous clinical populations in this diverse condition.

Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.

PubMed

Fu, Michael J; Cavuşoğlu, M Cenk

2012-12-01

Haptic interface research benefits from accurate human arm models for control and system design. The literature contains many human arm dynamic models but lacks detailed variability analyses. Without accurate measurements, variability is modeled in a very conservative manner, leading to less than optimal controller and system designs. This paper not only presents models for human arm dynamics but also develops inter- and intrasubject variability models for a stylus-based haptic device. Data from 15 human subjects (nine male, six female, ages 20-32) were collected using a Phantom Premium 1.5a haptic device for system identification. In this paper, grip-force-dependent models were identified for 1-3-N grip forces in the three spatial axes. Also, variability due to human subjects and grip-force variation were modeled as both structured and unstructured uncertainties. For both forms of variability, the maximum variation, 95 %, and 67 % confidence interval limits were examined. All models were in the frequency domain with force as input and position as output. The identified models enable precise controllers targeted to a subset of possible human operator dynamics.

Modeling Academic Education Processes by Dynamic Storyboarding

ERIC Educational Resources Information Center

Sakurai, Yoshitaka; Dohi, Shinichi; Tsuruta, Setsuo; Knauf, Rainer

2009-01-01

In high-level education such as university studies, there is a flexible but complicated system of subject offerings and registration rules such as prerequisite subjects. Those offerings, connected with registration rules, should be matched to the students' learning needs and desires, which change dynamically. Students need assistance in such a…

Analyzing the effect of carbon fiber reinforced polymer on the crashworthiness of aluminum square hollow beam for crash box application

NASA Astrophysics Data System (ADS)

Raman, R.; Jayanth, K.; Sarkar, I.; Ravi, K.

2017-11-01

Crashworthiness of a material is a measure of its ability to absorb energy during a crash. A well-designed crash box is instrumental in protecting the costly vehicle components. A square, hollow, hybrid beam of aluminum/CFRP was subjected to dynamic axial load to analyze the effect of five different lay-up sequences on its crashworthiness. The beam was placed between two plates. Boundary conditions were imposed on them to simulate a frontal body crash test model. Modeling and dynamic analysis of composite structures was done on ABAQUS. Different orientation of carbon fibers varies the crashworthiness of the hybrid beam. Addition of CFRP layer showed clear improvement in specific energy absorption and crush force efficiency compared to pure aluminum beam. Two layers of CFRP oriented at 90° on Aluminum showed 52% increase in CFE.

Directional asymmetries and age effects in human self-motion perception.

PubMed

Roditi, Rachel E; Crane, Benjamin T

2012-06-01

Directional asymmetries in vestibular reflexes have aided the diagnosis of vestibular lesions; however, potential asymmetries in vestibular perception have not been well defined. This investigation sought to measure potential asymmetries in human vestibular perception. Vestibular perception thresholds were measured in 24 healthy human subjects between the ages of 21 and 68 years. Stimuli consisted of a single cycle of sinusoidal acceleration in a single direction lasting 1 or 2 s (1 or 0.5 Hz), delivered in sway (left-right), surge (forward-backward), heave (up-down), or yaw rotation. Subject identified self-motion directions were analyzed using a forced choice technique, which permitted thresholds to be independently determined for each direction. Non-motion stimuli were presented to measure possible response bias. A significant directional asymmetry in the dynamic response occurred in 27% of conditions tested within subjects, and in at least one type of motion in 92% of subjects. Directional asymmetries were usually consistent when retested in the same subject but did not occur consistently in one direction across the population with the exception of heave at 0.5 Hz. Responses during null stimuli presentation suggested that asymmetries were not due to biased guessing. Multiple models were applied and compared to determine if sensitivities were direction specific. Using Akaike information criterion, it was found that the model with direction specific sensitivities better described the data in 86% of runs when compared with a model that used the same sensitivity for both directions. Mean thresholds for yaw were 1.3±0.9°/s at 0.5 Hz and 0.9±0.7°/s at 1 Hz and were independent of age. Thresholds for surge and sway were 1.7±0.8 cm/s at 0.5 Hz and 0.7±0.3 cm/s at 1.0 Hz for subjects <50 and were significantly higher in subjects >50 years old. Heave thresholds were higher and were independent of age.

Gender Dimorphic ACL Strain In Response to Combined Dynamic 3D Knee Joint Loading: Implications for ACL Injury Risk

PubMed Central

Mizuno, Kiyonori; Andrish, Jack T.; van den Bogert, Antonie J.; McLean, Scott G.

2009-01-01

While gender-based differences in knee joint anatomies/laxities are well documented, the potential for them to precipitate gender-dimorphic ACL loading and resultant injury risk has not been considered. To this end, we generated gender-specific models of ACL strain as a function of any six degrees of freedom (6DOF) knee joint load state via a combined cadaveric and analytical approach. Continuously varying joint forces and torques were applied to five male and five female cadaveric specimens and recorded along with synchronous knee flexion and ACL strain data. All data (~10,000 samples) were submitted to specimen-specific regression analyses, affording ACL strain predictions as a function of the combined 6 DOF knee loads. Following individual model verifications, generalized gender-specific models were generated and subjected to 6 DOF external load scenarios consistent with both a clinical examination and a dynamic sports maneuver. The ensuing model-based strain predictions were subsequently examined for gender-based discrepancies. Male and female specimen specific models predicted ACL strain within 0.51% ± 0.10% and 0.52% ± 0.07% of the measured data respectively, and explained more than 75% of the associated variance in each case. Predicted female ACL strains were also significantly larger than respective male values for both of simulated 6 DOF load scenarios. Outcomes suggest that the female ACL will rupture in response to comparatively smaller external load applications. Future work must address the underlying anatomical/laxity contributions to knee joint mechanical and resultant ACL loading, ultimately affording prevention strategies that may cater to individual joint vulnerabilities. PMID:19464897

Insights into channel dysfunction from modelling and molecular dynamics simulations.

PubMed

Musgaard, Maria; Paramo, Teresa; Domicevica, Laura; Andersen, Ole Juul; Biggin, Philip C

2018-04-01

Developments in structural biology mean that the number of different ion channel structures has increased significantly in recent years. Structures of ion channels enable us to rationalize how mutations may lead to channelopathies. However, determining the structures of ion channels is still not trivial, especially as they necessarily exist in many distinct functional states. Therefore, the use of computational modelling can provide complementary information that can refine working hypotheses of both wild type and mutant ion channels. The simplest but still powerful tool is homology modelling. Many structures are available now that can provide suitable templates for many different types of ion channels, allowing a full three-dimensional interpretation of mutational effects. These structural models, and indeed the structures themselves obtained by X-ray crystallography, and more recently cryo-electron microscopy, can be subjected to molecular dynamics simulations, either as a tool to help explore the conformational dynamics in detail or simply as a means to refine the models further. Here we review how these approaches have been used to improve our understanding of how diseases might be linked to specific mutations in ion channel proteins. This article is part of the Special Issue entitled 'Channelopathies.' Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identification of Potent Virtual Leads Specific to S1' Loop of ADAMTS4: Pharmacophore Modeling, 3D-QSAR, Molecular Docking and Dynamic Studies.

PubMed

Suganya, P Rathi; Kalva, Sukesh; Saleena, Lilly M

2016-01-01

ADAMTS4 (Aggrecanase-1) is an important enzyme, which belongs to ADAMTS family. Aggrecanase-1 is involved in aggrecan degradation of articular cartilage in osteoarthritis and rheumatoid arthritis. Overall variability of S1' domain of ADAMTS4 has been the main selectivity determinant to design the unique inhibitors. 34 inhibitors from Binding database and literature were used to develop the pharmacophore model. The five featured pharmacophore model AHHRR had the best survival score of 3.493 and post-hoc score of 2.545, indicating that the model is highly reliable. The 3D-QSAR acquired had excellent r(2) value of 0.99 and GH score of 0.839. The validated pharmacophore model was used for insilico screening of Asinex and ZINC database for finding the potential lead compounds. ZINC00987406 and ASN04459656 which pose high glide score i.e >7 Kcal/mol and H-bond and hydrophobic interactions in the S1'loop residues of ADAMTS4 were subjected to Molecular Dynamics Simulation studies. Molecular dynamic simulation result indicates that the RMSD and RMSF of backbone atoms for the above complexes were within the limit of 2.0 A˚. These compounds can be potential candidates for osteoarthritis by inhibiting ADAMTS4.

Polarization and dynamical properties of VCSELs-based photonic neuron subject to optical pulse injection

NASA Astrophysics Data System (ADS)

Xiang, Shuiying; Wen, Aijun; Zhang, Hao; Li, Jiafu; Guo, Xingxing; Shang, Lei; Lin, Lin

2016-11-01

The polarization-resolved nonlinear dynamics of vertical-cavity surface-emitting lasers (VCSELs) subject to orthogonally polarized optical pulse injection are investigated numerically based on the spin flip model. By extensive numerical bifurcation analysis, the responses dynamics of photonic neuron based on VCSELs under the arrival of external stimuli of orthogonally polarized optical pulse injection are mainly discussed. It is found that, several neuron-like dynamics, such as phasic spiking of a single abrupt large amplitude pulse followed with or without subthreshold oscillation, and tonic spiking with multiple periodic pulses, are successfully reproduced in the numerical model of VCSELs. Besides, the effects of stimuli strength, pump current, frequency detuning, as well as the linewidth enhancement factor on the neuron-like response dynamics are examined carefully. The operating parameters ranges corresponding to different neuron-like dynamics are further identified. Thus, the numerical model and simulation results are very useful and interesting for the ultrafast brain-inspired neuromorphic photonics systems based on VCSELs.

Software life cycle dynamic simulation model: The organizational performance submodel

NASA Technical Reports Server (NTRS)

Tausworthe, Robert C.

1985-01-01

The submodel structure of a software life cycle dynamic simulation model is described. The software process is divided into seven phases, each with product, staff, and funding flows. The model is subdivided into an organizational response submodel, a management submodel, a management influence interface, and a model analyst interface. The concentration here is on the organizational response model, which simulates the performance characteristics of a software development subject to external and internal influences. These influences emanate from two sources: the model analyst interface, which configures the model to simulate the response of an implementing organization subject to its own internal influences, and the management submodel that exerts external dynamic control over the production process. A complete characterization is given of the organizational response submodel in the form of parameterized differential equations governing product, staffing, and funding levels. The parameter values and functions are allocated to the two interfaces.

Estimation method of finger tapping dynamics using simple magnetic detection system

NASA Astrophysics Data System (ADS)

Kandori, Akihiko; Sano, Yuko; Miyashita, Tsuyoshi; Okada, Yoshihisa; Irokawa, Masataka; Shima, Keisuke; Tsuji, Toshio; Yokoe, Masaru; Sakoda, Saburo

2010-05-01

We have developed the simple estimation method of a finger tapping dynamics model for investigating muscle resistance and stiffness during tapping movement in normal subjects. We measured finger tapping movements of 207 normal subjects using a magnetic finger tapping detection system. Each subject tapped two fingers in time with a metronome at 1, 2, 3, 4, and 5 Hz. The velocity and acceleration values for both the closing and opening tapping data were used to estimate a finger tapping dynamics model. Using the frequency response of the ratio of acceleration to velocity of the mechanical impedance parameters, we estimated the resistance (friction coefficient) and compliance (stiffness). We found two dynamics models for the maximum open position and tap position. In the maximum open position, the extensor muscle resistance was twice as high as the flexor muscle resistance and males had a higher spring constant. In the tap position, the flexor muscle resistance was much higher than the extensor muscle resistance. This indicates that the tapping dynamics in the maximum open position are controlled by the balance of extensor and flexor muscle friction resistances and the flexor stiffness, and the flexor friction resistance is the main component in the tap position. It can be concluded that our estimation method makes it possible to understand the tapping dynamics.

Estimation method of finger tapping dynamics using simple magnetic detection system.

PubMed

Kandori, Akihiko; Sano, Yuko; Miyashita, Tsuyoshi; Okada, Yoshihisa; Irokawa, Masataka; Shima, Keisuke; Tsuji, Toshio; Yokoe, Masaru; Sakoda, Saburo

2010-05-01

We have developed the simple estimation method of a finger tapping dynamics model for investigating muscle resistance and stiffness during tapping movement in normal subjects. We measured finger tapping movements of 207 normal subjects using a magnetic finger tapping detection system. Each subject tapped two fingers in time with a metronome at 1, 2, 3, 4, and 5 Hz. The velocity and acceleration values for both the closing and opening tapping data were used to estimate a finger tapping dynamics model. Using the frequency response of the ratio of acceleration to velocity of the mechanical impedance parameters, we estimated the resistance (friction coefficient) and compliance (stiffness). We found two dynamics models for the maximum open position and tap position. In the maximum open position, the extensor muscle resistance was twice as high as the flexor muscle resistance and males had a higher spring constant. In the tap position, the flexor muscle resistance was much higher than the extensor muscle resistance. This indicates that the tapping dynamics in the maximum open position are controlled by the balance of extensor and flexor muscle friction resistances and the flexor stiffness, and the flexor friction resistance is the main component in the tap position. It can be concluded that our estimation method makes it possible to understand the tapping dynamics.

Symbolic dynamics marker of heart rate variability combined with clinical variables enhance obstructive sleep apnea screening

NASA Astrophysics Data System (ADS)

Ravelo-García, A. G.; Saavedra-Santana, P.; Juliá-Serdá, G.; Navarro-Mesa, J. L.; Navarro-Esteva, J.; Álvarez-López, X.; Gapelyuk, A.; Penzel, T.; Wessel, N.

2014-06-01

Many sleep centres try to perform a reduced portable test in order to decrease the number of overnight polysomnographies that are expensive, time-consuming, and disturbing. With some limitations, heart rate variability (HRV) has been useful in this task. The aim of this investigation was to evaluate if inclusion of symbolic dynamics variables to a logistic regression model integrating clinical and physical variables, can improve the detection of subjects for further polysomnographies. To our knowledge, this is the first contribution that innovates in that strategy. A group of 133 patients has been referred to the sleep center for suspected sleep apnea. Clinical assessment of the patients consisted of a sleep related questionnaire and a physical examination. The clinical variables related to apnea and selected in the statistical model were age (p < 10-3), neck circumference (p < 10-3), score on a questionnaire scale intended to quantify daytime sleepiness (p < 10-3), and intensity of snoring (p < 10-3). The validation of this model demonstrated an increase in classification performance when a variable based on non-linear dynamics of HRV (p < 0.01) was used additionally to the other variables. For diagnostic rule based only on clinical and physical variables, the corresponding area under the receiver operating characteristic (ROC) curve was 0.907 (95% confidence interval (CI) = 0.848, 0.967), (sensitivity 87.10% and specificity 80%). For the model including the average of a symbolic dynamic variable, the area under the ROC curve was increased to 0.941 (95% = 0.897, 0.985), (sensitivity 88.71% and specificity 82.86%). In conclusion, symbolic dynamics, coupled with significant clinical and physical variables can help to prioritize polysomnographies in patients with a high probability of apnea. In addition, the processing of the HRV is a well established low cost and robust technique.

Decision Criterion Dynamics in Animals Performing an Auditory Detection Task

PubMed Central

Mill, Robert W.; Alves-Pinto, Ana; Sumner, Christian J.

2014-01-01

Classical signal detection theory attributes bias in perceptual decisions to a threshold criterion, against which sensory excitation is compared. The optimal criterion setting depends on the signal level, which may vary over time, and about which the subject is naïve. Consequently, the subject must optimise its threshold by responding appropriately to feedback. Here a series of experiments was conducted, and a computational model applied, to determine how the decision bias of the ferret in an auditory signal detection task tracks changes in the stimulus level. The time scales of criterion dynamics were investigated by means of a yes-no signal-in-noise detection task, in which trials were grouped into blocks that alternately contained easy- and hard-to-detect signals. The responses of the ferrets implied both long- and short-term criterion dynamics. The animals exhibited a bias in favour of responding “yes” during blocks of harder trials, and vice versa. Moreover, the outcome of each single trial had a strong influence on the decision at the next trial. We demonstrate that the single-trial and block-level changes in bias are a manifestation of the same criterion update policy by fitting a model, in which the criterion is shifted by fixed amounts according to the outcome of the previous trial and decays strongly towards a resting value. The apparent block-level stabilisation of bias arises as the probabilities of outcomes and shifts on single trials mutually interact to establish equilibrium. To gain an intuition into how stable criterion distributions arise from specific parameter sets we develop a Markov model which accounts for the dynamic effects of criterion shifts. Our approach provides a framework for investigating the dynamics of decisions at different timescales in other species (e.g., humans) and in other psychological domains (e.g., vision, memory). PMID:25485733

Inferring Muscle-Tendon Unit Power from Ankle Joint Power during the Push-Off Phase of Human Walking: Insights from a Multiarticular EMG-Driven Model

PubMed Central

2016-01-01

Introduction Inverse dynamics joint kinetics are often used to infer contributions from underlying groups of muscle-tendon units (MTUs). However, such interpretations are confounded by multiarticular (multi-joint) musculature, which can cause inverse dynamics to over- or under-estimate net MTU power. Misestimation of MTU power could lead to incorrect scientific conclusions, or to empirical estimates that misguide musculoskeletal simulations, assistive device designs, or clinical interventions. The objective of this study was to investigate the degree to which ankle joint power overestimates net plantarflexor MTU power during the Push-off phase of walking, due to the behavior of the flexor digitorum and hallucis longus (FDHL)–multiarticular MTUs crossing the ankle and metatarsophalangeal (toe) joints. Methods We performed a gait analysis study on six healthy participants, recording ground reaction forces, kinematics, and electromyography (EMG). Empirical data were input into an EMG-driven musculoskeletal model to estimate ankle power. This model enabled us to parse contributions from mono- and multi-articular MTUs, and required only one scaling and one time delay factor for each subject and speed, which were solved for based on empirical data. Net plantarflexing MTU power was computed by the model and quantitatively compared to inverse dynamics ankle power. Results The EMG-driven model was able to reproduce inverse dynamics ankle power across a range of gait speeds (R2 ≥ 0.97), while also providing MTU-specific power estimates. We found that FDHL dynamics caused ankle power to slightly overestimate net plantarflexor MTU power, but only by ~2–7%. Conclusions During Push-off, FDHL MTU dynamics do not substantially confound the inference of net plantarflexor MTU power from inverse dynamics ankle power. However, other methodological limitations may cause inverse dynamics to overestimate net MTU power; for instance, due to rigid-body foot assumptions. Moving forward, the EMG-driven modeling approach presented could be applied to understand other tasks or larger multiarticular MTUs. PMID:27764110

Inferring Muscle-Tendon Unit Power from Ankle Joint Power during the Push-Off Phase of Human Walking: Insights from a Multiarticular EMG-Driven Model.

PubMed

Honert, Eric C; Zelik, Karl E

2016-01-01

Inverse dynamics joint kinetics are often used to infer contributions from underlying groups of muscle-tendon units (MTUs). However, such interpretations are confounded by multiarticular (multi-joint) musculature, which can cause inverse dynamics to over- or under-estimate net MTU power. Misestimation of MTU power could lead to incorrect scientific conclusions, or to empirical estimates that misguide musculoskeletal simulations, assistive device designs, or clinical interventions. The objective of this study was to investigate the degree to which ankle joint power overestimates net plantarflexor MTU power during the Push-off phase of walking, due to the behavior of the flexor digitorum and hallucis longus (FDHL)-multiarticular MTUs crossing the ankle and metatarsophalangeal (toe) joints. We performed a gait analysis study on six healthy participants, recording ground reaction forces, kinematics, and electromyography (EMG). Empirical data were input into an EMG-driven musculoskeletal model to estimate ankle power. This model enabled us to parse contributions from mono- and multi-articular MTUs, and required only one scaling and one time delay factor for each subject and speed, which were solved for based on empirical data. Net plantarflexing MTU power was computed by the model and quantitatively compared to inverse dynamics ankle power. The EMG-driven model was able to reproduce inverse dynamics ankle power across a range of gait speeds (R2 ≥ 0.97), while also providing MTU-specific power estimates. We found that FDHL dynamics caused ankle power to slightly overestimate net plantarflexor MTU power, but only by ~2-7%. During Push-off, FDHL MTU dynamics do not substantially confound the inference of net plantarflexor MTU power from inverse dynamics ankle power. However, other methodological limitations may cause inverse dynamics to overestimate net MTU power; for instance, due to rigid-body foot assumptions. Moving forward, the EMG-driven modeling approach presented could be applied to understand other tasks or larger multiarticular MTUs.

Noninvasive estimation of pharyngeal airway resistance and compliance in children based on volume-gated dynamic MRI and computational fluid dynamics.

PubMed

Persak, Steven C; Sin, Sanghun; McDonough, Joseph M; Arens, Raanan; Wootton, David M

2011-12-01

Computational fluid dynamics (CFD) analysis was used to model the effect of collapsing airway geometry on internal pressure and velocity in the pharyngeal airway of three sedated children with obstructive sleep apnea syndrome (OSAS) and three control subjects. Model geometry was reconstructed from volume-gated magnetic resonance images during normal tidal breathing at 10 increments of tidal volume through the respiratory cycle. Each geometry was meshed with an unstructured grid and solved using a low-Reynolds number k-ω turbulence model driven by flow data averaged over 12 consecutive breathing cycles. Combining gated imaging with CFD modeling created a dynamic three-dimensional view of airway anatomy and mechanics, including the evolution of airway collapse and flow resistance and estimates of the local effective compliance. The upper airways of subjects with OSAS were generally much more compliant during tidal breathing. Compliance curves (pressure vs. cross-section area), derived for different locations along the airway, quantified local differences along the pharynx and between OSAS subjects. In one subject, the distal oropharynx was more compliant than the nasopharynx (1.028 vs. 0.450 mm(2)/Pa) and had a lower theoretical limiting flow rate, confirming the distal oropharynx as the flow-limiting segment of the airway in this subject. Another subject had a more compliant nasopharynx (0.053 mm(2)/Pa) during inspiration and apparent stiffening of the distal oropharynx (C = 0.0058 mm(2)/Pa), and the theoretical limiting flow rate indicated the nasopharynx as the flow-limiting segment. This new method may help to differentiate anatomical and functional factors in airway collapse.

Self-Organized Behavior Generation for Musculoskeletal Robots.

PubMed

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.

Self-Organized Behavior Generation for Musculoskeletal Robots

PubMed Central

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors “waiting” to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics. PMID:28360852

Using Innovative Outliers to Detect Discrete Shifts in Dynamics in Group-Based State-Space Models

ERIC Educational Resources Information Center

Chow, Sy-Miin; Hamaker, Ellen L.; Allaire, Jason C.

2009-01-01

Outliers are typically regarded as data anomalies that should be discarded. However, dynamic or "innovative" outliers can be appropriately utilized to capture unusual but substantively meaningful shifts in a system's dynamics. We extend De Jong and Penzer's 1998 approach for representing outliers in single-subject state-space models to a…

EEG classification of emotions using emotion-specific brain functional network.

PubMed

Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

2015-08-01

The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.

Dynamic balance control in elders: gait initiation assessment as a screening tool

NASA Technical Reports Server (NTRS)

Chang, H.; Krebs, D. E.; Wall, C. C. (Principal Investigator)

1999-01-01

OBJECTIVE: To determine whether measurements of center of gravity-center of pressure separation (CG-CP moment arm) during gait initiation can differentiate healthy from disabled subjects with sufficient specificity and sensitivity to be useful as a screening test for dynamic balance in elderly patients. SUBJECTS: Three groups of elderly subjects (age, 74.97+/-6.56 yrs): healthy elders (HE, n = 21), disabled elders (DE, n = 20), and elders with vestibular hypofunction (VH, n = 18). DESIGN: Cross-sectional, intact-groups research design. Peak CG-CP moment arm measures how far the subject will tolerate the whole-body CG to deviate from the ground reaction force's CP; it represents dynamic balance control. Screening test cutoff points at 16 to 18 cm peak CG-CP moment arm predicted group membership. RESULTS: The magnitude of peak CG-CP moment arm was significantly greater in HE than in DE and VH subjects (p<.01) and was not different between the DE and VH groups. The peak CG-CP moment arm occurred at the end of single stance phase in all groups. As a screening test, the peak moment arm has greater than 50% sensitivity and specificity to discriminate the HE group from the DE and VH groups with peak CG-CP moment arm cutoff points between 16 and 18 cm. CONCLUSIONS: Examining dynamic balance through the use of the CG-CP moment arm during single stance in gait initiation discriminates between nondisabled and disabled older persons and warrants further investigation as a potential tool to identify people with balance dysfunction.

Specific Non-Local Interactions Are Not Necessary for Recovering Native Protein Dynamics

PubMed Central

Dasgupta, Bhaskar; Kasahara, Kota; Kamiya, Narutoshi; Nakamura, Haruki; Kinjo, Akira R.

2014-01-01

The elastic network model (ENM) is a widely used method to study native protein dynamics by normal mode analysis (NMA). In ENM we need information about all pairwise distances, and the distance between contacting atoms is restrained to the native value. Therefore ENM requires O(N2) information to realize its dynamics for a protein consisting of N amino acid residues. To see if (or to what extent) such a large amount of specific structural information is required to realize native protein dynamics, here we introduce a novel model based on only O(N) restraints. This model, named the ‘contact number diffusion’ model (CND), includes specific distance restraints for only local (along the amino acid sequence) atom pairs, and semi-specific non-local restraints imposed on each atom, rather than atom pairs. The semi-specific non-local restraints are defined in terms of the non-local contact numbers of atoms. The CND model exhibits the dynamic characteristics comparable to ENM and more correlated with the explicit-solvent molecular dynamics simulation than ENM. Moreover, unrealistic surface fluctuations often observed in ENM were suppressed in CND. On the other hand, in some ligand-bound structures CND showed larger fluctuations of buried protein atoms interacting with the ligand compared to ENM. In addition, fluctuations from CND and ENM show comparable correlations with the experimental B-factor. Although there are some indications of the importance of some specific non-local interactions, the semi-specific non-local interactions are mostly sufficient for reproducing the native protein dynamics. PMID:24625758

Non-linear dynamical classification of short time series of the rössler system in high noise regimes.

PubMed

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E; Poizner, Howard; Sejnowski, Terrence J

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson's disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to -30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A' under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data.

Non-Linear Dynamical Classification of Short Time Series of the Rössler System in High Noise Regimes

PubMed Central

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E.; Poizner, Howard; Sejnowski, Terrence J.

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson’s disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to −30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A′ under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data. PMID:24379798

Stochastic simulation of ecohydrological interactions between vegetation and groundwater

NASA Astrophysics Data System (ADS)

Dwelle, M. C.; Ivanov, V. Y.; Sargsyan, K.

2017-12-01

The complex interactions between groundwater and vegetation in the Amazon rainforest may yield vital ecophysiological interactions in specific landscape niches such as buffering plant water stress during dry season or suppression of water uptake due to anoxic conditions. Representation of such processes is greatly impacted by both external and internal sources of uncertainty: inaccurate data and subjective choice of model representation. The models that can simulate these processes are complex and computationally expensive, and therefore make it difficult to address uncertainty using traditional methods. We use the ecohydrologic model tRIBS+VEGGIE and a novel uncertainty quantification framework applied to the ZF2 watershed near Manaus, Brazil. We showcase the capability of this framework for stochastic simulation of vegetation-hydrology dynamics. This framework is useful for simulation with internal and external stochasticity, but this work will focus on internal variability of groundwater depth distribution and model parameterizations. We demonstrate the capability of this framework to make inferences on uncertain states of groundwater depth from limited in situ data, and how the realizations of these inferences affect the ecohydrological interactions between groundwater dynamics and vegetation function. We place an emphasis on the probabilistic representation of quantities of interest and how this impacts the understanding and interpretation of the dynamics at the groundwater-vegetation interface.

The Cirque du Soleil of Golgi membrane dynamics

PubMed Central

2009-01-01

The role of lipid metabolic enzymes in Golgi membrane remodeling is a subject of intense interest. Now, in this issue, Schmidt and Brown (2009. J. Cell Biol. doi:10.1083/jcb.200904147) report that lysophosphatidic acid–specific acyltransferase, LPAAT3, contributes to Golgi membrane dynamics by suppressing tubule formation. PMID:19635838

The Cirque du Soleil of Golgi membrane dynamics.

PubMed

Bankaitis, Vytas A

2009-07-27

The role of lipid metabolic enzymes in Golgi membrane remodeling is a subject of intense interest. Now, in this issue, Schmidt and Brown (2009. J. Cell Biol. doi:10.1083/jcb.200904147) report that lysophosphatidic acid-specific acyltransferase, LPAAT3, contributes to Golgi membrane dynamics by suppressing tubule formation.

A multi-segment foot model based on anatomically registered technical coordinate systems: method repeatability in pediatric feet.

PubMed

Saraswat, Prabhav; MacWilliams, Bruce A; Davis, Roy B

2012-04-01

Several multi-segment foot models to measure the motion of intrinsic joints of the foot have been reported. Use of these models in clinical decision making is limited due to lack of rigorous validation including inter-clinician, and inter-lab variability measures. A model with thoroughly quantified variability may significantly improve the confidence in the results of such foot models. This study proposes a new clinical foot model with the underlying strategy of using separate anatomic and technical marker configurations and coordinate systems. Anatomical landmark and coordinate system identification is determined during a static subject calibration. Technical markers are located at optimal sites for dynamic motion tracking. The model is comprised of the tibia and three foot segments (hindfoot, forefoot and hallux) and inter-segmental joint angles are computed in three planes. Data collection was carried out on pediatric subjects at two sites (Site 1: n=10 subjects by two clinicians and Site 2: five subjects by one clinician). A plaster mold method was used to quantify static intra-clinician and inter-clinician marker placement variability by allowing direct comparisons of marker data between sessions for each subject. Intra-clinician and inter-clinician joint angle variability were less than 4°. For dynamic walking kinematics, intra-clinician, inter-clinician and inter-laboratory variability were less than 6° for the ankle and forefoot, but slightly higher for the hallux. Inter-trial variability accounted for 2-4° of the total dynamic variability. Results indicate the proposed foot model reduces the effects of marker placement variability on computed foot kinematics during walking compared to similar measures in previous models. Copyright © 2011 Elsevier B.V. All rights reserved.

Estimation of effective connectivity via data-driven neural modeling

PubMed Central

Freestone, Dean R.; Karoly, Philippa J.; Nešić, Dragan; Aram, Parham; Cook, Mark J.; Grayden, David B.

2014-01-01

This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination. PMID:25506315

General contrast effects in speech perception: effect of preceding liquid on stop consonant identification.

PubMed

Lotto, A J; Kluender, K R

1998-05-01

When members of a series of synthesized stop consonants varying acoustically in F3 characteristics and varying perceptually from /da/ to /ga/ are preceded by /al/, subjects report hearing more /ga/ syllables relative to when each member is preceded by /ar/ (Mann, 1980). It has been suggested that this result demonstrates the existence of a mechanism that compensates for coarticulation via tacit knowledge of articulatory dynamics and constraints, or through perceptual recovery of vocal-tract dynamics. The present study was designed to assess the degree to which these perceptual effects are specific to qualities of human articulatory sources. In three experiments, series of consonant-vowel (CV) stimuli varying in F3-onset frequency (/da/-/ga/) were preceded by speech versions or nonspeech analogues of /al/ and /ar/. The effect of liquid identity on stop consonant labeling remained when the preceding VC was produced by a female speaker and the CV syllable was modeled after a male speaker's productions. Labeling boundaries also shifted when the CV was preceded by a sine wave glide modeled after F3 characteristics of /al/ and /ar/. Identifications shifted even when the preceding sine wave was of constant frequency equal to the offset frequency of F3 from a natural production. These results suggest an explanation in terms of general auditory processes as opposed to recovery of or knowledge of specific articulatory dynamics.

Neural correlates of the perception of dynamic versus static facial expressions of emotion.

PubMed

Kessler, Henrik; Doyen-Waldecker, Cornelia; Hofer, Christian; Hoffmann, Holger; Traue, Harald C; Abler, Birgit

2011-04-20

This study investigated brain areas involved in the perception of dynamic facial expressions of emotion. A group of 30 healthy subjects was measured with fMRI when passively viewing prototypical facial expressions of fear, disgust, sadness and happiness. Using morphing techniques, all faces were displayed as still images and also dynamically as a film clip with the expressions evolving from neutral to emotional. Irrespective of a specific emotion, dynamic stimuli selectively activated bilateral superior temporal sulcus, visual area V5, fusiform gyrus, thalamus and other frontal and parietal areas. Interaction effects of emotion and mode of presentation (static/dynamic) were only found for the expression of happiness, where static faces evoked greater activity in the medial prefrontal cortex. Our results confirm previous findings on neural correlates of the perception of dynamic facial expressions and are in line with studies showing the importance of the superior temporal sulcus and V5 in the perception of biological motion. Differential activation in the fusiform gyrus for dynamic stimuli stands in contrast to classical models of face perception but is coherent with new findings arguing for a more general role of the fusiform gyrus in the processing of socially relevant stimuli.

Incorporating spatial constraint in co-activation pattern analysis to explore the dynamics of resting-state networks: An application to Parkinson's disease.

PubMed

Zhuang, Xiaowei; Walsh, Ryan R; Sreenivasan, Karthik; Yang, Zhengshi; Mishra, Virendra; Cordes, Dietmar

2018-05-15

The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD. Copyright © 2018 Elsevier Inc. All rights reserved.

DNA breathing dynamics distinguish binding from nonbinding consensus sites for transcription factor YY1 in cells.

PubMed

Alexandrov, Boian S; Fukuyo, Yayoi; Lange, Martin; Horikoshi, Nobuo; Gelev, Vladimir; Rasmussen, Kim Ø; Bishop, Alan R; Usheva, Anny

2012-11-01

The genome-wide mapping of the major gene expression regulators, the transcription factors (TFs) and their DNA binding sites, is of great importance for describing cellular behavior and phenotypic diversity. Presently, the methods for prediction of genomic TF binding produce a large number of false positives, most likely due to insufficient description of the physiochemical mechanisms of protein-DNA binding. Growing evidence suggests that, in the cell, the double-stranded DNA (dsDNA) is subject to local transient strands separations (breathing) that contribute to genomic functions. By using site-specific chromatin immunopecipitations, gel shifts, BIOBASE data, and our model that accurately describes the melting behavior and breathing dynamics of dsDNA we report a specific DNA breathing profile found at YY1 binding sites in cells. We find that the genomic flanking sequence variations and SNPs, may exert long-range effects on DNA dynamics and predetermine YY1 binding. The ubiquitous TF YY1 has a fundamental role in essential biological processes by activating, initiating or repressing transcription depending upon the sequence context it binds. We anticipate that consensus binding sequences together with the related DNA dynamics profile may significantly improve the accuracy of genomic TF binding sites and TF binding-related functional SNPs.

Qualitative models of seat discomfort including static and dynamic factors.

PubMed

Ebe, K; Griffin, M J

2000-06-01

Judgements of overall seating comfort in dynamic conditions sometimes correlate better with the static characteristics of a seat than with measures of the dynamic environment. This study developed qualitative models of overall seat discomfort to include both static and dynamic seat characteristics. A dynamic factor that reflected how vibration discomfort increased as vibration magnitude increased was combined with a static seat factor which reflected seating comfort without vibration. The ability of the model to predict the relative and overall importance of dynamic and static seat characteristics on comfort was tested in two experiments. A paired comparison experiment, using four polyurethane foam cushions (50, 70, 100, 120 mm thick), provided different static and dynamic comfort when 12 subjects were exposed to one-third octave band random vertical vibration with centre frequencies of 2.5 and 5.5 Hz, at magnitudes of 0.00, 0.25 and 0.50 m x s(-2) rms measured beneath the foam samples. Subject judgements of the relative discomfort of the different conditions depended on both static and dynamic characteristics in a manner consistent with the model. The effect of static and dynamic seat factors on overall seat discomfort was investigated by magnitude estimation using three foam cushions (of different hardness) and a rigid wooden seat at six vibration magnitudes with 20 subjects. Static seat factors (i.e. cushion stiffness) affected the manner in which vibration influenced the overall discomfort: cushions with lower stiffness were more comfortable and more sensitive to changes in vibration magnitude than those with higher stiffness. The experiments confirm that judgements of overall seat discomfort can be affected by both the static and dynamic characteristics of a seat, with the effect depending on vibration magnitude: when vibration magnitude was low, discomfort was dominated by static seat factors; as the vibration magnitude increased, discomfort became dominated by dynamic factors.

Effects of Thermal Noise on the Transitional Dynamics of an Inextensible Elastic Filament in Stagnation Flow

PubMed Central

Deng, Mingge; Grinberg, Leopold; Caswell, Bruce

2015-01-01

We investigate the dynamics of a single inextensible elastic filament subject to anisotropic friction in a viscous stagnation-point flow, by employing both a continuum model represented by Langevin type stochastic partial differential equations (SPDEs) and a Dissipative Particle Dynamics (DPD) method. Unlike previous works1, the filament is free to rotate and the tension along the filament is determined by the local inextensible constraint. The kinematics of the filament is recorded and studied with normal modes analysis. The results show that the filament displays an instability induced by negative tension, which is analogous to Euler buckling of a beam. Symmetry breaking of normal modes dynamics and stretch-coil transitions are observed above the threshold of the buckling instability point. Furthermore, both temporal and spatial noise are amplified resulting from the interaction of thermal fluctuations and nonlinear filament dynamics. Specifically, the spatial noise is amplified with even normal modes being excited due to symmetry breaking, while the temporal noise is amplified with increasing time correlation length and variance. PMID:26023834

Hysteresis losses and specific absorption rate measurements in magnetic nanoparticles for hyperthermia applications.

PubMed

Coïsson, Marco; Barrera, Gabriele; Celegato, Federica; Martino, Luca; Kane, Shashank N; Raghuvanshi, Saroj; Vinai, Franco; Tiberto, Paola

2017-06-01

Magnetic hysteresis loops areas and hyperthermia on magnetic nanoparticles have been studied with the aim of providing reliable and reproducible methods of measuring the specific absorption rate (SAR). The SAR of Fe 3 O 4 nanoparticles with two different mean sizes, and Ni 1-x Zn x Fe 2 O 4 ferrites with 0 ≤ x ≤ 0.8 has been measured with three approaches: static hysteresis loops areas, dynamic hysteresis loops areas and hyperthermia of a water solution. For dynamic loops and thermometric measurements, specific experimental setups have been developed, that operate at comparable frequencies (≈ 69kHz and ≈ 100kHz respectively) and rf magnetic field peak values (up to 100mT). The hyperthermia setup has been fully modelled to provide a direct measurement of the SAR of the magnetic nanoparticles by taking into account the heat exchange with the surrounding environment in non-adiabatic conditions and the parasitic heating of the water due to ionic currents. Dynamic hysteresis loops are shown to provide an accurate determination of the SAR except for superparamagnetic samples, where the boundary with a blocked regime could be crossed in dynamic conditions. Static hysteresis loops consistently underestimate the specific absorption rate but can be used to select the most promising samples. A means of reliably measure SAR of magnetic nanoparticles by different approaches for hyperthermia applications is presented and its validity discussed by comparing different methods. This work fits within the general subject of metrological traceability in medicine with a specific focus on magnetic hyperthermia. This article is part of a Special Issue entitled "Recent Advances in Bionanomaterials" Guest Editor: Dr. Marie-Louise Saboungi and Dr. Samuel D. Bader. Copyright © 2016 Elsevier B.V. All rights reserved.

An improved method to estimate reflectance parameters for high dynamic range imaging

NASA Astrophysics Data System (ADS)

Li, Shiying; Deguchi, Koichiro; Li, Renfa; Manabe, Yoshitsugu; Chihara, Kunihiro

2008-01-01

Two methods are described to accurately estimate diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness, over the dynamic range of the camera used to capture input images. Neither method needs to segment color areas on an image, or to reconstruct a high dynamic range (HDR) image. The second method improves on the first, bypassing the requirement for specific separation of diffuse and specular reflection components. For the latter method, diffuse and specular reflectance parameters are estimated separately, using the least squares method. Reflection values are initially assumed to be diffuse-only reflection components, and are subjected to the least squares method to estimate diffuse reflectance parameters. Specular reflection components, obtained by subtracting the computed diffuse reflection components from reflection values, are then subjected to a logarithmically transformed equation of the Torrance-Sparrow reflection model, and specular reflectance parameters for gloss intensity and surface roughness are finally estimated using the least squares method. Experiments were carried out using both methods, with simulation data at different saturation levels, generated according to the Lambert and Torrance-Sparrow reflection models, and the second method, with spectral images captured by an imaging spectrograph and a moving light source. Our results show that the second method can estimate the diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness more accurately and faster than the first one, so that colors and gloss can be reproduced more efficiently for HDR imaging.

Molecular Modeling of Nucleic Acid Structure: Electrostatics and Solvation

PubMed Central

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E.

2014-01-01

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand the structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as means to sample conformational space for a better understanding of the relevance of a given model. From this discussion, the major limitations with modeling, in general, were highlighted. These are the difficult issues in sampling conformational space effectively—the multiple minima or conformational sampling problems—and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These are discussed in detail in this unit. PMID:18428877

Automated Processing of Dynamic Contrast-Enhanced MRI: Correlation of Advanced Pharmacokinetic Metrics with Tumor Grade in Pediatric Brain Tumors.

PubMed

Vajapeyam, S; Stamoulis, C; Ricci, K; Kieran, M; Poussaint, T Young

2017-01-01

Pharmacokinetic parameters from dynamic contrast-enhanced MR imaging have proved useful for differentiating brain tumor grades in adults. In this study, we retrospectively reviewed dynamic contrast-enhanced perfusion data from children with newly diagnosed brain tumors and analyzed the pharmacokinetic parameters correlating with tumor grade. Dynamic contrast-enhanced MR imaging data from 38 patients were analyzed by using commercially available software. Subjects were categorized into 2 groups based on pathologic analyses consisting of low-grade (World Health Organization I and II) and high-grade (World Health Organization III and IV) tumors. Pharmacokinetic parameters were compared between the 2 groups by using linear regression models. For parameters that were statistically distinct between the 2 groups, sensitivity and specificity were also estimated. Eighteen tumors were classified as low-grade, and 20, as high-grade. Transfer constant from the blood plasma into the extracellular extravascular space (K trans ), rate constant from extracellular extravascular space back into blood plasma (K ep ), and extracellular extravascular volume fraction (V e ) were all significantly correlated with tumor grade; high-grade tumors showed higher K trans , higher K ep , and lower V e . Although all 3 parameters had high specificity (range, 82%-100%), K ep had the highest specificity for both grades. Optimal sensitivity was achieved for V e , with a combined sensitivity of 76% (compared with 71% for K trans and K ep ). Pharmacokinetic parameters derived from dynamic contrast-enhanced MR imaging can effectively discriminate low- and high-grade pediatric brain tumors. © 2017 by American Journal of Neuroradiology.

Dynamical modelling of coordinated multiple robot systems

NASA Technical Reports Server (NTRS)

Hayati, Samad

1987-01-01

The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.

System Dynamic Analysis of a Wind Tunnel Model with Applications to Improve Aerodynamic Data Quality

NASA Technical Reports Server (NTRS)

Buehrle, Ralph David

1997-01-01

The research investigates the effect of wind tunnel model system dynamics on measured aerodynamic data. During wind tunnel tests designed to obtain lift and drag data, the required aerodynamic measurements are the steady-state balance forces and moments, pressures, and model attitude. However, the wind tunnel model system can be subjected to unsteady aerodynamic and inertial loads which result in oscillatory translations and angular rotations. The steady-state force balance and inertial model attitude measurements are obtained by filtering and averaging data taken during conditions of high model vibrations. The main goals of this research are to characterize the effects of model system dynamics on the measured steady-state aerodynamic data and develop a correction technique to compensate for dynamically induced errors. Equations of motion are formulated for the dynamic response of the model system subjected to arbitrary aerodynamic and inertial inputs. The resulting modal model is examined to study the effects of the model system dynamic response on the aerodynamic data. In particular, the equations of motion are used to describe the effect of dynamics on the inertial model attitude, or angle of attack, measurement system that is used routinely at the NASA Langley Research Center and other wind tunnel facilities throughout the world. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration while testing in the National Transonic Facility at the NASA Langley Research Center. The inertial attitude sensor cannot distinguish between the gravitational acceleration and centrifugal accelerations associated with wind tunnel model system vibration, which results in a model attitude measurement bias error. Bias errors over an order of magnitude greater than the required device accuracy were found in the inertial model attitude measurements during dynamic testing of two model systems. Based on a theoretical modal approach, a method using measured vibration amplitudes and measured or calculated modal characteristics of the model system is developed to correct for dynamic bias errors in the model attitude measurements. The correction method is verified through dynamic response tests on two model systems and actual wind tunnel test data.

Symptom variability, affect and physical activity in ambulatory persons with multiple sclerosis: Understanding patterns and time-bound relationships.

PubMed

Kasser, Susan L; Goldstein, Amanda; Wood, Phillip K; Sibold, Jeremy

2017-04-01

Individuals with multiple sclerosis (MS) experience a clinical course that is highly variable with daily fluctuations in symptoms significantly affecting functional ability and quality of life. Yet, understanding how MS symptoms co-vary and associate with physical and psychological health is unclear. The purpose of the study was to explore variability patterns and time-bound relationships across symptoms, affect, and physical activity in individuals with MS. The study employed a multivariate, replicated, single-subject repeated-measures (MRSRM) design and involved four individuals with MS. Mood, fatigue, pain, balance confidence, and losses of balance were measured daily over 28 days by self-report. Physical activity was also measured daily over this same time period via accelerometry. Dynamic factor analysis (DFA) was used to determine the dimensionality and lagged relationships across the variables. Person-specific models revealed considerable time-dependent co-variation patterns as well as pattern variation across subjects. Results also offered insight into distinct variability structures at varying levels of disability. Modeling person-level variability may be beneficial for addressing the heterogeneity of experiences in individuals with MS and for understanding temporal and dynamic interrelationships among perceived symptoms, affect, and health outcomes in this group. Copyright © 2016 Elsevier Inc. All rights reserved.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

Development of compositional and contextual communicable congruence in robots by using dynamic neural network models.

PubMed

Park, Gibeom; Tani, Jun

2015-12-01

The current study presents neurorobotics experiments on acquisition of skills for "communicable congruence" with human via learning. A dynamic neural network model which is characterized by its multiple timescale dynamics property was utilized as a neuromorphic model for controlling a humanoid robot. In the experimental task, the humanoid robot was trained to generate specific sequential movement patterns as responding to various sequences of imperative gesture patterns demonstrated by the human subjects by following predefined compositional semantic rules. The experimental results showed that (1) the adopted MTRNN can achieve generalization by learning in the lower feature perception level by using a limited set of tutoring patterns, (2) the MTRNN can learn to extract compositional semantic rules with generalization in its higher level characterized by slow timescale dynamics, (3) the MTRNN can develop another type of cognitive capability for controlling the internal contextual processes as situated to on-going task sequences without being provided with cues for explicitly indicating task segmentation points. The analysis on the dynamic property developed in the MTRNN via learning indicated that the aforementioned cognitive mechanisms were achieved by self-organization of adequate functional hierarchy by utilizing the constraint of the multiple timescale property and the topological connectivity imposed on the network configuration. These results of the current research could contribute to developments of socially intelligent robots endowed with cognitive communicative competency similar to that of human. Copyright © 2015 Elsevier Ltd. All rights reserved.

Practical approach to subject-specific estimation of knee joint contact force.

PubMed

Knarr, Brian A; Higginson, Jill S

2015-08-20

Compressive forces experienced at the knee can significantly contribute to cartilage degeneration. Musculoskeletal models enable predictions of the internal forces experienced at the knee, but validation is often not possible, as experimental data detailing loading at the knee joint is limited. Recently available data reporting compressive knee force through direct measurement using instrumented total knee replacements offer a unique opportunity to evaluate the accuracy of models. Previous studies have highlighted the importance of subject-specificity in increasing the accuracy of model predictions; however, these techniques may be unrealistic outside of a research setting. Therefore, the goal of our work was to identify a practical approach for accurate prediction of tibiofemoral knee contact force (KCF). Four methods for prediction of knee contact force were compared: (1) standard static optimization, (2) uniform muscle coordination weighting, (3) subject-specific muscle coordination weighting and (4) subject-specific strength adjustments. Walking trials for three subjects with instrumented knee replacements were used to evaluate the accuracy of model predictions. Predictions utilizing subject-specific muscle coordination weighting yielded the best agreement with experimental data; however this method required in vivo data for weighting factor calibration. Including subject-specific strength adjustments improved models' predictions compared to standard static optimization, with errors in peak KCF less than 0.5 body weight for all subjects. Overall, combining clinical assessments of muscle strength with standard tools available in the OpenSim software package, such as inverse kinematics and static optimization, appears to be a practical method for predicting joint contact force that can be implemented for many applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Trust information-based privacy architecture for ubiquitous health.

PubMed

Ruotsalainen, Pekka Sakari; Blobel, Bernd; Seppälä, Antto; Nykänen, Pirkko

2013-10-08

Ubiquitous health is defined as a dynamic network of interconnected systems that offers health services independent of time and location to a data subject (DS). The network takes place in open and unsecure information space. It is created and managed by the DS who sets rules that regulate the way personal health information is collected and used. Compared to health care, it is impossible in ubiquitous health to assume the existence of a priori trust between the DS and service providers and to produce privacy using static security services. In ubiquitous health features, business goals and regulations systems followed often remain unknown. Furthermore, health care-specific regulations do not rule the ways health data is processed and shared. To be successful, ubiquitous health requires novel privacy architecture. The goal of this study was to develop a privacy management architecture that helps the DS to create and dynamically manage the network and to maintain information privacy. The architecture should enable the DS to dynamically define service and system-specific rules that regulate the way subject data is processed. The architecture should provide to the DS reliable trust information about systems and assist in the formulation of privacy policies. Furthermore, the architecture should give feedback upon how systems follow the policies of DS and offer protection against privacy and trust threats existing in ubiquitous environments. A sequential method that combines methodologies used in system theory, systems engineering, requirement analysis, and system design was used in the study. In the first phase, principles, trust and privacy models, and viewpoints were selected. Thereafter, functional requirements and services were developed on the basis of a careful analysis of existing research published in journals and conference proceedings. Based on principles, models, and requirements, architectural components and their interconnections were developed using system analysis. The architecture mimics the way humans use trust information in decision making, and enables the DS to design system-specific privacy policies using computational trust information that is based on systems' measured features. The trust attributes that were developed describe the level systems for support awareness and transparency, and how they follow general and domain-specific regulations and laws. The monitoring component of the architecture offers dynamic feedback concerning how the system enforces the polices of DS. The privacy management architecture developed in this study enables the DS to dynamically manage information privacy in ubiquitous health and to define individual policies for all systems considering their trust value and corresponding attributes. The DS can also set policies for secondary use and reuse of health information. The architecture offers protection against privacy threats existing in ubiquitous environments. Although the architecture is targeted to ubiquitous health, it can easily be modified to other ubiquitous applications.

Trust Information-Based Privacy Architecture for Ubiquitous Health

PubMed Central

2013-01-01

Background Ubiquitous health is defined as a dynamic network of interconnected systems that offers health services independent of time and location to a data subject (DS). The network takes place in open and unsecure information space. It is created and managed by the DS who sets rules that regulate the way personal health information is collected and used. Compared to health care, it is impossible in ubiquitous health to assume the existence of a priori trust between the DS and service providers and to produce privacy using static security services. In ubiquitous health features, business goals and regulations systems followed often remain unknown. Furthermore, health care-specific regulations do not rule the ways health data is processed and shared. To be successful, ubiquitous health requires novel privacy architecture. Objective The goal of this study was to develop a privacy management architecture that helps the DS to create and dynamically manage the network and to maintain information privacy. The architecture should enable the DS to dynamically define service and system-specific rules that regulate the way subject data is processed. The architecture should provide to the DS reliable trust information about systems and assist in the formulation of privacy policies. Furthermore, the architecture should give feedback upon how systems follow the policies of DS and offer protection against privacy and trust threats existing in ubiquitous environments. Methods A sequential method that combines methodologies used in system theory, systems engineering, requirement analysis, and system design was used in the study. In the first phase, principles, trust and privacy models, and viewpoints were selected. Thereafter, functional requirements and services were developed on the basis of a careful analysis of existing research published in journals and conference proceedings. Based on principles, models, and requirements, architectural components and their interconnections were developed using system analysis. Results The architecture mimics the way humans use trust information in decision making, and enables the DS to design system-specific privacy policies using computational trust information that is based on systems’ measured features. The trust attributes that were developed describe the level systems for support awareness and transparency, and how they follow general and domain-specific regulations and laws. The monitoring component of the architecture offers dynamic feedback concerning how the system enforces the polices of DS. Conclusions The privacy management architecture developed in this study enables the DS to dynamically manage information privacy in ubiquitous health and to define individual policies for all systems considering their trust value and corresponding attributes. The DS can also set policies for secondary use and reuse of health information. The architecture offers protection against privacy threats existing in ubiquitous environments. Although the architecture is targeted to ubiquitous health, it can easily be modified to other ubiquitous applications. PMID:25099213

Monitoring the injured brain: registered, patient specific atlas models to improve accuracy of recovered brain saturation values

NASA Astrophysics Data System (ADS)

Clancy, Michael; Belli, Antonio; Davies, David; Lucas, Samuel J. E.; Su, Zhangjie; Dehghani, Hamid

2015-07-01

The subject of superficial contamination and signal origins remains a widely debated topic in the field of Near Infrared Spectroscopy (NIRS), yet the concept of using the technology to monitor an injured brain, in a clinical setting, poses additional challenges concerning the quantitative accuracy of recovered parameters. Using high density diffuse optical tomography probes, quantitatively accurate parameters from different layers (skin, bone and brain) can be recovered from subject specific reconstruction models. This study assesses the use of registered atlas models for situations where subject specific models are not available. Data simulated from subject specific models were reconstructed using the 8 registered atlas models implementing a regional (layered) parameter recovery in NIRFAST. A 3-region recovery based on the atlas model yielded recovered brain saturation values which were accurate to within 4.6% (percentage error) of the simulated values, validating the technique. The recovered saturations in the superficial regions were not quantitatively accurate. These findings highlight differences in superficial (skin and bone) layer thickness between the subject and atlas models. This layer thickness mismatch was propagated through the reconstruction process decreasing the parameter accuracy.

A generalised porous medium approach to study thermo-fluid dynamics in human eyes.

PubMed

Mauro, Alessandro; Massarotti, Nicola; Salahudeen, Mohamed; Romano, Mario R; Romano, Vito; Nithiarasu, Perumal

2018-03-22

The present work describes the application of the generalised porous medium model to study heat and fluid flow in healthy and glaucomatous eyes of different subject specimens, considering the presence of ocular cavities and porous tissues. The 2D computational model, implemented into the open-source software OpenFOAM, has been verified against benchmark data for mixed convection in domains partially filled with a porous medium. The verified model has been employed to simulate the thermo-fluid dynamic phenomena occurring in the anterior section of four patient-specific human eyes, considering the presence of anterior chamber (AC), trabecular meshwork (TM), Schlemm's canal (SC), and collector channels (CC). The computational domains of the eye are extracted from tomographic images. The dependence of TM porosity and permeability on intraocular pressure (IOP) has been analysed in detail, and the differences between healthy and glaucomatous eye conditions have been highlighted, proving that the different physiological conditions of patients have a significant influence on the thermo-fluid dynamic phenomena. The influence of different eye positions (supine and standing) on thermo-fluid dynamic variables has been also investigated: results are presented in terms of velocity, pressure, temperature, friction coefficient and local Nusselt number. The results clearly indicate that porosity and permeability of TM are two important parameters that affect eye pressure distribution. Graphical abstract Velocity contours and vectors for healthy eyes (top) and glaucomatous eyes (bottom) for standing position.

The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems.

PubMed

Zhang, Xingye; Wang, Shaoqian; Hoagg, Jesse B; Seigler, T Michael

2018-02-01

We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.

Towards Subject-Specific Strength Training Design through Predictive Use of Musculoskeletal Models.

PubMed

Plüss, Michael; Schellenberg, Florian; Taylor, William R; Lorenzetti, Silvio

2018-01-01

Lower extremity dysfunction is often associated with hip muscle strength deficiencies. Detailed knowledge of the muscle forces generated in the hip under specific external loading conditions enables specific structures to be trained. The aim of this study was to find the most effective movement type and loading direction to enable the training of specific parts of the hip muscles using a standing posture and a pulley system. In a novel approach to release the predictive power of musculoskeletal modelling techniques based on inverse dynamics, flexion/extension and ab-/adduction movements were virtually created. To demonstrate the effectiveness of this approach, three hip orientations and an external loading force that was systematically rotated around the body were simulated using a state-of-the art OpenSim model in order to establish ideal designs for training of the anterior and posterior parts of the M. gluteus medius (GM). The external force direction as well as the hip orientation greatly influenced the muscle forces in the different parts of the GM. No setting was found for simultaneous training of the anterior and posterior parts with a muscle force higher than 50% of the maximum. Importantly, this study has demonstrated the use of musculoskeletal models as an approach to predict muscle force variations for different strength and rehabilitation exercise variations.

Towards Subject-Specific Strength Training Design through Predictive Use of Musculoskeletal Models

PubMed Central

Plüss, Michael; Schellenberg, Florian

2018-01-01

Lower extremity dysfunction is often associated with hip muscle strength deficiencies. Detailed knowledge of the muscle forces generated in the hip under specific external loading conditions enables specific structures to be trained. The aim of this study was to find the most effective movement type and loading direction to enable the training of specific parts of the hip muscles using a standing posture and a pulley system. In a novel approach to release the predictive power of musculoskeletal modelling techniques based on inverse dynamics, flexion/extension and ab-/adduction movements were virtually created. To demonstrate the effectiveness of this approach, three hip orientations and an external loading force that was systematically rotated around the body were simulated using a state-of-the art OpenSim model in order to establish ideal designs for training of the anterior and posterior parts of the M. gluteus medius (GM). The external force direction as well as the hip orientation greatly influenced the muscle forces in the different parts of the GM. No setting was found for simultaneous training of the anterior and posterior parts with a muscle force higher than 50% of the maximum. Importantly, this study has demonstrated the use of musculoskeletal models as an approach to predict muscle force variations for different strength and rehabilitation exercise variations. PMID:29796082

NetFlow Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corbet Jr., Thomas F; Beyeler, Walter E; Vanwestrienen, Dirk

NetFlow Dynamics is a web-accessible analysis environment for simulating dynamic flows of materials on model networks. Performing a simulation requires both the NetFlow Dynamics application and a network model which is a description of the structure of the nodes and edges of a network including the flow capacity of each edge and the storage capacity of each node, and the sources and sinks of the material flowing on the network. NetFlow Dynamics consists of databases for storing network models, algorithms to calculate flows on networks, and a GIS-based graphical interface for performing simulations and viewing simulation results. Simulated flows aremore » dynamic in the sense that flows on each edge of the network and inventories at each node change with time and can be out of equilibrium with boundary conditions. Any number of network models could be simulated using Net Flow Dynamics. To date, the models simulated have been models of petroleum infrastructure. The main model has been the National Transportation Fuels Model (NTFM), a network of U.S. oil fields, transmission pipelines, rail lines, refineries, tank farms, and distribution terminals. NetFlow Dynamics supports two different flow algorithms, the Gradient Flow algorithm and the Inventory Control algorithm, that were developed specifically for the NetFlow Dynamics application. The intent is to add additional algorithms in the future as needed. The ability to select from multiple algorithms is desirable because a single algorithm never covers all analysis needs. The current algorithms use a demand-driven capacity-constrained formulation which means that the algorithms strive to use all available capacity and stored inventory to meet desired flows to sinks, subject to the capacity constraints of each network component. The current flow algorithms are best suited for problems in which a material flows on a capacity-constrained network representing a supply chain in which the material supplied can be stored at each node of the network. In the petroleum models, the flowing materials are crude oil and refined products that can be stored at tank farms, refineries, or terminals (i.e. the nodes of the network). Examples of other network models that could be simulated are currency flowing in a financial network, agricultural products moving to market, or natural gas flowing on a pipeline network.« less

Foreword to the Special Issue on "Dynamic Models in Economics and Finance"

NASA Astrophysics Data System (ADS)

Gardini, Laura; Kubin, Ingrid; Tramontana, Fabio; Wagener, Florian

2018-05-01

International workshops on Dynamic Models in Economics and Finance (MDEF) take place every two years in Urbino (Italy); since the inception of the series in 2000, there have been nine editions. The subject has become a central topic for scholars working on economic dynamics. In 2016 the workshop was held under the auspices of University of Urbino "Carlo Bo" , DESP1

Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

ERIC Educational Resources Information Center

Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

2011-01-01

Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

Estimating apparent maximum muscle stress of trunk extensor muscles in older adults using subject-specific musculoskeletal models.

PubMed

Burkhart, Katelyn A; Bruno, Alexander G; Bouxsein, Mary L; Bean, Jonathan F; Anderson, Dennis E

2018-01-01

Maximum muscle stress (MMS) is a critical parameter in musculoskeletal modeling, defining the maximum force that a muscle of given size can produce. However, a wide range of MMS values have been reported in literature, and few studies have estimated MMS in trunk muscles. Due to widespread use of musculoskeletal models in studies of the spine and trunk, there is a need to determine reasonable magnitude and range of trunk MMS. We measured trunk extension strength in 49 participants over 65 years of age, surveyed participants about low back pain, and acquired quantitative computed tomography (QCT) scans of their lumbar spines. Trunk muscle morphology was assessed from QCT scans and used to create a subject-specific musculoskeletal model for each participant. Model-predicted extension strength was computed using a trunk muscle MMS of 100 N/cm 2 . The MMS of each subject-specific model was then adjusted until the measured strength matched the model-predicted strength (±20 N). We found that measured trunk extension strength was significantly higher in men. With the initial constant MMS value, the musculoskeletal model generally over-predicted trunk extension strength. By adjusting MMS on a subject-specific basis, we found apparent MMS values ranging from 40 to 130 N/cm 2 , with an average of 75.5 N/cm 2 for both men and women. Subjects with low back pain had lower apparent MMS than subjects with no back pain. This work incorporates a unique approach to estimate subject-specific trunk MMS values via musculoskeletal modeling and provides a useful insight into MMS variation. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:498-505, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Analysis, simulation and visualization of 1D tapping via reduced dynamical models

NASA Astrophysics Data System (ADS)

Blackmore, Denis; Rosato, Anthony; Tricoche, Xavier; Urban, Kevin; Zou, Luo

2014-04-01

A low-dimensional center-of-mass dynamical model is devised as a simplified means of approximately predicting some important aspects of the motion of a vertical column comprised of a large number of particles subjected to gravity and periodic vertical tapping. This model is investigated first as a continuous dynamical system using analytical, simulation and visualization techniques. Then, by employing an approach analogous to that used to approximate the dynamics of a bouncing ball on an oscillating flat plate, it is modeled as a discrete dynamical system and analyzed to determine bifurcations and transitions to chaotic motion along with other properties. The predictions of the analysis are then compared-primarily qualitatively-with visualization and simulation results of the reduced continuous model, and ultimately with simulations of the complete system dynamics.

A plastic corticostriatal circuit model of adaptation in perceptual decision making

PubMed Central

Hsiao, Pao-Yueh; Lo, Chung-Chuan

2013-01-01

The ability to optimize decisions and adapt them to changing environments is a crucial brain function that increase survivability. Although much has been learned about the neuronal activity in various brain regions that are associated with decision making, and about how the nervous systems may learn to achieve optimization, the underlying neuronal mechanisms of how the nervous systems optimize decision strategies with preference given to speed or accuracy, and how the systems adapt to changes in the environment, remain unclear. Based on extensive empirical observations, we addressed the question by extending a previously described cortico-basal ganglia circuit model of perceptual decisions with the inclusion of a dynamic dopamine (DA) system that modulates spike-timing dependent plasticity (STDP). We found that, once an optimal model setting that maximized the reward rate was selected, the same setting automatically optimized decisions across different task environments through dynamic balancing between the facilitating and depressing components of the DA dynamics. Interestingly, other model parameters were also optimal if we considered the reward rate that was weighted by the subject's preferences for speed or accuracy. Specifically, the circuit model favored speed if we increased the phasic DA response to the reward prediction error, whereas the model favored accuracy if we reduced the tonic DA activity or the phasic DA responses to the estimated reward probability. The proposed model provides insight into the roles of different components of DA responses in decision adaptation and optimization in a changing environment. PMID:24339814

Subject-specific knee joint geometry improves predictions of medial tibiofemoral contact forces.

PubMed

Gerus, Pauline; Sartori, Massimo; Besier, Thor F; Fregly, Benjamin J; Delp, Scott L; Banks, Scott A; Pandy, Marcus G; D'Lima, Darryl D; Lloyd, David G

2013-11-15

Estimating tibiofemoral joint contact forces is important for understanding the initiation and progression of knee osteoarthritis. However, tibiofemoral contact force predictions are influenced by many factors including muscle forces and anatomical representations of the knee joint. This study aimed to investigate the influence of subject-specific geometry and knee joint kinematics on the prediction of tibiofemoral contact forces using a calibrated EMG-driven neuromusculoskeletal model of the knee. One participant fitted with an instrumented total knee replacement walked at a self-selected speed while medial and lateral tibiofemoral contact forces, ground reaction forces, whole-body kinematics, and lower-limb muscle activity were simultaneously measured. The combination of generic and subject-specific knee joint geometry and kinematics resulted in four different OpenSim models used to estimate muscle-tendon lengths and moment arms. The subject-specific geometric model was created from CT scans and the subject-specific knee joint kinematics representing the translation of the tibia relative to the femur was obtained from fluoroscopy. The EMG-driven model was calibrated using one walking trial, but with three different cost functions that tracked the knee flexion/extension moments with and without constraint over the estimated joint contact forces. The calibrated models then predicted the medial and lateral tibiofemoral contact forces for five other different walking trials. The use of subject-specific models with minimization of the peak tibiofemoral contact forces improved the accuracy of medial contact forces by 47% and lateral contact forces by 7%, respectively compared with the use of generic musculoskeletal model. © 2013 Published by Elsevier Ltd.

Subject-specific knee joint geometry improves predictions of medial tibiofemoral contact forces

PubMed Central

Gerus, Pauline; Sartori, Massimo; Besier, Thor F.; Fregly, Benjamin J.; Delp, Scott L.; Banks, Scott A.; Pandy, Marcus G.; D’Lima, Darryl D.; Lloyd, David G.

2013-01-01

Estimating tibiofemoral joint contact forces is important for understanding the initiation and progression of knee osteoarthritis. However, tibiofemoral contact force predictions are influenced by many factors including muscle forces and anatomical representations of the knee joint. This study aimed to investigate the influence of subject-specific geometry and knee joint kinematics on the prediction of tibiofemoral contact forces using a calibrated EMG-driven neuromusculoskeletal model of the knee. One participant fitted with an instrumented total knee replacement walked at a self-selected speed while medial and lateral tibiofemoral contact forces, ground reaction forces, whole-body kinematics, and lower-limb muscle activity were simultaneously measured. The combination of generic and subject-specific knee joint geometry and kinematics resulted in four different OpenSim models used to estimate muscle-tendon lengths and moment arms. The subject-specific geometric model was created from CT scans and the subject-specific knee joint kinematics representing the translation of the tibia relative to the femur was obtained from fluoroscopy. The EMG-driven model was calibrated using one walking trial, but with three different cost functions that tracked the knee flexion/extension moments with and without constraint over the estimated joint contact forces. The calibrated models then predicted the medial and lateral tibiofemoral contact forces for five other different walking trials. The use of subject-specific models with minimization of the peak tibiofemoral contact forces improved the accuracy of medial contact forces by 47% and lateral contact forces by 7%, respectively compared with the use of generic musculoskeletal model. PMID:24074941

Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling.

PubMed

Nasiri, Masoud; Luo, Yunhua

2016-09-01

There is controversy about whether or not body parameters affect hip fracture in men and women in the same way. In addition, although bone mineral density (BMD) is currently the most important single discriminator of hip fracture, it is unclear if BMD alone is equally effective for men and women. The objective of this study was to quantify and compare the associations of hip fracture risk with BMD and body parameters in men and women using our recently developed two-level biomechanical model that combines a whole-body dynamics model with a proximal-femur finite element model. Sideways fall induced impact force of 130 Chinese clinical cases, including 50 males and 80 females, were determined by subject-specific dynamics modeling. Then, a DXA-based finite element model was used to simulate the femur bone under the fall-induced loading conditions and calculate the hip fracture risk. Body weight, body height, body mass index, trochanteric soft tissue thickness, and hip bone mineral density were determined for each subject and their associations with impact force and hip fracture risk were quantified. Results showed that the association between impact force and hip fracture risk was not strong enough in both men (r=-0.31,p<0.05) and women (r=0.42,p<0.001) to consider the force as a sole indicator of hip fracture risk. The correlation between hip BMD and hip fracture risk in men (r=-0.83,p<0.001) was notably stronger than that in women (r=-0.68,p<0.001). Increased body mass index was not a protective factor against hip fracture in men (r=-0.13,p>0.05), but it can be considered as a protective factor among women (r=-0.28,p<0.05). In contrast to men, trochanteric soft tissue thickness can be considered as a protective factor against hip fracture in women (r=-0.50,p<0.001). This study suggested that the biomechanical risk/protective factors for hip fracture are sex-specific. Therefore, the effect of body parameters should be considered differently for men and women in hip fracture risk assessment tools. These findings support further exploration of sex-specific preventive and protective measurements to reduce the incidence of hip fractures. Copyright © 2016 Elsevier Inc. All rights reserved.

Higher medially-directed joint reaction forces are a characteristic of dysplastic hips: A comparative study using subject-specific musculoskeletal models.

PubMed

Harris, Michael D; MacWilliams, Bruce A; Bo Foreman, K; Peters, Christopher L; Weiss, Jeffrey A; Anderson, Andrew E

2017-03-21

Acetabular dysplasia is a known cause of hip osteoarthritis. In addition to abnormal anatomy, changes in kinematics, joint reaction forces (JRFs), and muscle forces could cause tissue damage to the cartilage and labrum, and may contribute to pain and fatigue. The objective of this study was to compare lower extremity joint angles, moments, hip JRFs and muscle forces during gait between patients with symptomatic acetabular dysplasia and healthy controls. Marker trajectories and ground reaction forces were measured in 10 dysplasia patients and 10 typically developing control subjects. A musculoskeletal model was scaled in OpenSim to each subject and subject-specific hip joint centers were determined using reconstructions from CT images. Joint kinematics and moments were calculated using inverse kinematics and inverse dynamics, respectively. Muscle forces and hip JRFs were estimated with static optimization. Inter-group differences were tested for statistical significance (p≤0.05) and large effect sizes (d≥0.8). Results demonstrated that dysplasia patients had higher medially directed JRFs. Joint angles and moments were mostly similar between the groups, but large inter-group effect sizes suggested some restriction in range of motion by patients at the hip and ankle. Higher medially-directed JRFs and inter-group differences in hip muscle forces likely stem from lateralization of the hip joint center in dysplastic patients. Joint force differences, combined with reductions in range of motion at the hip and ankle may also indicate compensatory strategies by patients with dysplasia to maintain joint stability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Higher Medially-directed Joint Reaction Forces are a Characteristic of Dysplastic Hips: A Comparative Study Using Subject-Specific Musculoskeletal Models

PubMed Central

Harris, Michael D.; MacWilliams, Bruce A.; Foreman, K. Bo; Peters, Christopher L.; Weiss, Jeffrey A.; Anderson, Andrew E.

2018-01-01

Acetabular dysplasia is a known cause of hip osteoarthritis. In addition to abnormal anatomy, changes in kinematics, joint reaction forces (JRFs), and muscle forces could cause tissue damage to the cartilage and labrum, and may contribute to pain and fatigue. The objective of this study was to compare lower extremity joint angles, moments, hip JRFs and muscle forces during gait between patients with symptomatic acetabular dysplasia and healthy controls. Marker trajectories and ground reaction forces were measured in 10 dysplasia patients and 10 typically developing control subjects. A musculoskeletal model was scaled in OpenSim to each subject and subject-specific hip joint centers were determined using reconstructions from CT images. Joint kinematics and moments were calculated using inverse kinematics and inverse dynamics, respectively. Muscle forces and hip JRFs were estimated with static optimization. Inter-group differences were tested for statistical significance (p≤0.05) and large effect sizes (d≥0.8). Results demonstrated that dysplasia patients had higher medially directed JRFs. Joint angles and moments were mostly similar between the groups, but large inter-group effect sizes suggested some restriction in range of motion by patients at the hip and ankle. Higher medially-directed JRFs and inter-group differences in hip muscle forces likely stem from lateralization of the hip joint center in dysplastic patients. Joint force differences, combined with reductions in range of motion at the hip and ankle may also indicate compensatory strategies by patients with dysplasia to maintain joint stability. PMID:28233552

Stability basin estimates fall risk from observed kinematics, demonstrated on the Sit-to-Stand task.

PubMed

Shia, Victor; Moore, Talia Yuki; Holmes, Patrick; Bajcsy, Ruzena; Vasudevan, Ram

2018-04-27

The ability to quantitatively measure stability is essential to ensuring the safety of locomoting systems. While the response to perturbation directly reflects the stability of a motion, this experimental method puts human subjects at risk. Unfortunately, existing indirect methods for estimating stability from unperturbed motion have been shown to have limited predictive power. This paper leverages recent advances in dynamical systems theory to accurately estimate the stability of human motion without requiring perturbation. This approach relies on kinematic observations of a nominal Sit-to-Stand motion to construct an individual-specific dynamic model, input bounds, and feedback control that are then used to compute the set of perturbations from which the model can recover. This set, referred to as the stability basin, was computed for 14 individuals, and was able to successfully differentiate between less and more stable Sit-to-Stand strategies for each individual with greater accuracy than existing methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Motivation: What have we learned and what is still missing?

PubMed

Studer, B; Knecht, S

2016-01-01

This final chapter deliberates three overarching topics and conclusions of the research presented in this volume: the endurance of the concept of extrinsic vs intrinsic motivation, the importance of considering subjective costs of activities when aiming to understand and enhance motivation, and current knowledge of the neurobiological underpinnings of motivation. Furthermore, three topics for future motivation research are outlined, namely the assessment and determinants of intrinsic benefits, the reconciliation of activity-specific motivation models with generalized motivation impairments in clinical populations, and the motivational dynamics of groups. © 2016 Elsevier B.V. All rights reserved.

Using subject-specific three-dimensional (3D) anthropometry data in digital human modelling: case study in hand motion simulation.

PubMed

Tsao, Liuxing; Ma, Liang

2016-11-01

Digital human modelling enables ergonomists and designers to consider ergonomic concerns and design alternatives in a timely and cost-efficient manner in the early stages of design. However, the reliability of the simulation could be limited due to the percentile-based approach used in constructing the digital human model. To enhance the accuracy of the size and shape of the models, we proposed a framework to generate digital human models using three-dimensional (3D) anthropometric data. The 3D scan data from specific subjects' hands were segmented based on the estimated centres of rotation. The segments were then driven in forward kinematics to perform several functional postures. The constructed hand models were then verified, thereby validating the feasibility of the framework. The proposed framework helps generate accurate subject-specific digital human models, which can be utilised to guide product design and workspace arrangement. Practitioner Summary: Subject-specific digital human models can be constructed under the proposed framework based on three-dimensional (3D) anthropometry. This approach enables more reliable digital human simulation to guide product design and workspace arrangement.

3D Reconstruction of Chick Embryo Vascular Geometries Using Non-invasive High-Frequency Ultrasound for Computational Fluid Dynamics Studies.

PubMed

Tan, Germaine Xin Yi; Jamil, Muhammad; Tee, Nicole Gui Zhen; Zhong, Liang; Yap, Choon Hwai

2015-11-01

Recent animal studies have provided evidence that prenatal blood flow fluid mechanics may play a role in the pathogenesis of congenital cardiovascular malformations. To further these researches, it is important to have an imaging technique for small animal embryos with sufficient resolution to support computational fluid dynamics studies, and that is also non-invasive and non-destructive to allow for subject-specific, longitudinal studies. In the current study, we developed such a technique, based on ultrasound biomicroscopy scans on chick embryos. Our technique included a motion cancelation algorithm to negate embryonic body motion, a temporal averaging algorithm to differentiate blood spaces from tissue spaces, and 3D reconstruction of blood volumes in the embryo. The accuracy of the reconstructed models was validated with direct stereoscopic measurements. A computational fluid dynamics simulation was performed to model fluid flow in the generated construct of a Hamburger-Hamilton (HH) stage 27 embryo. Simulation results showed that there were divergent streamlines and a low shear region at the carotid duct, which may be linked to the carotid duct's eventual regression and disappearance by HH stage 34. We show that our technique has sufficient resolution to produce accurate geometries for computational fluid dynamics simulations to quantify embryonic cardiovascular fluid mechanics.

Toward modeling locomotion using electromyography-informed 3D models: application to cerebral palsy.

PubMed

Sartori, M; Fernandez, J W; Modenese, L; Carty, C P; Barber, L A; Oberhofer, K; Zhang, J; Handsfield, G G; Stott, N S; Besier, T F; Farina, D; Lloyd, D G

2017-03-01

This position paper proposes a modeling pipeline to develop clinically relevant neuromusculoskeletal models to understand and treat complex neurological disorders. Although applicable to a variety of neurological conditions, we provide direct pipeline applicative examples in the context of cerebral palsy (CP). This paper highlights technologies in: (1) patient-specific segmental rigid body models developed from magnetic resonance imaging for use in inverse kinematics and inverse dynamics pipelines; (2) efficient population-based approaches to derive skeletal models and muscle origins/insertions that are useful for population statistics and consistent creation of continuum models; (3) continuum muscle descriptions to account for complex muscle architecture including spatially varying material properties with muscle wrapping; (4) muscle and tendon properties specific to CP; and (5) neural-based electromyography-informed methods for muscle force prediction. This represents a novel modeling pipeline that couples for the first time electromyography extracted features of disrupted neuromuscular behavior with advanced numerical methods for modeling CP-specific musculoskeletal morphology and function. The translation of such pipeline to the clinical level will provide a new class of biomarkers that objectively describe the neuromusculoskeletal determinants of pathological locomotion and complement current clinical assessment techniques, which often rely on subjective judgment. WIREs Syst Biol Med 2017, 9:e1368. doi: 10.1002/wsbm.1368 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Telomere length dynamics in human memory T cells specific for viruses causing acute or latent infections

PubMed Central

2013-01-01

Background Declining telomere length (TL) is associated with T cell senescence. While TL in naïve and memory T cells declines with increasing age, there is limited data on TL dynamics in virus-specific memory CD4+ T cells in healthy adults. We combined BrdU-labeling of virus-stimulated T cells followed with flow cytometry-fluorescent in situ hybridization for TL determination. We analyzed TL in T cells specific for several virus infections: non-recurring acute (vaccinia virus, VACV), recurring-acute (influenza A virus, IAV), and reactivating viruses (varicella-zoster virus, VZV, and cytomegalovirus, CMV) in 10 healthy subjects. Additionally, five subjects provided multiple blood samples separated by up to 10 years. Results VACV- and CMV-specific T cells had longer average TL than IAV-specific CD4+ T cells. Although most virus-specific cells were CD45RA-, we observed a minor population of BrdU+ CD45RA+ T cells characterized by long telomeres. Longitudinal analysis demonstrated a slow decline in average TL in virus-specific T cells. However, in one subject, VZV reactivation led to an increase in average TL in VZV-specific memory T cells, suggesting a conversion of longer TL cells from the naïve T cell repertoire. Conclusions TLs in memory CD4+ T cells in otherwise healthy adults are heterogeneous and follow distinct virus-specific kinetics. These findings suggests that the distribution of TL and the creation and maintenance of long TL memory T cells could be important for the persistence of long-lived T cell memory. PMID:23971624

Telomere length dynamics in human memory T cells specific for viruses causing acute or latent infections.

PubMed

O'Bryan, Joel M; Woda, Marcia; Co, Mary; Mathew, Anuja; Rothman, Alan L

2013-08-26

Declining telomere length (TL) is associated with T cell senescence. While TL in naïve and memory T cells declines with increasing age, there is limited data on TL dynamics in virus-specific memory CD4+ T cells in healthy adults. We combined BrdU-labeling of virus-stimulated T cells followed with flow cytometry-fluorescent in situ hybridization for TL determination. We analyzed TL in T cells specific for several virus infections: non-recurring acute (vaccinia virus, VACV), recurring-acute (influenza A virus, IAV), and reactivating viruses (varicella-zoster virus, VZV, and cytomegalovirus, CMV) in 10 healthy subjects. Additionally, five subjects provided multiple blood samples separated by up to 10 years. VACV- and CMV-specific T cells had longer average TL than IAV-specific CD4+ T cells. Although most virus-specific cells were CD45RA-, we observed a minor population of BrdU+ CD45RA+ T cells characterized by long telomeres. Longitudinal analysis demonstrated a slow decline in average TL in virus-specific T cells. However, in one subject, VZV reactivation led to an increase in average TL in VZV-specific memory T cells, suggesting a conversion of longer TL cells from the naïve T cell repertoire. TLs in memory CD4+ T cells in otherwise healthy adults are heterogeneous and follow distinct virus-specific kinetics. These findings suggests that the distribution of TL and the creation and maintenance of long TL memory T cells could be important for the persistence of long-lived T cell memory.

The Longitudinal Stability and Dynamics of Group Membership in the Dual-Factor Model of Mental Health: Psychosocial Predictors of Mental Health

ERIC Educational Resources Information Center

Kelly, Ryan M.; Hills, Kimberly J.; Huebner, E. Scott; McQuillin, Samuel D.

2012-01-01

This study examined the longitudinal stability and dynamics of group membership within the Greenspoon and Sakflofske's dual-factor model of mental health. This expanded model incorporates information about subjective well-being (SWB), in addition to psychopathological symptoms, to better identify the mental health status and current functioning of…

Failure Resistance of Fiber-Reinforced Ultra-High Performance Concrete (FRUHPC) Subjected to Blast Loading

NASA Astrophysics Data System (ADS)

Ellis, Brett; Zhou, Min; McDowell, David

2011-06-01

As part of a hierarchy-based computational materials design program, a fully dynamic 3D mesoscale model is developed to quantify the effects of energy storage and dissipation mechanisms in Fiber-Reinforced Ultra-High Performance Concretes (FRUHPCs) subjected to blast loading. This model accounts for three constituent components: reinforcement fibers, cementitious matrix, and fiber-matrix interfaces. Microstructure instantiations encompass a range of fiber volume fraction (0-2%), fiber length (10-15 mm), and interfacial bonding strength (1-100 MPa). Blast loading with scaled distances between 5 and 10 m/kg1/3 are considered. Calculations have allowed the delineation and characterization of the evolutions of kinetic energy, strain energy, work expended on interfacial damage and failure, frictional dissipation along interfaces, and bulk dissipation through granular flow as functions of microstructure, loading and constituent attributes. The relations obtained point out avenues for designing FRUHPCs with properties tailored for specific load environments and reveal trade-offs between various design scenarios.

Two dissimilar approaches to dynamical systems on hyper MV -algebras and their information entropy

NASA Astrophysics Data System (ADS)

Mehrpooya, Adel; Ebrahimi, Mohammad; Davvaz, Bijan

2017-09-01

Measuring the flow of information that is related to the evolution of a system which is modeled by applying a mathematical structure is of capital significance for science and usually for mathematics itself. Regarding this fact, a major issue in concern with hyperstructures is their dynamics and the complexity of the varied possible dynamics that exist over them. Notably, the dynamics and uncertainty of hyper MV -algebras which are hyperstructures and extensions of a central tool in infinite-valued Lukasiewicz propositional calculus that models many valued logics are of primary concern. Tackling this problem, in this paper we focus on the subject of dynamical systems on hyper MV -algebras and their entropy. In this respect, we adopt two varied approaches. One is the set-based approach in which hyper MV -algebra dynamical systems are developed by employing set functions and set partitions. By the other method that is based on points and point partitions, we establish the concept of hyper injective dynamical systems on hyper MV -algebras. Next, we study the notion of entropy for both kinds of systems. Furthermore, we consider essential ergodic characteristics of those systems and their entropy. In particular, we introduce the concept of isomorphic hyper injective and hyper MV -algebra dynamical systems, and we demonstrate that isomorphic systems have the same entropy. We present a couple of theorems in order to help calculate entropy. In particular, we prove a contemporary version of addition and Kolmogorov-Sinai Theorems. Furthermore, we provide a comparison between the indispensable properties of hyper injective and semi-independent dynamical systems. Specifically, we present and prove theorems that draw comparisons between the entropies of such systems. Lastly, we discuss some possible relationships between the theories of hyper MV -algebra and MV -algebra dynamical systems.

Subject specific finite element modeling of periprosthetic femoral fracture using element deactivation to simulate bone failure.

PubMed

Miles, Brad; Kolos, Elizabeth; Walter, William L; Appleyard, Richard; Shi, Angela; Li, Qing; Ruys, Andrew J

2015-06-01

Subject-specific finite element (FE) modeling methodology could predict peri-prosthetic femoral fracture (PFF) for cementless hip arthoplasty in the early postoperative period. This study develops methodology for subject-specific finite element modeling by using the element deactivation technique to simulate bone failure and validate with experimental testing, thereby predicting peri-prosthetic femoral fracture in the early postoperative period. Material assignments for biphasic and triphasic models were undertaken. Failure modeling with the element deactivation feature available in ABAQUS 6.9 was used to simulate a crack initiation and propagation in the bony tissue based upon a threshold of fracture strain. The crack mode for the biphasic models was very similar to the experimental testing crack mode, with a similar shape and path of the crack. The fracture load is sensitive to the friction coefficient at the implant-bony interface. The development of a novel technique to simulate bone failure by element deactivation of subject-specific finite element models could aid prediction of fracture load in addition to fracture risk characterization for PFF. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

The Art of Molecular Dynamics Simulation (by D. C. Rapaport)

NASA Astrophysics Data System (ADS)

Molner, Stephen P.

1999-02-01

Cambridge University Press: New York, 1996. 400 pp. ISBN 0 521 44561 2. $74.95. This book describes the extremely powerful techniques of molecular dynamics simulation. The techniques involve solving the classical many-body problems in contexts relevant to the study of matter at the atomic level. The method allows the prediction of static and dynamics properties of substances directly from the underlying interactions between molecules. This is, of course, a very broad subject and the author has adopted a dual approach in that the text is partly tutorial and also contains a large number of computer programs for practical use. Rapaport has adopted the attitude of trying the simplest method first. Atoms are modeled as point particles interacting through point potentials. Molecules are represented by atoms with orientation dependent forces, or as extended structures each containing several interaction sites. The molecules may be rigid, flexible, or somewhere in between, and if there are internal degrees of freedom there will be internal forces as well. The intent of the book is not to discuss the design of molecular models, but rather to make use of existing models, and from a pedagogical viewpoint the simpler the model the better. The aim of the book is to demonstrate the general methodology of molecular dynamics simulation by example, not to review the large body of literature covering the many different kinds of models developed for specific applications. The text is partly tutorial, but also contains a large number of computer programs for practical use. This volume will serve as an introduction to the subject for beginners and as a reference manual for the more experienced practitioner. The material covers a wide range of practical methods and real applications and is organized as a series of case studies. The typical case study includes a summary of the theoretical background used for the formulation of the computational approach. That is described by either a complete program listing or a series of modifications or additions to a program from an earlier case study. The initial conditions of the model, organization of the input and output, accuracy, convergence, and efficiency are also addressed for each case and, of course, the results of the computation are given and discussed. The book begins with the simplest case of basic molecular dynamics, a sift-disk fluid. The development is discussed in considerable depth to set the tone of the work. Later chapters extend the basic model in various directions, deal with various types of measurements, improve the computational methods, and introduce new models for more complex problems. These chapters also discuss the methodology for simulating monatomic systems and focus on measuring the thermodynamic and structural properties of systems in equilibrium. Consideration is given to the dynamical properties of equilibrium systems, including transport coefficients and the correlation functions that characterize space- and time-dependent properties. Chapters are devoted to the study of systems under constant temperature and pressure and the dynamics of rigid systems. It is difficult to cover all aspects of such a broad topic as the subject of this book; and the author has not attempted an exhaustive or encyclopedic coverage, but has produced an excellent introduction to the subject. The publisher has made the implementation of the numerous programs essentially painless by making them available via browser and the World Wide Web. The easy availability of the software, written in C, was welcomed by this old Fortran programmer. It is to be hoped that this service is representative of a trend in technical publishing. Overall this work is a pleasure to read and study and would be a valuable addition to the library of both the beginner and the experienced practitioner of the art.

Dynamic Stability of Uncertain Laminated Beams Under Subtangential Loads

NASA Technical Reports Server (NTRS)

Goyal, Vijay K.; Kapania, Rakesh K.; Adelman, Howard (Technical Monitor); Horta, Lucas (Technical Monitor)

2002-01-01

Because of the inherent complexity of fiber-reinforced laminated composites, it can be challenging to manufacture composite structures according to their exact design specifications, resulting in unwanted material and geometric uncertainties. In this research, we focus on the deterministic and probabilistic stability analysis of laminated structures subject to subtangential loading, a combination of conservative and nonconservative tangential loads, using the dynamic criterion. Thus a shear-deformable laminated beam element, including warping effects, is derived to study the deterministic and probabilistic response of laminated beams. This twenty-one degrees of freedom element can be used for solving both static and dynamic problems. In the first-order shear deformable model used here we have employed a more accurate method to obtain the transverse shear correction factor. The dynamic version of the principle of virtual work for laminated composites is expressed in its nondimensional form and the element tangent stiffness and mass matrices are obtained using analytical integration The stability is studied by giving the structure a small disturbance about an equilibrium configuration, and observing if the resulting response remains small. In order to study the dynamic behavior by including uncertainties into the problem, three models were developed: Exact Monte Carlo Simulation, Sensitivity Based Monte Carlo Simulation, and Probabilistic FEA. These methods were integrated into the developed finite element analysis. Also, perturbation and sensitivity analysis have been used to study nonconservative problems, as well as to study the stability analysis, using the dynamic criterion.

Analysis of piezoelectric energy harvester under modulated and filtered white Gaussian noise

NASA Astrophysics Data System (ADS)

Quaranta, Giuseppe; Trentadue, Francesco; Maruccio, Claudio; Marano, Giuseppe C.

2018-05-01

This paper proposes a comprehensive method for the electromechanical probabilistic analysis of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN) at the base. Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN, which is filtered through the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with a concentrated mass at the free-end, and its global behavior is approximated by the fundamental vibration mode (which is tuned with the dominant frequency of the dynamic input). A resistive electrical load is considered in the circuit. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original and efficient semi-analytical procedure is proposed to estimate mean and standard deviation of the electrical energy extracted from the piezoelectric layers.

Time and frequency domain analysis of sampled data controllers via mixed operation equations

NASA Technical Reports Server (NTRS)

Frisch, H. P.

1981-01-01

Specification of the mathematical equations required to define the dynamic response of a linear continuous plant, subject to sampled data control, is complicated by the fact that the digital components of the control system cannot be modeled via linear ordinary differential equations. This complication can be overcome by introducing two new mathematical operations; namely, the operation of zero order hold and digial delay. It is shown that by direct utilization of these operations, a set of linear mixed operation equations can be written and used to define the dynamic response characteristics of the controlled system. It also is shown how these linear mixed operation equations lead, in an automatable manner, directly to a set of finite difference equations which are in a format compatible with follow on time and frequency domain analysis methods.

Aesthetic episodes, domains, and the mind. Comment on: "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Jacobsen, Thomas

2017-07-01

Aesthetic episodes, as all behavior, are situated. They take place as an interaction of person and situation variables [1]. There are different artistic and aesthetic domains that afford, in part, mutual mental processes, but also fundamentally different, e.g., modality-specific ones [2]. For the infinite number of possible aesthetic episodes a plethora of component processes can be selectively combined and dynamically configured. Following psychophysics' pragmatic dualism of mind and body, this results in dynamically configured (neuro-) biological networks subserving these mental processes [1]. These are, of course, also subject to evolutionary, biological, historical, cultural, and social change [1,3].

Practical approach to subject-specific estimation of knee joint contact force

PubMed Central

Knarr, Brian A.; Higginson, Jill S.

2015-01-01

Compressive forces experienced at the knee can significantly contribute to cartilage degeneration. Musculoskeletal models enable predictions of the internal forces experienced at the knee, but validation is often not possible, as experimental data detailing loading at the knee joint is limited. Recently available data reporting compressive knee force through direct measurement using instrumented total knee replacements offer a unique opportunity to evaluate the accuracy of models. Previous studies have highlighted the importance of subject-specificity in increasing the accuracy of model predictions; however, these techniques may be unrealistic outside of a research setting. Therefore, the goal of our work was to identify a practical approach for accurate prediction of tibiofemoral knee contact force (KCF). Four methods for prediction of knee contact force were compared: (1) standard static optimization, (2) uniform muscle coordination weighting, (3) subject-specific muscle coordination weighting and (4) subject-specific strength adjustments. Walking trials for three subjects with instrumented knee replacements were used to evaluate the accuracy of model predictions. Predictions utilizing subject-specific muscle coordination weighting yielded the best agreement with experimental data, however this method required in vivo data for weighting factor calibration. Including subject-specific strength adjustments improved models’ predictions compared to standard static optimization, with errors in peak KCF less than 0.5 body weight for all subjects. Overall, combining clinical assessments of muscle strength with standard tools available in the OpenSim software package, such as inverse kinematics and static optimization, appears to be a practical method for predicting joint contact force that can be implemented for many applications. PMID:25952546

Estimating the actual subject-specific genetic correlations in behavior genetics.

PubMed

Molenaar, Peter C M

2012-10-01

Generalization of the standard behavior longitudinal genetic factor model for the analysis of interindividual phenotypic variation to a genetic state space model for the analysis of intraindividual variation enables the possibility to estimate subject-specific heritabilities.

Structure and dynamics of zymogen human blood coagulation factor X.

PubMed

Venkateswarlu, Divi; Perera, Lalith; Darden, Tom; Pedersen, Lee G

2002-03-01

The solution structure and dynamics of the human coagulation factor X (FX) have been investigated to understand the key structural elements in the zymogenic form that participates in the activation process. The model was constructed based on the 2.3-A-resolution x-ray crystallographic structure of active-site inhibited human FXa (PDB:1XKA). The missing gamma-carboxyglutamic acid (GLA) and part of epidermal growth factor 1 (EGF1) domains of the light chain were modeled based on the template of GLA-EGF1 domains of the tissue factor (TF)-bound FVIIa structure (PDB:1DAN). The activation peptide and other missing segments of FX were introduced using homology modeling. The full calcium-bound model of FX was subjected to 6.2 ns of molecular dynamics simulation in aqueous medium using the AMBER6.0 package. We observed significant reorientation of the serine-protease (SP) domain upon activation leading to a compact multi-domain structure. The solution structure of zymogen appears to be in a well-extended conformation with the distance between the calcium ions in the GLA domain and the catalytic residues estimated to be approximately 95 A in contrast to approximately 83 A in the activated form. The latter is in close agreement with fluorescence studies on FXa. The S1-specificity residues near the catalytic triad show significant differences between the zymogen and activated structures.

Tracking slow modulations in synaptic gain using dynamic causal modelling: validation in epilepsy.

PubMed

Papadopoulou, Margarita; Leite, Marco; van Mierlo, Pieter; Vonck, Kristl; Lemieux, Louis; Friston, Karl; Marinazzo, Daniele

2015-02-15

In this work we propose a proof of principle that dynamic causal modelling can identify plausible mechanisms at the synaptic level underlying brain state changes over a timescale of seconds. As a benchmark example for validation we used intracranial electroencephalographic signals in a human subject. These data were used to infer the (effective connectivity) architecture of synaptic connections among neural populations assumed to generate seizure activity. Dynamic causal modelling allowed us to quantify empirical changes in spectral activity in terms of a trajectory in parameter space - identifying key synaptic parameters or connections that cause observed signals. Using recordings from three seizures in one patient, we considered a network of two sources (within and just outside the putative ictal zone). Bayesian model selection was used to identify the intrinsic (within-source) and extrinsic (between-source) connectivity. Having established the underlying architecture, we were able to track the evolution of key connectivity parameters (e.g., inhibitory connections to superficial pyramidal cells) and test specific hypotheses about the synaptic mechanisms involved in ictogenesis. Our key finding was that intrinsic synaptic changes were sufficient to explain seizure onset, where these changes showed dissociable time courses over several seconds. Crucially, these changes spoke to an increase in the sensitivity of principal cells to intrinsic inhibitory afferents and a transient loss of excitatory-inhibitory balance. Copyright © 2014. Published by Elsevier Inc.

Transferring and generalizing deep-learning-based neural encoding models across subjects.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-08-01

Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or encoding models), requires measuring cortical responses to large and diverse sets of natural visual stimuli from single subjects. This requirement limits prior studies to few subjects, making it difficult to generalize findings across subjects or for a population. In this study, we developed new methods to transfer and generalize encoding models across subjects. To train encoding models specific to a target subject, the models trained for other subjects were used as the prior models and were refined efficiently using Bayesian inference with a limited amount of data from the target subject. To train encoding models for a population, the models were progressively trained and updated with incremental data from different subjects. For the proof of principle, we applied these methods to functional magnetic resonance imaging (fMRI) data from three subjects watching tens of hours of naturalistic videos, while a deep residual neural network driven by image recognition was used to model visual cortical processing. Results demonstrate that the methods developed herein provide an efficient and effective strategy to establish both subject-specific and population-wide predictive models of cortical representations of high-dimensional and hierarchical visual features. Copyright © 2018 Elsevier Inc. All rights reserved.

A Unified Point Process Probabilistic Framework to Assess Heartbeat Dynamics and Autonomic Cardiovascular Control

PubMed Central

Chen, Zhe; Purdon, Patrick L.; Brown, Emery N.; Barbieri, Riccardo

2012-01-01

In recent years, time-varying inhomogeneous point process models have been introduced for assessment of instantaneous heartbeat dynamics as well as specific cardiovascular control mechanisms and hemodynamics. Assessment of the model’s statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR) structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR), heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and baroreceptor-cardiac reflex (baroreflex) sensitivity (BRS), are derived within a parametric framework and instantaneously updated with adaptive and local maximum likelihood estimation algorithms. Inclusion of second-order non-linearities, with subsequent bispectral quantification in the frequency domain, further allows for definition of instantaneous metrics of non-linearity. We here present a comprehensive review of the devised methods as applied to experimental recordings from healthy subjects during propofol anesthesia. Collective results reveal interesting dynamic trends across the different pharmacological interventions operated within each anesthesia session, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, non-invasive assessment in clinical practice. We also discuss the limitations and other alternative modeling strategies of our point process approach. PMID:22375120

A Prediction of Response of the Head and Neck of the U.S. Adult Military Population to Dynamic Impact Acceleration from Selected Dynamic Test Subjects.

DTIC Science & Technology

1976-05-01

to Review Grants for Clinical Research and Investigation Involving Human Beings, Medical School, The University of Michigan. 3 of biomechanical models...human volunteers in dynamic sled tests found no clinically observable effects. due to acceleration on a subject in which the peak mouth angular...minutes cf rest between trials , and the average fo-ce of each set computed. Figure 2.7 shows typi- cal forcc curves and the EMG signal resulting from

Dynamic and kinematic strategies for head movement control

NASA Technical Reports Server (NTRS)

Peterson, B. W.; Choi, H.; Hain, T.; Keshner, E.; Peng, G. C.

2001-01-01

This paper describes our analysis of the complex head-neck system using a combination of experimental and modeling approaches. Dynamical analysis of head movements and EMG activation elicited by perturbation of trunk position has examined functional contributions of biomechanically and neurally generated forces in lumped systems with greatly simplified kinematics. This has revealed that visual and voluntary control of neck muscles and the dynamic and static vestibulocollic and cervicocollic reflexes preferentially govern head-neck system state in different frequency domains. It also documents redundant control, which allows the system to compensate for lesions and creates a potential for substantial variability within and between subjects. Kinematic studies have indicated the existence of reciprocal and co-contraction strategies for voluntary force generation, of a vestibulocollic strategy for stabilizing the head during body perturbations and of at least two strategies for voluntary head tracking. Each strategy appears to be executed by a specific muscle synergy that is presumably optimized to efficiently meet the demands of the task.

Space station structures and dynamics test program

NASA Technical Reports Server (NTRS)

Moore, Carleton J.; Townsend, John S.; Ivey, Edward W.

1987-01-01

The design, construction, and operation of a low-Earth orbit space station poses unique challenges for development and implementation of new technology. The technology arises from the special requirement that the station be built and constructed to function in a weightless environment, where static loads are minimal and secondary to system dynamics and control problems. One specific challenge confronting NASA is the development of a dynamics test program for: (1) defining space station design requirements, and (2) identifying the characterizing phenomena affecting the station's design and development. A general definition of the space station dynamic test program, as proposed by MSFC, forms the subject of this report. The test proposal is a comprehensive structural dynamics program to be launched in support of the space station. The test program will help to define the key issues and/or problems inherent to large space structure analysis, design, and testing. Development of a parametric data base and verification of the math models and analytical analysis tools necessary for engineering support of the station's design, construction, and operation provide the impetus for the dynamics test program. The philosophy is to integrate dynamics into the design phase through extensive ground testing and analytical ground simulations of generic systems, prototype elements, and subassemblies. On-orbit testing of the station will also be used to define its capability.

Goddard trajectory determination subsystem: Mathematical specifications

NASA Technical Reports Server (NTRS)

Wagner, W. E. (Editor); Velez, C. E. (Editor)

1972-01-01

The mathematical specifications of the Goddard trajectory determination subsystem of the flight dynamics system are presented. These specifications include the mathematical description of the coordinate systems, dynamic and measurement model, numerical integration techniques, and statistical estimation concepts.

Dynamic Causal Modeling of Preclinical Autosomal-Dominant Alzheimer's Disease.

PubMed

Penny, Will; Iglesias-Fuster, Jorge; Quiroz, Yakeel T; Lopera, Francisco Javier; Bobes, Maria A

2018-03-16

Dynamic causal modeling (DCM) is a framework for making inferences about changes in brain connectivity using neuroimaging data. We fitted DCMs to high-density EEG data from subjects performing a semantic picture matching task. The subjects are carriers of the PSEN1 mutation, which leads to early onset Alzheimer's disease, but at the time of EEG acquisition in 1999, these subjects were cognitively unimpaired. We asked 1) what is the optimal model architecture for explaining the event-related potentials in this population, 2) which connections are different between this Presymptomatic Carrier (PreC) group and a Non-Carrier (NonC) group performing the same task, and 3) which network connections are predictive of subsequent Mini-Mental State Exam (MMSE) trajectories. We found 1) a model with hierarchical rather than lateral connections between hemispheres to be optimal, 2) that a pathway from right inferotemporal cortex (IT) to left medial temporal lobe (MTL) was preferentially activated by incongruent items for subjects in the PreC group but not the NonC group, and 3) that increased effective connectivity among left MTL, right IT, and right MTL was predictive of subsequent MMSE scores.

Construction of 4D high-definition cortical surface atlases of infants: Methods and applications.

PubMed

Li, Gang; Wang, Li; Shi, Feng; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-10-01

In neuroimaging, cortical surface atlases play a fundamental role for spatial normalization, analysis, visualization, and comparison of results across individuals and different studies. However, existing cortical surface atlases created for adults are not suitable for infant brains during the first two postnatal years, which is the most dynamic period of postnatal structural and functional development of the highly-folded cerebral cortex. Therefore, spatiotemporal cortical surface atlases for infant brains are highly desired yet still lacking for accurate mapping of early dynamic brain development. To bridge this significant gap, leveraging our infant-dedicated computational pipeline for cortical surface-based analysis and the unique longitudinal infant MRI dataset acquired in our research center, in this paper, we construct the first spatiotemporal (4D) high-definition cortical surface atlases for the dynamic developing infant cortical structures at seven time points, including 1, 3, 6, 9, 12, 18, and 24 months of age, based on 202 serial MRI scans from 35 healthy infants. For this purpose, we develop a novel method to ensure the longitudinal consistency and unbiasedness to any specific subject and age in our 4D infant cortical surface atlases. Specifically, we first compute the within-subject mean cortical folding by unbiased groupwise registration of longitudinal cortical surfaces of each infant. Then we establish longitudinally-consistent and unbiased inter-subject cortical correspondences by groupwise registration of the geometric features of within-subject mean cortical folding across all infants. Our 4D surface atlases capture both longitudinally-consistent dynamic mean shape changes and the individual variability of cortical folding during early brain development. Experimental results on two independent infant MRI datasets show that using our 4D infant cortical surface atlases as templates leads to significantly improved accuracy for spatial normalization of cortical surfaces across infant individuals, in comparison to the infant surface atlases constructed without longitudinal consistency and also the FreeSurfer adult surface atlas. Moreover, based on our 4D infant surface atlases, for the first time, we reveal the spatially-detailed, region-specific correlation patterns of the dynamic cortical developmental trajectories between different cortical regions during early brain development. Copyright © 2015 Elsevier B.V. All rights reserved.

A 3D subject-specific model of the spinal subarachnoid space with anatomically realistic ventral and dorsal spinal cord nerve rootlets.

PubMed

Sass, Lucas R; Khani, Mohammadreza; Natividad, Gabryel Connely; Tubbs, R Shane; Baledent, Olivier; Martin, Bryn A

2017-12-19

The spinal subarachnoid space (SSS) has a complex 3D fluid-filled geometry with multiple levels of anatomic complexity, the most salient features being the spinal cord and dorsal and ventral nerve rootlets. An accurate anthropomorphic representation of these features is needed for development of in vitro and numerical models of cerebrospinal fluid (CSF) dynamics that can be used to inform and optimize CSF-based therapeutics. A subject-specific 3D model of the SSS was constructed based on high-resolution anatomic MRI. An expert operator completed manual segmentation of the CSF space with detailed consideration of the anatomy. 31 pairs of semi-idealized dorsal and ventral nerve rootlets (NR) were added to the model based on anatomic reference to the magnetic resonance (MR) imaging and cadaveric measurements in the literature. Key design criteria for each NR pair included the radicular line, descending angle, number of NR, attachment location along the spinal cord and exit through the dura mater. Model simplification and smoothing was performed to produce a final model with minimum vertices while maintaining minimum error between the original segmentation and final design. Final model geometry and hydrodynamics were characterized in terms of axial distribution of Reynolds number, Womersley number, hydraulic diameter, cross-sectional area and perimeter. The final model had a total of 139,901 vertices with a total CSF volume within the SSS of 97.3 cm 3 . Volume of the dura mater, spinal cord and NR was 123.1, 19.9 and 5.8 cm 3 . Surface area of these features was 318.52, 112.2 and 232.1 cm 2 respectively. Maximum Reynolds number was 174.9 and average Womersley number was 9.6, likely indicating presence of a laminar inertia-dominated oscillatory CSF flow field. This study details an anatomically realistic anthropomorphic 3D model of the SSS based on high-resolution MR imaging of a healthy human adult female. The model is provided for re-use under the Creative Commons Attribution-ShareAlike 4.0 International license (CC BY-SA 4.0) and can be used as a tool for development of in vitro and numerical models of CSF dynamics for design and optimization of intrathecal therapeutics.

LMI-Based Fuzzy Optimal Variance Control of Airfoil Model Subject to Input Constraints

NASA Technical Reports Server (NTRS)

Swei, Sean S.M.; Ayoubi, Mohammad A.

2017-01-01

This paper presents a study of fuzzy optimal variance control problem for dynamical systems subject to actuator amplitude and rate constraints. Using Takagi-Sugeno fuzzy modeling and dynamic Parallel Distributed Compensation technique, the stability and the constraints can be cast as a multi-objective optimization problem in the form of Linear Matrix Inequalities. By utilizing the formulations and solutions for the input and output variance constraint problems, we develop a fuzzy full-state feedback controller. The stability and performance of the proposed controller is demonstrated through its application to the airfoil flutter suppression.

Vortex Dynamics and Shear-Layer Instability in High-Intensity Cyclotrons.

PubMed

Cerfon, Antoine J

2016-04-29

We show that the space-charge dynamics of high-intensity beams in the plane perpendicular to the magnetic field in cyclotrons is described by the two-dimensional Euler equations for an incompressible fluid. This analogy with fluid dynamics gives a unified and intuitive framework to explain the beam spiraling and beam breakup behavior observed in experiments and in simulations. Specifically, we demonstrate that beam breakup is the result of a classical instability occurring in fluids subject to a sheared flow. We give scaling laws for the instability and predict the nonlinear evolution of beams subject to it. Our work suggests that cyclotrons may be uniquely suited for the experimental study of shear layers and vortex distributions that are not achievable in Penning-Malmberg traps.

Experimental studies on the tripping behavior of narrow T-stiffened flat plates subjected to hydrostatic pressure and underwater shock

NASA Technical Reports Server (NTRS)

Budweg, H. L.; Shin, Y. S.

1987-01-01

An experimental investigation was conducted to determine the static and dynamic responses of a specific stiffened flat plate design. The air-backed rectangular flat plates of 6061-T6 aluminum with an externally machined longitudinal narrow-flanged T-stiffener and clamped boundary conditions were subjected to static loading by water hydropump pressure and shock loading from an eight pound TNT charge detonated underwater. The dynamic test plate was instrumented to measure transient strains and free field pressure. The static test plate was instrumented to measure transient strains, plate deflection, and pressure. Emphasis was placed upon forcing static and dynamic stiffener tripping, obtaining relevant strain and pressure data, and studying the associated plate-stiffener behavior.

The internal model: A study of the relative contribution of proprioception and visual information to failure detection in dynamic systems. [sensitivity of operators versus monitors to failures

NASA Technical Reports Server (NTRS)

Kessel, C.; Wickens, C. D.

1978-01-01

The development of the internal model as it pertains to the detection of step changes in the order of control dynamics is investigated for two modes of participation: whether the subjects are actively controlling those dynamics or are monitoring an autopilot controlling them. A transfer of training design was used to evaluate the relative contribution of proprioception and visual information to the overall accuracy of the internal model. Sixteen subjects either tracked or monitored the system dynamics as a 2-dimensional pursuit display under single task conditions and concurrently with a sub-critical tracking task at two difficulty levels. Detection performance was faster and more accurate in the manual as opposed to the autopilot mode. The concurrent tracking task produced a decrement in detection performance for all conditions though this was more marked for the manual mode. The development of an internal model in the manual mode transferred positively to the automatic mode producing enhanced detection performance. There was no transfer from the internal model developed in the automatic mode to the manual mode.

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.

PubMed

Ferradal, Silvina L; Eggebrecht, Adam T; Hassanpour, Mahlega; Snyder, Abraham Z; Culver, Joseph P

2014-01-15

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available. Copyright © 2013. Published by Elsevier Inc.

Visualizing Hyolaryngeal Mechanics in Swallowing Using Dynamic MRI

PubMed Central

Pearson, William G.; Zumwalt, Ann C.

2013-01-01

Introduction Coordinates of anatomical landmarks are captured using dynamic MRI to explore whether a proposed two-sling mechanism underlies hyolaryngeal elevation in pharyngeal swallowing. A principal components analysis (PCA) is applied to coordinates to determine the covariant function of the proposed mechanism. Methods Dynamic MRI (dMRI) data were acquired from eleven healthy subjects during a repeated swallows task. Coordinates mapping the proposed mechanism are collected from each dynamic (frame) of a dynamic MRI swallowing series of a randomly selected subject in order to demonstrate shape changes in a single subject. Coordinates representing minimum and maximum hyolaryngeal elevation of all 11 subjects were also mapped to demonstrate shape changes of the system among all subjects. MophoJ software was used to perform PCA and determine vectors of shape change (eigenvectors) for elements of the two-sling mechanism of hyolaryngeal elevation. Results For both single subject and group PCAs, hyolaryngeal elevation accounted for the first principal component of variation. For the single subject PCA, the first principal component accounted for 81.5% of the variance. For the between subjects PCA, the first principal component accounted for 58.5% of the variance. Eigenvectors and shape changes associated with this first principal component are reported. Discussion Eigenvectors indicate that two-muscle slings and associated skeletal elements function as components of a covariant mechanism to elevate the hyolaryngeal complex. Morphological analysis is useful to model shape changes in the two-sling mechanism of hyolaryngeal elevation. PMID:25090608

Reproducibility of haemodynamical simulations in a subject-specific stented aneurysm model--a report on the Virtual Intracranial Stenting Challenge 2007.

PubMed

Radaelli, A G; Augsburger, L; Cebral, J R; Ohta, M; Rüfenacht, D A; Balossino, R; Benndorf, G; Hose, D R; Marzo, A; Metcalfe, R; Mortier, P; Mut, F; Reymond, P; Socci, L; Verhegghe, B; Frangi, A F

2008-07-19

This paper presents the results of the Virtual Intracranial Stenting Challenge (VISC) 2007, an international initiative whose aim was to establish the reproducibility of state-of-the-art haemodynamical simulation techniques in subject-specific stented models of intracranial aneurysms (IAs). IAs are pathological dilatations of the cerebral artery walls, which are associated with high mortality and morbidity rates due to subarachnoid haemorrhage following rupture. The deployment of a stent as flow diverter has recently been indicated as a promising treatment option, which has the potential to protect the aneurysm by reducing the action of haemodynamical forces and facilitating aneurysm thrombosis. The direct assessment of changes in aneurysm haemodynamics after stent deployment is hampered by limitations in existing imaging techniques and currently requires resorting to numerical simulations. Numerical simulations also have the potential to assist in the personalized selection of an optimal stent design prior to intervention. However, from the current literature it is difficult to assess the level of technological advancement and the reproducibility of haemodynamical predictions in stented patient-specific models. The VISC 2007 initiative engaged in the development of a multicentre-controlled benchmark to analyse differences induced by diverse grid generation and computational fluid dynamics (CFD) technologies. The challenge also represented an opportunity to provide a survey of available technologies currently adopted by international teams from both academic and industrial institutions for constructing computational models of stented aneurysms. The results demonstrate the ability of current strategies in consistently quantifying the performance of three commercial intracranial stents, and contribute to reinforce the confidence in haemodynamical simulation, thus taking a step forward towards the introduction of simulation tools to support diagnostics and interventional planning.

Training Maneuver Evaluation for Reduced Order Modeling of Stability & Control Properties Using Computational Fluid Dynamics

DTIC Science & Technology

2013-03-01

reduced order model is created. Finally, previous research in this area of study will be examined, and its application to this research will be...TRAINING MANEUVER EVALUATION FOR REDUCED ORDER MODELING OF STABILITY & CONTROL PROPERTIES USING COMPUTATIONAL FLUID DYNAMICS THESIS Craig Curtis...Government and is not subject to copyright protection in the United States. AFIT-ENY-13-M-28 TRAINING MANEUVER EVALUATION FOR REDUCED ORDER MODELING OF

RELATING ACCUMULATOR MODEL PARAMETERS AND NEURAL DYNAMICS

PubMed Central

Purcell, Braden A.; Palmeri, Thomas J.

2016-01-01

Accumulator models explain decision-making as an accumulation of evidence to a response threshold. Specific model parameters are associated with specific model mechanisms, such as the time when accumulation begins, the average rate of evidence accumulation, and the threshold. These mechanisms determine both the within-trial dynamics of evidence accumulation and the predicted behavior. Cognitive modelers usually infer what mechanisms vary during decision-making by seeing what parameters vary when a model is fitted to observed behavior. The recent identification of neural activity with evidence accumulation suggests that it may be possible to directly infer what mechanisms vary from an analysis of how neural dynamics vary. However, evidence accumulation is often noisy, and noise complicates the relationship between accumulator dynamics and the underlying mechanisms leading to those dynamics. To understand what kinds of inferences can be made about decision-making mechanisms based on measures of neural dynamics, we measured simulated accumulator model dynamics while systematically varying model parameters. In some cases, decision- making mechanisms can be directly inferred from dynamics, allowing us to distinguish between models that make identical behavioral predictions. In other cases, however, different parameterized mechanisms produce surprisingly similar dynamics, limiting the inferences that can be made based on measuring dynamics alone. Analyzing neural dynamics can provide a powerful tool to resolve model mimicry at the behavioral level, but we caution against drawing inferences based solely on neural analyses. Instead, simultaneous modeling of behavior and neural dynamics provides the most powerful approach to understand decision-making and likely other aspects of cognition and perception. PMID:28392584

Rearfoot eversion has indirect effects on plantar fascia tension by changing the amount of arch collapse.

PubMed

Lee, Sae Yong; Hertel, Jay; Lee, Sung Cheol

2010-01-01

Rearfoot eversion motion and arch height are believed to contribute to increased tension on the plantar fascia and arch collapse during gait but the specifics of these relationships are not clear. To examine the relationships among static arch height, rearfoot eversion, dynamic arch height, and plantar fascia tension. 28 healthy males participated. After static arch height was measured, the subjects were asked to run at 4.5m/s while frontal plane rearfoot motion, dynamic arch height, and ground reaction forces were collected. The relationships among variables were examined with bivariate correlations and path analysis. The results indicated a high correlation between dynamic arch height and static arch height (r=0.642), plantar fascia tension (r=-0.797), and maximum rearfoot eversion motion during gait (r=-0.518). The path analysis model without the direct rearfoot eversion effect explained 81.2% of the variance in plantar fascia tension, while the model with the direct rearfoot eversion effect explained 82.1% of the variance in plantar fascia tension. Including the indirect effect of maximum rearfoot eversion motion on plantar fascia tension through control of dynamic arch height is the model that best explains the interrelationships of these foot characteristics. The amount of maximum rearfoot eversion motion itself is not a good predictor of plantar fascia tension, however, together with the arch height, maximum rearfoot eversion motion is a good predictor because it has a pronounced indirect effect on plantar fascia tension. Copyright 2010. Published by Elsevier Ltd.

Longitudinal Validation of General and Specific Structural Features of Personality Pathology

PubMed Central

Wright, Aidan G.C.; Hopwood, Christopher J.; Skodol, Andrew E.; Morey, Leslie C.

2016-01-01

Theorists have long argued that personality disorder (PD) is best understood in terms of general impairments shared across the disorders as well as more specific instantiations of pathology. A model based on this theoretical structure was proposed as part of the DSM-5 revision process. However, only recently has this structure been subjected to formal quantitative evaluation, with little in the way of validation efforts via external correlates or prospective longitudinal prediction. We used the Collaborative Longitudinal Study of Personality Disorders dataset to: (1) estimate structural models that parse general from specific variance in personality disorder features, (2) examine patterns of growth in general and specific features over the course of 10 years, and (3) establish concurrent and dynamic longitudinal associations in PD features and a host of external validators including basic personality traits and psychosocial functioning scales. We found that general PD exhibited much lower absolute stability and was most strongly related to broad markers of psychosocial functioning, concurrently and longitudinally, whereas specific features had much higher mean stability and exhibited more circumscribed associations with functioning. However, both general and specific factors showed recognizable associations with normative and pathological traits. These results can inform efforts to refine the conceptualization and diagnosis of personality pathology. PMID:27819472

Comparing predictions of extinction risk using models and subjective judgement

NASA Astrophysics Data System (ADS)

McCarthy, Michael A.; Keith, David; Tietjen, Justine; Burgman, Mark A.; Maunder, Mark; Master, Larry; Brook, Barry W.; Mace, Georgina; Possingham, Hugh P.; Medellin, Rodrigo; Andelman, Sandy; Regan, Helen; Regan, Tracey; Ruckelshaus, Mary

2004-10-01

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models.

Conditional random matrix ensembles and the stability of dynamical systems

NASA Astrophysics Data System (ADS)

Kirk, Paul; Rolando, Delphine M. Y.; MacLean, Adam L.; Stumpf, Michael P. H.

2015-08-01

Random matrix theory (RMT) has found applications throughout physics and applied mathematics, in subject areas as diverse as communications networks, population dynamics, neuroscience, and models of the banking system. Many of these analyses exploit elegant analytical results, particularly the circular law and its extensions. In order to apply these results, assumptions must be made about the distribution of matrix elements. Here we demonstrate that the choice of matrix distribution is crucial. In particular, adopting an unrealistic matrix distribution for the sake of analytical tractability is liable to lead to misleading conclusions. We focus on the application of RMT to the long-standing, and at times fractious, ‘diversity-stability debate’, which is concerned with establishing whether large complex systems are likely to be stable. Early work (and subsequent elaborations) brought RMT to bear on the debate by modelling the entries of a system’s Jacobian matrix as independent and identically distributed (i.i.d.) random variables. These analyses were successful in yielding general results that were not tied to any specific system, but relied upon a restrictive i.i.d. assumption. Other studies took an opposing approach, seeking to elucidate general principles of stability through the analysis of specific systems. Here we develop a statistical framework that reconciles these two contrasting approaches. We use a range of illustrative dynamical systems examples to demonstrate that: (i) stability probability cannot be summarily deduced from any single property of the system (e.g. its diversity); and (ii) our assessment of stability depends on adequately capturing the details of the systems analysed. Failing to condition on the structure of dynamical systems will skew our analysis and can, even for very small systems, result in an unnecessarily pessimistic diagnosis of their stability.

The mathematical cell model reconstructed from interference microscopy data

NASA Astrophysics Data System (ADS)

Rogotnev, A. A.; Nikitiuk, A. S.; Naimark, O. B.; Nebogatikov, V. O.; Grishko, V. V.

2017-09-01

The mathematical model of cell dynamics is developed to link the dynamics of the phase cell thickness with the signs of the oncological pathology. The measurements of irregular oscillations of cancer cells phase thickness were made with laser interference microscope MIM-340 in order to substantiate this model. These data related to the dynamics of phase thickness for different cross-sections of cells (nuclei, nucleolus, and cytoplasm) allow the reconstruction of the attractor of dynamic system. The attractor can be associated with specific types of collective modes of phase thickness responsible for the normal and cancerous cell dynamics. Specific type of evolution operator was determined using an algorithm of designing of the mathematical cell model and temporal phase thickness data for cancerous and normal cells. Qualitative correspondence of attractor types to the cell states was analyzed in terms of morphological signs associated with maximum value of mean square irregular oscillations of phase thickness dynamics.

Characterizing psychological dimensions in non-pathological subjects through autonomic nervous system dynamics

PubMed Central

Nardelli, Mimma; Valenza, Gaetano; Cristea, Ioana A.; Gentili, Claudio; Cotet, Carmen; David, Daniel; Lanata, Antonio; Scilingo, Enzo P.

2015-01-01

The objective assessment of psychological traits of healthy subjects and psychiatric patients has been growing interest in clinical and bioengineering research fields during the last decade. Several experimental evidences strongly suggest that a link between Autonomic Nervous System (ANS) dynamics and specific dimensions such as anxiety, social phobia, stress, and emotional regulation might exist. Nevertheless, an extensive investigation on a wide range of psycho-cognitive scales and ANS non-invasive markers gathered from standard and non-linear analysis still needs to be addressed. In this study, we analyzed the discerning and correlation capabilities of a comprehensive set of ANS features and psycho-cognitive scales in 29 non-pathological subjects monitored during resting conditions. In particular, the state of the art of standard and non-linear analysis was performed on Heart Rate Variability, InterBreath Interval series, and InterBeat Respiration series, which were considered as monovariate and multivariate measurements. Experimental results show that each ANS feature is linked to specific psychological traits. Moreover, non-linear analysis outperforms the psychological assessment with respect to standard analysis. Considering that the current clinical practice relies only on subjective scores from interviews and questionnaires, this study provides objective tools for the assessment of psychological dimensions. PMID:25859212

Molecular Dynamics Studies of Liposomes as Carriers for Photosensitizing Drugs: Development, Validation, and Simulations with a Coarse-Grained Model.

PubMed

Jämbeck, Joakim P M; Eriksson, Emma S E; Laaksonen, Aatto; Lyubartsev, Alexander P; Eriksson, Leif A

2014-01-14

Liposomes are proposed as drug delivery systems and can in principle be designed so as to cohere with specific tissue types or local environments. However, little detail is known about the exact mechanisms for drug delivery and the distributions of drug molecules inside the lipid carrier. In the current work, a coarse-grained (CG) liposome model is developed, consisting of over 2500 lipids, with varying degrees of drug loading. For the drug molecule, we chose hypericin, a natural compound proposed for use in photodynamic therapy, for which a CG model was derived and benchmarked against corresponding atomistic membrane bilayer model simulations. Liposomes with 21-84 hypericin molecules were generated and subjected to 10 microsecond simulations. Distribution of the hypericins, their orientations within the lipid bilayer, and the potential of mean force for transferring a hypericin molecule from the interior aqueous "droplet" through the liposome bilayer are reported herein.

The Dynamics of a Periodically Forced Cortical Microcircuit, With an Application to Schizophrenia

NASA Astrophysics Data System (ADS)

Vierling-Claassen, Dorea; Kopell, Nancy

2009-01-01

Synchronous neural activity in the brain in the gamma and beta frequency bands (50-70 Hz)is thought to be important for sensory processing and is altered in schizophrenia. In a previous study, gamma/beta click-train auditory stimuli were used to probe cortical oscillatory activity in control and schizophrenic subjects. We found that control subjects exhibited preferential 40 Hz responses to both 20 and 40 Hz stimulations, while schizophrenic subjects had enhanced 20 Hz responses to the same stimuli [D. Vierling-Claassen, P. Siekmeier, S. Stufflebeam, and N. Kopell, J. Neurophysiol., 99 (2008), p. 2656]. High-dimensional computational network models constructed previously, which were based on evidence of altered inhibition in schizophrenia, numerically generated the entrainment behaviors observed experimentally. However, questions regarding the dynamic origin of model behaviors remained. It was not clear that the 20 Hz response to 40 Hz drive in the schizophrenic network was robust to parameter changes, which would be necessary for the predicted mechanism to explain data from a heterogeneous subject population. In the schizophrenic network we observed 30 Hz drive responses with a frequency component below 30 Hz, for which no analogue appeared in experimental data, and wondered if these were dynamically distinct from the modeled 20 Hz response to 40 Hz drive. We also wished to explore the role of background noise in model behavior. To address these questions, we consider a system of two mutually coupled oscillators representative of neural cells, driven periodically in the gamma/beta frequency band. We show that there is a one-parameter family of discontinuous discrete maps, whose dynamics clarifies issues of robustness, classifies entrainment patterns, and provides insight into the role of excitatory noise.

Planetary Suit Hip Bearing Model for Predicting Design vs. Performance

NASA Technical Reports Server (NTRS)

Cowley, Matthew S.; Margerum, Sarah; Harvil, Lauren; Rajulu, Sudhakar

2011-01-01

Designing a planetary suit is very complex and often requires difficult trade-offs between performance, cost, mass, and system complexity. In order to verifying that new suit designs meet requirements, full prototypes must eventually be built and tested with human subjects. Using computer models early in the design phase of new hardware development can be advantageous, allowing virtual prototyping to take place. Having easily modifiable models of the suit hard sections may reduce the time it takes to make changes to the hardware designs and then to understand their impact on suit and human performance. A virtual design environment gives designers the ability to think outside the box and exhaust design possibilities before building and testing physical prototypes with human subjects. Reductions in prototyping and testing may eventually reduce development costs. This study is an attempt to develop computer models of the hard components of the suit with known physical characteristics, supplemented with human subject performance data. Objectives: The primary objective was to develop an articulating solid model of the Mark III hip bearings to be used for evaluating suit design performance of the hip joint. Methods: Solid models of a planetary prototype (Mark III) suit s hip bearings and brief section were reverse-engineered from the prototype. The performance of the models was then compared by evaluating the mobility performance differences between the nominal hardware configuration and hardware modifications. This was accomplished by gathering data from specific suited tasks. Subjects performed maximum flexion and abduction tasks while in a nominal suit bearing configuration and in three off-nominal configurations. Performance data for the hip were recorded using state-of-the-art motion capture technology. Results: The results demonstrate that solid models of planetary suit hard segments for use as a performance design tool is feasible. From a general trend perspective, the suited performance trends were comparable between the model and the suited subjects. With the three off-nominal bearing configurations compared to the nominal bearing configurations, human subjects showed decreases in hip flexion of 64%, 6%, and 13% and in hip abduction of 59%, 2%, and 20%. Likewise the solid model showed decreases in hip flexion of 58%, 1%, and 25% and in hip abduction of 56%, 0%, and 30%, under the same condition changes from the nominal configuration. Differences seen between the model predictions and the human subject performance data could be attributed to the model lacking dynamic elements and performing kinematic analysis only, the level of fit of the subjects with the suit, the levels of the subject s suit experience.

Model-based active control of a continuous structure subjected to moving loads

NASA Astrophysics Data System (ADS)

Stancioiu, D.; Ouyang, H.

2016-09-01

Modelling of a structure is an important preliminary step of structural control. The main objectives of the modelling, which are almost always antagonistic are accuracy and simplicity of the model. The first part of this study focuses on the experimental and theoretical modelling of a structure subjected to the action of one or two decelerating moving carriages modelled as masses. The aim of this part is to obtain a simple but accurate model which will include not only the structure-moving load interaction but also the actuators dynamics. A small scale rig is designed to represent a four-span continuous metallic bridge structure with miniature guiding rails. A series of tests are run subjecting the structure to the action of one or two minicarriages with different loads that were launched along the structure at different initial speeds. The second part is dedicated to model based control design where a feedback controller is designed and tested against the validated model. The study shows that a positive position feedback is able to improve system dynamics but also shows some of the limitations of state- space methods for this type of system.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait.

PubMed

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E; Del-Ama, Antonio J; Dimbwadyo, Iris; Moreno, Juan C; Florez, Julian; Pons, Jose L

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait

PubMed Central

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E.; del-Ama, Antonio J.; Dimbwadyo, Iris; Moreno, Juan C.; Florez, Julian; Pons, Jose L.

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton. PMID:29755336

A Comparison of Pseudo-Maximum Likelihood and Asymptotically Distribution-Free Dynamic Factor Analysis Parameter Estimation in Fitting Covariance Structure Models to Block-Toeplitz Matrices Representing Single-Subject Multivariate Time-Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

1998-01-01

Pseudo-Maximum Likelihood (p-ML) and Asymptotically Distribution Free (ADF) estimation methods for estimating dynamic factor model parameters within a covariance structure framework were compared through a Monte Carlo simulation. Both methods appear to give consistent model parameter estimates, but only ADF gives standard errors and chi-square…

Design of patient-specific gait modifications for knee osteoarthritis rehabilitation.

PubMed

Fregly, Benjamin J; Reinbolt, Jeffrey A; Rooney, Kelly L; Mitchell, Kim H; Chmielewski, Terese L

2007-09-01

Abstract-Gait modification is a nonsurgical approach for reducing the external knee adduction torque in patients with knee osteoarthritis (OA). The magnitude of the first adduction torque peak in particular is strongly associated with knee OA progression. While toeing out has been shown to reduce the second peak, no clinically realistic gait modifications have been identified that effectively reduce both peaks simultaneously. This study predicts novel patient-specific gait modifications that achieve this goal without changing the foot path. The modified gait motion was designed for a single patient with knee OA using dynamic optimization of a patient-specific, full-body gait model. The cost function minimized the knee adduction torque subject to constraints limiting how much the new gait motion could deviate from the patient's normal gait motion. The optimizations predicted a "medial-thrust" gait pattern that reduced the first adduction torque peak between 32% and 54% and the second peak between 34% and 56%. The new motion involved three synergistic kinematic changes: slightly decreased pelvis obliquity, slightly increased leg flexion, and slightly increased pelvis axial rotation. After gait retraining, the patient achieved adduction torque reductions of 39% to 50% in the first peak and 37% to 55% in the second one. These reductions are comparable to those reported after high tibial osteotomy surgery. The associated kinematic changes were consistent with the predictions except for pelvis obliquity, which showed little change. This study demonstrates that it is feasible to design novel patient-specific gait modifications with potential clinical benefit using dynamic optimization of patient-specific, full-body gait models. Further investigation is needed to assess the extent to which similar gait modifications may be effective for other patients with knee OA.

Median regression spline modeling of longitudinal FEV1 measurements in cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) patients.

PubMed

Conrad, Douglas J; Bailey, Barbara A; Hardie, Jon A; Bakke, Per S; Eagan, Tomas M L; Aarli, Bernt B

2017-01-01

Clinical phenotyping, therapeutic investigations as well as genomic, airway secretion metabolomic and metagenomic investigations can benefit from robust, nonlinear modeling of FEV1 in individual subjects. We demonstrate the utility of measuring FEV1 dynamics in representative cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) populations. Individual FEV1 data from CF and COPD subjects were modeled by estimating median regression splines and their predicted first and second derivatives. Classes were created from variables that capture the dynamics of these curves in both cohorts. Nine FEV1 dynamic variables were identified from the splines and their predicted derivatives in individuals with CF (n = 177) and COPD (n = 374). Three FEV1 dynamic classes (i.e. stable, intermediate and hypervariable) were generated and described using these variables from both cohorts. In the CF cohort, the FEV1 hypervariable class (HV) was associated with a clinically unstable, female-dominated phenotypes while stable FEV1 class (S) individuals were highly associated with the male-dominated milder clinical phenotype. In the COPD cohort, associations were found between the FEV1 dynamic classes, the COPD GOLD grades, with exacerbation frequency and symptoms. Nonlinear modeling of FEV1 with splines provides new insights and is useful in characterizing CF and COPD clinical phenotypes.

Formation of an internal model of environment dynamics during upper limb reaching movements: a fuzzy approach.

PubMed

MacDonald, Chad; Moussavi, Zahra; Sarkodie-Gyan, Thompson

2007-01-01

This paper presents the development and simulation of a fuzzy logic based learning mechanism to emulate human motor learning. In particular, fuzzy inference was used to develop an internal model of a novel dynamic environment experienced during planar reaching movements with the upper limb. A dynamic model of the human arm was developed and a fuzzy if-then rule base was created to relate trajectory movement and velocity errors to internal model update parameters. An experimental simulation was performed to compare the fuzzy system's performance with that of human subjects. It was found that the dynamic model behaved as expected, and the fuzzy learning mechanism created an internal model that was capable of opposing the environmental force field to regain a trajectory closely resembling the desired ideal.

On the dynamics of a generalized predator-prey system with Z-type control.

PubMed

Lacitignola, Deborah; Diele, Fasma; Marangi, Carmela; Provenzale, Antonello

2016-10-01

We apply the Z-control approach to a generalized predator-prey system and consider the specific case of indirect control of the prey population. We derive the associated Z-controlled model and investigate its properties from the point of view of the dynamical systems theory. The key role of the design parameter λ for the successful application of the method is stressed and related to specific dynamical properties of the Z-controlled model. Critical values of the design parameter are also found, delimiting the λ-range for the effectiveness of the Z-method. Analytical results are then numerically validated by the means of two ecological models: the classical Lotka-Volterra model and a model related to a case study of the wolf-wild boar dynamics in the Alta Murgia National Park. Investigations on these models also highlight how the Z-control method acts in respect to different dynamical regimes of the uncontrolled model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Dynamic and functional balance tasks in subjects with persistent whiplash: a pilot trial.

PubMed

Stokell, Raina; Yu, Annie; Williams, Katrina; Treleaven, Julia

2011-08-01

Disturbances in static balance have been demonstrated in subjects with persistent whiplash. Some also report loss of balance and falls. These disturbances may contribute to difficulties in dynamic tasks. The aim of this study was to determine whether subjects with whiplash had deficits in dynamic and functional balance tasks when compared to a healthy control group. Twenty subjects with persistent pain following a whiplash injury and twenty healthy controls were assessed in single leg stance with eyes open and closed, the step test, Fukuda stepping test, tandem walk on a firm and soft surface, Singleton test with eyes open and closed, a stair walking test and the timed 10 m walk with and without head movement. Subjects with whiplash demonstrated significant deficits (p < 0.01) in single leg stance with eyes closed, the step test, tandem walk on a firm and soft surface, stair walking and the timed 10 m walk with and without head movement when compared to the control subjects. Specific assessment and rehabilitation directed towards improving these deficits may need to be considered in the management of patients with persistent whiplash if these results are confirmed in a larger cohort. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Cyclic fatigue resistance of ProTaper Universal instruments when subjected to static and dynamic tests.

PubMed

Lopes, Hélio P; Britto, Izabelle M O; Elias, Carlos N; Machado de Oliveira, Julio C; Neves, Mônica A S; Moreira, Edson J L; Siqueira, José F

2010-09-01

This study evaluated the number of cycles to fracture of ProTaper Universal S2 instruments when subjected to static and dynamic cyclic fatigue tests. ProTaper Universal S2 instruments were used until fracture in an artificial curved canal under rotational speed of 300 rpm in either a static or a dynamic test model. Afterward, the length of the fractured segments was measured and fractured surfaces and helical shafts analyzed by scanning electron microscopy (SEM). The number of cycles to fracture was significantly increased when instruments were tested in the dynamic model (P<.001). Instrument separation occurred at the point of maximum flexure within the artificial canals, i.e., the midpoint of the curved canal segment. SEM analysis revealed that fractured surfaces exhibited characteristics of the ductile mode. Plastic deformation was not observed in the helical shaft of fractured instruments. The number of cycles to fracture ProTaper Universal S2 instruments significantly increased with the use of instruments in a dynamic cyclic fatigue test compared with a static model. These findings reinforce the need for performing continuous pecking motions during rotary instrumentation of curved root canals. Copyright (c) 2010 Mosby, Inc. All rights reserved.

Thermal effect on the dynamic response of axially functionally graded beam subjected to a moving harmonic load

NASA Astrophysics Data System (ADS)

Wang, Yuewu; Wu, Dafang

2016-10-01

Dynamic response of an axially functionally graded (AFG) beam under thermal environment subjected to a moving harmonic load is investigated within the frameworks of classical beam theory (CBT) and Timoshenko beam theory (TBT). The Lagrange method is employed to derive the equations of thermal buckling for AFG beam, and then with the critical buckling temperature as a parameter the Newmark-β method is adopted to evaluate the dynamic response of AFG beam under thermal environments. Admissible functions denoting transverse displacement are expressed in simple algebraic polynomial forms. Temperature-dependency of material constituent is considered. The rule of mixture (Voigt model) and Mori-Tanaka (MT) scheme are used to evaluate the beam's effective material properties. A ceramic-metal AFG beam with immovable boundary condition is considered as numerical illustration to show the thermal effects on the dynamic behaviors of the beam subjected to a moving harmonic load.

Your eyes give you away: pupillary responses, EEG dynamics, and applications for BCI (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sajda, Paul

2017-05-01

As we move through an environment, we are constantly making assessments, judgments, and decisions about the things we encounter. Some are acted upon immediately, but many more become mental notes or fleeting impressions - our implicit "labeling" of the world. In this talk I will describe our work using physiological correlates of this labeling to construct a hybrid brain-computer interface (hBCI) system for efficient navigation of a 3-D environment. Specifically, we record electroencephalographic (EEG), saccadic, and pupillary data from subjects as they move through a small part of a 3-D virtual city under free-viewing conditions. Using machine learning, we integrate the neural and ocular signals evoked by the objects they encounter to infer which ones are of subjective interest. These inferred labels are propagated through a large computer vision graph of objects in the city, using semi-supervised learning to identify other, unseen objects that are visually similar to those that are labelled. Finally, the system plots an efficient route so that subjects visit similar objects of interest. We show that by exploiting the subjects' implicit labeling, the median search precision is increased from 25% to 97%, and the median subject need only travel 40% of the distance to see 84% of the objects of interest. We also find that the neural and ocular signals contribute in a complementary fashion to the classifiers' inference of subjects' implicit labeling. In summary, we show that neural and ocular signals reflecting subjective assessment of objects in a 3-D environment can be used to inform a graph-based learning model of that environment, resulting in an hBCI system that improves navigation and information delivery specific to the user's interests.

Two spatial memories are not better than one: evidence of exclusivity in memory for object location.

PubMed

Baguley, Thom; Lansdale, Mark W; Lines, Lorna K; Parkin, Jennifer K

2006-05-01

This paper studies the dynamics of attempting to access two spatial memories simultaneously and its implications for the accuracy of recall. Experiment 1 demonstrates in a range of conditions that two cues pointing to different experiences of the same object location produce little or no higher recall than that observed with a single cue. Experiment 2 confirms this finding in a within-subject design where both cues have previously elicited recall. Experiment 3 shows that these findings are only consistent with a model in which two representations of the same object location are mutually exclusive at both encoding and retrieval, and inconsistent with models that assume information from both representations is available. We propose that these representations quantify directionally specific judgments of location relative to specific anchor points in the stimulus; a format that precludes the parallel processing of like representations. Finally, we consider the apparent paradox of how such representations might contribute to the acquisition of spatial knowledge from multiple experiences of the same stimuli.

Dynamic Response of Finite Length Maglev Vehicles Subjected to Crosswind Gusts

DOT National Transportation Integrated Search

1980-03-01

This report presents a two-degree-of-freedom model for magnetically levitated finite-length vehicles incorporating sway and yaw dynamics. Aerodynamic lateral forces and yawing moments on the vehicle resulting from constant speed wind gusts were compu...

A new model-free index of dynamic cerebral blood flow autoregulation.

PubMed

Chacón, Max; Jara, José Luis; Panerai, Ronney B

2014-01-01

The classic dynamic autoregulatory index (ARI), proposed by Aaslid and Tiecks, is one of the most widely used methods to assess the efficiency of dynamic cerebral autoregulation. Although this index is often used in clinical research and is also included in some commercial equipment, it exhibits considerable intra-subject variability, and has the tendency to produce false positive results in clinical applications. An alternative index of dynamic cerebral autoregulation is proposed, which overcomes most of the limitations of the classic method and also has the advantage of being model-free. This new index uses two parameters that are obtained directly from the response signal of the cerebral blood flow velocity to a transient decrease in arterial blood pressure provoked by the sudden release of bilateral thigh cuffs, and a third parameter measuring the difference in slope of this response and the change in arterial blood pressure achieved. With the values of these parameters, a corresponding classic autoregulatory index value could be calculated by using a linear regression model built from theoretical curves generated with the Aaslid-Tiecks model. In 16 healthy subjects who underwent repeated thigh-cuff manoeuvres, the model-free approach exhibited significantly lower intra-subject variability, as measured by the unbiased coefficient of variation, than the classic autoregulatory index (p = 0.032) and the Rate of Return (p<0.001), another measure of cerebral autoregulation used for this type of systemic pressure stimulus, from 39.23%±41.91% and 55.31%±31.27%, respectively, to 15.98%±7.75%.

A New Model-Free Index of Dynamic Cerebral Blood Flow Autoregulation

PubMed Central

Chacón, Max; Jara, José Luis; Panerai, Ronney B.

2014-01-01

The classic dynamic autoregulatory index (ARI), proposed by Aaslid and Tiecks, is one of the most widely used methods to assess the efficiency of dynamic cerebral autoregulation. Although this index is often used in clinical research and is also included in some commercial equipment, it exhibits considerable intra-subject variability, and has the tendency to produce false positive results in clinical applications. An alternative index of dynamic cerebral autoregulation is proposed, which overcomes most of the limitations of the classic method and also has the advantage of being model-free. This new index uses two parameters that are obtained directly from the response signal of the cerebral blood flow velocity to a transient decrease in arterial blood pressure provoked by the sudden release of bilateral thigh cuffs, and a third parameter measuring the difference in slope of this response and the change in arterial blood pressure achieved. With the values of these parameters, a corresponding classic autoregulatory index value could be calculated by using a linear regression model built from theoretical curves generated with the Aaslid-Tiecks model. In 16 healthy subjects who underwent repeated thigh-cuff manoeuvres, the model-free approach exhibited significantly lower intra-subject variability, as measured by the unbiased coefficient of variation, than the classic autoregulatory index (p = 0.032) and the Rate of Return (p<0.001), another measure of cerebral autoregulation used for this type of systemic pressure stimulus, from 39.23%±41.91% and 55.31%±31.27%, respectively, to 15.98%±7.75%. PMID:25313519

Dynamics in thin folded polymer films

NASA Astrophysics Data System (ADS)

Croll, Andrew; Rozairo, Damith

Origami and Kirigami inspired structures depend on a complex interplay between geometry and material properties. While clearly important to the overall function, very little attention has focused on how extreme curvatures and singularities in real materials influence the overall dynamic behaviour of folded structures. In this work we use a set of three polymer thin films in order to closely examine the interaction of material and geometry. Specifically, we use polydimethylsiloxane (PDMS), polystyrene (PS) and polycarbonate (PC) thin films which we subject to loading in several model geometries of varying complexity. Depending on the material, vastly different responses are noted in our experiments; D-cones can annihilate, cut or lead to a crumpling cascade when pushed through a film. Remarkably, order can be generated with additional perturbation. Finally, the role of adhesion in complex folded structures can be addressed. AFOSR under the Young Investigator Program (FA9550-15-1-0168).

Cardiorespiratory dynamics: sensitivity of the on-transition to endurance-training status.

PubMed

Taylor, N A; Osborne, M A; Bube, T L; Stocks, J M

1999-10-01

This project investigated the sensitivity of oxygen uptake (VO(2)) dynamics to training-induced physiological changes, across a broad spectrum of endurance-training histories. Forty subjects participated: sedentary (n = 10), active healthy (n = 10), regular runners (n = 10), and competitive distance runners (n = 10). Subjects completed a cycle step-function protocol, to elicit a steady state at 60% maximal work rate. Breath-by-breath data were collected for VO(2) and cardiac frequency (f(c)), and modelled mathematically, and used to determine the average response times to attain 20%, 40%, 60%, 80% and 100% of the respective steady states. The between-group comparisons for both VO(2) and f(c) revealed significantly faster response times to 40%, 60%, 80% and 100% of the induced response, for the better trained subjects (P < 0.05). In general, this technique permitted differentiation between the VO(2) and f(c) response dynamics of non-elite subjects from a broad range of endurance-training histories, with differences becoming more pronounced as subjects approached the steady state.

Cross Coursing in Mathematics: Physical Modelling in Differential Equations Crossing to Discrete Dynamical Systems

ERIC Educational Resources Information Center

Winkel, Brian

2012-01-01

We give an example of cross coursing in which a subject or approach in one course in undergraduate mathematics is used in a completely different course. This situation crosses falling body modelling in an upper level differential equations course into a modest discrete dynamical systems unit of a first-year mathematics course. (Contains 1 figure.)

Interpersonal distance modeling during fighting activities.

PubMed

Dietrich, Gilles; Bredin, Jonathan; Kerlirzin, Yves

2010-10-01

The aim of this article is to elaborate a general framework for modeling dual opposition activities, or more generally, dual interaction. The main hypothesis is that opposition behavior can be measured directly from a global variable and that the relative distance between the two subjects can be this parameter. Moreover, this parameter should be considered as multidimensional parameter depending not only on the dynamics of the subjects but also on the "internal" parameters of the subjects, such as sociological and/or emotional states. Standard and simple mechanical formalization will be used to model this multifactorial distance. To illustrate such a general modeling methodology, this model was compared with actual data from an opposition activity like Japanese fencing (kendo). This model captures not only coupled coordination, but more generally interaction in two-subject activities.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

PubMed

Fuchs, Julian E; Huber, Roland G; Waldner, Birgit J; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

Capturing the Interplay of Dynamics and Networks through Parameterizations of Laplacian Operators

DTIC Science & Technology

2016-08-24

important vertices and communities in the network. Specifically, for each dynamical process in this framework, we define a centrality measure that...vertices as a potential cluster (or community ) with respect to this process. We show that the subset-quality function generalizes the traditional conductance...compare the different perspectives they create on network structure. Subjects Network Science and Online Social Networks Keywords Network, Community

Portable Brain-Computer Interface for the Intensive Care Unit Patient Communication Using Subject-Dependent SSVEP Identification.

PubMed

Dehzangi, Omid; Farooq, Muhamed

2018-01-01

A major predicament for Intensive Care Unit (ICU) patients is inconsistent and ineffective communication means. Patients rated most communication sessions as difficult and unsuccessful. This, in turn, can cause distress, unrecognized pain, anxiety, and fear. As such, we designed a portable BCI system for ICU communications (BCI4ICU) optimized to operate effectively in an ICU environment. The system utilizes a wearable EEG cap coupled with an Android app designed on a mobile device that serves as visual stimuli and data processing module. Furthermore, to overcome the challenges that BCI systems face today in real-world scenarios, we propose a novel subject-specific Gaussian Mixture Model- (GMM-) based training and adaptation algorithm. First, we incorporate subject-specific information in the training phase of the SSVEP identification model using GMM-based training and adaptation. We evaluate subject-specific models against other subjects. Subsequently, from the GMM discriminative scores, we generate the transformed vectors, which are passed to our predictive model. Finally, the adapted mixture mean scores of the subject-specific GMMs are utilized to generate the high-dimensional supervectors. Our experimental results demonstrate that the proposed system achieved 98.7% average identification accuracy, which is promising in order to provide effective and consistent communication for patients in the intensive care.

Static compression down-regulates N-cadherin expression and facilitates loss of cell phenotype of nucleus pulposus cells in a disc perfusion culture.

PubMed

Zhou, Haibo; Shi, Jianmin; Zhang, Chao; Li, Pei

2018-02-28

Mechanical compression often induces degenerative changes of disc nucleus pulposus (NP) tissue. It has been indicated that N-cadherin (N-CDH)-mediated signaling helps to preserve the NP cell phenotype. However, N-CDH expression and the resulting NP-specific phenotype alteration under the static compression and dynamic compression remain unclear. To study the effects of static compression and dynamic compression on N-CDH expression and NP-specific phenotype in an in vitro disc organ culture. Porcine discs were organ cultured in a self-developed mechanically active bioreactor for 7 days and subjected to static or dynamic compression (0.4 MPa for 2 h once per day). The noncompressed discs were used as controls. Compared with the dynamic compression, static compression significantly down-regulated the expression of N-CDH and NP-specific markers (laminin, brachyury, and keratin 19); decreased the Alcian Blue staining intensity, glycosaminoglycan and hydroxyproline contents; and declined the matrix macromolecule (aggrecan and collagen II) expression. Compared with the dynamic compression, static compression causes N-CDH down-regulation, loss of NP-specific phenotype, and the resulting decrease in NP matrix synthesis. © 2018 The Author(s).

Effect of Interpersonal Interaction on Festinating Gait Rehabilitation in Patients with Parkinson’s Disease

PubMed Central

Uchitomi, Hirotaka; Ogawa, Ken-ichiro; Orimo, Satoshi; Wada, Yoshiaki; Miyake, Yoshihiro

2016-01-01

Although human walking gait rhythms are generated by native individual gait dynamics, these gait dynamics change during interactions between humans. A typical phenomenon is synchronization of gait rhythms during cooperative walking. Our previous research revealed that fluctuation characteristics in stride interval of subjects with Parkinson’s disease changed from random to 1/f fluctuation as fractal characteristics during cooperative walking with the gait assist system Walk-Mate, which emulates a human interaction using interactive rhythmic cues. Moreover, gait dynamics were relearned through Walk-Mate gait training. However, the system’s clinical efficacy was unclear because the previous studies did not focus on specific gait rhythm disorder symptoms. Therefore, this study aimed to evaluate the effect of Walk-Mate on festinating gait among subjects with Parkinson’s disease. Three within-subject experimental conditions were used: (1) preinteraction condition, (2) interaction condition, and (3) postinteraction condition. The only difference between conditions was the interactive rhythmic cues generated by Walk-Mate. Because subjects with festinating gait gradually and involuntarily decreased their stride interval, the regression slope of stride interval as an index of severity of preinteraction festinating gait was elevated. The regression slope in the interaction condition was more gradual than during the preinteraction condition, indicating that the interactive rhythmic cues contributed to relieving festinating gait and stabilizing gait dynamics. Moreover, the gradual regression slope was carried over to the postinteraction condition, indicating that subjects with festinating gait have the potential to relearn stable gait dynamics. These results suggest that disordered gait dynamics are clinically restored through interactive rhythmic cues and that Walk-Mate may have the potential to assist therapists in more effective rehabilitation. Trial Registration: UMIN Clinical Trials Registry UMIN000012591 PMID:27253376

Effect of Interpersonal Interaction on Festinating Gait Rehabilitation in Patients with Parkinson's Disease.

PubMed

Uchitomi, Hirotaka; Ogawa, Ken-Ichiro; Orimo, Satoshi; Wada, Yoshiaki; Miyake, Yoshihiro

2016-01-01

Although human walking gait rhythms are generated by native individual gait dynamics, these gait dynamics change during interactions between humans. A typical phenomenon is synchronization of gait rhythms during cooperative walking. Our previous research revealed that fluctuation characteristics in stride interval of subjects with Parkinson's disease changed from random to 1/f fluctuation as fractal characteristics during cooperative walking with the gait assist system Walk-Mate, which emulates a human interaction using interactive rhythmic cues. Moreover, gait dynamics were relearned through Walk-Mate gait training. However, the system's clinical efficacy was unclear because the previous studies did not focus on specific gait rhythm disorder symptoms. Therefore, this study aimed to evaluate the effect of Walk-Mate on festinating gait among subjects with Parkinson's disease. Three within-subject experimental conditions were used: (1) preinteraction condition, (2) interaction condition, and (3) postinteraction condition. The only difference between conditions was the interactive rhythmic cues generated by Walk-Mate. Because subjects with festinating gait gradually and involuntarily decreased their stride interval, the regression slope of stride interval as an index of severity of preinteraction festinating gait was elevated. The regression slope in the interaction condition was more gradual than during the preinteraction condition, indicating that the interactive rhythmic cues contributed to relieving festinating gait and stabilizing gait dynamics. Moreover, the gradual regression slope was carried over to the postinteraction condition, indicating that subjects with festinating gait have the potential to relearn stable gait dynamics. These results suggest that disordered gait dynamics are clinically restored through interactive rhythmic cues and that Walk-Mate may have the potential to assist therapists in more effective rehabilitation. UMIN Clinical Trials Registry UMIN000012591.

ASRDI oxygen technology survey. Volume 3: Heat transfer and fluid dynamics. Abstracts of selected technical reports and publications

NASA Technical Reports Server (NTRS)

Schmidt, A. F. (Editor)

1972-01-01

Selected information is presented from an assemblage of reports and publications on heat transfer and fluid dynamics with direct applicability to oxygen systems. For each document cited, an abstract has been prepared together with key words and a listing of most important references found in the document. Additionally, an author index, a subject index, and a key word index have been provided to simplify the retrieval of specific information from this work. In each subject area - e.g., boiling heat transfer - the individual citations are listed alphabetically by first author, with review papers dually noted under the appropriate subject category and under review papers. Of the documents reviewed and evaluated for inclusion in this publication, coverage of existing information directly concerned with oxygen was given primary emphasis. However, work not specifically oxygen-designated but considered applicable to oxygen by the reviewer e.g., a two-phase friction factor correlation derived from nitrogen experiments is occasionally given where no actual oxygen data exist, as an aid to the reader. Approximately 130 abstracts are listed.

Facial Emotion Recognition in Bipolar Disorder and Healthy Aging.

PubMed

Altamura, Mario; Padalino, Flavia A; Stella, Eleonora; Balzotti, Angela; Bellomo, Antonello; Palumbo, Rocco; Di Domenico, Alberto; Mammarella, Nicola; Fairfield, Beth

2016-03-01

Emotional face recognition is impaired in bipolar disorder, but it is not clear whether this is specific for the illness. Here, we investigated how aging and bipolar disorder influence dynamic emotional face recognition. Twenty older adults, 16 bipolar patients, and 20 control subjects performed a dynamic affective facial recognition task and a subsequent rating task. Participants pressed a key as soon as they were able to discriminate whether the neutral face was assuming a happy or angry facial expression and then rated the intensity of each facial expression. Results showed that older adults recognized happy expressions faster, whereas bipolar patients recognized angry expressions faster. Furthermore, both groups rated emotional faces more intensely than did the control subjects. This study is one of the first to compare how aging and clinical conditions influence emotional facial recognition and underlines the need to consider the role of specific and common factors in emotional face recognition.

Hidden Markov Item Response Theory Models for Responses and Response Times.

PubMed

Molenaar, Dylan; Oberski, Daniel; Vermunt, Jeroen; De Boeck, Paul

2016-01-01

Current approaches to model responses and response times to psychometric tests solely focus on between-subject differences in speed and ability. Within subjects, speed and ability are assumed to be constants. Violations of this assumption are generally absorbed in the residual of the model. As a result, within-subject departures from the between-subject speed and ability level remain undetected. These departures may be of interest to the researcher as they reflect differences in the response processes adopted on the items of a test. In this article, we propose a dynamic approach for responses and response times based on hidden Markov modeling to account for within-subject differences in responses and response times. A simulation study is conducted to demonstrate acceptable parameter recovery and acceptable performance of various fit indices in distinguishing between different models. In addition, both a confirmatory and an exploratory application are presented to demonstrate the practical value of the modeling approach.

An Automated Method for Landmark Identification and Finite-Element Modeling of the Lumbar Spine.

PubMed

Campbell, Julius Quinn; Petrella, Anthony J

2015-11-01

The purpose of this study was to develop a method for the automated creation of finite-element models of the lumbar spine. Custom scripts were written to extract bone landmarks of lumbar vertebrae and assemble L1-L5 finite-element models. End-plate borders, ligament attachment points, and facet surfaces were identified. Landmarks were identified to maintain mesh correspondence between meshes for later use in statistical shape modeling. 90 lumbar vertebrae were processed creating 18 subject-specific finite-element models. Finite-element model surfaces and ligament attachment points were reproduced within 1e-5 mm of the bone surface, including the critical contact surfaces of the facets. Element quality exceeded specifications in 97% of elements for the 18 models created. The current method is capable of producing subject-specific finite-element models of the lumbar spine with good accuracy, quality, and robustness. The automated methods developed represent advancement in the state of the art of subject-specific lumbar spine modeling to a scale not possible with prior manual and semiautomated methods.

A musculoskeletal model of human locomotion driven by a low dimensional set of impulsive excitation primitives

PubMed Central

Sartori, Massimo; Gizzi, Leonardo; Lloyd, David G.; Farina, Dario

2013-01-01

Human locomotion has been described as being generated by an impulsive (burst-like) excitation of groups of musculotendon units, with timing dependent on the biomechanical goal of the task. Despite this view being supported by many experimental observations on specific locomotion tasks, it is still unknown if the same impulsive controller (i.e., a low-dimensional set of time-delayed excitastion primitives) can be used as input drive for large musculoskeletal models across different human locomotion tasks. For this purpose, we extracted, with non-negative matrix factorization, five non-negative factors from a large sample of muscle electromyograms in two healthy subjects during four motor tasks. These included walking, running, sidestepping, and crossover cutting maneuvers. The extracted non-negative factors were then averaged and parameterized to obtain task-generic Gaussian-shaped impulsive excitation curves or primitives. These were used to drive a subject-specific musculoskeletal model of the human lower extremity. Results showed that the same set of five impulsive excitation primitives could be used to predict the dynamics of 34 musculotendon units and the resulting hip, knee and ankle joint moments (i.e., NRMSE = 0.18 ± 0.08, and R2 = 0.73 ± 0.22 across all tasks and subjects) without substantial loss of accuracy with respect to using experimental electromyograms (i.e., NRMSE = 0.16 ± 0.07, and R2 = 0.78 ± 0.18 across all tasks and subjects). Results support the hypothesis that biomechanically different motor tasks might share similar neuromuscular control strategies. This might have implications in neurorehabilitation technologies such as human-machine interfaces for the torque-driven, proportional control of powered prostheses and orthoses. In this, device control commands (i.e., predicted joint torque) could be derived without direct experimental data but relying on simple parameterized Gaussian-shaped curves, thus decreasing the input drive complexity and the number of needed sensors. PMID:23805099

A musculoskeletal model of human locomotion driven by a low dimensional set of impulsive excitation primitives.

PubMed

Sartori, Massimo; Gizzi, Leonardo; Lloyd, David G; Farina, Dario

2013-01-01

Human locomotion has been described as being generated by an impulsive (burst-like) excitation of groups of musculotendon units, with timing dependent on the biomechanical goal of the task. Despite this view being supported by many experimental observations on specific locomotion tasks, it is still unknown if the same impulsive controller (i.e., a low-dimensional set of time-delayed excitastion primitives) can be used as input drive for large musculoskeletal models across different human locomotion tasks. For this purpose, we extracted, with non-negative matrix factorization, five non-negative factors from a large sample of muscle electromyograms in two healthy subjects during four motor tasks. These included walking, running, sidestepping, and crossover cutting maneuvers. The extracted non-negative factors were then averaged and parameterized to obtain task-generic Gaussian-shaped impulsive excitation curves or primitives. These were used to drive a subject-specific musculoskeletal model of the human lower extremity. Results showed that the same set of five impulsive excitation primitives could be used to predict the dynamics of 34 musculotendon units and the resulting hip, knee and ankle joint moments (i.e., NRMSE = 0.18 ± 0.08, and R (2) = 0.73 ± 0.22 across all tasks and subjects) without substantial loss of accuracy with respect to using experimental electromyograms (i.e., NRMSE = 0.16 ± 0.07, and R (2) = 0.78 ± 0.18 across all tasks and subjects). Results support the hypothesis that biomechanically different motor tasks might share similar neuromuscular control strategies. This might have implications in neurorehabilitation technologies such as human-machine interfaces for the torque-driven, proportional control of powered prostheses and orthoses. In this, device control commands (i.e., predicted joint torque) could be derived without direct experimental data but relying on simple parameterized Gaussian-shaped curves, thus decreasing the input drive complexity and the number of needed sensors.

Effects of global climate on infectious disease: the cholera model.

PubMed

Lipp, Erin K; Huq, Anwar; Colwell, Rita R

2002-10-01

Recently, the role of the environment and climate in disease dynamics has become a subject of increasing interest to microbiologists, clinicians, epidemiologists, and ecologists. Much of the interest has been stimulated by the growing problems of antibiotic resistance among pathogens, emergence and/or reemergence of infectious diseases worldwide, the potential of bioterrorism, and the debate concerning climate change. Cholera, caused by Vibrio cholerae, lends itself to analyses of the role of climate in infectious disease, coupled to population dynamics of pathogenic microorganisms, for several reasons. First, the disease has a historical context linking it to specific seasons and biogeographical zones. In addition, the population dynamics of V. cholerae in the environment are strongly controlled by environmental factors, such as water temperature, salinity, and the presence of copepods, which are, in turn, controlled by larger-scale climate variability. In this review, the association between plankton and V. cholerae that has been documented over the last 20 years is discussed in support of the hypothesis that cholera shares properties of a vector-borne disease. In addition, a model for environmental transmission of cholera to humans in the context of climate variability is presented. The cholera model provides a template for future research on climate-sensitive diseases, allowing definition of critical parameters and offering a means of developing more sophisticated methods for prediction of disease outbreaks.

Accuracy of 4D Flow measurement of cerebrospinal fluid dynamics in the cervical spine: An in vitro verification against numerical simulation

PubMed Central

Pahlavian, Soroush Heidari; Bunck, Alexander C.; Thyagaraj, Suraj; Giese, Daniel; Loth, Francis; Hedderich, Dennis M.; Kröger, Jan Robert; Martin, Bryn A.

2016-01-01

Abnormal alterations in cerebrospinal fluid (CSF) flow are thought to play an important role in pathophysiology of various craniospinal disorders such as hydrocephalus and Chiari malformation. Three directional phase contrast MRI (4D Flow) has been proposed as one method for quantification of the CSF dynamics in healthy and disease states, but prior to further implementation of this technique, its accuracy in measuring CSF velocity magnitude and distribution must be evaluated. In this study, an MR-compatible experimental platform was developed based on an anatomically detailed 3D printed model of the cervical subarachnoid space and subject specific flow boundary conditions. Accuracy of 4D Flow measurements was assessed by comparison of CSF velocities obtained within the in vitro model with the numerically predicted velocities calculated from a spatially averaged computational fluid dynamics (CFD) model based on the same geometry and flow boundary conditions. Good agreement was observed between CFD and 4D Flow in terms of spatial distribution and peak magnitude of through-plane velocities with an average difference of 7.5% and 10.6% for peak systolic and diastolic velocities, respectively. Regression analysis showed lower accuracy of 4D Flow measurement at the timeframes corresponding to low CSF flow rate and poor correlation between CFD and 4D Flow in-plane velocities. PMID:27043214

A data-driven algorithm integrating clinical and laboratory features for the diagnosis and prognosis of necrotizing enterocolitis.

PubMed

Ji, Jun; Ling, Xuefeng B; Zhao, Yingzhen; Hu, Zhongkai; Zheng, Xiaolin; Xu, Zhening; Wen, Qiaojun; Kastenberg, Zachary J; Li, Ping; Abdullah, Fizan; Brandt, Mary L; Ehrenkranz, Richard A; Harris, Mary Catherine; Lee, Timothy C; Simpson, B Joyce; Bowers, Corinna; Moss, R Lawrence; Sylvester, Karl G

2014-01-01

Necrotizing enterocolitis (NEC) is a major source of neonatal morbidity and mortality. Since there is no specific diagnostic test or risk of progression model available for NEC, the diagnosis and outcome prediction of NEC is made on clinical grounds. The objective in this study was to develop and validate new NEC scoring systems for automated staging and prognostic forecasting. A six-center consortium of university based pediatric teaching hospitals prospectively collected data on infants under suspicion of having NEC over a 7-year period. A database comprised of 520 infants was utilized to develop the NEC diagnostic and prognostic models by dividing the entire dataset into training and testing cohorts of demographically matched subjects. Developed on the training cohort and validated on the blind testing cohort, our multivariate analyses led to NEC scoring metrics integrating clinical data. Machine learning using clinical and laboratory results at the time of clinical presentation led to two nec models: (1) an automated diagnostic classification scheme; (2) a dynamic prognostic method for risk-stratifying patients into low, intermediate and high NEC scores to determine the risk for disease progression. We submit that dynamic risk stratification of infants with NEC will assist clinicians in determining the need for additional diagnostic testing and guide potential therapies in a dynamic manner. http://translationalmedicine.stanford.edu/cgi-bin/NEC/index.pl and smartphone application upon request.

Generalization in Adaptation to Stable and Unstable Dynamics

PubMed Central

Kadiallah, Abdelhamid; Franklin, David W.; Burdet, Etienne

2012-01-01

Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization. PMID:23056191

Bayesian model reduction and empirical Bayes for group (DCM) studies

PubMed Central

Friston, Karl J.; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E.; van Wijk, Bernadette C.M.; Ziegler, Gabriel; Zeidman, Peter

2016-01-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level – e.g., dynamic causal models – and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. PMID:26569570

The non-linear response of a muscle in transverse compression: assessment of geometry influence using a finite element model.

PubMed

Gras, Laure-Lise; Mitton, David; Crevier-Denoix, Nathalie; Laporte, Sébastien

2012-01-01

Most recent finite element models that represent muscles are generic or subject-specific models that use complex, constitutive laws. Identification of the parameters of such complex, constitutive laws could be an important limit for subject-specific approaches. The aim of this study was to assess the possibility of modelling muscle behaviour in compression with a parametric model and a simple, constitutive law. A quasi-static compression test was performed on the muscles of dogs. A parametric finite element model was designed using a linear, elastic, constitutive law. A multi-variate analysis was performed to assess the effects of geometry on muscle response. An inverse method was used to define Young's modulus. The non-linear response of the muscles was obtained using a subject-specific geometry and a linear elastic law. Thus, a simple muscle model can be used to have a bio-faithful, biomechanical response.

Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights

NASA Technical Reports Server (NTRS)

Chatzimavroudis, George P.; Spirka, Thomas A.; Setser, Randolph M.; Myers, Jerry G.

2004-01-01

One of NASA's objectives is to be able to perform a complete, pre-flight, evaluation of cardiovascular changes in astronauts scheduled for prolonged space missions. Computational fluid dynamics (CFD) has shown promise as a method for estimating cardiovascular function during reduced gravity conditions. For this purpose, MRI can provide geometrical information, to reconstruct vessel geometries, and measure all spatial velocity components, providing location specific boundary conditions. The objective of this study was to investigate the reliability of MRI-based model reconstruction and measured boundary conditions for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T Siemens MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction (slice thickness 3 and 5 mm; pixel size 1x1 and 0.5x0.5 square millimeters). Velocity acquisitions provided measured inlet boundary conditions and localized three-directional steady-flow velocity data (0.7-3.0 L/min). The vessel walls were isolated using NIH provided software (ImageJ) and lofted to form the geometric surface. Constructed and idealized geometries were imported into a commercial CFD code for meshing and simulation. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with less than 10% differences in the local velocity values. CFD results on models reconstructed from different MRI resolution settings showed insignificant differences (less than 5%). This study illustrated, quantitatively, that reliable CFD simulations can be performed with MRI reconstructed models and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system alteration during space travel is feasible.

Analysis of Instantaneous Linear, Nonlinear and Complex Cardiovascular Dynamics from Videophotoplethysmography.

PubMed

Valenza, Gaetano; Iozzia, Luca; Cerina, Luca; Mainardi, Luca; Barbieri, Riccardo

2018-05-01

There is a fast growing interest in the use of non-contact devices for health and performance assessment in humans. In particular, the use of non-contact videophotoplethysmography (vPPG) has been recently demonstrated as a feasible way to extract cardiovascular information. Nevertheless, proper validation of vPPG-derived heartbeat dynamics is still missing. We aim to an in-depth validation of time-varying, linear and nonlinear/complex dynamics of the pulse rate variability extracted from vPPG. We apply inhomogeneous pointprocess nonlinear models to assess instantaneous measures defined in the time, frequency, and bispectral domains as estimated through vPPG and standard ECG. Instantaneous complexity measures, such as the instantaneous Lyapunov exponents and the recently defined inhomogeneous point-process approximate and sample entropy, were estimated as well. Video recordings were processed using our recently proposed method based on zerophase principal component analysis. Experimental data were gathered from 60 young healthy subjects (age: 24±3 years) undergoing postural changes (rest-to-stand maneuver). Group averaged results show that there is an overall agreement between linear and nonlinear/complexity indices computed from ECG and vPPG during resting state conditions. However, important differences are found, particularly in the bispectral and complexity domains, in recordings where the subjects has been instructed to stand up. Although significant differences exist between cardiovascular estimates from vPPG and ECG, it is very promising that instantaneous sympathovagal changes, as well as time-varying complex dynamics, were correctly identified, especially during resting state. In addition to a further improvement of the video signal quality, more research is advocated towards a more precise estimation of cardiovascular dynamics by a comprehensive nonlinear/complex paradigm specifically tailored to the non-contact quantification. Schattauer GmbH.

Expressive facial animation synthesis by learning speech coarticulation and expression spaces.

PubMed

Deng, Zhigang; Neumann, Ulrich; Lewis, J P; Kim, Tae-Yong; Bulut, Murtaza; Narayanan, Shrikanth

2006-01-01

Synthesizing expressive facial animation is a very challenging topic within the graphics community. In this paper, we present an expressive facial animation synthesis system enabled by automated learning from facial motion capture data. Accurate 3D motions of the markers on the face of a human subject are captured while he/she recites a predesigned corpus, with specific spoken and visual expressions. We present a novel motion capture mining technique that "learns" speech coarticulation models for diphones and triphones from the recorded data. A Phoneme-Independent Expression Eigenspace (PIEES) that encloses the dynamic expression signals is constructed by motion signal processing (phoneme-based time-warping and subtraction) and Principal Component Analysis (PCA) reduction. New expressive facial animations are synthesized as follows: First, the learned coarticulation models are concatenated to synthesize neutral visual speech according to novel speech input, then a texture-synthesis-based approach is used to generate a novel dynamic expression signal from the PIEES model, and finally the synthesized expression signal is blended with the synthesized neutral visual speech to create the final expressive facial animation. Our experiments demonstrate that the system can effectively synthesize realistic expressive facial animation.

Synaptic augmentation in a cortical circuit model reproduces serial dependence in visual working memory

PubMed Central

D’Esposito, Mark

2017-01-01

Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic “activity-silent” synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior. PMID:29244810

Estimation of Quasi-Stiffness of the Human Knee in the Stance Phase of Walking

PubMed Central

Shamaei, Kamran; Sawicki, Gregory S.; Dollar, Aaron M.

2013-01-01

Biomechanical data characterizing the quasi-stiffness of lower-limb joints during human locomotion is limited. Understanding joint stiffness is critical for evaluating gait function and designing devices such as prostheses and orthoses intended to emulate biological properties of human legs. The knee joint moment-angle relationship is approximately linear in the flexion and extension stages of stance, exhibiting nearly constant stiffnesses, known as the quasi-stiffnesses of each stage. Using a generalized inverse dynamics analysis approach, we identify the key independent variables needed to predict knee quasi-stiffness during walking, including gait speed, knee excursion, and subject height and weight. Then, based on the identified key variables, we used experimental walking data for 136 conditions (speeds of 0.75–2.63 m/s) across 14 subjects to obtain best fit linear regressions for a set of general models, which were further simplified for the optimal gait speed. We found R2 > 86% for the most general models of knee quasi-stiffnesses for the flexion and extension stages of stance. With only subject height and weight, we could predict knee quasi-stiffness for preferred walking speed with average error of 9% with only one outlier. These results provide a useful framework and foundation for selecting subject-specific stiffness for prosthetic and exoskeletal devices designed to emulate biological knee function during walking. PMID:23533662

Detection of a Moving Gas Source and Estimation of its Concentration Field with a Sensing Aerial Vehicle Integration of Theoretical Controls and Computational Fluids

DTIC Science & Technology

2016-07-21

constants. The model (2.42) is popular for simulation of the UAV motion [60], [61], [62] due to the fact that it models the aircraft response to...inputs to the dynamic model (2.42). The concentration sensors onboard the UAV record concentration ( simulated ) data according to its spatial location...vehicle dynamics and guidance, and the onboard sensor modeling . 15. SUBJECT TERMS State estimation; UAVs , mobile sensors; grid adaptationj; plume

Fundamental Properties of Soils for Complex Dynamic Loadings: Dynamic Constitutive Modeling of Sandy Soils.

DTIC Science & Technology

1983-04-01

1.0 INTRODUCTION AND SCOPE 1 2.0 PROGRESS SUMMARY 3 2.1 Soil Element Model Development 3 2.2 U.S. Any Engineer Waterways Experiment Station (WES...LABORATORY BEHAVIOR OF SAND 8 3.1 Introduction 8 3.2 Material Description 8 3.3 Laboratory Tests Performed 9 3.4 Laboratory Test Results 14 4.0 MODELING THE... INTRODUCTION AND SCOPE The subject of this annual report is constitutive modeling of cohesionless soil, for both laboratory standard static test conditions

OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange.

PubMed

Seth, Ajay; Sherman, Michael; Reinbolt, Jeffrey A; Delp, Scott L

Movement science is driven by observation, but observation alone cannot elucidate principles of human and animal movement. Biomechanical modeling and computer simulation complement observations and inform experimental design. Biological models are complex and specialized software is required for building, validating, and studying them. Furthermore, common access is needed so that investigators can contribute models to a broader community and leverage past work. We are developing OpenSim, a freely available musculoskeletal modeling and simulation application and libraries specialized for these purposes, by providing: musculoskeletal modeling elements, such as biomechanical joints, muscle actuators, ligament forces, compliant contact, and controllers; and tools for fitting generic models to subject-specific data, performing inverse kinematics and forward dynamic simulations. OpenSim performs an array of physics-based analyses to delve into the behavior of musculoskeletal models by employing Simbody, an efficient and accurate multibody system dynamics code. Models are publicly available and are often reused for multiple investigations because they provide a rich set of behaviors that enables different lines of inquiry. This report will discuss one model developed to study walking and applied to gain deeper insights into muscle function in pathological gait and during running. We then illustrate how simulations can test fundamental hypotheses and focus the aims of in vivo experiments, with a postural stability platform and human model that provide a research environment for performing human posture experiments in silico . We encourage wide adoption of OpenSim for community exchange of biomechanical models and methods and welcome new contributors.

Countermovement strategy changes with vertical jump height to accommodate feasible force constraints.

PubMed

Kim, Seyoung; Park, Sukyung; Choi, Sangkyu

2014-09-22

In this study, we developed a curve-fit model of countermovement dynamics and examined whether the characteristics of a countermovement jump can be quantified using the model parameter and its scaling; we expected that the model-based analysis would facilitate an understanding of the basic mechanisms of force reduction and propulsion with a simplified framework of the center of mass (CoM) mechanics. Ten healthy young subjects jumped straight up to five different levels ranging from approximately 10% to 35% of their body heights. The kinematic and kinetic data on the CoM were measured using a force plate system synchronized with motion capture cameras. All subjects generated larger vertical forces compared with their body weights from the countermovement and sufficiently lowered their CoM position to support the work performed by push-off as the vertical elevations became more challenging. The model simulation reasonably reproduced the trajectories of vertical force during the countermovement, and the model parameters were replaced by linear and polynomial regression functions in terms of the vertical jump height. Gradual scaling trends of the individual model parameters were observed as a function of the vertical jump height with different degrees of scaling, depending on the subject. The results imply that the subjects may be aware of the jumping dynamics when subjected to various vertical jump heights and may select their countermovement strategies to effectively accommodate biomechanical constraints, i.e., limited force generation for the standing vertical jump. Copyright © 2014 Elsevier Ltd. All rights reserved.

A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing.

PubMed

Sillin, Henry O; Aguilera, Renato; Shieh, Hsien-Hang; Avizienis, Audrius V; Aono, Masakazu; Stieg, Adam Z; Gimzewski, James K

2013-09-27

Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated the model against various experimental results highlighting the possibility to functionalize the network plasticity and the differences between an atomic switch in isolation and its behaviors in a network. The effects of changing connectivity density on the nonlinear dynamics were examined as characterized by higher harmonic generation in response to AC inputs. To demonstrate their utility for computation, we subjected the simulated network to training within the framework of reservoir computing and showed initial evidence of the ASN acting as a reservoir which may be optimized for specific tasks by adjusting the input gain. The work presented represents steps in a unified approach to experimentation and theory of complex systems to make ASNs a uniquely scalable platform for neuromorphic computing.

A dynamic model of the radiation-belt electron phase-space density based on POLAR/HIST measurements

NASA Astrophysics Data System (ADS)

Vassiliadis, D.; Green, J. C.

2007-12-01

The response of the energetic-electron phase-space density (PSD) in the radiation belts is subject to a delicate combination of acceleration and loss processes which are strongly determined by the magnetospheric configuration and field disturbance level. We quantify the response of the density to stormtime fields as observed by the HIST detector on board POLAR. Several distinct modes are identified, characterized by peak second- and third- adiabatic invariants and peak delay time. The modes represent quasiadiabatic transport due to ring current activity; high L* (~6), day-long acceleration linked to ULF wave-particle interaction; and low-L* (~3), minute- to hour-long acceleration interpreted to be due to transient inductive fields or VLF wave-particle interaction. The net transport due to these responses is not always or everywhere diffusive, therefore we quantify the degree of departure from diffusive transport for specific storm intervals and radial ranges. Taken together the response modes comprise a dynamic, nonlinear model which allows us to better understand the historic variability of the high-energy tail of the electron distribution in the inner magnetosphere.

A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing

NASA Astrophysics Data System (ADS)

Sillin, Henry O.; Aguilera, Renato; Shieh, Hsien-Hang; Avizienis, Audrius V.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2013-09-01

Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated the model against various experimental results highlighting the possibility to functionalize the network plasticity and the differences between an atomic switch in isolation and its behaviors in a network. The effects of changing connectivity density on the nonlinear dynamics were examined as characterized by higher harmonic generation in response to AC inputs. To demonstrate their utility for computation, we subjected the simulated network to training within the framework of reservoir computing and showed initial evidence of the ASN acting as a reservoir which may be optimized for specific tasks by adjusting the input gain. The work presented represents steps in a unified approach to experimentation and theory of complex systems to make ASNs a uniquely scalable platform for neuromorphic computing.

The inaccuracy of surface-measured model-derived tibiofemoral kinematics

PubMed Central

Li, Kang; Zheng, Liying; Tashman, Scott; Zhang, Xudong

2014-01-01

This study assessed the accuracy of surface-measured OpenSim-derived tibiofemoral kinematics in functional activities. Ten subjects with unilateral, isolated grade II PCL deficiency performed level running and stair ascent. A dynamic stereo radiography (DSX) system and a Vicon motion capture system simultaneously measured their knee or lower extremity movement. Surface marker motion data from the Vicon system were used to create subject-specific models in OpenSim and derive the tibiofemoral kinematics. The surface-measured model-derived tibiofemoral kinematics in all 6 degrees of freedom (DOFs) were then compared with those measured by the DSX as the benchmarks. The differences between surface- and DSX-measured tibiofemoral kinematics were found to be substantial: the overall mean (±SD) RMS differences during running were 9.1±3.2°, 2.0 ± 1.2°, 6.4 ± 4.5° for the flexion-extension, abduction-adduction, and internal-external rotations, and 7.1± 3.2mm, 8.8± 3.7mm, and 1.9± 1.2mm for anterior-posterior, proximal-distal, and medial-lateral translations. The differences were more pronounced in the relatively higher speed running than in stair ascent. It was also found that surface-based measures significantly underestimated the mean as well as inter-subject variability of the differences between PCL-injured and intact knees in abduction-adduction, internal-external rotation, and anterior-posterior translation. PMID:22964018

Are Autonomous and Controlled Motivations School-Subjects-Specific?

PubMed

Chanal, Julien; Guay, Frédéric

2015-01-01

This research sought to test whether autonomous and controlled motivations are specific to school subjects or more general to the school context. In two cross-sectional studies, 252 elementary school children (43.7% male; mean age = 10.7 years, SD = 1.3 years) and 334 junior high school children (49.7% male, mean age = 14.07 years, SD = 1.01 years) were administered a questionnaire assessing their motivation for various school subjects. Results based on structural equation modeling using the correlated trait-correlated method minus one model (CTCM-1) showed that autonomous and controlled motivations assessed at the school subject level are not equally school-subject-specific. We found larger specificity effects for autonomous (intrinsic and identified) than for controlled (introjected and external) motivation. In both studies, results of factor loadings and the correlations with self-concept and achievement demonstrated that more evidence of specificity was obtained for autonomous regulations than for controlled ones. These findings suggest a new understanding of the hierarchical and multidimensional academic structure of autonomous and controlled motivations and of the mechanisms involved in the development of types of regulations for school subjects.

Are Autonomous and Controlled Motivations School-Subjects-Specific?

PubMed Central

Chanal, Julien; Guay, Frédéric

2015-01-01

This research sought to test whether autonomous and controlled motivations are specific to school subjects or more general to the school context. In two cross-sectional studies, 252 elementary school children (43.7% male; mean age = 10.7 years, SD = 1.3 years) and 334 junior high school children (49.7% male, mean age = 14.07 years, SD = 1.01 years) were administered a questionnaire assessing their motivation for various school subjects. Results based on structural equation modeling using the correlated trait-correlated method minus one model (CTCM-1) showed that autonomous and controlled motivations assessed at the school subject level are not equally school-subject-specific. We found larger specificity effects for autonomous (intrinsic and identified) than for controlled (introjected and external) motivation. In both studies, results of factor loadings and the correlations with self-concept and achievement demonstrated that more evidence of specificity was obtained for autonomous regulations than for controlled ones. These findings suggest a new understanding of the hierarchical and multidimensional academic structure of autonomous and controlled motivations and of the mechanisms involved in the development of types of regulations for school subjects. PMID:26247788

Concurrent prediction of muscle and tibiofemoral contact forces during treadmill gait.

PubMed

Guess, Trent M; Stylianou, Antonis P; Kia, Mohammad

2014-02-01

Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the "Grand Challenge Competition to Predict in-vivo Knee Loads" for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, "Grand Challenge Competition to Predict in vivo Knee Loads," J. Orthop. Res., 30, pp. 503-513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cycle and 43 N, 15 N, and 96 N in the anterior-posterior, medial-lateral, and vertical directions for the second gait cycle.

Characteristics of 3-D transport simulations of the stratosphere and mesosphere

NASA Technical Reports Server (NTRS)

Fairlie, T. D. A.; Siskind, D. E.; Turner, R. E.; Fisher, M.

1992-01-01

A 3D mechanistic, primitive-equation model of the stratosphere and mesosphere is coupled to an offline spectral transport model. The dynamics model is initialized with and forced by observations so that the coupled models may be used to study specific episodes. Results are compared with those obtained by transport online in the dynamics model. Although some differences are apparent, the results suggest that coupling of the models to a comprehensive photochemical package will provide a useful tool for studying the evolution of constituents in the middle atmosphere during specific episodes.

Quantifying the effect of side branches in endothelial shear stress estimates

PubMed Central

Giannopoulos, Andreas A.; Chatzizisis, Yiannis S.; Maurovich-Horvat, Pal; Antoniadis, Antonios P.; Hoffmann, Udo; Steigner, Michael L.; Rybicki, Frank J.; Mitsouras, Dimitrios

2016-01-01

Background and aims Low and high endothelial shear stress (ESS) is associated with coronary atherosclerosis progression and high-risk plaque features. Coronary ESS is currently assessed via computational fluid dynamic (CFD) simulation in the lumen geometry determined from invasive imaging such as intravascular ultrasound and optical coherence tomography. This process typically omits side branches of the target vessel in the CFD model as invasive imaging of those vessels is not clinically-indicated. The purpose of this study was to determine the extent to which this simplification affects the determination of those regions of the coronary endothelium subjected to pathologic ESS. Methods We determined the diagnostic accuracy of ESS profiling without side branches to detect pathologic ESS in the major coronary arteries of 5 hearts imaged ex vivo with CT angiography. ESS of the three major coronary arteries was calculated both without (test model), and with (reference model) inclusion of all side branches >1.5 mm in diameter, using previously-validated CFD approaches. Diagnostic test characteristics (accuracy, sensitivity, specificity and negative and positive predictive value [NPV/PPV]) with respect to the reference model were assessed for both the entire length as well as only the proximal portion of each major coronary artery, where the majority of high-risk plaques occur. Results Using the model without side branches overall accuracy, sensitivity, specificity, NPV and PPV were 83.4%, 54.0%, 96%, 95.9% and 55.1%, respectively to detect low ESS, and 87.0%, 67.7%, 90.7%, 93.7% and 57.5%, respectively to detect high ESS. When considering only the proximal arteries, test characteristics differed for low and high ESS, with low sensitivity (67.7%) and high specificity (90.7%) to detect low ESS, and low sensitivity (44.7%) and high specificity (95.5%) to detect high ESS. Conclusions The exclusion of side branches in ESS vascular profiling studies greatly reduces the ability to detect regions of the major coronary arteries subjected to pathologic ESS. Single-conduit models can in general only be used to rule out pathologic ESS. PMID:27372207

Quantifying the effect of side branches in endothelial shear stress estimates.

PubMed

Giannopoulos, Andreas A; Chatzizisis, Yiannis S; Maurovich-Horvat, Pal; Antoniadis, Antonios P; Hoffmann, Udo; Steigner, Michael L; Rybicki, Frank J; Mitsouras, Dimitrios

2016-08-01

Low and high endothelial shear stress (ESS) is associated with coronary atherosclerosis progression and high-risk plaque features. Coronary ESS is currently assessed via computational fluid dynamic (CFD) simulation of coronary blood flow in the lumen geometry determined from invasive imaging such as intravascular ultrasound and optical coherence tomography. This process typically omits side branches of the target vessel in the CFD model as invasive imaging of those vessels is not usually clinically-indicated. The purpose of this study was to determine the extent to which this simplification affects the determination of those regions of the coronary endothelium subjected to pathologic ESS. We determined the diagnostic accuracy of ESS profiling without side branches to detect pathologic ESS in the major coronary arteries of 5 hearts imaged ex vivo with computed tomography angiography (CTA). ESS of the three major coronary arteries was calculated both without (test model), and with (reference model) inclusion of all side branches >1.5 mm in diameter, using previously-validated CFD approaches. Diagnostic test characteristics (accuracy, sensitivity, specificity and negative and positive predictive value [NPV/PPV]) with respect to the reference model were assessed for both the entire length as well as only the proximal portion of each major coronary artery, where the majority of high-risk plaques occur. Using the model without side branches overall accuracy, sensitivity, specificity, NPV and PPV were 83.4%, 54.0%, 96%, 95.9% and 55.1%, respectively to detect low ESS, and 87.0%, 67.7%, 90.7%, 93.7% and 57.5%, respectively to detect high ESS. When considering only the proximal arteries, test characteristics differed for low and high ESS, with low sensitivity (67.7%) and high specificity (90.7%) to detect low ESS, and low sensitivity (44.7%) and high specificity (95.5%) to detect high ESS. The exclusion of side branches in ESS vascular profiling studies greatly reduces the ability to detect regions of the major coronary arteries subjected to pathologic ESS. Single-conduit models can in general only be used to rule out pathologic ESS. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

New techniques for positron emission tomography in the study of human neurological disorders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhl, D.E.

1992-07-01

The general goals of the physics and kinetic modeling projects are to: (1) improve the quantitative information extractable from PET images, and (2) develop, implement and optimize tracer kinetic models for new PET neurotransmitter/receptor ligands aided by computer simulations. Work towards improving PET quantification has included projects evaluating: (1) iterative reconstruction algorithms using supplemental boundary information, (2) automated registration of dynamic PET emission and transmission data using sinogram edge detection, and (3) automated registration of multiple subjects to a common coordinate system, including the use of non-linear warping methods. Simulation routines have been developed providing more accurate representation of datamore » generated from neurotransmitter/receptor studies. Routines consider data generated from complex compartmental models, high or low specific activity administrations, non-specific binding, pre- or post-injection of cold or competing ligands, temporal resolution of the data, and radiolabeled metabolites. Computer simulations and human PET studies have been performed to optimize kinetic models for four new neurotransmitter/receptor ligands, [{sup 11}C]TRB (muscarinic), [{sup 11}C]flumazenil (benzodiazepine), [{sup 18}F]GBR12909, (dopamine), and [{sup 11}C]NMPB (muscarinic).« less

New techniques for positron emission tomography in the study of human neurological disorders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhl, D.E.

1992-01-01

The general goals of the physics and kinetic modeling projects are to: (1) improve the quantitative information extractable from PET images, and (2) develop, implement and optimize tracer kinetic models for new PET neurotransmitter/receptor ligands aided by computer simulations. Work towards improving PET quantification has included projects evaluating: (1) iterative reconstruction algorithms using supplemental boundary information, (2) automated registration of dynamic PET emission and transmission data using sinogram edge detection, and (3) automated registration of multiple subjects to a common coordinate system, including the use of non-linear warping methods. Simulation routines have been developed providing more accurate representation of datamore » generated from neurotransmitter/receptor studies. Routines consider data generated from complex compartmental models, high or low specific activity administrations, non-specific binding, pre- or post-injection of cold or competing ligands, temporal resolution of the data, and radiolabeled metabolites. Computer simulations and human PET studies have been performed to optimize kinetic models for four new neurotransmitter/receptor ligands, ({sup 11}C)TRB (muscarinic), ({sup 11}C)flumazenil (benzodiazepine), ({sup 18}F)GBR12909, (dopamine), and ({sup 11}C)NMPB (muscarinic).« less

Nonlinear digital signal processing in mental health: characterization of major depression using instantaneous entropy measures of heartbeat dynamics.

PubMed

Valenza, Gaetano; Garcia, Ronald G; Citi, Luca; Scilingo, Enzo P; Tomaz, Carlos A; Barbieri, Riccardo

2015-01-01

Nonlinear digital signal processing methods that address system complexity have provided useful computational tools for helping in the diagnosis and treatment of a wide range of pathologies. More specifically, nonlinear measures have been successful in characterizing patients with mental disorders such as Major Depression (MD). In this study, we propose the use of instantaneous measures of entropy, namely the inhomogeneous point-process approximate entropy (ipApEn) and the inhomogeneous point-process sample entropy (ipSampEn), to describe a novel characterization of MD patients undergoing affective elicitation. Because these measures are built within a nonlinear point-process model, they allow for the assessment of complexity in cardiovascular dynamics at each moment in time. Heartbeat dynamics were characterized from 48 healthy controls and 48 patients with MD while emotionally elicited through either neutral or arousing audiovisual stimuli. Experimental results coming from the arousing tasks show that ipApEn measures are able to instantaneously track heartbeat complexity as well as discern between healthy subjects and MD patients. Conversely, standard heart rate variability (HRV) analysis performed in both time and frequency domains did not show any statistical significance. We conclude that measures of entropy based on nonlinear point-process models might contribute to devising useful computational tools for care in mental health.

Chaotic Transport in Circumterrestrial Orbits

NASA Astrophysics Data System (ADS)

Rosengren, Aaron Jay

2018-04-01

The slow deformation of circumterrestrial orbits in the medium region, subject to lunisolar secular resonances, is well approximated by a Hamiltonian system with 2.5 degrees of freedom. This dynamical model is referred to in the astrophysical and celestial dynamics communities as the quadrupolar, secular, hierarchical three-body problem, and, in the non-autonomous case, gives rise to the classical Kozai-Lidov mechanism. In the time-dependent model, brought about in our case by the Moon's perturbed motion, the action variables of the system may experience chaotic variations and large drifts due to the possible overlap of nearby resonances. Using variational chaos indicators, we compute high-resolution portraits of the action space, revealing the existence of tori and structures filling chaotic regions. Our refined and elaborate calculations allow us to isolate precise initial conditions near specific areas of interest and to study their asymptotic behavior in time. We highlight in particular how the drift in phase space is mediated by the complement of the numerically detected KAM tori. Despite their reputed normality, Earth satellite orbits can possess an extraordinarily rich spectrum of dynamical behaviors, and, like the small body remnants of Solar system formation, they have all the complications that make them very interesting candidates for testing the modern tools of chaos theory.

Automatic detection and classification of artifacts in single-channel EEG.

PubMed

Olund, Thomas; Duun-Henriksen, Jonas; Kjaer, Troels W; Sorensen, Helge B D

2014-01-01

Ambulatory EEG monitoring can provide medical doctors important diagnostic information, without hospitalizing the patient. These recordings are however more exposed to noise and artifacts compared to clinically recorded EEG. An automatic artifact detection and classification algorithm for single-channel EEG is proposed to help identifying these artifacts. Features are extracted from the EEG signal and wavelet subbands. Subsequently a selection algorithm is applied in order to identify the best discriminating features. A non-linear support vector machine is used to discriminate among different artifact classes using the selected features. Single-channel (Fp1-F7) EEG recordings are obtained from experiments with 12 healthy subjects performing artifact inducing movements. The dataset was used to construct and validate the model. Both subject-specific and generic implementation, are investigated. The detection algorithm yield an average sensitivity and specificity above 95% for both the subject-specific and generic models. The classification algorithm show a mean accuracy of 78 and 64% for the subject-specific and generic model, respectively. The classification model was additionally validated on a reference dataset with similar results.

Digitized Spiral Drawing: A Possible Biomarker for Early Parkinson's Disease.

PubMed

San Luciano, Marta; Wang, Cuiling; Ortega, Roberto A; Yu, Qiping; Boschung, Sarah; Soto-Valencia, Jeannie; Bressman, Susan B; Lipton, Richard B; Pullman, Seth; Saunders-Pullman, Rachel

2016-01-01

Pre-clinical markers of Parkinson's Disease (PD) are needed, and to be relevant in pre-clinical disease, they should be quantifiably abnormal in early disease as well. Handwriting is impaired early in PD and can be evaluated using computerized analysis of drawn spirals, capturing kinematic, dynamic, and spatial abnormalities and calculating indices that quantify motor performance and disability. Digitized spiral drawing correlates with motor scores and may be more sensitive in detecting early changes than subjective ratings. However, whether changes in spiral drawing are abnormal compared with controls and whether changes are detected in early PD are unknown. 138 PD subjects (50 with early PD) and 150 controls drew spirals on a digitizing tablet, generating x, y, z (pressure) data-coordinates and time. Derived indices corresponded to overall spiral execution (severity), shape and kinematic irregularity (second order smoothness, first order zero-crossing), tightness, mean speed and variability of spiral width. Linear mixed effect adjusted models comparing these indices and cross-validation were performed. Receiver operating characteristic analysis was applied to examine discriminative validity of combined indices. All indices were significantly different between PD cases and controls, except for zero-crossing. A model using all indices had high discriminative validity (sensitivity = 0.86, specificity = 0.81). Discriminative validity was maintained in patients with early PD. Spiral analysis accurately discriminates subjects with PD and early PD from controls supporting a role as a promising quantitative biomarker. Further assessment is needed to determine whether spiral changes are PD specific compared with other disorders and if present in pre-clinical PD.

Digitized Spiral Drawing: A Possible Biomarker for Early Parkinson’s Disease

PubMed Central

San Luciano, Marta; Wang, Cuiling; Ortega, Roberto A.; Yu, Qiping; Boschung, Sarah; Soto-Valencia, Jeannie; Bressman, Susan B.; Lipton, Richard B.; Pullman, Seth; Saunders-Pullman, Rachel

2016-01-01

Introduction Pre-clinical markers of Parkinson’s Disease (PD) are needed, and to be relevant in pre-clinical disease, they should be quantifiably abnormal in early disease as well. Handwriting is impaired early in PD and can be evaluated using computerized analysis of drawn spirals, capturing kinematic, dynamic, and spatial abnormalities and calculating indices that quantify motor performance and disability. Digitized spiral drawing correlates with motor scores and may be more sensitive in detecting early changes than subjective ratings. However, whether changes in spiral drawing are abnormal compared with controls and whether changes are detected in early PD are unknown. Methods 138 PD subjects (50 with early PD) and 150 controls drew spirals on a digitizing tablet, generating x, y, z (pressure) data-coordinates and time. Derived indices corresponded to overall spiral execution (severity), shape and kinematic irregularity (second order smoothness, first order zero-crossing), tightness, mean speed and variability of spiral width. Linear mixed effect adjusted models comparing these indices and cross-validation were performed. Receiver operating characteristic analysis was applied to examine discriminative validity of combined indices. Results All indices were significantly different between PD cases and controls, except for zero-crossing. A model using all indices had high discriminative validity (sensitivity = 0.86, specificity = 0.81). Discriminative validity was maintained in patients with early PD. Conclusion Spiral analysis accurately discriminates subjects with PD and early PD from controls supporting a role as a promising quantitative biomarker. Further assessment is needed to determine whether spiral changes are PD specific compared with other disorders and if present in pre-clinical PD. PMID:27732597

Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions

PubMed Central

Meyer, Andrew J.; Eskinazi, Ilan; Jackson, Jennifer N.; Rao, Anil V.; Patten, Carolynn; Fregly, Benjamin J.

2016-01-01

Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject’s self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot–ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject’s walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject’s walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject’s walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations. PMID:27790612

Cortical subnetwork dynamics during human language tasks.

PubMed

Collard, Maxwell J; Fifer, Matthew S; Benz, Heather L; McMullen, David P; Wang, Yujing; Milsap, Griffin W; Korzeniewska, Anna; Crone, Nathan E

2016-07-15

Language tasks require the coordinated activation of multiple subnetworks-groups of related cortical interactions involved in specific components of task processing. Although electrocorticography (ECoG) has sufficient temporal and spatial resolution to capture the dynamics of event-related interactions between cortical sites, it is difficult to decompose these complex spatiotemporal patterns into functionally discrete subnetworks without explicit knowledge of each subnetwork's timing. We hypothesized that subnetworks corresponding to distinct components of task-related processing could be identified as groups of interactions with co-varying strengths. In this study, five subjects implanted with ECoG grids over language areas performed word repetition and picture naming. We estimated the interaction strength between each pair of electrodes during each task using a time-varying dynamic Bayesian network (tvDBN) model constructed from the power of high gamma (70-110Hz) activity, a surrogate for population firing rates. We then reduced the dimensionality of this model using principal component analysis (PCA) to identify groups of interactions with co-varying strengths, which we term functional network components (FNCs). This data-driven technique estimates both the weight of each interaction's contribution to a particular subnetwork, and the temporal profile of each subnetwork's activation during the task. We found FNCs with temporal and anatomical features consistent with articulatory preparation in both tasks, and with auditory and visual processing in the word repetition and picture naming tasks, respectively. These FNCs were highly consistent between subjects with similar electrode placement, and were robust enough to be characterized in single trials. Furthermore, the interaction patterns uncovered by FNC analysis correlated well with recent literature suggesting important functional-anatomical distinctions between processing external and self-produced speech. Our results demonstrate that subnetwork decomposition of event-related cortical interactions is a powerful paradigm for interpreting the rich dynamics of large-scale, distributed cortical networks during human cognitive tasks. Copyright © 2016 Elsevier Inc. All rights reserved.

An integrative fuzzy Kansei engineering and Kano model for logistics services

NASA Astrophysics Data System (ADS)

Hartono, M.; Chuan, T. K.; Prayogo, D. N.; Santoso, A.

2017-11-01

Nowadays, customer emotional needs (known as Kansei) in product and especially in services become a major concern. One of the emerging services is the logistics services. In obtaining a global competitive advantage, logistics services should understand and satisfy their customer affective impressions (Kansei). How to capture, model and analyze the customer emotions has been well structured by Kansei Engineering, equipped with Kano model to strengthen its methodology. However, its methodology lacks of the dynamics of customer perception. More specifically, there is a criticism of perceived scores on user preferences, in both perceived service quality and Kansei response, whether they represent an exact numerical value. Thus, this paper is proposed to discuss an approach of fuzzy Kansei in logistics service experiences. A case study in IT-based logistics services involving 100 subjects has been conducted. Its findings including the service gaps accompanied with prioritized improvement initiatives are discussed.

Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions

PubMed Central

Golkar, Mahsa A.; Sobhani Tehrani, Ehsan; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness is a dynamic, nonlinear relationship between the position of a joint and the torque acting about it, which can be used to describe the biomechanics of the joint and associated limb(s). This paper models and quantifies changes in ankle dynamic stiffness and its individual elements, intrinsic and reflex stiffness, in healthy human subjects during isometric, time-varying (TV) contractions of the ankle plantarflexor muscles. A subspace, linear parameter varying, parallel-cascade (LPV-PC) algorithm was used to identify the model from measured input position perturbations and output torque data using voluntary torque as the LPV scheduling variable (SV). Monte-Carlo simulations demonstrated that the algorithm is accurate, precise, and robust to colored measurement noise. The algorithm was then used to examine stiffness changes associated with TV isometric contractions. The SV was estimated from the Soleus EMG using a Hammerstein model of EMG-torque dynamics identified from unperturbed trials. The LPV-PC algorithm identified (i) a non-parametric LPV impulse response function (LPV IRF) for intrinsic stiffness and (ii) a LPV-Hammerstein model for reflex stiffness consisting of a LPV static nonlinearity followed by a time-invariant state-space model of reflex dynamics. The results demonstrated that: (a) intrinsic stiffness, in particular ankle elasticity, increased significantly and monotonically with activation level; (b) the gain of the reflex pathway increased from rest to around 10–20% of subject's MVC and then declined; and (c) the reflex dynamics were second order. These findings suggest that in healthy human ankle, reflex stiffness contributes most at low muscle contraction levels, whereas, intrinsic contributions monotonically increase with activation level. PMID:28579954

Multiscale Modeling for the Analysis for Grain-Scale Fracture Within Aluminum Microstructures

NASA Technical Reports Server (NTRS)

Glaessgen, Edward H.; Phillips, Dawn R.; Yamakov, Vesselin; Saether, Erik

2005-01-01

Multiscale modeling methods for the analysis of metallic microstructures are discussed. Both molecular dynamics and the finite element method are used to analyze crack propagation and stress distribution in a nanoscale aluminum bicrystal model subjected to hydrostatic loading. Quantitative similarity is observed between the results from the two very different analysis methods. A bilinear traction-displacement relationship that may be embedded into cohesive zone finite elements is extracted from the nanoscale molecular dynamics results.

Different developmental trajectories across feature types support a dynamic field model of visual working memory development.

PubMed

Simmering, Vanessa R; Miller, Hilary E; Bohache, Kevin

2015-05-01

Research on visual working memory has focused on characterizing the nature of capacity limits as "slots" or "resources" based almost exclusively on adults' performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to "slot" or "resource" explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children's (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model-purportedly arising through experience-can capture differences across feature types.

Visual Modelling of Learning Processes

ERIC Educational Resources Information Center

Copperman, Elana; Beeri, Catriel; Ben-Zvi, Nava

2007-01-01

This paper introduces various visual models for the analysis and description of learning processes. The models analyse learning on two levels: the dynamic level (as a process over time) and the functional level. Two types of model for dynamic modelling are proposed: the session trace, which documents a specific learner in a particular learning…

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging.

PubMed

Hsu, Vivian M; Wes, Ari M; Tahiri, Youssef; Cornman-Homonoff, Joshua; Percec, Ivona

2014-09-01

The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time.

Ideal free distribution or dynamic game? An agent-based simulation study of trawling strategies with varying information

NASA Astrophysics Data System (ADS)

Beecham, J. A.; Engelhard, G. H.

2007-10-01

An ecological economic model of trawling is presented to demonstrate the effect of trawling location choice strategy on net input (rate of economic gain of fish caught per time spent less costs). Fishing location choice is considered to be a dynamic process whereby trawlers chose from among a repertoire of plastic strategies that they modify if their gains fall below a fixed proportion of the mean gains of the fleet as a whole. The distribution of fishing across different areas of a fishery follows an approximate ideal free distribution (IFD) with varying noise due to uncertainty. The least-productive areas are not utilised because initial net input never reaches the mean yield of better areas subject to competitive exploitation. In cases, where there is a weak temporal autocorrelation between fish stocks in a specific location, a plastic strategy of local translocation between trawls mixed with longer-range translocation increases realised input. The trawler can change its translocation strategy in the light of information about recent trawling success compared to its long-term average but, in contrast to predictions of the Marginal Value Theorem (MVT) model, does not know for certain what it will find by moving, so may need to sample new patches. The combination of the two types of translocation mirrored beam-trawling strategies used by the Dutch fleet and the resultant distribution of trawling effort is confirmed by analysis of historical effort distribution of British otter trawling fleets in the North Sea. Fisheries exploitation represents an area where dynamic agent-based adaptive models may be a better representation of the economic dynamics of a fleet than classically inspired optimisation models.

A Theoretical Approach to Understanding Population Dynamics with Seasonal Developmental Durations

NASA Astrophysics Data System (ADS)

Lou, Yijun; Zhao, Xiao-Qiang

2017-04-01

There is a growing body of biological investigations to understand impacts of seasonally changing environmental conditions on population dynamics in various research fields such as single population growth and disease transmission. On the other side, understanding the population dynamics subject to seasonally changing weather conditions plays a fundamental role in predicting the trends of population patterns and disease transmission risks under the scenarios of climate change. With the host-macroparasite interaction as a motivating example, we propose a synthesized approach for investigating the population dynamics subject to seasonal environmental variations from theoretical point of view, where the model development, basic reproduction ratio formulation and computation, and rigorous mathematical analysis are involved. The resultant model with periodic delay presents a novel term related to the rate of change of the developmental duration, bringing new challenges to dynamics analysis. By investigating a periodic semiflow on a suitably chosen phase space, the global dynamics of a threshold type is established: all solutions either go to zero when basic reproduction ratio is less than one, or stabilize at a positive periodic state when the reproduction ratio is greater than one. The synthesized approach developed here is applicable to broader contexts of investigating biological systems with seasonal developmental durations.

Comparison of 4D Phase-Contrast MRI Flow Measurements to Computational Fluid Dynamics Simulations of Cerebrospinal Fluid Motion in the Cervical Spine

PubMed Central

Yiallourou, Theresia I.; Kröger, Jan Robert; Stergiopulos, Nikolaos; Maintz, David

2012-01-01

Cerebrospinal fluid (CSF) dynamics in the cervical spinal subarachnoid space (SSS) have been thought to be important to help diagnose and assess craniospinal disorders such as Chiari I malformation (CM). In this study we obtained time-resolved three directional velocity encoded phase-contrast MRI (4D PC MRI) in three healthy volunteers and four CM patients and compared the 4D PC MRI measurements to subject-specific 3D computational fluid dynamics (CFD) simulations. The CFD simulations considered the geometry to be rigid-walled and did not include small anatomical structures such as nerve roots, denticulate ligaments and arachnoid trabeculae. Results were compared at nine axial planes along the cervical SSS in terms of peak CSF velocities in both the cranial and caudal direction and visual interpretation of thru-plane velocity profiles. 4D PC MRI peak CSF velocities were consistently greater than the CFD peak velocities and these differences were more pronounced in CM patients than in healthy subjects. In the upper cervical SSS of CM patients the 4D PC MRI quantified stronger fluid jets than the CFD. Visual interpretation of the 4D PC MRI thru-plane velocity profiles showed greater pulsatile movement of CSF in the anterior SSS in comparison to the posterior and reduction in local CSF velocities near nerve roots. CFD velocity profiles were relatively uniform around the spinal cord for all subjects. This study represents the first comparison of 4D PC MRI measurements to CFD of CSF flow in the cervical SSS. The results highlight the utility of 4D PC MRI for evaluation of complex CSF dynamics and the need for improvement of CFD methodology. Future studies are needed to investigate whether integration of fine anatomical structures and gross motion of the brain and/or spinal cord into the computational model will lead to a better agreement between the two techniques. PMID:23284970

Using Mobile TLA as a Logic for Dynamic I/O Automata

NASA Astrophysics Data System (ADS)

Kapus, Tatjana

Input/Output (I/O) automata and the Temporal Logic of Actions (TLA) are two well-known techniques for the specification and verification of concurrent systems. Over the past few years, they have been extended to the so-called dynamic I/O automata and, respectively, Mobile TLA (MTLA) in order to be more appropriate for mobile agent systems. Dynamic I/O automata is just a mathematical model, whereas MTLA is a logic with a formally defined language. In this paper, therefore, we investigate how MTLA could be used as a formal language for the specification of dynamic I/O automata. We do this by writing an MTLA specification of a travel agent system which has been specified semi-formally in the literature on that model. In this specification, we deal with always existing agents as well as with an initially unknown number of dynamically created agents, with mobile and non-mobile agents, with I/O-automata-style communication, and with the changing communication capabilities of mobile agents. We have previously written a TLA specification of this system. This paper shows that an MTLA specification of such a system can be more elegant and faithful to the dynamic I/O automata definition because the agent existence and location can be expressed directly by using agent and location names instead of special variables as in TLA. It also shows how the reuse of names for dynamically created and destroyed agents within the dynamic I/O automata framework can be specified in MTLA.

Relationship between dynamic infrared thermal images and blood perfusion rate of the tongue in anaemia patients

NASA Astrophysics Data System (ADS)

Xie, Haiwei; Zhang, Yan

2018-03-01

The relationship between dynamic infrared (IR) thermal images and blood perfusion rate of the tongues of anaemia patients was investigated. Blood perfusion rates at multiple locations on the tongues of 62 anaemia patients and 70 control subjects were measured. For both groups of subjects, dynamic IR thermal images were also recorded within 16 s after the mouth opened. The results showed that the blood perfusion rates at different sites (apex, middle, left side and right side) on the tongues in anaemia patients (3.49, 3.71, 3.85 and 3.77 kg/s m-3) were significantly lower than those at the corresponding sites in control subjects (4.45, 4.66, 4.81 and 4.70 kg/s m-3). After the mouth opened, the tongue temperature decreased more rapidly in anaemia patients than in control subjects. To analyse the heat transfer mechanism, a transient heat transfer model of the tongue was developed. The tongue temperatures in anaemia patients and control subjects were calculated using this model and compared to the tongue temperatures measured by the IR thermal imager. The relationship between the tongue surface temperature and the tongue blood perfusion rate was analysed. The simulation results indicated that the low blood perfusion rate and the correlated changes in anaemia patients can cause faster temperature decreases of the tongue surface.

Dynamical simulation of E-ELT segmented primary mirror

NASA Astrophysics Data System (ADS)

Sedghi, B.; Muller, M.; Bauvir, B.

2011-09-01

The dynamical behavior of the primary mirror (M1) has an important impact on the control of the segments and the performance of the telescope. Control of large segmented mirrors with a large number of actuators and sensors and multiple control loops in real life is a challenging problem. In virtual life, modeling, simulation and analysis of the M1 bears similar difficulties and challenges. In order to capture the dynamics of the segment subunits (high frequency modes) and the telescope back structure (low frequency modes), high order dynamical models with a very large number of inputs and outputs need to be simulated. In this paper, different approaches for dynamical modeling and simulation of the M1 segmented mirror subject to various perturbations, e.g. sensor noise, wind load, vibrations, earthquake are presented.

Subject-specific longitudinal shape analysis by coupling spatiotemporal shape modeling with medial analysis

NASA Astrophysics Data System (ADS)

Hong, Sungmin; Fishbaugh, James; Rezanejad, Morteza; Siddiqi, Kaleem; Johnson, Hans; Paulsen, Jane; Kim, Eun Young; Gerig, Guido

2017-02-01

Modeling subject-specific shape change is one of the most important challenges in longitudinal shape analysis of disease progression. Whereas anatomical change over time can be a function of normal aging, anatomy can also be impacted by disease related degeneration. Anatomical shape change may also be affected by structural changes from neighboring shapes, which may cause non-linear variations in pose. In this paper, we propose a framework to analyze disease related shape changes by coupling extrinsic modeling of the ambient anatomical space via spatiotemporal deformations with intrinsic shape properties from medial surface analysis. We compare intrinsic shape properties of a subject-specific shape trajectory to a normative 4D shape atlas representing normal aging to isolate shape changes related to disease. The spatiotemporal shape modeling establishes inter/intra subject anatomical correspondence, which in turn enables comparisons between subjects and the 4D shape atlas, and also quantitative analysis of disease related shape change. The medial surface analysis captures intrinsic shape properties related to local patterns of deformation. The proposed framework jointly models extrinsic longitudinal shape changes in the ambient anatomical space, as well as intrinsic shape properties to give localized measurements of degeneration. Six high risk subjects and six controls are randomly sampled from a Huntington's disease image database for qualitative and quantitative comparison.

Research on Generating Method of Embedded Software Test Document Based on Dynamic Model

NASA Astrophysics Data System (ADS)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper provides a dynamic model-based test document generation method for embedded software that provides automatic generation of two documents: test requirements specification documentation and configuration item test documentation. This method enables dynamic test requirements to be implemented in dynamic models, enabling dynamic test demand tracking to be easily generated; able to automatically generate standardized, standardized test requirements and test documentation, improved document-related content inconsistency and lack of integrity And other issues, improve the efficiency.

Human perceptual overestimation of whole body roll tilt in hypergravity

PubMed Central

Newman, Michael C.; Oman, Charles M.; Merfeld, Daniel M.; Young, Laurence R.

2014-01-01

Hypergravity provides a unique environment to study human perception of orientation. We utilized a long-radius centrifuge to study perception of both static and dynamic whole body roll tilt in hypergravity, across a range of angles, frequencies, and net gravito-inertial levels (referred to as G levels). While studies of static tilt perception in hypergravity have been published, this is the first to measure dynamic tilt perception (i.e., with time-varying canal stimulation) in hypergravity using a continuous matching task. In complete darkness, subjects reported their orientation perception using a haptic task, whereby they attempted to align a hand-held bar with their perceived horizontal. Static roll tilt was overestimated in hypergravity, with more overestimation at larger angles and higher G levels, across the conditions tested (overestimated by ∼35% per additional G level, P < 0.001). As our primary contribution, we show that dynamic roll tilt was also consistently overestimated in hypergravity (P < 0.001) at all angles and frequencies tested, again with more overestimation at higher G levels. The overestimation was similar to that for static tilts at low angular velocities but decreased at higher angular velocities (P = 0.006), consistent with semicircular canal sensory integration. To match our findings, we propose a modification to a previous Observer-type canal-otolith interaction model. Specifically, our data were better modeled by including the hypothesis that the central nervous system treats otolith stimulation in the utricular plane differently than stimulation out of the utricular plane. This modified model was able to simulate quantitatively both the static and the dynamic roll tilt overestimation in hypergravity measured experimentally. PMID:25540216

Bayesian integration and non-linear feedback control in a full-body motor task.

PubMed

Stevenson, Ian H; Fernandes, Hugo L; Vilares, Iris; Wei, Kunlin; Körding, Konrad P

2009-12-01

A large number of experiments have asked to what degree human reaching movements can be understood as being close to optimal in a statistical sense. However, little is known about whether these principles are relevant for other classes of movements. Here we analyzed movement in a task that is similar to surfing or snowboarding. Human subjects stand on a force plate that measures their center of pressure. This center of pressure affects the acceleration of a cursor that is displayed in a noisy fashion (as a cloud of dots) on a projection screen while the subject is incentivized to keep the cursor close to a fixed position. We find that salient aspects of observed behavior are well-described by optimal control models where a Bayesian estimation model (Kalman filter) is combined with an optimal controller (either a Linear-Quadratic-Regulator or Bang-bang controller). We find evidence that subjects integrate information over time taking into account uncertainty. However, behavior in this continuous steering task appears to be a highly non-linear function of the visual feedback. While the nervous system appears to implement Bayes-like mechanisms for a full-body, dynamic task, it may additionally take into account the specific costs and constraints of the task.

A summary of recent NASA/Army contributions to rotorcraft vibrations and structural dynamics technology

NASA Technical Reports Server (NTRS)

Kvaternik, Raymond G.; Bartlett, Felton D., Jr.; Cline, John H.

1988-01-01

The requirement for low vibrations has achieved the status of a critical design consideration in modern helicopters. There is now a recognized need to account for vibrations during both the analytical and experimental phases of design. Research activities in this area were both broad and varied and notable advances were made in recent years in the critical elements of the technology base needed to achieve the goal of a jet smooth ride. The purpose is to present an overview of accomplishments and current activities of govern and government-sponsored research in the area of rotorcraft vibrations and structural dynamics, focusing on NASA and Army contributions over the last decade or so. Specific topics addressed include: airframe finite-element modeling for static and dynamic analyses, analysis of coupled rotor-airframe vibrations, optimization of airframes subject to vibration constraints, active and passive control of vibrations in both the rotating and fixed systems, and integration of testing and analysis in such guises as modal analysis, system identification, structural modification, and vibratory loads measurement.

The Dynamics of the Human Infant Gut Microbiome in Development and in Progression towards Type 1 Diabetes

PubMed Central

Kostic, Aleksandar D.; Gevers, Dirk; Siljander, Heli; Vatanen, Tommi; Hyötyläinen, Tuulia; Hämäläinen, Anu-Maaria; Peet, Aleksandr; Tillmann, Vallo; Pöhö, Päivi; Mattila, Ismo; Lähdesmäki, Harri; Franzosa, Eric A.; Vaarala, Outi; de Goffau, Marcus; Harmsen, Hermie; Ilonen, Jorma; Virtanen, Suvi M.; Clish, Clary B.; Orešič, Matej; Huttenhower, Curtis; Knip, Mikael

2015-01-01

SUMMARY Colonization of the fetal and infant gut microbiome results in dynamic changes in diversity, which can impact disease susceptibility. To examine the relationship between human gut microbiome dynamics throughout infancy and type 1 diabetes (T1D), we examined a cohort of 33 infants genetically predisposed to T1D. Modeling trajectories of microbial abundances through infancy revealed a subset of microbial relationships shared across most subjects. Although strain composition of a given species was highly variable between individuals, it was stable within individuals throughout infancy. Metabolic composition and metabolic pathway abundance remained constant across time. A marked drop in alpha-diversity was observed in T1D progressors in the time-window between seroconversion and T1D diagnosis, accompanied by spikes in inflammation-favoring organisms, gene functions, and serum and stool metabolites. This work identifies trends in the development of the human infant gut microbiome along with specific alterations that precede T1D onset and distinguish T1D progressors from non-progressors. PMID:25662751

A service-oriented data access control model

NASA Astrophysics Data System (ADS)

Meng, Wei; Li, Fengmin; Pan, Juchen; Song, Song; Bian, Jiali

2017-01-01

The development of mobile computing, cloud computing and distributed computing meets the growing individual service needs. Facing with complex application system, it's an urgent problem to ensure real-time, dynamic, and fine-grained data access control. By analyzing common data access control models, on the basis of mandatory access control model, the paper proposes a service-oriented access control model. By regarding system services as subject and data of databases as object, the model defines access levels and access identification of subject and object, and ensures system services securely to access databases.

[Virtual audiovisual talking heads: articulatory data and models--applications].

PubMed

Badin, P; Elisei, F; Bailly, G; Savariaux, C; Serrurier, A; Tarabalka, Y

2007-01-01

In the framework of experimental phonetics, our approach to the study of speech production is based on the measurement, the analysis and the modeling of orofacial articulators such as the jaw, the face and the lips, the tongue or the velum. Therefore, we present in this article experimental techniques that allow characterising the shape and movement of speech articulators (static and dynamic MRI, computed tomodensitometry, electromagnetic articulography, video recording). We then describe the linear models of the various organs that we can elaborate from speaker-specific articulatory data. We show that these models, that exhibit a good geometrical resolution, can be controlled from articulatory data with a good temporal resolution and can thus permit the reconstruction of high quality animation of the articulators. These models, that we have integrated in a virtual talking head, can produce augmented audiovisual speech. In this framework, we have assessed the natural tongue reading capabilities of human subjects by means of audiovisual perception tests. We conclude by suggesting a number of other applications of talking heads.

Three-dimensional finite element modelling of muscle forces during mastication.

PubMed

Röhrle, Oliver; Pullan, Andrew J

2007-01-01

This paper presents a three-dimensional finite element model of human mastication. Specifically, an anatomically realistic model of the masseter muscles and associated bones is used to investigate the dynamics of chewing. A motion capture system is used to track the jaw motion of a subject chewing standard foods. The three-dimensional nonlinear deformation of the masseter muscles are calculated via the finite element method, using the jaw motion data as boundary conditions. Motion-driven muscle activation patterns and a transversely isotropic material law, defined in a muscle-fibre coordinate system, are used in the calculations. Time-force relationships are presented and analysed with respect to different tasks during mastication, e.g. opening, closing, and biting, and are also compared to a more traditional one-dimensional model. The results strongly suggest that, due to the complex arrangement of muscle force directions, modelling skeletal muscles as conventional one-dimensional lines of action might introduce a significant source of error.

Vertical resolution of baroclinic modes in global ocean models

NASA Astrophysics Data System (ADS)

Stewart, K. D.; Hogg, A. McC.; Griffies, S. M.; Heerdegen, A. P.; Ward, M. L.; Spence, P.; England, M. H.

2017-05-01

Improvements in the horizontal resolution of global ocean models, motivated by the horizontal resolution requirements for specific flow features, has advanced modelling capabilities into the dynamical regime dominated by mesoscale variability. In contrast, the choice of the vertical grid remains a subjective choice, and it is not clear that efforts to improve vertical resolution adequately support their horizontal counterparts. Indeed, considering that the bulk of the vertical ocean dynamics (including convection) are parameterized, it is not immediately obvious what the vertical grid is supposed to resolve. Here, we propose that the primary purpose of the vertical grid in a hydrostatic ocean model is to resolve the vertical structure of horizontal flows, rather than to resolve vertical motion. With this principle we construct vertical grids based on their abilities to represent baroclinic modal structures commensurate with the theoretical capabilities of a given horizontal grid. This approach is designed to ensure that the vertical grids of global ocean models complement (and, importantly, to not undermine) the resolution capabilities of the horizontal grid. We find that for z-coordinate global ocean models, at least 50 well-positioned vertical levels are required to resolve the first baroclinic mode, with an additional 25 levels per subsequent mode. High-resolution ocean-sea ice simulations are used to illustrate some of the dynamical enhancements gained by improving the vertical resolution of a 1/10° global ocean model. These enhancements include substantial increases in the sea surface height variance (∼30% increase south of 40°S), the barotropic and baroclinic eddy kinetic energies (up to 200% increase on and surrounding the Antarctic continental shelf and slopes), and the overturning streamfunction in potential density space (near-tripling of the Antarctic Bottom Water cell at 65°S).

Comparison of Standard Wind Turbine Models with Vendor Models for Power System Stability Analysis: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Honrubia-Escribano, A.; Gomez Lazaro, E.; Jimenez-Buendia, F.

The International Electrotechnical Commission Standard 61400-27-1 was published in February 2015. This standard deals with the development of generic terms and parameters to specify the electrical characteristics of wind turbines. Generic models of very complex technological systems, such as wind turbines, are thus defined based on the four common configurations available in the market. Due to its recent publication, the comparison of the response of generic models with specific vendor models plays a key role in ensuring the widespread use of this standard. This paper compares the response of a specific Gamesa dynamic wind turbine model to the corresponding genericmore » IEC Type III wind turbine model response when the wind turbine is subjected to a three-phase voltage dip. This Type III model represents the doubly-fed induction generator wind turbine, which is not only one of the most commonly sold and installed technologies in the current market but also a complex variable-speed operation implementation. In fact, active and reactive power transients are observed due to the voltage reduction. Special attention is given to the reactive power injection provided by the wind turbine models because it is a requirement of current grid codes. Further, the boundaries of the generic models associated with transient events that cannot be represented exactly are included in the paper.« less

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

A SIMPLE CELLULAR AUTOMATON MODEL FOR HIGH-LEVEL VEGETATION DYNAMICS

EPA Science Inventory

We have produced a simple two-dimensional (ground-plan) cellular automata model of vegetation dynamics specifically to investigate high-level community processes. The model is probabilistic, with individual plant behavior determined by physiologically-based rules derived from a w...

Transport theory and fluid dynamics

NASA Astrophysics Data System (ADS)

Greenberg, W.; Zweifel, P. F.

We report progress in various areas of applied mathematics relevant to transport theory under the subjects: abstract transport theory, explicit transport models and computation, and fluid dynamics. We present a brief review of progress during the past year and personnel supported, and we indicate the direction of our future research.

Dynamic 3D scanning as a markerless method to calculate multi-segment foot kinematics during stance phase: methodology and first application.

PubMed

Van den Herrewegen, Inge; Cuppens, Kris; Broeckx, Mario; Barisch-Fritz, Bettina; Vander Sloten, Jos; Leardini, Alberto; Peeraer, Louis

2014-08-22

Multi-segmental foot kinematics have been analyzed by means of optical marker-sets or by means of inertial sensors, but never by markerless dynamic 3D scanning (D3DScanning). The use of D3DScans implies a radically different approach for the construction of the multi-segment foot model: the foot anatomy is identified via the surface shape instead of distinct landmark points. We propose a 4-segment foot model consisting of the shank (Sha), calcaneus (Cal), metatarsus (Met) and hallux (Hal). These segments are manually selected on a static scan. To track the segments in the dynamic scan, the segments of the static scan are matched on each frame of the dynamic scan using the iterative closest point (ICP) fitting algorithm. Joint rotations are calculated between Sha-Cal, Cal-Met, and Met-Hal. Due to the lower quality scans at heel strike and toe off, the first and last 10% of the stance phase is excluded. The application of the method to 5 healthy subjects, 6 trials each, shows a good repeatability (intra-subject standard deviations between 1° and 2.5°) for Sha-Cal and Cal-Met joints, and inferior results for the Met-Hal joint (>3°). The repeatability seems to be subject-dependent. For the validation, a qualitative comparison with joint kinematics from a corresponding established marker-based multi-segment foot model is made. This shows very consistent patterns of rotation. The ease of subject preparation and also the effective and easy to interpret visual output, make the present technique very attractive for functional analysis of the foot, enhancing usability in clinical practice. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

[How our subjective coherence is built? The model of cognitive dissonance].

PubMed

Naccache, Lionel; El Karoui, Imen; Salti, Moti; Chammat, Mariam; Maillet, Mathurin; Allali, Sébastien

2015-01-01

Our conscious, subjective discourse, demonstrates a temporal coherence that distinguishes it from the many unconscious cognitive representations explored by cognitive neuroscience. This subjective coherence, --particularly its dynamics--can be modified in certain psychiatric syndromes including a " dissociative state " (e.g. schizophrenia), or in several neuropsychiatric disorders (e.g. frontal lobe syndrome). The medical and environmental consequences of these changes are significant. However, the psychological and neural mechanisms of this fundamental property remain largely unknown. We explored the dynamics of subjective coherence in an experimental paradigm (the "free choice "paradigm) originating for the field of cognitive dissonance. Using a series of behavioral experiments, conducted in healthy volunteers, we have discovered a key role for the episodic memory in the preference change process when simply making a choice. These results highlight the importance of conscious memory in the construction of subjective consistency, of which the subjects do not yet seem to be the conscious agents.

Effect of Posterior Horn Medial Meniscus Root Tear on In Vivo Knee Kinematics.

PubMed

Marsh, Chelsea A; Martin, Daniel E; Harner, Christopher D; Tashman, Scott

2014-07-01

Medial meniscus root tear (MMRT) is a recently recognized yet frequently missed meniscal tear pattern that biomechanically creates an environment approaching meniscal deficiency. The purpose of this study was to assess the effect of MMRT on tibiofemoral kinematics and arthrokinematics during daily activities by comparing the injured knees of subjects with isolated MMRT to their uninjured contralateral knees. The hypothesis was that the injured knee will demonstrate significantly more lateral tibial translation and adduction than the uninjured knee, and that the medial compartment will exhibit significantly different arthrokinematics than the lateral compartment in the affected limb. Cross-sectional study; Level of evidence, 3. Seven subjects with isolated MMRT were recruited and volumetric, density-based 3-dimensional models of their distal femurs and proximal tibia were created from computed tomography scans. High-speed, biplane radiographs were obtained of both their affected and unaffected knees. Moving 3-dimensional models of tibiofemoral kinematics were calculated using model-based tracking to assess overall kinematic variables and specific measures of tibiofemoral joint contact. The affected knees of the subjects were then compared to their unaffected contralateral knees. Affected knees demonstrated significantly more lateral tibial translation than the uninjured contralateral limb in all dynamic activities. Additionally, the medial compartment displayed greater amounts of mobility than the lateral compartment in the injured limbs. This study suggests that MMRT causes significant changes in in vivo knee kinematics and arthrokinematics and that the magnitude of these changes is influenced by dynamic task difficulty. Medial meniscus root tears lead to significant changes in joint arthrokinematics, with increased lateral tibial translation and greater medial compartment excursion. With complete root tears, essentially 100% of circumferential fibers are lost. This study will further our knowledge of meniscal deficiency and osteoarthritis and provide a baseline for more common forms of medial meniscal injuries (vertical, horizontal, radial), with various degrees of circumferential fiber function remaining.

Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models.

PubMed

Nolte, Daniel; Tsang, Chui Kit; Zhang, Kai Yu; Ding, Ziyun; Kedgley, Angela E; Bull, Anthony M J

2016-10-03

Accurate muscle geometry for musculoskeletal models is important to enable accurate subject-specific simulations. Commonly, linear scaling is used to obtain individualised muscle geometry. More advanced methods include non-linear scaling using segmented bone surfaces and manual or semi-automatic digitisation of muscle paths from medical images. In this study, a new scaling method combining non-linear scaling with reconstructions of bone surfaces using statistical shape modelling is presented. Statistical Shape Models (SSMs) of femur and tibia/fibula were used to reconstruct bone surfaces of nine subjects. Reference models were created by morphing manually digitised muscle paths to mean shapes of the SSMs using non-linear transformations and inter-subject variability was calculated. Subject-specific models of muscle attachment and via points were created from three reference models. The accuracy was evaluated by calculating the differences between the scaled and manually digitised models. The points defining the muscle paths showed large inter-subject variability at the thigh and shank - up to 26mm; this was found to limit the accuracy of all studied scaling methods. Errors for the subject-specific muscle point reconstructions of the thigh could be decreased by 9% to 20% by using the non-linear scaling compared to a typical linear scaling method. We conclude that the proposed non-linear scaling method is more accurate than linear scaling methods. Thus, when combined with the ability to reconstruct bone surfaces from incomplete or scattered geometry data using statistical shape models our proposed method is an alternative to linear scaling methods. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Common challenges for ecological modelling: synthesis of facilitated discussions held at the symposia organized for the 2009 conference of the International Society for Ecological Modelling in Quebec City, Canada, (October 6-9, 2009)

USGS Publications Warehouse

Larocque, Guy R.; Mailly, D.; Yue, T.-X.; Anand, M.; Peng, C.; Kazanci, C.; Etterson, M.; Goethals, P.; Jorgensen, S.E.; Schramski, J.R.; McIntire, E.J.B.; Marceau, D.J.; Chen, B.; Chen, G.Q.; Yang, Z.F.; Novotna, B.; Luckai, N.; Bhatti, Jagtar S.; Liu, J.; Munson, A.; Gordon, Andrew M.; Ascough, J.C.

2011-01-01

The eleven symposia organized for the 2009 conference of the International Society for Ecological Modelling (ISEM 2009) held in Quebec City, Canada, October 6–9, 2009, included facilitated discussion sessions following formal presentations. Each symposium focused on a specific subject, and all the subjects could be classified into three broad categories: theoretical development, population dynamics and ecosystem processes. Following discussions with the symposia organizers, which indicated that they all shared similar issues and concerns, the facilitated discussions were task-oriented around four basic questions: (1) key challenges in the research area, (2) generating and sharing new ideas, (3) improving collaboration and networking, and (4) increasing visibility to decision-makers, partners and clients. Common challenges that emerged from the symposia included the need for improved communication and collaboration among different academic disciplines, further progress in both theoretical and practical modelling approaches, and accentuation of technology transfer. Regarding the generation and sharing of new ideas, the main issue that emerged was the type of positive interactions that should be encouraged among potential collaborators. The usefulness of the Internet, particularly for the sharing of open-source software and conducting discussion forums, was highlighted for improving collaboration and networking. Several communication tools are available today, and it is important for modellers to use them more intensively. Visibility can be increased by publishing professional newsletters, maintaining informal contacts with the public, organizing educational sessions in primary and secondary schools, and developing simplified analytical frameworks and pilot studies. Specific issues raised in each symposium are also discussed.

Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

PubMed

Patel, Kevin R; Tobyne, Sean; Porter, Daria; Bireley, John Daniel; Smith, Victoria; Klawiter, Eric

2018-06-01

Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnection, contribute to increased network rsFC. We obtain measures of rsFC using fMRI and SC using probabilistic tractography in 50 healthy and 28 multiple sclerosis subjects. Using a computational model of neuronal dynamics, we simulate BOLD using healthy subject SC to couple regions. We find that altering the model by introducing structural disconnection patterns observed in those multiple sclerosis subjects with high network rsFC generates simulations with high rsFC as well, suggesting that disconnection itself plays a role in producing high network functional connectivity. We then examine SC data in individuals. In multiple sclerosis subjects with high network rsFC, we find a preferential disconnection between the relevant network and wider system. We examine the significance of such network isolation by introducing random disconnection into the model. As observed empirically, simulated network rsFC increases with removal of connections bridging a community with the remainder of the brain. We thus show that structural disconnection known to occur in multiple sclerosis contributes to network rsFC changes in multiple sclerosis and further that community isolation is responsible for elevated network functional connectivity.

Cortical oscillatory dynamics in a social interaction model.

PubMed

Knyazev, Gennady G; Slobodskoj-Plusnin, Jaroslav Y; Bocharov, Andrey V; Pylkova, Liudmila V

2013-03-15

In this study we sought to investigate cortical oscillatory dynamics accompanying three major kinds of social behavior: aggressive, friendly, and avoidant. Behavioral and EEG data were collected in 48 participants during a computer game modeling social interactions with virtual 'persons'. 3D source reconstruction and independent component analysis were applied to EEG data. Results showed that social behavior was partly reactive and partly proactive with subject's personality playing an important role in shaping this behavior. Most salient differences were found between avoidance and approach behaviors, whereas the two kinds of approach behavior (i.e., aggression and friendship) did not differ from each other. Comparative to avoidance, approach behaviors were associated with higher induced responses in most frequency bands which were mostly observed in cortical areas overlapping with the default mode network. The difference between approach- and avoidance-related oscillatory dynamics was more salient in subjects predisposed to approach behaviors (i.e., in aggressive or sociable subjects) and was less pronounced in subjects predisposed to avoidance behavior (i.e., in high trait anxiety scorers). There was a trend to higher low frequency phase-locking in motor area in approach than in avoid condition. Results are discussed in light of the concept linking induced responses with top-down and evoked responses with bottom-up processes. Copyright © 2012 Elsevier B.V. All rights reserved.

Level of functional capacities following soccer-specific warm-up methods among elite collegiate soccer players.

PubMed

Vazini Taher, Amir; Parnow, Abdolhossein

2017-05-01

Different methods of warm-up may have implications in improving various aspects of soccer performance. The present study aimed to investigate acute effects of soccer specific warm-up protocols on functional performance tests. This study using randomized within-subject design, investigated the performance of 22 collegiate elite soccer player following soccer specific warm-ups using dynamic stretching, static stretching, and FIFA 11+ program. Post warm-up examinations consisted: 1) Illinois Agility Test; 2) vertical jump; 3) 30 meter sprint; 4) consecutive turns; 5) flexibility of knee. Vertical jump performance was significantly lower following static stretching, as compared to dynamic stretching (P=0.005). Sprint performance declined significantly following static stretching as compared to FIFA 11+ (P=0.023). Agility time was significantly faster following dynamic stretching as compared to FIFA 11+ (P=0.001) and static stretching (P=0.001). Knee flexibility scores were significantly improved following the static stretching as compared to dynamic stretching (P=016). No significant difference was observed for consecutive turns between three warm-up protocol. The present finding showed that a soccer specific warm-up protocol relied on dynamic stretching is preferable in enhancing performance as compared to protocols relying on static stretches and FIFA 11+ program. Investigators suggest that while different soccer specific warm-up protocols have varied types of effects on performance, acute effects of dynamic stretching on performance in elite soccer players are assured, however application of static stretching in reducing muscle stiffness is demonstrated.

Validation of a computational knee joint model using an alignment method for the knee laxity test and computed tomography.

PubMed

Kang, Kyoung-Tak; Kim, Sung-Hwan; Son, Juhyun; Lee, Young Han; Koh, Yong-Gon

2017-01-01

Computational models have been identified as efficient techniques in the clinical decision-making process. However, computational model was validated using published data in most previous studies, and the kinematic validation of such models still remains a challenge. Recently, studies using medical imaging have provided a more accurate visualization of knee joint kinematics. The purpose of the present study was to perform kinematic validation for the subject-specific computational knee joint model by comparison with subject's medical imaging under identical laxity condition. The laxity test was applied to the anterior-posterior drawer under 90° flexion and the varus-valgus under 20° flexion with a series of stress radiographs, a Telos device, and computed tomography. The loading condition in the computational subject-specific knee joint model was identical to the laxity test condition in the medical image. Our computational model showed knee laxity kinematic trends that were consistent with the computed tomography images, except for negligible differences because of the indirect application of the subject's in vivo material properties. Medical imaging based on computed tomography with the laxity test allowed us to measure not only the precise translation but also the rotation of the knee joint. This methodology will be beneficial in the validation of laxity tests for subject- or patient-specific computational models.

Gamma Ray Observatory (GRO) dynamics simulator requirements and mathematical specifications, revision 1

NASA Technical Reports Server (NTRS)

Harman, R.; Blejer, D.

1990-01-01

The requirements and mathematical specifications for the Gamma Ray Observatory (GRO) Dynamics Simulator are presented. The complete simulator system, which consists of the profie subsystem, simulation control and input/output subsystem, truth model subsystem, onboard computer model subsystem, and postprocessor, is described. The simulator will be used to evaluate and test the attitude determination and control models to be used on board GRO under conditions that simulate the expected in-flight environment.

The Dynamics of Phonological Planning

ERIC Educational Resources Information Center

Roon, Kevin D.

2013-01-01

This dissertation proposes a dynamical computational model of the timecourse of phonological parameter setting. In the model, phonological representations embrace phonetic detail, with phonetic parameters represented as activation fields that evolve over time and determine the specific parameter settings of a planned utterance. Existing models of…

Matters of simulation of the semicircular canal system

NASA Technical Reports Server (NTRS)

Gurfinkel, V. S.; Petukhov, S. V.

1977-01-01

A scale model of the human semicircular canal system was developed based on the theory of dynamic similitude. This enlarged model makes it convenient to conduct tests on the vestibular processes and dynamics in the semicircular canals. Tests revealed hydromechanical interaction between canals, with asymmetry of the conditions of movement of the endolymph in the canals in opposite directions. A type of vestibular reactions, occurring with angular oscillations of the head, was predicted and demonstrated using this model and human test subjects.

Method and Application for Dynamic Comprehensive Evaluation with Subjective and Objective Information

PubMed Central

Liu, Dinglin; Zhao, Xianglian

2013-01-01

In an effort to deal with more complicated evaluation situations, scientists have focused their efforts on dynamic comprehensive evaluation research. How to make full use of the subjective and objective information has become one of the noteworthy content. In this paper, a dynamic comprehensive evaluation method with subjective and objective information is proposed. We use the combination weighting method to determine the index weight. Analysis hierarchy process method is applied to dispose the subjective information, and criteria importance through intercriteria correlation method is used to handle the objective information. And for the time weight determination, we consider both time distance and information size to embody the principle of esteeming the present over the past. And then the linear weighted average model is constructed to make the evaluation process more practicable. Finally, an example is presented to illustrate the effectiveness of this method. Overall, the results suggest that the proposed method is reasonable and effective. PMID:24386176

On use of characteristic wavelengths of track irregularities to predict track portions with deteriorated wheel/rail forces

NASA Astrophysics Data System (ADS)

Xu, Lei; Zhai, Wanming; Chen, Zhaowei

2018-05-01

The dynamic performance of the railway vehicles and the guiding tracks is mainly governed by the wheel-rail interactions, particularly in cases of track irregularities. In this work, a united model was developed to investigate the track portions subject to violent wheel/rail forces triggered by track irregularities at middle-low frequencies. In the modeling procedures, a time-frequency unification method combining wavelet transform and Wigner-Ville distribution for characterizing time-frequency characteristics of track irregularities and a three-dimensional nonlinear model for describing vehicle-track interaction signatures were developed and coupled, based on which the method for predicting track portions subject to deteriorated wheel/rail forces was proposed. The theoretical models developed in this paper were comprehensively validated by numerical investigations. The significance of this present study mainly lies on offering a new path to establish correlation and realize mutual prediction between track irregularity and railway system dynamics.

Identification of the numerical model of FEM in reference to measurements in situ

NASA Astrophysics Data System (ADS)

Jukowski, Michał; Bec, Jarosław; Błazik-Borowa, Ewa

2018-01-01

The paper deals with the verification of various numerical models in relation to the pilot-phase measurements of a rail bridge subjected to dynamic loading. Three types of FEM models were elaborated for this purpose. Static, modal and dynamic analyses were performed. The study consisted of measuring the acceleration values of the structural components of the object at the moment of the train passing. Based on this, FFT analysis was performed, the main natural frequencies of the bridge were determined, the structural damping ratio and the dynamic amplification factor (DAF) were calculated and compared with the standard values. Calculations were made using Autodesk Simulation Multiphysics (Algor).

Dynamics of financial crises in the world trade network

NASA Astrophysics Data System (ADS)

Askari, Marziyeh; Shirazi, Homayoun; Aghababaei Samani, Keivan

2018-07-01

A simple dynamical model is introduced to simulate the spreading of financial crises in the world trade network. In this model a directed network is constructed in which a weighted and directed link indicates the export value between two countries. The weights are subject to the change by a simple dynamical rule. The process begins with a crisis, i.e. a sudden decrease in the export value of a certain country and spreads throughout the whole network. We compare our results with the real values corresponding to the global financial crisis of 2008 and show that the results of our model are in good agreement with reality.

nmsBuilder: Freeware to create subject-specific musculoskeletal models for OpenSim.

PubMed

Valente, Giordano; Crimi, Gianluigi; Vanella, Nicola; Schileo, Enrico; Taddei, Fulvia

2017-12-01

Musculoskeletal modeling and simulations of movement have been increasingly used in orthopedic and neurological scenarios, with increased attention to subject-specific applications. In general, musculoskeletal modeling applications have been facilitated by the development of dedicated software tools; however, subject-specific studies have been limited also by time-consuming modeling workflows and high skilled expertise required. In addition, no reference tools exist to standardize the process of musculoskeletal model creation and make it more efficient. Here we present a freely available software application, nmsBuilder 2.0, to create musculoskeletal models in the file format of OpenSim, a widely-used open-source platform for musculoskeletal modeling and simulation. nmsBuilder 2.0 is the result of a major refactoring of a previous implementation that moved a first step toward an efficient workflow for subject-specific model creation. nmsBuilder includes a graphical user interface that provides access to all functionalities, based on a framework for computer-aided medicine written in C++. The operations implemented can be used in a workflow to create OpenSim musculoskeletal models from 3D surfaces. A first step includes data processing to create supporting objects necessary to create models, e.g. surfaces, anatomical landmarks, reference systems; and a second step includes the creation of OpenSim objects, e.g. bodies, joints, muscles, and the corresponding model. We present a case study using nmsBuilder 2.0: the creation of an MRI-based musculoskeletal model of the lower limb. The model included four rigid bodies, five degrees of freedom and 43 musculotendon actuators, and was created from 3D surfaces of the segmented images of a healthy subject through the modeling workflow implemented in the software application. We have presented nmsBuilder 2.0 for the creation of musculoskeletal OpenSim models from image-based data, and made it freely available via nmsbuilder.org. This application provides an efficient workflow for model creation and helps standardize the process. We hope this would help promote personalized applications in musculoskeletal biomechanics, including larger sample size studies, and might also represent a basis for future developments for specific applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Looking to Score: The Dissociation of Goal Influence on Eye Movement and Meta-Attentional Allocation in a Complex Dynamic Natural Scene

PubMed Central

Taya, Shuichiro; Windridge, David; Osman, Magda

2012-01-01

Several studies have reported that task instructions influence eye-movement behavior during static image observation. In contrast, during dynamic scene observation we show that while the specificity of the goal of a task influences observers’ beliefs about where they look, the goal does not in turn influence eye-movement patterns. In our study observers watched short video clips of a single tennis match and were asked to make subjective judgments about the allocation of visual attention to the items presented in the clip (e.g., ball, players, court lines, and umpire). However, before attending to the clips, observers were either told to simply watch clips (non-specific goal), or they were told to watch the clips with a view to judging which of the two tennis players was awarded the point (specific goal). The results of subjective reports suggest that observers believed that they allocated their attention more to goal-related items (e.g. court lines) if they performed the goal-specific task. However, we did not find the effect of goal specificity on major eye-movement parameters (i.e., saccadic amplitudes, inter-saccadic intervals, and gaze coherence). We conclude that the specificity of a task goal can alter observer’s beliefs about their attention allocation strategy, but such task-driven meta-attentional modulation does not necessarily correlate with eye-movement behavior. PMID:22768058

Characterization of mechanical properties of pseudoelastic shape memory alloys under harmonic excitation

NASA Astrophysics Data System (ADS)

Böttcher, J.; Jahn, M.; Tatzko, S.

2017-12-01

Pseudoelastic shape memory alloys exhibit a stress-induced phase transformation which leads to high strains during deformation of the material. The stress-strain characteristic during this thermomechanical process is hysteretic and results in the conversion of mechanical energy into thermal energy. This energy conversion allows for the use of shape memory alloys in vibration reduction. For the application of shape memory alloys as vibration damping devices a dynamic modeling of the material behavior is necessary. In this context experimentally determined material parameters which accurately represent the material behavior are essential for a reliable material model. Subject of this publication is the declaration of suitable material parameters for pseudoelastic shape memory alloys and the methodology of their identification from experimental investigations. The used test rig was specifically designed for the characterization of pseudoelastic shape memory alloys.

Simultaneous event-specific estimates of transport, loss, and source rates for relativistic outer radiation belt electrons: Event-Specific 1-D Modeling

DOE PAGES

Schiller, Q.; Tu, W.; Ali, A. F.; ...

2017-03-11

The most significant unknown regarding relativistic electrons in Earth’s outer Van Allen radiation belt is the relative contribution of loss, transport, and acceleration processes within the inner magnetosphere. Detangling each individual process is critical to improve the understanding of radiation belt dynamics, but determining a single component is challenging due to sparse measurements in diverse spatial and temporal regimes. However, there are currently an unprecedented number of spacecraft taking measurements that sample different regions of the inner magnetosphere. With the increasing number of varied observational platforms, system dynamics can begin to be unraveled. In this work, we employ in-situ measurementsmore » during the 13-14 January 2013 enhancement event to isolate transport, loss, and source dynamics in a one dimensional radial diffusion model. We then validate the results by comparing them to Van Allen Probes and THEMIS observations, indicating that the three terms have been accurately and individually quantified for the event. Finally, a direct comparison is performed between the model containing event-specific terms and various models containing terms parameterized by geomagnetic index. Models using a simple 3/Kp loss timescale show deviation from the event specific model of nearly two orders of magnitude within 72 hours of the enhancement event. However, models using alternative loss timescales closely resemble the event specific model.« less

Simultaneous event-specific estimates of transport, loss, and source rates for relativistic outer radiation belt electrons: Event-Specific 1-D Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiller, Q.; Tu, W.; Ali, A. F.

The most significant unknown regarding relativistic electrons in Earth’s outer Van Allen radiation belt is the relative contribution of loss, transport, and acceleration processes within the inner magnetosphere. Detangling each individual process is critical to improve the understanding of radiation belt dynamics, but determining a single component is challenging due to sparse measurements in diverse spatial and temporal regimes. However, there are currently an unprecedented number of spacecraft taking measurements that sample different regions of the inner magnetosphere. With the increasing number of varied observational platforms, system dynamics can begin to be unraveled. In this work, we employ in-situ measurementsmore » during the 13-14 January 2013 enhancement event to isolate transport, loss, and source dynamics in a one dimensional radial diffusion model. We then validate the results by comparing them to Van Allen Probes and THEMIS observations, indicating that the three terms have been accurately and individually quantified for the event. Finally, a direct comparison is performed between the model containing event-specific terms and various models containing terms parameterized by geomagnetic index. Models using a simple 3/Kp loss timescale show deviation from the event specific model of nearly two orders of magnitude within 72 hours of the enhancement event. However, models using alternative loss timescales closely resemble the event specific model.« less

Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing.

PubMed

Rekik, Islem; Li, Gang; Lin, Weili; Shen, Dinggang

2016-02-01

Longitudinal neuroimaging analysis methods have remarkably advanced our understanding of early postnatal brain development. However, learning predictive models to trace forth the evolution trajectories of both normal and abnormal cortical shapes remains broadly absent. To fill this critical gap, we pioneered the first prediction model for longitudinal developing cortical surfaces in infants using a spatiotemporal current-based learning framework solely from the baseline cortical surface. In this paper, we detail this prediction model and even further improve its performance by introducing two key variants. First, we use the varifold metric to overcome the limitations of the current metric for surface registration that was used in our preliminary study. We also extend the conventional varifold-based surface registration model for pairwise registration to a spatiotemporal surface regression model. Second, we propose a morphing process of the baseline surface using its topographic attributes such as normal direction and principal curvature sign. Specifically, our method learns from longitudinal data both the geometric (vertices positions) and dynamic (temporal evolution trajectories) features of the infant cortical surface, comprising a training stage and a prediction stage. In the training stage, we use the proposed varifold-based shape regression model to estimate geodesic cortical shape evolution trajectories for each training subject. We then build an empirical mean spatiotemporal surface atlas. In the prediction stage, given an infant, we select the best learnt features from training subjects to simultaneously predict the cortical surface shapes at all later timepoints, based on similarity metrics between this baseline surface and the learnt baseline population average surface atlas. We used a leave-one-out cross validation method to predict the inner cortical surface shape at 3, 6, 9 and 12 months of age from the baseline cortical surface shape at birth. Our method attained a higher prediction accuracy and better captured the spatiotemporal dynamic change of the highly folded cortical surface than the previous proposed prediction method. Copyright © 2015 Elsevier B.V. All rights reserved.

Opinion Formation by Social Influence: From Experiments to Modeling

PubMed Central

Chacoma, Andrés; Zanette, Damián H.

2015-01-01

Predicting different forms of collective behavior in human populations, as the outcome of individual attitudes and their mutual influence, is a question of major interest in social sciences. In particular, processes of opinion formation have been theoretically modeled on the basis of a formal similarity with the dynamics of certain physical systems, giving rise to an extensive collection of mathematical models amenable to numerical simulation or even to exact solution. Empirical ground for these models is however largely missing, which confine them to the level of mere metaphors of the real phenomena they aim at explaining. In this paper we present results of an experiment which quantifies the change in the opinions given by a subject on a set of specific matters under the influence of others. The setup is a variant of a recently proposed experiment, where the subject’s confidence on his or her opinion was evaluated as well. In our realization, which records the quantitative answers of 85 subjects to 20 questions before and after an influence event, the focus is put on characterizing the change in answers and confidence induced by such influence. Similarities and differences with the previous version of the experiment are highlighted. We find that confidence changes are to a large extent independent of any other recorded quantity, while opinion changes are strongly modulated by the original confidence. On the other hand, opinion changes are not influenced by the initial difference with the reference opinion. The typical time scales on which opinion varies are moreover substantially longer than those of confidence change. Experimental results are then used to estimate parameters for a dynamical agent-based model of opinion formation in a large population. In the context of the model, we study the convergence to full consensus and the effect of opinion leaders on the collective distribution of opinions. PMID:26517825

A general science-based framework for dynamical spatio-temporal models

USGS Publications Warehouse

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

Peripheral erythrocytes decrease upon specific respiratory challenge with grass pollen allergen in sensitized mice and in human subjects.

PubMed

Jordakieva, Galateja; Wallmann, Julia; Schmutz, René; Lemell, Patrick; Wegmann, Michael; Nittke, Thomas; Mittlböck, Martina; Fehrenbach, Heinz; Godnic-Cvar, Jasminka; Zieglmayer, René; Jensen-Jarolim, Erika

2014-01-01

Specific hyper-responsiveness towards an allergen and non-specific airway hyperreactivity both impair quality of life in patients with respiratory allergic diseases. We aimed to investigate cellular responses following specific and non-specific airway challenges locally and systemically in i) sensitized BALB/c mice challenged with grass pollen allergen Phl p 5, and in ii) grass pollen sensitized allergic rhinitis subjects undergoing specific airway challenge in the Vienna Challenge Chamber (VCC). BALB/c mice (n = 20) were intraperitoneally immunized with grass pollen allergen Phl p 5 and afterwards aerosol challenged with either the specific allergen Phl p 5 (n = 10) or the non-specific antigen ovalbumin (OVA) (n = 10). A protocol for inducing allergic asthma as well as allergic rhinitis, according to the united airway concept, was used. Both groups of exposed mice showed significantly reduced physical activity after airway challenge. Specific airway challenge further resulted in goblet cell hyperplasia, enhanced mucous secretion, intrapulmonary leukocyte infiltration and lymphoid follicle formation, associated with significant expression of IL-4, IL-5 and IL-13 in splenocytes and also partially in lung tissue. Concerning circulating blood cell dynamics, we observed a significant drop of erythrocyte counts, hemoglobin and hematocrit levels in both mouse groups, challenged with allergen or OVA. A significant decrease in circulating erythrocytes and hematocrit levels after airway challenges with grass pollen allergen was also found in grass pollen sensitized human rhinitis subjects (n = 42) at the VCC. The effects on peripheral leukocyte counts in mice and humans however were opposed, possibly due to the different primary inflammation sites. Our data revealed that, besides significant leukocyte dynamics, particularly erythrocytes are involved in acute hypersensitivity reactions to respiratory allergens. A rapid recruitment of erythrocytes to the lungs to compensate for hypoxia is a possible explanation for these findings.

Non-Deterministic Dynamic Instability of Composite Shells

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2004-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics, and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties, in that order.

Dynamic Probabilistic Instability of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2009-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties in that order.

Clinically Anxious Individuals Show Disrupted Feedback between Inferior Frontal Gyrus and Prefrontal-Limbic Control Circuit.

PubMed

Cha, Jiook; DeDora, Daniel; Nedic, Sanja; Ide, Jaime; Greenberg, Tsafrir; Hajcak, Greg; Mujica-Parodi, Lilianne Rivka

2016-04-27

Clinical anxiety is associated with generalization of conditioned fear, in which innocuous stimuli elicit alarm. Using Pavlovian fear conditioning (electric shock), we quantify generalization as the degree to which subjects' neurobiological responses track perceptual similarity gradients to a conditioned stimulus. Previous studies show that the ventromedial prefrontal cortex (vmPFC) inversely and ventral tegmental area directly track the gradient of perceptual similarity to the conditioned stimulus in healthy individuals, whereas clinically anxious individuals fail to discriminate. Here, we extend this work by identifying specific functional roles within the prefrontal-limbic circuit. We analyzed fMRI time-series acquired from 57 human subjects during a fear generalization task using entropic measures of circuit-wide regulation and feedback (power spectrum scale invariance/autocorrelation), in combination with structural (diffusion MRI-probabilistic tractography) and functional (stochastic dynamic causal modeling) measures of prefrontal-limbic connectivity within the circuit. Group comparison and correlations with anxiety severity across 57 subjects revealed dysregulatory dynamic signatures within the inferior frontal gyrus (IFG), which our prior work has linked to impaired feedback within the circuit. Bayesian model selection then identified a fully connected prefrontal-limbic model comprising the IFG, vmPFC, and amygdala. Dysregulatory IFG dynamics were associated with weaker reciprocal excitatory connectivity between the IFG and the vmPFC. The vmPFC exhibited inhibitory influence on the amygdala. Our current results, combined with our previous work across a threat-perception spectrum of 137 subjects and a meta-analysis of 366 fMRI studies, dissociate distinct roles for three prefrontal-limbic regions, wherein the IFG provides evaluation of stimulus meaning, which then informs the vmPFC in inhibiting the amygdala. Affective neuroscience has generally treated prefrontal regions (orbitofrontal cortex, dorsolateral prefrontal cortex, inferior frontal gyrus, ventromedial prefrontal cortex) equivalently as inhibitory components of the prefrontal-limbic system. Yet research across the anxiety spectrum suggests that the inferior frontal gyrus may have a more complex role in emotion regulation, as this region shows abnormal function in disorders of both hyperarousal and hypoarousal. Using entropic measures of circuit-wide regulation and feedback, in combination with measures of structural and functional connectivity, we dissociate distinct roles for three prefrontal-limbic regions, wherein the inferior frontal gyrus provides evaluation of stimulus meaning, which then informs the ventromedial prefrontal cortex in inhibiting the amygdala. This reconfiguration coheres with studies of conceptual disambiguation also implicating the inferior frontal gyrus. Copyright © 2016 the authors 0270-6474/16/364708-11$15.00/0.

Bayesian model reduction and empirical Bayes for group (DCM) studies.

PubMed

Friston, Karl J; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E; van Wijk, Bernadette C M; Ziegler, Gabriel; Zeidman, Peter

2016-03-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Bayesian inference in an extended SEIR model with nonparametric disease transmission rate: an application to the Ebola epidemic in Sierra Leone.

PubMed

Frasso, Gianluca; Lambert, Philippe

2016-10-01

SummaryThe 2014 Ebola outbreak in Sierra Leone is analyzed using a susceptible-exposed-infectious-removed (SEIR) epidemic compartmental model. The discrete time-stochastic model for the epidemic evolution is coupled to a set of ordinary differential equations describing the dynamics of the expected proportions of subjects in each epidemic state. The unknown parameters are estimated in a Bayesian framework by combining data on the number of new (laboratory confirmed) Ebola cases reported by the Ministry of Health and prior distributions for the transition rates elicited using information collected by the WHO during the follow-up of specific Ebola cases. The time-varying disease transmission rate is modeled in a flexible way using penalized B-splines. Our framework represents a valuable stochastic tool for the study of an epidemic dynamic even when only irregularly observed and possibly aggregated data are available. Simulations and the analysis of the 2014 Sierra Leone Ebola data highlight the merits of the proposed methodology. In particular, the flexible modeling of the disease transmission rate makes the estimation of the effective reproduction number robust to the misspecification of the initial epidemic states and to underreporting of the infectious cases. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Human-robot cooperative movement training: learning a novel sensory motor transformation during walking with robotic assistance-as-needed.

PubMed

Emken, Jeremy L; Benitez, Raul; Reinkensmeyer, David J

2007-03-28

A prevailing paradigm of physical rehabilitation following neurologic injury is to "assist-as-needed" in completing desired movements. Several research groups are attempting to automate this principle with robotic movement training devices and patient cooperative algorithms that encourage voluntary participation. These attempts are currently not based on computational models of motor learning. Here we assume that motor recovery from a neurologic injury can be modelled as a process of learning a novel sensory motor transformation, which allows us to study a simplified experimental protocol amenable to mathematical description. Specifically, we use a robotic force field paradigm to impose a virtual impairment on the left leg of unimpaired subjects walking on a treadmill. We then derive an "assist-as-needed" robotic training algorithm to help subjects overcome the virtual impairment and walk normally. The problem is posed as an optimization of performance error and robotic assistance. The optimal robotic movement trainer becomes an error-based controller with a forgetting factor that bounds kinematic errors while systematically reducing its assistance when those errors are small. As humans have a natural range of movement variability, we introduce an error weighting function that causes the robotic trainer to disregard this variability. We experimentally validated the controller with ten unimpaired subjects by demonstrating how it helped the subjects learn the novel sensory motor transformation necessary to counteract the virtual impairment, while also preventing them from experiencing large kinematic errors. The addition of the error weighting function allowed the robot assistance to fade to zero even though the subjects' movements were variable. We also show that in order to assist-as-needed, the robot must relax its assistance at a rate faster than that of the learning human. The assist-as-needed algorithm proposed here can limit error during the learning of a dynamic motor task. The algorithm encourages learning by decreasing its assistance as a function of the ongoing progression of movement error. This type of algorithm is well suited for helping people learn dynamic tasks for which large kinematic errors are dangerous or discouraging, and thus may prove useful for robot-assisted movement training of walking or reaching following neurologic injury.

Mode-Specific SN2 Reaction Dynamics.

PubMed

Wang, Yan; Song, Hongwei; Szabó, István; Czakó, Gábor; Guo, Hua; Yang, Minghui

2016-09-01

Despite its importance in chemistry, the microscopic dynamics of bimolecular nucleophilic substitution (SN2) reactions is still not completely elucidated. In this publication, the dynamics of a prototypical SN2 reaction (F(-) + CH3Cl → CH3F + Cl(-)) is investigated using a high-dimensional quantum mechanical model on an accurate potential energy surface (PES) and further analyzed by quasi-classical trajectories on the same PES. While the indirect mechanism dominates at low collision energies, the direct mechanism makes a significant contribution. The reactivity is found to depend on the specific reactant vibrational mode excitation. The mode specificity, which is more prevalent in the direct reaction, is rationalized by a transition-state-based model.

Parkinsonian Balance Deficits Quantified Using a Game Industry Board and a Specific Battery of Four Paradigms.

PubMed

Darbin, Olivier; Gubler, Coral; Naritoku, Dean; Dees, Daniel; Martino, Anthony; Adams, Elizabeth

2016-01-01

This study describes a cost-effective screening protocol for parkinsonism based on combined objective and subjective monitoring of balance function. Objective evaluation of balance function was performed using a game industry balance board and an automated analyses of the dynamic of the center of pressure in time, frequency, and non-linear domains collected during short series of stand up tests with different modalities and severity of sensorial deprivation. The subjective measurement of balance function was performed using the Dizziness Handicap Inventory questionnaire. Principal component analyses on both objective and subjective measurements of balance function allowed to obtained a specificity and selectivity for parkinsonian patients (vs. healthy subjects) of 0.67 and 0.71 respectively. The findings are discussed regarding the relevance of cost-effective balance-based screening system as strategy to meet the needs of broader and earlier screening for parkinsonism in communities with limited access to healthcare.

Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation.

PubMed

Meadows, Adam L; Karnik, Rahi; Lam, Harry; Forestell, Sean; Snedecor, Brad

2010-03-01

We have developed a reactor-scale model of Escherichia coli metabolism and growth in a 1000 L process for the production of a recombinant therapeutic protein. The model consists of two distinct parts: (1) a dynamic, process specific portion that describes the time evolution of 37 process variables of relevance and (2) a flux balance based, 123-reaction metabolic model of E. coli metabolism. This model combines several previously reported modeling approaches including a growth rate-dependent biomass composition, maximum growth rate objective function, and dynamic flux balancing. In addition, we introduce concentration-dependent boundary conditions of transport fluxes, dynamic maintenance demands, and a state-dependent cellular objective. This formulation was able to describe specific runs with high-fidelity over process conditions including rich media, simultaneous acetate and glucose consumption, glucose minimal media, and phosphate depleted media. Furthermore, the model accurately describes the effect of process perturbations--such as glucose overbatching and insufficient aeration--on growth, metabolism, and titer. (c) 2009 Elsevier Inc. All rights reserved.

EEG-based emotion recognition in music listening.

PubMed

Lin, Yuan-Pin; Wang, Chi-Hong; Jung, Tzyy-Ping; Wu, Tien-Lin; Jeng, Shyh-Kang; Duann, Jeng-Ren; Chen, Jyh-Horng

2010-07-01

Ongoing brain activity can be recorded as electroencephalograph (EEG) to discover the links between emotional states and brain activity. This study applied machine-learning algorithms to categorize EEG dynamics according to subject self-reported emotional states during music listening. A framework was proposed to optimize EEG-based emotion recognition by systematically 1) seeking emotion-specific EEG features and 2) exploring the efficacy of the classifiers. Support vector machine was employed to classify four emotional states (joy, anger, sadness, and pleasure) and obtained an averaged classification accuracy of 82.29% +/- 3.06% across 26 subjects. Further, this study identified 30 subject-independent features that were most relevant to emotional processing across subjects and explored the feasibility of using fewer electrodes to characterize the EEG dynamics during music listening. The identified features were primarily derived from electrodes placed near the frontal and the parietal lobes, consistent with many of the findings in the literature. This study might lead to a practical system for noninvasive assessment of the emotional states in practical or clinical applications.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin

PubMed Central

Fuchs, Julian E.; Huber, Roland G.; Waldner, Birgit J.; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R.

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm “dynamics govern specificity” might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design. PMID:26496636

Patient specific CFD models of nasal airflow: overview of methods and challenges.

PubMed

Kim, Sung Kyun; Na, Yang; Kim, Jee-In; Chung, Seung-Kyu

2013-01-18

Respiratory physiology and pathology are strongly dependent on the airflow inside the nasal cavity. However, the nasal anatomy, which is characterized by complex airway channels and significant individual differences, is difficult to analyze. Thus, commonly adopted diagnostic tools have yielded limited success. Nevertheless, with the rapid advances in computer resources, there have been more elaborate attempts to correlate airflow characteristics in human nasal airways with the symptoms and functions of the nose by computational fluid dynamics study. Furthermore, the computed nasal geometry can be virtually modified to reflect predicted results of the proposed surgical technique. In this article, several computational fluid mechanics (CFD) issues on patient-specific three dimensional (3D) modeling of nasal cavity and clinical applications were reviewed in relation to the cases of deviated nasal septum (decision for surgery), turbinectomy, and maxillary sinus ventilation (simulated- and post-surgery). Clinical relevance of fluid mechanical parameters, such as nasal resistance, flow allocation, wall shear stress, heat/humidity/NO gas distributions, to the symptoms and surgical outcome were discussed. Absolute values of such parameters reported by many research groups were different each other due to individual difference of nasal anatomy, the methodology for 3D modeling and numerical grid, laminar/turbulent flow model in CFD code. But, the correlation of these parameters to symptoms and surgery outcome seems to be obvious in each research group with subject-specific models and its variations (virtual- and post-surgery models). For the more reliable, patient-specific, and objective tools for diagnosis and outcomes of nasal surgery by using CFD, the future challenges will be the standardizations on the methodology for creating 3D airway models and the CFD procedures. Copyright © 2012 Elsevier Ltd. All rights reserved.

Understanding the complexity of human gait dynamics

NASA Astrophysics Data System (ADS)

Scafetta, Nicola; Marchi, Damiano; West, Bruce J.

2009-06-01

Time series of human gait stride intervals exhibit fractal and multifractal properties under several conditions. Records from subjects walking at normal, slow, and fast pace speed are analyzed to determine changes in the fractal scalings as a function of the stress condition of the system. Records from subjects with different age from children to elderly and patients suffering from neurodegenerative disease are analyzed to determine changes in the fractal scalings as a function of the physical maturation or degeneration of the system. A supercentral pattern generator model is presented to simulate the above two properties that are typically found in dynamical network performance: that is, how a dynamical network responds to stress and to evolution.

Temporal Dynamics Assessment of Spatial Overlap Pattern of Functional Brain Networks Reveals Novel Functional Architecture of Cerebral Cortex.

PubMed

Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhao, Shijie; Zhang, Shu; Zhang, Wei; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2018-06-01

Various studies in the brain mapping field have demonstrated that there exist multiple concurrent functional networks that are spatially overlapped and interacting with each other during specific task performance to jointly realize the total brain function. Assessing such spatial overlap patterns of functional networks (SOPFNs) based on functional magnetic resonance imaging (fMRI) has thus received increasing interest for brain function studies. However, there are still two crucial issues to be addressed. First, the SOPFNs are assessed over the entire fMRI scan assuming the temporal stationarity, while possibly time-dependent dynamics of the SOPFNs is not sufficiently explored. Second, the SOPFNs are assessed within individual subjects, while group-wise consistency of the SOPFNs is largely unknown. To address the two issues, we propose a novel computational framework of group-wise sparse representation of whole-brain fMRI temporal segments to assess the temporal dynamic spatial patterns of SOPFNs that are consistent across different subjects. Experimental results based on the recently publicly released Human Connectome Project grayordinate task fMRI data demonstrate that meaningful SOPFNs exhibiting dynamic spatial patterns across different time periods are effectively and robustly identified based on the reconstructed concurrent functional networks via the proposed framework. Specifically, those SOPFNs locate significantly more on gyral regions than on sulcal regions across different time periods. These results reveal novel functional architecture of cortical gyri and sulci. Moreover, these results help better understand functional dynamics mechanisms of cerebral cortex in the future.

THREE-DIMENSIONAL MODELING OF THE DYNAMICS OF THERAPEUTIC ULTRASOUND CONTRAST AGENTS

PubMed Central

Hsiao, Chao-Tsung; Lu, Xiaozhen; Chahine, Georges

2010-01-01

A 3-D thick-shell contrast agent dynamics model was developed by coupling a finite volume Navier-Stokes solver and a potential boundary element method flow solver to simulate the dynamics of thick-shelled contrast agents subjected to pressure waves. The 3-D model was validated using a spherical thick-shell model validated by experimental observations. We then used this model to study shell break-up during nonspherical deformations resulting from multiple contrast agent interaction or the presence of a nearby solid wall. Our simulations indicate that the thick viscous shell resists the contrast agent from forming a re-entrant jet, as normally observed for an air bubble oscillating near a solid wall. Instead, the shell thickness varies significantly from location to location during the dynamics, and this could lead to shell break-up caused by local shell thinning and stretching. PMID:20950929

Asymptotic dynamics of some t-periodic one-dimensional model with application to prostate cancer immunotherapy.

PubMed

Foryś, U; Bodnar, M; Kogan, Y

2016-10-01

In the case of some specific cancers, immunotherapy is one of the possible treatments that can be considered. Our study is based on a mathematical model of patient-specific immunotherapy proposed in Kronik et al. (PLoS One 5(12):e15,482, 2010). This model was validated for clinical trials presented in Michael et al. (Clin Cancer Res 11(12):4469-4478, 2005). It consists of seven ordinary differential equations and its asymptotic dynamics can be described by some t-periodic one-dimensional dynamical system. In this paper we propose a generalised version of this t-periodic system and study the dynamics of the proposed model. We show that there are three possible types of the model behaviour: the solution either converges to zero, or diverges to infinity, or it is periodic. Moreover, the periodic solution is unique, and it divides the phase space into two sub-regions. The general results are applied to the PC specific case, which allow to derive conditions guaranteeing successful as well as unsuccessful treatment. The results indicate that a single vaccination is not sufficient to cure the cancer.

Model of chromosomal loci dynamics in bacteria as fractional diffusion with intermittent transport

NASA Astrophysics Data System (ADS)

Gherardi, Marco; Calabrese, Ludovico; Tamm, Mikhail; Cosentino Lagomarsino, Marco

2017-10-01

The short-time dynamics of bacterial chromosomal loci is a mixture of subdiffusive and active motion, in the form of rapid relocations with near-ballistic dynamics. While previous work has shown that such rapid motions are ubiquitous, we still have little grasp on their physical nature, and no positive model is available that describes them. Here, we propose a minimal theoretical model for loci movements as a fractional Brownian motion subject to a constant but intermittent driving force, and compare simulations and analytical calculations to data from high-resolution dynamic tracking in E. coli. This analysis yields the characteristic time scales for intermittency. Finally, we discuss the possible shortcomings of this model, and show that an increase in the effective local noise felt by the chromosome associates to the active relocations.

Bubble Dynamics and Resulting Noise from Traveling Bubble Cavitation.

DTIC Science & Technology

1982-04-13

proportional to the gas content. The subjectivity of visual cavitation determination is evidenced by the maximum standard deviation. As mentioned before...bubble radii at the maximum radius position on the model. The point on the model where the bubble will be at its maximum volume was determined by...48 3.7 Recording Bubble Dynamics . • . * . . . . 52 3.8 Measurement of Gas Nuclei in Water 0 • 52 3 TABLE OF CONTENTS (continued) Paqe

OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange

PubMed Central

Seth, Ajay; Sherman, Michael; Reinbolt, Jeffrey A.; Delp, Scott L.

2015-01-01

Movement science is driven by observation, but observation alone cannot elucidate principles of human and animal movement. Biomechanical modeling and computer simulation complement observations and inform experimental design. Biological models are complex and specialized software is required for building, validating, and studying them. Furthermore, common access is needed so that investigators can contribute models to a broader community and leverage past work. We are developing OpenSim, a freely available musculoskeletal modeling and simulation application and libraries specialized for these purposes, by providing: musculoskeletal modeling elements, such as biomechanical joints, muscle actuators, ligament forces, compliant contact, and controllers; and tools for fitting generic models to subject-specific data, performing inverse kinematics and forward dynamic simulations. OpenSim performs an array of physics-based analyses to delve into the behavior of musculoskeletal models by employing Simbody, an efficient and accurate multibody system dynamics code. Models are publicly available and are often reused for multiple investigations because they provide a rich set of behaviors that enables different lines of inquiry. This report will discuss one model developed to study walking and applied to gain deeper insights into muscle function in pathological gait and during running. We then illustrate how simulations can test fundamental hypotheses and focus the aims of in vivo experiments, with a postural stability platform and human model that provide a research environment for performing human posture experiments in silico. We encourage wide adoption of OpenSim for community exchange of biomechanical models and methods and welcome new contributors. PMID:25893160

Walking Ahead: The Headed Social Force Model.

PubMed

Farina, Francesco; Fontanelli, Daniele; Garulli, Andrea; Giannitrapani, Antonio; Prattichizzo, Domenico

2017-01-01

Human motion models are finding an increasing number of novel applications in many different fields, such as building design, computer graphics and robot motion planning. The Social Force Model is one of the most popular alternatives to describe the motion of pedestrians. By resorting to a physical analogy, individuals are assimilated to point-wise particles subject to social forces which drive their dynamics. Such a model implicitly assumes that humans move isotropically. On the contrary, empirical evidence shows that people do have a preferred direction of motion, walking forward most of the time. Lateral motions are observed only in specific circumstances, such as when navigating in overcrowded environments or avoiding unexpected obstacles. In this paper, the Headed Social Force Model is introduced in order to improve the realism of the trajectories generated by the classical Social Force Model. The key feature of the proposed approach is the inclusion of the pedestrians' heading into the dynamic model used to describe the motion of each individual. The force and torque representing the model inputs are computed as suitable functions of the force terms resulting from the traditional Social Force Model. Moreover, a new force contribution is introduced in order to model the behavior of people walking together as a single group. The proposed model features high versatility, being able to reproduce both the unicycle-like trajectories typical of people moving in open spaces and the point-wise motion patterns occurring in high density scenarios. Extensive numerical simulations show an increased regularity of the resulting trajectories and confirm a general improvement of the model realism.

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging

PubMed Central

Hsu, Vivian M.; Wes, Ari M.; Tahiri, Youssef; Cornman-Homonoff, Joshua

2014-01-01

Background: The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Methods: Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. Results: The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). Conclusions: This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time. PMID:25426394

Analysis of structural dynamic data from Skylab. Volume 1: Technical discussion

NASA Technical Reports Server (NTRS)

Demchak, L.; Harcrow, H.

1976-01-01

The results of a study to analyze data and document dynamic program highlights of the Skylab Program are presented. Included are structural model sources, illustration of the analytical models, utilization of models and the resultant derived data, data supplied to organization and subsequent utilization, and specifications of model cycles.

Learning a stick-balancing task involves task-specific coupling between posture and hand displacements.

PubMed

Cluff, Tyler; Boulet, Jason; Balasubramaniam, Ramesh

2011-08-01

Theories of motor learning argue that the acquisition of novel motor skills requires a task-specific organization of sensory and motor subsystems. We examined task-specific coupling between motor subsystems as subjects learned a novel stick-balancing task. We focused on learning-induced changes in finger movements and body sway and investigated the effect of practice on their coupling. Eight subjects practiced balancing a cylindrical wooden stick for 30 min a day during a 20 day learning period. Finger movements and center of pressure trajectories were recorded in every fifth practice session (4 in total) using a ten camera VICON motion capture system interfaced with two force platforms. Motor learning was quantified using average balancing trial lengths, which increased with practice and confirmed that subjects learned the task. Nonlinear time series and phase space reconstruction methods were subsequently used to investigate changes in the spatiotemporal properties of finger movements, body sway and their progressive coupling. Systematic increases in subsystem coupling were observed despite reduced autocorrelation and differences in the temporal properties of center of pressure and finger trajectories. The average duration of these coupled trajectories increased systematically across the learning period. In short, the abrupt transition between coupled and decoupled subsystem dynamics suggested that stick balancing is regulated by a hierarchical control mechanism that switches from collective to independent control of the finger and center of pressure. In addition to traditional measures of motor performance, dynamical analyses revealed changes in motor subsystem organization that occurred when subjects learned a novel stick-balancing task.

Inspiration & Insight - a tribute to Niels Reeh

NASA Astrophysics Data System (ADS)

Ahlstrom, A. P.; Vieli, A.

2009-12-01

Niels Reeh was highly regarded for his contributions to glaciology, specifically through his rigorous combination of numerical modelling and field observations. In 1966 he began his work on the application of beam mechanics to floating glaciers and ice shelves and throughout his life, Niels retained a strong interest in modelling glacier dynamics. In the early 1980s Niels developed a 3D-model for ice sheets and in the late 1980s an advanced flow-line model. Niels Reeh also took part in the early ice-core drilling efforts in Greenland and later pioneered the concept of retrieving similar records from the surface of the ice-sheet margin. Mass balance of glaciers and ice sheets was another theme in Niels Reeh’s research, with a number of important contributions and insights still used when teaching the subject to students. Niels developed elegant models for ablation and snow densification, notable for their applicability in large-scale ice-sheet models and studied the impact of climate change on ice sheets and glaciers. Niels also took his interest in ice-dynamics and mass balance into remote sensing and worked successfully on methods to utilize radar and laser data from airborne surveys and satellites in glaciology. In this, he pioneered the combination of field experiments, satellite observations and numerical modelling to solve problems on the Greenland Ice Sheet. In this presentation we will attempt to provide an overview of Niels Reeh’s many-facetted career in acknowledgement of his contributions to the field of glaciology.

Membership status and subjective group dynamics: who triggers the black sheep effect?

PubMed

Pinto, Isabel R; Marques, José M; Levine, John M; Abrams, Dominic

2010-07-01

In 3 experiments, participants (Ns = 50, 95, and 75, respectively) judged 2 ingroup or outgroup members who occupied 1 of 3 statuses--new members, full members, or marginal members. In each case, 1 of these members adopted a normative position and another supported a deviant position regarding a relevant issue. Participants upgraded normative ingroup full members and derogated deviant ingroup full members compared with all other members. In addition, derogation of deviant ingroup members was associated with a socializing and a punishing intention toward new members and full members, respectively. These results are discussed in terms of the group socialization model (e.g., Levine & Moreland, 1994) and the subjective group dynamics model (e.g., Marques, Paez, & Abrams, 1998).

Subject-based discriminative sparse representation model for detection of concealed information.

PubMed

Akhavan, Amir; Moradi, Mohammad Hassan; Vand, Safa Rafiei

2017-05-01

The use of machine learning approaches in concealed information test (CIT) plays a key role in the progress of this neurophysiological field. In this paper, we presented a new machine learning method for CIT in which each subject is considered independent of the others. The main goal of this study is to adapt the discriminative sparse models to be applicable for subject-based concealed information test. In order to provide sufficient discriminability between guilty and innocent subjects, we introduced a novel discriminative sparse representation model and its appropriate learning methods. For evaluation of the method forty-four subjects participated in a mock crime scenario and their EEG data were recorded. As the model input, in this study the recurrence plot features were extracted from single trial data of different stimuli. Then the extracted feature vectors were reduced using statistical dependency method. The reduced feature vector went through the proposed subject-based sparse model in which the discrimination power of sparse code and reconstruction error were applied simultaneously. Experimental results showed that the proposed approach achieved better performance than other competing discriminative sparse models. The classification accuracy, sensitivity and specificity of the presented sparsity-based method were about 93%, 91% and 95% respectively. Using the EEG data of a single subject in response to different stimuli types and with the aid of the proposed discriminative sparse representation model, one can distinguish guilty subjects from innocent ones. Indeed, this property eliminates the necessity of several subject EEG data in model learning and decision making for a specific subject. Copyright © 2017 Elsevier B.V. All rights reserved.

A multi-segment foot model based on anatomically registered technical coordinate systems: method repeatability and sensitivity in pediatric planovalgus feet.

PubMed

Saraswat, Prabhav; MacWilliams, Bruce A; Davis, Roy B; D'Astous, Jacques L

2013-01-01

Several multisegment foot models have been proposed and some have been used to study foot pathologies. These models have been tested and validated on typically developed populations; however application of such models to feet with significant deformities presents an additional set of challenges. For the first time, in this study, a multisegment foot model is tested for repeatability in a population of children with symptomatic abnormal feet. The results from this population are compared to the same metrics collected from an age matched (8-14 years) typically developing population. The modified Shriners Hospitals for Children, Greenville (mSHCG) foot model was applied to ten typically developing children and eleven children with planovalgus feet by two clinicians. Five subjects in each group were retested by both clinicians after 4-6 weeks. Both intra-clinician and inter-clinician repeatability were evaluated using static and dynamic measures. A plaster mold method was used to quantify variability arising from marker placement error. Dynamic variability was measured by examining trial differences from the same subjects when multiple clinicians carried out the data collection multiple times. For hindfoot and forefoot angles, static and dynamic variability in both groups was found to be less than 4° and 6° respectively. The mSHCG model strategy of minimal reliance on anatomical markers for dynamic measures and inherent flexibility enabled by separate anatomical and technical coordinate systems resulted in a model equally repeatable in typically developing and planovalgus populations. Copyright © 2012 Elsevier B.V. All rights reserved.

Interactive Structure (EUCLID) For Static And Dynamic Representation Of Human Body

NASA Astrophysics Data System (ADS)

Renaud, Ch.; Steck, R.

1983-07-01

A specific software (EUCLID) for static and dynamic representation of human models is described. The data processing system is connected with ERGODATA and used in interactive mode by intrinsic or specific functions. More or less complex representations in 3-D view of models of the human body are developed. Biostereometric and conventional anthropometric raw data from the data bank are processed for different applications in ergonomy.

Learning-based deformable image registration for infant MR images in the first year of life.

PubMed

Hu, Shunbo; Wei, Lifang; Gao, Yaozong; Guo, Yanrong; Wu, Guorong; Shen, Dinggang

2017-01-01

Many brain development studies have been devoted to investigate dynamic structural and functional changes in the first year of life. To quantitatively measure brain development in such a dynamic period, accurate image registration for different infant subjects with possible large age gap is of high demand. Although many state-of-the-art image registration methods have been proposed for young and elderly brain images, very few registration methods work for infant brain images acquired in the first year of life, because of (a) large anatomical changes due to fast brain development and (b) dynamic appearance changes due to white-matter myelination. To address these two difficulties, we propose a learning-based registration method to not only align the anatomical structures but also alleviate the appearance differences between two arbitrary infant MR images (with large age gap) by leveraging the regression forest to predict both the initial displacement vector and appearance changes. Specifically, in the training stage, two regression models are trained separately, with (a) one model learning the relationship between local image appearance (of one development phase) and its displacement toward the template (of another development phase) and (b) another model learning the local appearance changes between the two brain development phases. Then, in the testing stage, to register a new infant image to the template, we first predict both its voxel-wise displacement and appearance changes by the two learned regression models. Since such initializations can alleviate significant appearance and shape differences between new infant image and the template, it is easy to just use a conventional registration method to refine the remaining registration. We apply our proposed registration method to align 24 infant subjects at five different time points (i.e., 2-week-old, 3-month-old, 6-month-old, 9-month-old, and 12-month-old), and achieve more accurate and robust registration results, compared to the state-of-the-art registration methods. The proposed learning-based registration method addresses the challenging task of registering infant brain images and achieves higher registration accuracy compared with other counterpart registration methods. © 2016 American Association of Physicists in Medicine.

Error-enhancing robot therapy to induce motor control improvement in childhood onset primary dystonia.

PubMed

Casellato, Claudia; Pedrocchi, Alessandra; Zorzi, Giovanna; Rizzi, Giorgio; Ferrigno, Giancarlo; Nardocci, Nardo

2012-07-23

Robot-generated deviating forces during multijoint reaching movements have been applied to investigate motor control and to tune neuromotor adaptation. Can the application of force to limbs improve motor learning? In this framework, the response to altered dynamic environments of children affected by primary dystonia has never been studied. As preliminary pilot study, eleven children with primary dystonia and eleven age-matched healthy control subjects were asked to perform upper limb movements, triangle-reaching (three directions) and circle-writing, using a haptic robot interacting with ad-hoc developed task-specific visual interfaces. Three dynamic conditions were provided, null additive external force (A), constant disturbing force (B) and deactivation of the additive external force again (C). The path length for each trial was computed, from the recorded position data and interaction events. The results show that the disturbing force affects significantly the movement outcomes in healthy but not in dystonic subjects, already compromised in the reference condition: the external alteration uncalibrates the healthy sensorimotor system, while the dystonic one is already strongly uncalibrated. The lack of systematic compensation for perturbation effects during B condition is reflected into the absence of after-effects in C condition, which would be the evidence that CNS generates a prediction of the perturbing forces using an internal model of the environment.The most promising finding is that in dystonic population the altered dynamic exposure seems to induce a subsequent improvement, i.e. a beneficial after-effect in terms of optimal path control, compared with the correspondent reference movement outcome. The short-time error-enhancing training in dystonia could represent an effective approach for motor performance improvement, since the exposure to controlled dynamic alterations induces a refining of the existing but strongly imprecise motor scheme and sensorimotor patterns.

Error-enhancing robot therapy to induce motor control improvement in childhood onset primary dystonia

PubMed Central

2012-01-01

Background Robot-generated deviating forces during multijoint reaching movements have been applied to investigate motor control and to tune neuromotor adaptation. Can the application of force to limbs improve motor learning? In this framework, the response to altered dynamic environments of children affected by primary dystonia has never been studied. Methods As preliminary pilot study, eleven children with primary dystonia and eleven age-matched healthy control subjects were asked to perform upper limb movements, triangle-reaching (three directions) and circle-writing, using a haptic robot interacting with ad-hoc developed task-specific visual interfaces. Three dynamic conditions were provided, null additive external force (A), constant disturbing force (B) and deactivation of the additive external force again (C). The path length for each trial was computed, from the recorded position data and interaction events. Results The results show that the disturbing force affects significantly the movement outcomes in healthy but not in dystonic subjects, already compromised in the reference condition: the external alteration uncalibrates the healthy sensorimotor system, while the dystonic one is already strongly uncalibrated. The lack of systematic compensation for perturbation effects during B condition is reflected into the absence of after-effects in C condition, which would be the evidence that CNS generates a prediction of the perturbing forces using an internal model of the environment. The most promising finding is that in dystonic population the altered dynamic exposure seems to induce a subsequent improvement, i.e. a beneficial after-effect in terms of optimal path control, compared with the correspondent reference movement outcome. Conclusions The short-time error-enhancing training in dystonia could represent an effective approach for motor performance improvement, since the exposure to controlled dynamic alterations induces a refining of the existing but strongly imprecise motor scheme and sensorimotor patterns. PMID:22824547

An Experimental Investigation Into the Feasibility of Measuring Static and Dynamic Aerodynamic Derivatives in the DSTO Water Tunnel

DTIC Science & Technology

2013-08-01

The SDM was subjected to forced small (0.5) sinusoidal pitching oscillations and derivatives were computed from measured model loads, angles of... aluminium alloy when subjected to both tensile and torsional loading. He joined the Aeronautical Research Laboratories (now called the Defence...oscillations and derivatives were computed from measured model loads, angles of attack, reduced frequency of oscillation and aircraft geometrical parameters

Comparison of 3D dynamic virtual model to link segment model for estimation of net L4/L5 reaction moments during lifting.

PubMed

Abdoli-Eramaki, Mohammad; Stevenson, Joan M; Agnew, Michael J; Kamalzadeh, Amin

2009-04-01

The purpose of this study was to validate a 3D dynamic virtual model for lifting tasks against a validated link segment model (LSM). A face validation study was conducted by collecting x, y, z coordinate data and using them in both virtual and LSM models. An upper body virtual model was needed to calculate the 3D torques about human joints for use in simulated lifting styles and to estimate the effect of external mechanical devices on human body. Firstly, the model had to be validated to be sure it provided accurate estimates of 3D moments in comparison to a previously validated LSM. Three synchronised Fastrak units with nine sensors were used to record data from one male subject who completed dynamic box lifting under 27 different load conditions (box weights (3), lifting techniques (3) and rotations (3)). The external moments about three axes of L4/L5 were compared for both models. A pressure switch on the box was used to denote the start and end of the lift. An excellent agreement [image omitted] was found between the two models for dynamic lifting tasks, especially for larger moments in flexion and extension. This virtual model was considered valid for use in a complete simulation of the upper body skeletal system. This biomechanical virtual model of the musculoskeletal system can be used by researchers and practitioners to give a better tool to study the causes of LBP and the effect of intervention strategies, by permitting the researcher to see and control a virtual subject's motions.

The inaccuracy of surface-measured model-derived tibiofemoral kinematics.

PubMed

Li, Kang; Zheng, Liying; Tashman, Scott; Zhang, Xudong

2012-10-11

This study assessed the accuracy of surface-measured OpenSim-derived tibiofemoral kinematics in functional activities. Ten subjects with unilateral, isolated grade II PCL deficiency performed level running and stair ascent. A dynamic stereo radiography (DSX) system and a Vicon motion capture system simultaneously measured their knee or lower extremity movement. Surface marker motion data from the Vicon system were used to create subject-specific models in OpenSim and derive the tibiofemoral kinematics. The surface-measured model-derived tibiofemoral kinematics in all six degrees of freedom (DOFs) were then compared with those measured by the DSX as the benchmarks. The differences between surface- and DSX-measured tibiofemoral kinematics were found to be substantial: the overall mean (±SD) RMS differences during running were 9.1±3.2°, 2.0±1.2°, and 6.4±4.5° for the flexion-extension, abduction-adduction, and internal-external rotations, respectively, and 7.1±3.2 mm, 8.8±3.7 mm, and 1.9±1.2 mm for anterior-posterior, proximal-distal, and medial-lateral translations, respectively. The differences were more pronounced in relatively higher speed running than in stair ascent. It was also found that surface-based measures significantly underestimated the mean as well as inter-subject variability of the differences between PCL-injured and intact knees in abduction-adduction, internal-external rotations, and anterior-posterior translation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Real-Time and High-Fidelity Simulation Environment for Autonomous Ground Vehicle Dynamics

DTIC Science & Technology

2013-08-01

ENGINEERING AND TECHNOLOGY SYMPOSIUM (GVSETS), SET FOR AUG. 21-22, 2013 14. ABSTRACT briefing charts 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17...EDL & Aero-Flight DSENDS Airships Planetary & Terrain models SimScape Simulation framework Dshell Flex & Multibody dynamics DARTS 3D...7 DARTS Rigid/Flexible Real-Time Multibody Dynamics Engine Recipient of the NASA Software of the Year Award. Abhinandan Jain, "Robot and

Intrinsic, identified, and controlled types of motivation for school subjects in young elementary school children.

PubMed

Guay, Frédéric; Chanal, Julien; Ratelle, Catherine F; Marsh, Herbert W; Larose, Simon; Boivin, Michel

2010-12-01

There are two approaches to the differential examination of school motivation. The first is to examine motivation towards specific school subjects (between school subject differentiation). The second is to examine school motivation as a multidimensional concept that varies in terms of not only intensity but also quality (within school subject differentiation). These two differential approaches have led to important discoveries and provided a better understanding of student motivational dynamics. However, little research has combined these two approaches. This study examines young elementary students' motivations across school subjects (writing, reading, and maths) from the stance of self-determination theory. First, we tested whether children self-report different levels of intrinsic, identified, and controlled motivation towards specific school subjects. Second, we verified whether children self-report differentiated types of motivation across school subjects. Participants were 425 French-Canadian children (225 girls, 200 boys) from three elementary schools. Children were in Grades 1 (N=121), 2 (N=126), and 3 (N=178). Results show that, for a given school subject, young elementary students self-report different levels of intrinsic, identified, and controlled motivation. Results also indicate that children self-report different levels of motivation types across school subjects. Our findings also show that most differentiation effects increase across grades. Some gender effects were also observed. These results highlight the importance of distinguishing among types of school motivation towards specific school subjects in the early elementary years.

Effects of dendritic load on the firing frequency of oscillating neurons.

PubMed

Schwemmer, Michael A; Lewis, Timothy J

2011-03-01

We study the effects of passive dendritic properties on the dynamics of neuronal oscillators. We find that the addition of a passive dendrite can sometimes have counterintuitive effects on firing frequency. Specifically, the addition of a hyperpolarized passive dendritic load can either increase, decrease, or have negligible effects on firing frequency. We use the theory of weak coupling to derive phase equations for "ball-and-stick" model neurons and two-compartment model neurons. We then develop a framework for understanding how the addition of passive dendrites modulates the frequency of neuronal oscillators. We show that the average value of the neuronal oscillator's phase response curves measures the sensitivity of the neuron's firing rate to the dendritic load, including whether the addition of the dendrite causes an increase or decrease in firing frequency. We interpret this finding in terms of to the slope of the neuronal oscillator's frequency-applied current curve. We also show that equivalent results exist for constant and noisy point-source input to the dendrite. We note that the results are not specific to neurons but are applicable to any oscillator subject to a passive load.

NIMROD: a program for inference via a normal approximation of the posterior in models with random effects based on ordinary differential equations.

PubMed

Prague, Mélanie; Commenges, Daniel; Guedj, Jérémie; Drylewicz, Julia; Thiébaut, Rodolphe

2013-08-01

Models based on ordinary differential equations (ODE) are widespread tools for describing dynamical systems. In biomedical sciences, data from each subject can be sparse making difficult to precisely estimate individual parameters by standard non-linear regression but information can often be gained from between-subjects variability. This makes natural the use of mixed-effects models to estimate population parameters. Although the maximum likelihood approach is a valuable option, identifiability issues favour Bayesian approaches which can incorporate prior knowledge in a flexible way. However, the combination of difficulties coming from the ODE system and from the presence of random effects raises a major numerical challenge. Computations can be simplified by making a normal approximation of the posterior to find the maximum of the posterior distribution (MAP). Here we present the NIMROD program (normal approximation inference in models with random effects based on ordinary differential equations) devoted to the MAP estimation in ODE models. We describe the specific implemented features such as convergence criteria and an approximation of the leave-one-out cross-validation to assess the model quality of fit. In pharmacokinetics models, first, we evaluate the properties of this algorithm and compare it with FOCE and MCMC algorithms in simulations. Then, we illustrate NIMROD use on Amprenavir pharmacokinetics data from the PUZZLE clinical trial in HIV infected patients. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading

DOE PAGES

Sanborn, Brett; Song, Bo

2018-06-03

Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less

Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanborn, Brett; Song, Bo

Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less

Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models

PubMed Central

Ou, Jinli; Xie, Li; Jin, Changfeng; Li, Xiang; Zhu, Dajiang; Jiang, Rongxin; Chen, Yaowu

2014-01-01

Functional connectivity measured from resting state fMRI (R-fMRI) data has been widely used to examine the brain’s functional activities and has been recently used to characterize and differentiate brain conditions. However, the dynamical transition patterns of the brain’s functional states have been less explored. In this work, we propose a novel computational framework to quantitatively characterize the brain state dynamics via hidden Markov models (HMMs) learned from the observations of temporally dynamic functional connectomics, denoted as functional connectome states. The framework has been applied to the R-fMRI dataset including 44 post-traumatic stress disorder (PTSD) patients and 51 normal control (NC) subjects. Experimental results show that both PTSD and NC brains were undergoing remarkable changes in resting state and mainly transiting amongst a few brain states. Interestingly, further prediction with the best-matched HMM demonstrates that PTSD would enter into, but could not disengage from, a negative mood state. Importantly, 84 % of PTSD patients and 86 % of NC subjects are successfully classified via multiple HMMs using majority voting. PMID:25331991

Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

PubMed

Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

2016-06-01

Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

Effect of plantar intrinsic muscle training on medial longitudinal arch morphology and dynamic function.

PubMed

Mulligan, Edward P; Cook, Patrick G

2013-10-01

A specific training program emphasizing the neuromuscular recruitment of the plantar intrinsic foot muscles, colloquially referred to as "short foot" exercise (SFE) training, has been suggested as a means to dynamically support the medial longitudinal arch (MLA) during functional tasks. A single-group repeated measures pre- and post-intervention study design was utilized to determine if a 4-week intrinsic foot muscle training program would impact the amount of navicular drop (ND), increase the arch height index (AHI), improve performance during a unilateral functional reaching maneuver, or the qualitative assessment of the ability to hold the arch position in single limb stance position in an asymptomatic cohort. 21 asymptomatic subjects (42 feet) completed the 4-week SFE training program. Subject ND decreased by a mean of 1.8 mm at 4 weeks and 2.2 mm at 8 weeks (p < 0.05). AHI increased from 28 to 29% (p < 0.05). Intrinsic foot muscle performance during a static unilateral balancing activity improved from a grade of fair to good (p < 0.001) and subjects experienced a significant improvement during a functional balance and reach task in all directions with the exception of an anterior reach (p < 0.05). This study offers preliminary evidence to suggest that SFE training may have value in statically and dynamically supporting the MLA. Further research regarding the value of this exercise intervention in foot posture type or pathology specific patient populations is warranted. Copyright © 2013 Elsevier Ltd. All rights reserved.

A dynamic spatio-temporal model for spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin; Walsh, Daniel P.

2017-01-01

Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.

A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity

PubMed Central

Harris, Michael D.; Cyr, Adam J.; Ali, Azhar A.; Fitzpatrick, Clare K.; Rullkoetter, Paul J.; Maletsky, Lorin P.; Shelburne, Kevin B.

2016-01-01

Modeling complex knee biomechanics is a continual challenge, which has resulted in many models of varying levels of quality, complexity, and validation. Beyond modeling healthy knees, accurately mimicking pathologic knee mechanics, such as after cruciate rupture or meniscectomy, is difficult. Experimental tests of knee laxity can provide important information about ligament engagement and overall contributions to knee stability for development of subject-specific models to accurately simulate knee motion and loading. Our objective was to provide combined experimental tests and finite-element (FE) models of natural knee laxity that are subject-specific, have one-to-one experiment to model calibration, simulate ligament engagement in agreement with literature, and are adaptable for a variety of biomechanical investigations (e.g., cartilage contact, ligament strain, in vivo kinematics). Calibration involved perturbing ligament stiffness, initial ligament strain, and attachment location until model-predicted kinematics and ligament engagement matched experimental reports. Errors between model-predicted and experimental kinematics averaged <2 deg during varus–valgus (VV) rotations, <6 deg during internal–external (IE) rotations, and <3 mm of translation during anterior–posterior (AP) displacements. Engagement of the individual ligaments agreed with literature descriptions. These results demonstrate the ability of our constraint models to be customized for multiple individuals and simultaneously call attention to the need to verify that ligament engagement is in good general agreement with literature. To facilitate further investigations of subject-specific or population based knee joint biomechanics, data collected during the experimental and modeling phases of this study are available for download by the research community. PMID:27306137

Different developmental trajectories across feature types support a dynamic field model of visual working memory development

PubMed Central

Simmering, Vanessa R.; Miller, Hilary E.; Bohache, Kevin

2015-01-01

Research on visual working memory has focused on characterizing the nature of capacity limits as “slots” or “resources” based almost exclusively on adults’ performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to “slot” or “resource” explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children’s (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less-familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model—purportedly arising through experience—can capture differences across feature types. PMID:25737253

Estimation of Time-Varying, Intrinsic and Reflex Dynamic Joint Stiffness during Movement. Application to the Ankle Joint

PubMed Central

Guarín, Diego L.; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness determines the relation between joint position and torque, and plays a vital role in the control of posture and movement. Dynamic joint stiffness can be quantified during quasi-stationary conditions using disturbance experiments, where small position perturbations are applied to the joint and the torque response is recorded. Dynamic joint stiffness is composed of intrinsic and reflex mechanisms that act and change together, so that nonlinear, mathematical models and specialized system identification techniques are necessary to estimate their relative contributions to overall joint stiffness. Quasi-stationary experiments have demonstrated that dynamic joint stiffness is heavily modulated by joint position and voluntary torque. Consequently, during movement, when joint position and torque change rapidly, dynamic joint stiffness will be Time-Varying (TV). This paper introduces a new method to quantify the TV intrinsic and reflex components of dynamic joint stiffness during movement. The algorithm combines ensemble and deterministic approaches for estimation of TV systems; and uses a TV, parallel-cascade, nonlinear system identification technique to separate overall dynamic joint stiffness into intrinsic and reflex components from position and torque records. Simulation studies of a stiffness model, whose parameters varied with time as is expected during walking, demonstrated that the new algorithm accurately tracked the changes in dynamic joint stiffness using as little as 40 gait cycles. The method was also used to estimate the intrinsic and reflex dynamic ankle stiffness from an experiment with a healthy subject during which ankle movements were imposed while the subject maintained a constant muscle contraction. The method identified TV stiffness model parameters that predicted the measured torque very well, accounting for more than 95% of its variance. Moreover, both intrinsic and reflex dynamic stiffness were heavily modulated through the movement in a manner that could not be predicted from quasi-stationary experiments. The new method provides the tool needed to explore the role of dynamic stiffness in the control of movement. PMID:28649196

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets.

PubMed

Vyas, Urvi; Ghanouni, Pejman; Halpern, Casey H; Elias, Jeff; Pauly, Kim Butts

2016-09-01

In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. The simulated skull efficiency using individual-specific heterogeneous models predicts well (R(2) = 0.84) the experimental energy efficiency. This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible.

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets

PubMed Central

Vyas, Urvi; Ghanouni, Pejman; Halpern, Casey H.; Elias, Jeff; Pauly, Kim Butts

2016-01-01

Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R2 = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible. PMID:27587047

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vyas, Urvi, E-mail: urvi.vyas@gmail.com; Ghanouni,

Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen humanmore » subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R{sup 2} = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible.« less

Modeling Intraindividual Dynamics Using Stochastic Differential Equations: Age Differences in Affect Regulation.

PubMed

Wood, Julie; Oravecz, Zita; Vogel, Nina; Benson, Lizbeth; Chow, Sy-Miin; Cole, Pamela; Conroy, David E; Pincus, Aaron L; Ram, Nilam

2017-12-15

Life-span theories of aging suggest improvements and decrements in individuals' ability to regulate affect. Dynamic process models, with intensive longitudinal data, provide new opportunities to articulate specific theories about individual differences in intraindividual dynamics. This paper illustrates a method for operationalizing affect dynamics using a multilevel stochastic differential equation (SDE) model, and examines how those dynamics differ with age and trait-level tendencies to deploy emotion regulation strategies (reappraisal and suppression). Univariate multilevel SDE models, estimated in a Bayesian framework, were fit to 21 days of ecological momentary assessments of affect valence and arousal (average 6.93/day, SD = 1.89) obtained from 150 adults (age 18-89 years)-specifically capturing temporal dynamics of individuals' core affect in terms of attractor point, reactivity to biopsychosocial (BPS) inputs, and attractor strength. Older age was associated with higher arousal attractor point and less BPS-related reactivity. Greater use of reappraisal was associated with lower valence attractor point. Intraindividual variability in regulation strategy use was associated with greater BPS-related reactivity and attractor strength, but in different ways for valence and arousal. The results highlight the utility of SDE models for studying affect dynamics and informing theoretical predictions about how intraindividual dynamics change over the life course. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Language Training Strategy for Teaching Young Language-Delayed Children a Functional Syntactical Form.

ERIC Educational Resources Information Center

Hester, Peggy; Hendrickson, Jo

A modeling procedure involving dynamic interactions was used to train three language-delayed preschool children to emit five-element syntactic responses. A single-subject multiple baseline design using within- and across-subject replication was employed to study the acquisition of expanded "agent-action-object" sentences and the…

Holographic nondestructive testing in bone biomechanics

NASA Astrophysics Data System (ADS)

Silvennoinen, Raimo V. J.; Nygren, Kaarlo; Karna, Markku

1992-08-01

Holographic nondestructive testing (HNDT) is used to investigate the complex structures of bones of various shapes and sizes subjected to forces. During the course of the present study three antlered deer skulls of different species were investigated, and significant species- specific differences were observed. The HNDT method was also used to verify the advanced healing of an osteosynthetized sheep jawbone. Radioulnar bones of normal and orphaned moose calves were subjected to the bending test. Different bending dynamics were observed.

Investigation of Inner Loop Flight Control Strategies for High-Speed Research

NASA Technical Reports Server (NTRS)

Newman, Brett; Kassem, Ayman

1999-01-01

This report describes the activities and findings conducted under contract NAS1-19858 with NASA Langley Research Center. Subject matter is the investigation of suitable flight control design methodologies and solutions for large, flexible high-speed vehicles. Specifically, methodologies are to address the inner control loops used for stabilization and augmentation of a highly coupled airframe system possibly involving rigid-body motion, structural vibrations, unsteady aerodynamics, and actuator dynamics. Techniques considered in this body of work are primarily conventional-based, and the vehicle of interest is the High-Speed Civil Transport (HSCT). Major findings include 1) current aeroelastic vehicle modeling procedures require further emphasis and refinement, 2) traditional and nontraditional inner loop flight control strategies employing a single feedback loop do not appear sufficient for highly flexible HSCT class vehicles, 3) inner loop flight control systems will, in all likelihood, require multiple interacting feedback loops, and 4) Ref. H HSCT configuration presents major challenges to designing acceptable closed-loop flight dynamics.

A musculoskeletal model of the upper extremity for use in the development of neuroprosthetic systems

PubMed Central

Blana, Dimitra; Hincapie, Juan G.; Chadwick, Edward K.; Kirsch, Robert F.

2008-01-01

Upper extremity neuroprostheses use functional electrical stimulation (FES) to restore arm motor function to individuals with cervical level spinal cord injury. For the design and testing of these systems, a biomechanical model of the shoulder and elbow has been developed, to be used as a substitute for the human arm. It can be used to design and evaluate specific implementations of FES systems, as well as FES controllers. The model can be customized to simulate a variety of pathological conditions. For example, by adjusting the maximum force the muscles can produce, the model can be used to simulate an individual with tetraplegia and to explore the effects of FES of different muscle sets. The model comprises six bones, five joints, nine degrees of freedom, and 29 shoulder and arm muscles. It was developed using commercial, graphics-based modeling and simulation packages that are easily accessible to other researchers and can be readily interfaced to other analysis packages. It can be used for both forward-dynamic (inputs: muscle activation and external load; outputs:motions) and inverse-dynamic (inputs: motions and external load; outputs: muscle activation) simulations. Our model was verified by comparing the model-calculated muscle activations to electromyographic signals recorded from shoulder and arm muscles of five subjects. As an example of its application to neuroprosthesis design, the model was used to demonstrate the importance of rotator cuff muscle stimulation when aiming to restore humeral elevation. It is concluded that this model is a useful tool in the development and implementation of upper extremity neuroprosthetic systems. PMID:18420213

A musculoskeletal model of the upper extremity for use in the development of neuroprosthetic systems.

PubMed

Blana, Dimitra; Hincapie, Juan G; Chadwick, Edward K; Kirsch, Robert F

2008-01-01

Upper extremity neuroprostheses use functional electrical stimulation (FES) to restore arm motor function to individuals with cervical level spinal cord injury. For the design and testing of these systems, a biomechanical model of the shoulder and elbow has been developed, to be used as a substitute for the human arm. It can be used to design and evaluate specific implementations of FES systems, as well as FES controllers. The model can be customized to simulate a variety of pathological conditions. For example, by adjusting the maximum force the muscles can produce, the model can be used to simulate an individual with tetraplegia and to explore the effects of FES of different muscle sets. The model comprises six bones, five joints, nine degrees of freedom, and 29 shoulder and arm muscles. It was developed using commercial, graphics-based modeling and simulation packages that are easily accessible to other researchers and can be readily interfaced to other analysis packages. It can be used for both forward-dynamic (inputs: muscle activation and external load; outputs: motions) and inverse-dynamic (inputs: motions and external load; outputs: muscle activation) simulations. Our model was verified by comparing the model calculated muscle activations to electromyographic signals recorded from shoulder and arm muscles of five subjects. As an example of its application to neuroprosthesis design, the model was used to demonstrate the importance of rotator cuff muscle stimulation when aiming to restore humeral elevation. It is concluded that this model is a useful tool in the development and implementation of upper extremity neuroprosthetic systems.

Experimental Nonlinear Dynamics and Snap-Through of Post-Buckled Thin Laminated Composite Plates

NASA Astrophysics Data System (ADS)

Kim, Han-Gyu

Modern aerospace systems are increasingly being designed with composite panels and plates to achieve light weight and high specific strength and stiffness. For constrained panels, thermally-induced axial loading may cause buckling of the structure, which can lead to nonlinear and potentially chaotic behavior. When post-buckled composite plates experience snap-through, they are subjected to large-amplitude deformations and in-plane compressive loading. These phenomena pose a potential threat to the structural integrity of composite structures. In this work, the nonlinear dynamic behavior of post-buckled composite plates was investigated experimentally and computationally. For the experimental work, an electrodynamic shaker was used to apply harmonic loads and the dynamic response of plate specimens was measured using a single-point displacement-sensing laser, a double-point laser vibrometer (velocity-sensing), and a set of digital image correlation cameras. Both chaotic and periodic steady-state snap-through behaviors were investigated. The experimental data were used to characterize snap-through behaviors of the post-buckled specimens and their boundaries in the harmonic forcing parameter space. The nonlinear behavior of post-buckled plates was modeled using the classical laminated plate theory (CLPT) and the von Karman strain-displacement relations. The static equilibrium paths of the post-buckled plates were analyzed using an arc-length method with a branch-switching technique. For the dynamic analysis, the nonlinear equations of motion were derived based on CLPT and the nonlinear finite element model of the equations was constructed using the Hermite cubic interpolation functions for both conforming and nonconforming elements. The numerical analyses were conducted using the model and were compared with the experimental data.

Early-life family income and subjective well-being in adolescents.

PubMed

Gariepy, Genevieve; Elgar, Frank J; Sentenac, Mariane; Barrington-Leigh, Christopher

2017-01-01

Subjective well-being (SWB) in youths positively relates to family income, however its association with income during childhood is unclear. Using longitudinal data from the US Panel Study of Income Dynamics (n = 2234 adolescents, age 12-19 years), we examined whether the timing and duration of low family income in childhood was associated with adolescent SWB. We categorized family income during childhood into state-specific quintiles. Adolescent SWB was assessed using a 12-item questionnaire (score range 3-18). We used marginal structural modelling to test for sensitive periods of exposure to low income and tested cumulative effects of income by modelling the number of years spent in the poorest income quintiles. A period in early childhood (age 0-2 years) was particularly sensitive to low family income. Adolescent SWB was 1.65 (95% CI 0.40, 2.91) points lower in those who grew up in the poorest income quintiles during early childhood compared with the top quintile. Further, each childhood year spent in the poorest income quintiles was associated with a 0.10 point (95% CI 0.04, 0.16) lower SWB score in adolescence. The timing and duration of low family income in childhood both predict individual differences in adolescent SWB. Further studies are needed to clarify the mechanisms of these models and inform public policies.

Dynamic analysis of elastic rubber tired car wheel breaking under variable normal load

NASA Astrophysics Data System (ADS)

Fedotov, A. I.; Zedgenizov, V. G.; Ovchinnikova, N. I.

2017-10-01

The purpose of the paper is to analyze the dynamics of the braking of the wheel under normal load variations. The paper uses a mathematical simulation method according to which the calculation model of an object as a mechanical system is associated with a dynamically equivalent schematic structure of the automatic control. Transfer function tool analyzing structural and technical characteristics of an object as well as force disturbances were used. It was proved that the analysis of dynamic characteristics of the wheel subjected to external force disturbances has to take into account amplitude and phase-frequency characteristics. Normal load variations impact car wheel braking subjected to disturbances. The closer slip to the critical point is, the higher the impact is. In the super-critical area, load variations cause fast wheel blocking.

Complexity and spectral analysis of the heart rate variability dynamics for distant prediction of paroxysmal atrial fibrillation with artificial intelligence methods.

PubMed

Chesnokov, Yuriy V

2008-06-01

Paroxysmal atrial fibrillation (PAF) is a serious arrhythmia associated with morbidity and mortality. We explore the possibility of distant prediction of PAF by analyzing changes in heart rate variability (HRV) dynamics of non-PAF rhythms immediately before PAF event. We use that model for distant prognosis of PAF onset with artificial intelligence methods. We analyzed 30-min non-PAF HRV records from 51 subjects immediately before PAF onset and at least 45min distant from any PAF event. We used spectral and complexity analysis with sample (SmEn) and approximate (ApEn) entropies and their multiscale versions on extracted HRV data. We used that features to train the artificial neural networks (ANNs) and support vector machine (SVM) classifiers to differentiate the subjects. The trained classifiers were further tested for distant PAF event prognosis on 16 subjects from independent database on non-PAF rhythm lasting from 60 to 320 min before PAF onset classifying the 30-min segments as distant or leading to PAF. We found statistically significant increase in 30-min non-PAF HRV recordings from 51 subjects in the VLF, LF, HF bands and total power (p<0.0001) before PAF event compared to PAF distant ones. The SmEn and ApEn analysis provided significant decrease in complexity (p<0.0001 and p<0.001) before PAF onset. For training ANN and SVM classifiers the data from 51 subjects were randomly split to training, validation and testing. ANN provided better results in terms of sensitivity (Se), specificity (Sp) and positive predictivity (Pp) compared to SVM which became biased towards positive case. The validation results of the ANN classifier we achieved: Se 76%, Sp 93%, Pp 94%. Testing ANN and SVM classifiers on 16 subjects with non-PAF HRV data preceding PAF events we obtained distant prediction of PAF onset with SVM classifier in 10 subjects (58+/-18 min in advance). ANN classifier provided distant prediction of PAF event in 13 subjects (62+/-21 min in advance). From the results of distant PAF prediction we conclude that ANN and SVM classifiers learned the changes in the HRV dynamics immediately before PAF event and successfully identified them during distant PAF prognosis on independent database. This confirms the reported in the literature results that corresponding changes in the HRV data occur about 60 min before PAF onset and proves the possibility of distant PAF prediction with ANN and SVM methods.

A generalized partially linear mean-covariance regression model for longitudinal proportional data, with applications to the analysis of quality of life data from cancer clinical trials.

PubMed

Zheng, Xueying; Qin, Guoyou; Tu, Dongsheng

2017-05-30

Motivated by the analysis of quality of life data from a clinical trial on early breast cancer, we propose in this paper a generalized partially linear mean-covariance regression model for longitudinal proportional data, which are bounded in a closed interval. Cholesky decomposition of the covariance matrix for within-subject responses and generalized estimation equations are used to estimate unknown parameters and the nonlinear function in the model. Simulation studies are performed to evaluate the performance of the proposed estimation procedures. Our new model is also applied to analyze the data from the cancer clinical trial that motivated this research. In comparison with available models in the literature, the proposed model does not require specific parametric assumptions on the density function of the longitudinal responses and the probability function of the boundary values and can capture dynamic changes of time or other interested variables on both mean and covariance of the correlated proportional responses. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks.

PubMed

Samarasinghe, S; Ling, H

In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter estimation through adaptation, to larger signalling networks using a modular approach. Specifically, the signalling network is decomposed into several sub-models based on important temporal events in the network. Each sub-model is represented by the proposed RNN and trained using data generated from the corresponding ODE model. Trained sub-models are assembled into a whole system RNN which is then subjected to systems dynamics and sensitivity analyses. The concept is illustrated by application to G1/S transition in cell cycle using Iwamoto et al. (2008) ODE model. We decomposed the G1/S network into 3 sub-models: (i) E2F transcription factor release; (ii) E2F and CycE positive feedback loop for elevating cyclin levels; and (iii) E2F and CycA negative feedback to degrade E2F. The trained sub-models accurately represented system dynamics and parameters were in good agreement with the ODE model. The whole system RNN however revealed couple of parameters contributing to compounding errors due to feedback and required refinement to sub-model 2. These related to the reversible reaction between CycE/CDK2 and p27, its inhibitor. The revised whole system RNN model very accurately matched dynamics of the ODE system. Local sensitivity analysis of the whole system model further revealed the most dominant influence of the above two parameters in perturbing G1/S transition, giving support to a recent hypothesis that the release of inhibitor p27 from Cyc/CDK complex triggers cell cycle stage transition. To make the model useful in a practical setting, we modified each RNN sub-model with a time relay switch to facilitate larger interval input data (≈20min) (original model used data for 30s or less) and retrained them that produced parameters and protein concentrations similar to the original RNN system. Results thus demonstrated the reliability of the proposed RNN method for modelling relatively large networks by modularisation for practical settings. Advantages of the method are its ability to represent accurate continuous system dynamics and ease of: parameter estimation through training with data from a practical setting, model analysis (40% faster than ODE), fine tuning parameters when more data are available, sub-model extension when new elements and/or interactions come to light and model expansion with addition of sub-models. Copyright © 2017 Elsevier B.V. All rights reserved.

Clustering promotes switching dynamics in networks of noisy neurons

NASA Astrophysics Data System (ADS)

Franović, Igor; Klinshov, Vladimir

2018-02-01

Macroscopic variability is an emergent property of neural networks, typically manifested in spontaneous switching between the episodes of elevated neuronal activity and the quiescent episodes. We investigate the conditions that facilitate switching dynamics, focusing on the interplay between the different sources of noise and heterogeneity of the network topology. We consider clustered networks of rate-based neurons subjected to external and intrinsic noise and derive an effective model where the network dynamics is described by a set of coupled second-order stochastic mean-field systems representing each of the clusters. The model provides an insight into the different contributions to effective macroscopic noise and qualitatively indicates the parameter domains where switching dynamics may occur. By analyzing the mean-field model in the thermodynamic limit, we demonstrate that clustering promotes multistability, which gives rise to switching dynamics in a considerably wider parameter region compared to the case of a non-clustered network with sparse random connection topology.

WARP3D-Release 10.8: Dynamic Nonlinear Analysis of Solids using a Preconditioned Conjugate Gradient Software Architecture

NASA Technical Reports Server (NTRS)

Koppenhoefer, Kyle C.; Gullerud, Arne S.; Ruggieri, Claudio; Dodds, Robert H., Jr.; Healy, Brian E.

1998-01-01

This report describes theoretical background material and commands necessary to use the WARP3D finite element code. WARP3D is under continuing development as a research code for the solution of very large-scale, 3-D solid models subjected to static and dynamic loads. Specific features in the code oriented toward the investigation of ductile fracture in metals include a robust finite strain formulation, a general J-integral computation facility (with inertia, face loading), an element extinction facility to model crack growth, nonlinear material models including viscoplastic effects, and the Gurson-Tver-gaard dilatant plasticity model for void growth. The nonlinear, dynamic equilibrium equations are solved using an incremental-iterative, implicit formulation with full Newton iterations to eliminate residual nodal forces. The history integration of the nonlinear equations of motion is accomplished with Newmarks Beta method. A central feature of WARP3D involves the use of a linear-preconditioned conjugate gradient (LPCG) solver implemented in an element-by-element format to replace a conventional direct linear equation solver. This software architecture dramatically reduces both the memory requirements and CPU time for very large, nonlinear solid models since formation of the assembled (dynamic) stiffness matrix is avoided. Analyses thus exhibit the numerical stability for large time (load) steps provided by the implicit formulation coupled with the low memory requirements characteristic of an explicit code. In addition to the much lower memory requirements of the LPCG solver, the CPU time required for solution of the linear equations during each Newton iteration is generally one-half or less of the CPU time required for a traditional direct solver. All other computational aspects of the code (element stiffnesses, element strains, stress updating, element internal forces) are implemented in the element-by- element, blocked architecture. This greatly improves vectorization of the code on uni-processor hardware and enables straightforward parallel-vector processing of element blocks on multi-processor hardware.

Evolutionary dynamics of enzymes.

PubMed

Demetrius, L

1995-08-01

This paper codifies and rationalizes the large diversity in reaction rates and substrate specificity of enzymes in terms of a model which postulates that the kinetic properties of present-day enzymes are the consequence of the evolutionary force of mutation and selection acting on a class of primordial enzymes with poor catalytic activity and broad substrate specificity. Enzymes are classified in terms of their thermodynamic parameters, activation enthalpy delta H* and activation entropy delta S*, in their kinetically significant transition states as follows: type 1, delta H* > 0, delta S* < 0; type 2, delta H* < or = 0, delta S* < or = 0; type 3, delta H* > 0, delta S* > 0. We study the evolutionary dynamics of these three classes of enzymes subject to mutation, which acts at the level of the gene which codes for the enzyme and selection, which acts on the organism that contains the enzyme. Our model predicts the following evolutionary trends in the reaction rate and binding specificity for the three classes of molecules. In type 1 enzymes, evolution results in random, non-directional changes in the reaction rate and binding specificity. In type 2 and 3 enzymes, evolution results in a unidirectional increase in both the reaction rate and binding specificity. We exploit these results in order to codify the diversity in functional properties of present-day enzymes. Type 1 molecules will be described by intermediate reaction rates and broad substrate specificity. Type 2 enzymes will be characterized by diffusion-controlled rates and absolute substrate specificity. The type 3 catalysts can be further subdivided in terms of their activation enthalpy into two classes: type 3a (delta H* small) and type 3b (delta H* large). We show that type 3a will be represented by the same functional properties that identify type 2, namely, diffusion-controlled rates and absolute substrate specificity, whereas type 3b will be characterized by non-diffusion-controlled rates and absolute substrate specificity. We infer from this depiction of the three classes of enzymes, a general relation between the two functional properties, reaction rate and substrate specificity, namely, enzymes with diffusion-controlled rates have absolute substrate specificity. By appealing to energetic considerations, we furthermore show that enzymes with diffusion-controlled rates (types 2 and 3a) form a small subset of the class of all enzymes. This codification of present-day enzymes derived from an evolutionary model, essentially relates the structural properties of enzymes, as described by their thermodynamic parameters, to their functional properties, as represented by the reaction rate and substrate specificity.

Modelling of the AGS using Zgoubi - Status

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meot F.; Ahrens, L.; Dutheil, Y.

2012-05-20

This paper summarizes the progress achieved so far, and discusses various outcomes, regarding the development of a model of the Alternating Gradient Synchrotron at the RHIC collider. The model, based on stepwise ray-tracing methods, includes beam and polarization dynamics. This is an on-going work, and a follow-on of code developments and particle and spin dynamics simulations that have been subject to earlier publications at IPAC and PAC [1, 2, 3]. A companion paper [4] gives additional informations, regarding the use of the measured magnetic field maps of the AGS main magnets.

Overview of the DAEDALOS project

NASA Astrophysics Data System (ADS)

Bisagni, Chiara

2015-10-01

The "Dynamics in Aircraft Engineering Design and Analysis for Light Optimized Structures" (DAEDALOS) project aimed to develop methods and procedures to determine dynamic loads by considering the effects of dynamic buckling, material damping and mechanical hysteresis during aircraft service. Advanced analysis and design principles were assessed with the scope of partly removing the uncertainty and the conservatism of today's design and certification procedures. To reach these objectives a DAEDALOS aircraft model representing a mid-size business jet was developed. Analysis and in-depth investigation of the dynamic response were carried out on full finite element models and on hybrid models. Material damping was experimentally evaluated, and different methods for damping evaluation were developed, implemented in finite element codes and experimentally validated. They include a strain energy method, a quasi-linear viscoelastic material model, and a generalized Maxwell viscous material damping. Panels and shells representative of typical components of the DAEDALOS aircraft model were experimentally tested subjected to static as well as dynamic loads. Composite and metallic components of the aircraft model were investigated to evaluate the benefit in terms of weight saving.

Finding the Missing Physics: Simulating Polydisperse Polymer Melts

NASA Astrophysics Data System (ADS)

Rorrer, Nichoals; Dorgan, John

2014-03-01

A Monte Carlo algorithm has been developed to model polydisperse polymer melts. For the first time, this enables the specification of a predetermined molecular weight distribution for lattice based simulations. It is demonstrated how to map an arbitrary probability distributions onto a discrete number of chains residing on an fcc lattice. The resulting algorithm is able to simulate a wide variety of behaviors for polydisperse systems including confinement effects, shear flow, and parabolic flow. The dynamic version of the algorithm accurately captures Rouse dynamics for short polymer chains, and reptation-like dynamics for longer chain lengths.1 When polydispersity is introduced, smaller Rouse times and broadened the transition between different scaling regimes are observed. Rouse times also decrease under confinement for both polydisperse and monodisperse systems and chain length dependent migration effects are observed. The steady-state version of the algorithm enables the simulation of flow and when polydisperse systems are subject to parabolic (Poiseulle) flow, a migration phenomenon based on chain length is again present. These and other phenomena highlight the importance of including polydispersity in obtaining physically realistic simulations of polymeric melts. 1. Dorgan, J.R.; Rorrer, N.A.; Maupin, C.M., Macromolecules 2012, 45(21), 8833-8840. Work funded by the Fluid Dynamics program of the National Science Foundation under grant CBET-1067707.

Investigation of Moving Belt Radiator Technology Issues

NASA Technical Reports Server (NTRS)

Teagan, W. Peter; Aguilar, Jerry L.

1994-01-01

The development of an advanced spacecraft radiator technology is reported. The moving belt radiator is a thermal radiator concept with the promise of lower specific mass (per kW rejected) than that afforded by existing technologies. The results of a parametric study to estimate radiator mass for future space power systems is presented. It is shown that this technology can be scaled up to 200 MW for higher rejection temperatures. Several aspects of the design concept are discussed, including the dynamics of a large rotating belt in microgravity. The results of a computer code developed to model the belt dynamics are presented. A series of one-g experiments to investigate the dynamics of small belts is described. A comprehensive test program to investigate belt dynamics in microgravity aboard the NASA KC-135 aircraft is discussed. It was found that the desired circular shape can readily be achieved in microgravity. It is also shown that a rotating belt is stable when subjected to simulated attitude control maneuvers. Heat exchanger design is also investigated. Several sealing concepts were examined experimentally, and are discussed. Overall heat transfer coefficients to the rotating belt are presented. Material properties for various belt materials, including screen meshes, are also presented. The results presented in this report indicate that the moving belt radiator concept is technically feasible.

Cognitive Models for Learning to Control Dynamic Systems

DTIC Science & Technology

2008-09-26

1992 [47] G. F. Franklin and J. D. Powell, Feedback Control of Dynamic Systems, New Jersey: Pearson Prentice Hall 2006 [48] M . Fishbein and I . Ajzen ...the course of decision making, the valence of an action Vi ( i = A or M ) is defined as the subjective expected payoff for each action also fluctuates...research: The role of formal models, IEEE Transactions on Systems, Man, and Cybernetics 16, 1986, pp. 439–449. [54] M . I . Jordan, Constrained

Research on investment decisions model of trans-regional transmission network based on the theory of NPV

NASA Astrophysics Data System (ADS)

Zai, Wenjiao; Wang, Bo; Liu, Jichun; Shi, Haobo; Zeng, Pingliang

2018-02-01

The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.

A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

NASA Technical Reports Server (NTRS)

Oman, C. M.

1982-01-01

By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory-motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstance, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model is proposed which describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behaviours. The model admits several possibilities for adaptive mechanisms which do not involve internal model updating. Further systematic efforts to experimentally refine and validate the model are indicated.

Nonlinear dynamic modeling of a simple flexible rotor system subjected to time-variable base motions

NASA Astrophysics Data System (ADS)

Chen, Liqiang; Wang, Jianjun; Han, Qinkai; Chu, Fulei

2017-09-01

Rotor systems carried in transportation system or under seismic excitations are considered to have a moving base. To study the dynamic behavior of flexible rotor systems subjected to time-variable base motions, a general model is developed based on finite element method and Lagrange's equation. Two groups of Euler angles are defined to describe the rotation of the rotor with respect to the base and that of the base with respect to the ground. It is found that the base rotations would cause nonlinearities in the model. To verify the proposed model, a novel test rig which could simulate the base angular-movement is designed. Dynamic experiments on a flexible rotor-bearing system with base angular motions are carried out. Based upon these, numerical simulations are conducted to further study the dynamic response of the flexible rotor under harmonic angular base motions. The effects of base angular amplitude, rotating speed and base frequency on response behaviors are discussed by means of FFT, waterfall, frequency response curve and orbits of the rotor. The FFT and waterfall plots of the disk horizontal and vertical vibrations are marked with multiplications of the base frequency and sum and difference tones of the rotating frequency and the base frequency. Their amplitudes will increase remarkably when they meet the whirling frequencies of the rotor system.

Enhanced resting-state dynamics of the hemoglobin signal as a novel biomarker for detection of breast cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graber, Harry L., E-mail: harry.graber@downstate.edu; Xu, Yong; Barbour, Randall L.

Purpose: The work presented here demonstrates an application of diffuse optical tomography (DOT) to the problem of breast-cancer diagnosis. The potential for using spatial and temporal variability measures of the hemoglobin signal to identify useful biomarkers was studied. Methods: DOT imaging data were collected using two instrumentation platforms the authors developed, which were suitable for exploring tissue dynamics while performing a simultaneous bilateral exam. For each component of the hemoglobin signal (e.g., total, oxygenated), the image time series was reduced to eight scalar metrics that were affected by one or more dynamic properties of the breast microvasculature (e.g., average amplitude,more » amplitude heterogeneity, strength of spatial coordination). Receiver-operator characteristic (ROC) analyses, comparing groups of subjects with breast cancer to various control groups (i.e., all noncancer subjects, only those with diagnosed benign breast pathology, and only those with no known breast pathology), were performed to evaluate the effect of cancer on the magnitudes of the metrics and of their interbreast differences and ratios. Results: For women with known breast cancer, simultaneous bilateral DOT breast measures reveal a marked increase in the resting-state amplitude of the vasomotor response in the hemoglobin signal for the affected breast, compared to the contralateral, noncancer breast. Reconstructed 3D spatial maps of observed dynamics also show that this behavior extends well beyond the tumor border. In an effort to identify biomarkers that have the potential to support clinical aims, a group of scalar quantities extracted from the time series measures was systematically examined. This analysis showed that many of the quantities obtained by computing paired responses from the bilateral scans (e.g., interbreast differences, ratios) reveal statistically significant differences between the cancer-positive and -negative subject groups, while the corresponding measures derived from individual breast scans do not. ROC analyses yield area-under-curve values in the 77%–87% range, depending on the metric, with sensitivity and specificity values ranging from 66% to 91%. An interesting result is the initially unexpected finding that the hemodynamic-image metrics are only weakly dependent on the tumor burden, implying that the DOT technique employed is sensitive to tumor-induced changes in the vascular dynamics of the surrounding breast tissue as well. Computational modeling studies serve to identify which properties of the vasomotor response (e.g., average amplitude, amplitude heterogeneity, and phase heterogeneity) principally determine the values of the metrics and their codependences. Findings from the modeling studies also serve to clarify the influence of spatial-response heterogeneity and of system-design limitations, and they reveal the impact that a complex dependence of metric values on the modeled behaviors has on the success in distinguishing between cancer-positive and -negative subjects. Conclusions: The authors identified promising hemoglobin-based biomarkers for breast cancer from measures of the resting-state dynamics of the vascular bed. A notable feature of these biomarkers is that their spatial extent encompasses a large fraction of the breast volume, which is mainly independent of tumor size. Tumor-induced induction of nitric oxide synthesis, a well-established concomitant of many breast cancers, is offered as a plausible biological causal factor for the reported findings.« less

Selective entrainment of brain oscillations drives auditory perceptual organization.

PubMed

Costa-Faidella, Jordi; Sussman, Elyse S; Escera, Carles

2017-10-01

Perceptual sound organization supports our ability to make sense of the complex acoustic environment, to understand speech and to enjoy music. However, the neuronal mechanisms underlying the subjective experience of perceiving univocal auditory patterns that can be listened to, despite hearing all sounds in a scene, are poorly understood. We hereby investigated the manner in which competing sound organizations are simultaneously represented by specific brain activity patterns and the way attention and task demands prime the internal model generating the current percept. Using a selective attention task on ambiguous auditory stimulation coupled with EEG recordings, we found that the phase of low-frequency oscillatory activity dynamically tracks multiple sound organizations concurrently. However, whereas the representation of ignored sound patterns is circumscribed to auditory regions, large-scale oscillatory entrainment in auditory, sensory-motor and executive-control network areas reflects the active perceptual organization, thereby giving rise to the subjective experience of a unitary percept. Copyright © 2017 Elsevier Inc. All rights reserved.

A framework for determining improved placement of current energy converters subject to environmental constraints

DOE PAGES

Nelson, Kurt; James, Scott C.; Roberts, Jesse D.; ...

2017-06-05

A modelling framework identifies deployment locations for current-energy-capture devices that maximise power output while minimising potential environmental impacts. The framework, based on the Environmental Fluid Dynamics Code, can incorporate site-specific environmental constraints. Over a 29-day period, energy outputs from three array layouts were estimated for: (1) the preliminary configuration (baseline), (2) an updated configuration that accounted for environmental constraints, (3) and an improved configuration subject to no environmental constraints. Of these layouts, array placement that did not consider environmental constraints extracted the most energy from flow (4.38 MW-hr/day), 19% higher than output from the baseline configuration (3.69 MW-hr/day). Array placementmore » that considered environmental constraints removed 4.27 MW-hr/day of energy (16% more than baseline). In conclusion, this analysis framework accounts for bathymetry and flow-pattern variations that typical experimental studies cannot, demonstrating that it is a valuable tool for identifying improved array layouts for field deployments.« less

Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants

PubMed Central

Hill, Camilla Beate; Czauderna, Tobias; Klapperstück, Matthias; Roessner, Ute; Schreiber, Falk

2015-01-01

Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions. PMID:26557642

Prediction of subjective ratings of emotional pictures by EEG features

NASA Astrophysics Data System (ADS)

McFarland, Dennis J.; Parvaz, Muhammad A.; Sarnacki, William A.; Goldstein, Rita Z.; Wolpaw, Jonathan R.

2017-02-01

Objective. Emotion dysregulation is an important aspect of many psychiatric disorders. Brain-computer interface (BCI) technology could be a powerful new approach to facilitating therapeutic self-regulation of emotions. One possible BCI method would be to provide stimulus-specific feedback based on subject-specific electroencephalographic (EEG) responses to emotion-eliciting stimuli. Approach. To assess the feasibility of this approach, we studied the relationships between emotional valence/arousal and three EEG features: amplitude of alpha activity over frontal cortex; amplitude of theta activity over frontal midline cortex; and the late positive potential over central and posterior mid-line areas. For each feature, we evaluated its ability to predict emotional valence/arousal on both an individual and a group basis. Twenty healthy participants (9 men, 11 women; ages 22-68) rated each of 192 pictures from the IAPS collection in terms of valence and arousal twice (96 pictures on each of 4 d over 2 weeks). EEG was collected simultaneously and used to develop models based on canonical correlation to predict subject-specific single-trial ratings. Separate models were evaluated for the three EEG features: frontal alpha activity; frontal midline theta; and the late positive potential. In each case, these features were used to simultaneously predict both the normed ratings and the subject-specific ratings. Main results. Models using each of the three EEG features with data from individual subjects were generally successful at predicting subjective ratings on training data, but generalization to test data was less successful. Sparse models performed better than models without regularization. Significance. The results suggest that the frontal midline theta is a better candidate than frontal alpha activity or the late positive potential for use in a BCI-based paradigm designed to modify emotional reactions.

Complex dynamics of memristive circuits: Analytical results and universal slow relaxation

NASA Astrophysics Data System (ADS)

Caravelli, F.; Traversa, F. L.; Di Ventra, M.

2017-02-01

Networks with memristive elements (resistors with memory) are being explored for a variety of applications ranging from unconventional computing to models of the brain. However, analytical results that highlight the role of the graph connectivity on the memory dynamics are still few, thus limiting our understanding of these important dynamical systems. In this paper, we derive an exact matrix equation of motion that takes into account all the network constraints of a purely memristive circuit, and we employ it to derive analytical results regarding its relaxation properties. We are able to describe the memory evolution in terms of orthogonal projection operators onto the subspace of fundamental loop space of the underlying circuit. This orthogonal projection explicitly reveals the coupling between the spatial and temporal sectors of the memristive circuits and compactly describes the circuit topology. For the case of disordered graphs, we are able to explain the emergence of a power-law relaxation as a superposition of exponential relaxation times with a broad range of scales using random matrices. This power law is also universal, namely independent of the topology of the underlying graph but dependent only on the density of loops. In the case of circuits subject to alternating voltage instead, we are able to obtain an approximate solution of the dynamics, which is tested against a specific network topology. These results suggest a much richer dynamics of memristive networks than previously considered.

Validation of Inter-Subject Training for Hidden Markov Models Applied to Gait Phase Detection in Children with Cerebral Palsy.

PubMed

Taborri, Juri; Scalona, Emilia; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2015-09-23

Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs) represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6), with the best performance for the distributed classifier in two-phase recognition (G = 0.02). Differences were found among gait partitioning models, while no differences were found between training procedures with the exception of the shank classifier. Our results raise the possibility of avoiding subject-specific training in HMM for gait-phase recognition and its implementation to control exoskeletons for the pediatric population.

Validation of Inter-Subject Training for Hidden Markov Models Applied to Gait Phase Detection in Children with Cerebral Palsy

PubMed Central

Taborri, Juri; Scalona, Emilia; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2015-01-01

Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs) represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6), with the best performance for the distributed classifier in two-phase recognition (G = 0.02). Differences were found among gait partitioning models, while no differences were found between training procedures with the exception of the shank classifier. Our results raise the possibility of avoiding subject-specific training in HMM for gait-phase recognition and its implementation to control exoskeletons for the pediatric population. PMID:26404309

Visual Cortical Entrainment to Motion and Categorical Speech Features during Silent Lipreading

PubMed Central

O’Sullivan, Aisling E.; Crosse, Michael J.; Di Liberto, Giovanni M.; Lalor, Edmund C.

2017-01-01

Speech is a multisensory percept, comprising an auditory and visual component. While the content and processing pathways of audio speech have been well characterized, the visual component is less well understood. In this work, we expand current methodologies using system identification to introduce a framework that facilitates the study of visual speech in its natural, continuous form. Specifically, we use models based on the unheard acoustic envelope (E), the motion signal (M) and categorical visual speech features (V) to predict EEG activity during silent lipreading. Our results show that each of these models performs similarly at predicting EEG in visual regions and that respective combinations of the individual models (EV, MV, EM and EMV) provide an improved prediction of the neural activity over their constituent models. In comparing these different combinations, we find that the model incorporating all three types of features (EMV) outperforms the individual models, as well as both the EV and MV models, while it performs similarly to the EM model. Importantly, EM does not outperform EV and MV, which, considering the higher dimensionality of the V model, suggests that more data is needed to clarify this finding. Nevertheless, the performance of EMV, and comparisons of the subject performances for the three individual models, provides further evidence to suggest that visual regions are involved in both low-level processing of stimulus dynamics and categorical speech perception. This framework may prove useful for investigating modality-specific processing of visual speech under naturalistic conditions. PMID:28123363

How tibiofemoral alignment and contact locations affect predictions of medial and lateral tibiofemoral contact forces.

PubMed

Lerner, Zachary F; DeMers, Matthew S; Delp, Scott L; Browning, Raymond C

2015-02-26

Understanding degeneration of biological and prosthetic knee joints requires knowledge of the in-vivo loading environment during activities of daily living. Musculoskeletal models can estimate medial/lateral tibiofemoral compartment contact forces, yet anthropometric differences between individuals make accurate predictions challenging. We developed a full-body OpenSim musculoskeletal model with a knee joint that incorporates subject-specific tibiofemoral alignment (i.e. knee varus-valgus) and geometry (i.e. contact locations). We tested the accuracy of our model and determined the importance of these subject-specific parameters by comparing estimated to measured medial and lateral contact forces during walking in an individual with an instrumented knee replacement and post-operative genu valgum (6°). The errors in the predictions of the first peak medial and lateral contact force were 12.4% and 11.9%, respectively, for a model with subject-specific tibiofemoral alignment and contact locations determined through radiographic analysis, vs. 63.1% and 42.0%, respectively, for a model with generic parameters. We found that each degree of tibiofemoral alignment deviation altered the first peak medial compartment contact force by 51N (r(2)=0.99), while each millimeter of medial-lateral translation of the compartment contact point locations altered the first peak medial compartment contact force by 41N (r(2)=0.99). The model, available at www.simtk.org/home/med-lat-knee/, enables the specification of subject-specific joint alignment and compartment contact locations to more accurately estimate medial and lateral tibiofemoral contact forces in individuals with non-neutral alignment. Copyright © 2015 Elsevier Ltd. All rights reserved.

How Tibiofemoral Alignment and Contact Locations Affect Predictions of Medial and Lateral Tibiofemoral Contact Forces

PubMed Central

Lerner, Zachary F.; DeMers, Matthew S.; Delp, Scott L.; Browning, Raymond C.

2015-01-01

Understanding degeneration of biological and prosthetic knee joints requires knowledge of the in-vivo loading environment during activities of daily living. Musculoskeletal models can estimate medial/lateral tibiofemoral compartment contact forces, yet anthropometric differences between individuals make accurate predictions challenging. We developed a full-body OpenSim musculoskeletal model with a knee joint that incorporates subject-specific tibiofemoral alignment (i.e. knee varus-valgus) and geometry (i.e. contact locations). We tested the accuracy of our model and determined the importance of these subject-specific parameters by comparing estimated to measured medial and lateral contact forces during walking in an individual with an instrumented knee replacement and post-operative genu valgum (6°). The errors in the predictions of the first peak medial and lateral contact force were 12.4% and 11.9%, respectively, for a model with subject-specific tibiofemoral alignment and contact locations determined via radiographic analysis, vs. 63.1% and 42.0%, respectively, for a model with generic parameters. We found that each degree of tibiofemoral alignment deviation altered the first peak medial compartment contact force by 51N (r2=0.99), while each millimeter of medial-lateral translation of the compartment contact point locations altered the first peak medial compartment contact force by 41N (r2=0.99). The model, available at www.simtk.org/home/med-lat-knee/, enables the specification of subject-specific joint alignment and compartment contact locations to more accurately estimate medial and lateral tibiofemoral contact forces in individuals with non-neutral alignment. PMID:25595425

Nonlinearity in the vertical transmissibility of seating: the role of the human body apparent mass and seat dynamic stiffness

NASA Astrophysics Data System (ADS)

Tufano, Saverio; Griffin, Michael J.

2013-01-01

The efficiency of a seat in reducing vibration depends on the characteristics of the vibration, the dynamic characteristics of the seat, and the dynamic characteristics of the person sitting on the seat. However, it is not known whether seat cushions influence the dynamic response of the human body, whether the human body influences the dynamic response of seat cushions, or the relative importance of human body nonlinearity and seat nonlinearity in causing nonlinearity in measures of seat transmissibility. This study was designed to investigate the nonlinearity of the coupled seat and human body systems and to compare the apparent mass of the human body supported on rigid and foam seats. A frequency domain model was used to identify the dynamic parameters of seat foams and investigate their dependence on the subject-sitting weight and hip breadth. With 15 subjects, the force and acceleration at the seat base and acceleration at the subject interface were measured during random vertical vibration excitation (0.25-25 Hz) at each of five vibration magnitudes, (0.25-1.6 ms-2 r.m.s.) with four seating conditions (rigid flat seat and three foam cushions). The measurements are presented in terms of the subject's apparent mass on the rigid and foam seat surfaces, and the transmissibility and dynamic stiffness of each of the foam cushions. Both the human body and the foams showed nonlinear softening behaviour, which resulted in nonlinear cushion transmissibility. The apparent masses of subjects sitting on the rigid seat and on foam cushions were similar, but with an apparent increase in damping when sitting on the foams. The foam dynamic stiffness showed complex correlations with characteristics of the human body, which differed between foams. The nonlinearities in cushion transmissibilities, expressed in terms of changes in resonance frequencies and moduli, were more dependent on human body nonlinearity than on cushion nonlinearity.

Analysis of dynamics and fit of diving suits

NASA Astrophysics Data System (ADS)

Mahnic Naglic, M.; Petrak, S.; Gersak, J.; Rolich, T.

2017-10-01

Paper presents research on dynamical behaviour and fit analysis of customised diving suits. Diving suits models are developed using the 3D flattening method, which enables the construction of a garment model directly on the 3D computer body model and separation of discrete 3D surfaces as well as transformation into 2D cutting parts. 3D body scanning of male and female test subjects was performed with the purpose of body measurements analysis in static and dynamic postures and processed body models were used for construction and simulation of diving suits prototypes. All necessary parameters, for 3D simulation were applied on obtained cutting parts, as well as parameters values for mechanical properties of neoprene material. Developed computer diving suits prototypes were used for stretch analysis on areas relevant for body dimensional changes according to dynamic anthropometrics. Garment pressures against the body in static and dynamic conditions was also analysed. Garments patterns for which the computer prototype verification was conducted were used for real prototype production. Real prototypes were also used for stretch and pressure analysis in static and dynamic conditions. Based on the obtained results, correlation analysis between body changes in dynamic positions and dynamic stress, determined on computer and real prototypes, was performed.

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

PubMed Central

Sotiropoulos, Stamatios N.; Brookes, Matthew J.; Woolrich, Mark W.

2018-01-01

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. PMID:29474352

Formal Specification of Information Systems Requirements.

ERIC Educational Resources Information Center

Kampfner, Roberto R.

1985-01-01

Presents a formal model for specification of logical requirements of computer-based information systems that incorporates structural and dynamic aspects based on two separate models: the Logical Information Processing Structure and the Logical Information Processing Network. The model's role in systems development is discussed. (MBR)

Dynamic Identification for Control of Large Space Structures

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.

1985-01-01

This is a compilation of reports by the one author on one subject. It consists of the following five journal articles: (1) A Parametric Study of the Ibrahim Time Domain Modal Identification Algorithm; (2) Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique; (3) Computation of Normal Modes from Identified Complex Modes; (4) Dynamic Modeling of Structural from Measured Complex Modes; and (5) Time Domain Quasi-Linear Identification of Nonlinear Dynamic Systems.

Dynamic response of a modified water tank exposed to concentrated solar energy

NASA Astrophysics Data System (ADS)

Alhamdo, M. H.; Alkhakani, A. J.

2017-08-01

Power generation by using concentrated solar thermal energy on liquid enclosures is one of the most promising renewable energy technologies. In this work, a developed liquid enclosure fitted with various number and configurations of horizontal metal rings have been analyzed, fabricated and tested. The influence of adding metal rings arrangement is investigated for its potential to enhance radial heat conduction to the center-line of the enclosure from the side-walls. Experiments were carried out for fluid in both static and dynamic modes of operation inside the enclosure that subjected to high heat flux. A developed two-dimensional CFD model to predict the transient flow and thermal fields within liquid enclosure subjected to heat flux has been developed and tested. The developed numerical model takes into consideration energy transport between the liquid inside enclosure and the solid material of the enclosure. The numerical simulations have been compared with experimental measurement. The computational code has been found in a good level of agreement with the experimental data except for liquid at the peak part of the enclosure. The results indicate that adding metal rings produce significant impact on the transient temperature difference inside enclosure during both static and dynamic modes. The six-ring model is found to be more effective for enhancing radial heat transfer than other three models that have been tested. The in-line arrangement is found to provide better thermal effect as compared to the staggered rings. Two new correlations for natural heat transfer inside liquid enclosures subjected to high heat flux have been formulated (one for no-ring model and the other for six-ring model). The natural Nusselt number is found to be around a constant value for Rayleigh number less than (5 X 108). The recommended use of metal rings inside liquid enclosures subjected to heat flux, and the predicted Nusselt number correlation, will add to local knowledge a significant mean to gain more heat in large scale concentrated solar power plants. Two new correlations for natural heat transfer inside liquid enclosures subjected to high heat flux have been formulated (one for no-ring model and the other for six-ring model). The natural Nusselt number is found to be around a constant value for Rayleigh number less than (5 X 108). The recommended use of metal rings inside liquid enclosures subjected to heat flux, and the predicted Nusselt number correlation, will add to local knowledge a significant mean to gain more heat in large scale concentrated solar power plants.

Non-linear dynamic characteristics and optimal control of giant magnetostrictive film subjected to in-plane stochastic excitation

NASA Astrophysics Data System (ADS)

Zhu, Z. W.; Zhang, W. D.; Xu, J.

2014-03-01

The non-linear dynamic characteristics and optimal control of a giant magnetostrictive film (GMF) subjected to in-plane stochastic excitation were studied. Non-linear differential items were introduced to interpret the hysteretic phenomena of the GMF, and the non-linear dynamic model of the GMF subjected to in-plane stochastic excitation was developed. The stochastic stability was analysed, and the probability density function was obtained. The condition of stochastic Hopf bifurcation and noise-induced chaotic response were determined, and the fractal boundary of the system's safe basin was provided. The reliability function was solved from the backward Kolmogorov equation, and an optimal control strategy was proposed in the stochastic dynamic programming method. Numerical simulation shows that the system stability varies with the parameters, and stochastic Hopf bifurcation and chaos appear in the process; the area of the safe basin decreases when the noise intensifies, and the boundary of the safe basin becomes fractal; the system reliability improved through stochastic optimal control. Finally, the theoretical and numerical results were proved by experiments. The results are helpful in the engineering applications of GMF.

Kinetic modeling of benzodiazepine receptor binding with PET and high specific activity [(11)C]Iomazenil in healthy human subjects.

PubMed

Bremner, J D; Horti, A; Staib, L H; Zea-Ponce, Y; Soufer, R; Charney, D S; Baldwin, R

2000-01-01

Quantitation of the PET benzodiazepine receptor antagonist, [(11)C]Iomazenil, using low specific activity radioligand was recently described. The purpose of this study was to quantitate benzodiazepine receptor binding in human subjects using PET and high specific activity [(11)C]Iomazenil. Six healthy human subjects underwent PET imaging following a bolus injection of high specific activity (>100 Ci/mmol) [(11)C]iomazenil. Arterial samples were collected at multiple time points after injection for measurement of unmetabolized total and nonprotein-bound parent compound in plasma. Time activity curves of radioligand concentration in brain and plasma were analyzed using two and three compartment model. Kinetic rate constants of transfer of radioligand between plasma, nonspecifically bound brain tissue, and specifically bound brain tissue compartments were fitted to the model. Values for fitted kinetic rate constants were used in the calculation of measures of benzodiazepine receptor binding, including binding potential (the ratio of receptor density to affinity), and product of BP and the fraction of free nonprotein-bound parent compound (V(3)'). Use of the three compartment model improved the goodness of fit in comparison to the two compartment model. Values for kinetic rate constants and measures of benzodiazepine receptor binding, including BP and V(3)', were similar to results obtained with the SPECT radioligand [(123)I]iomazenil, and a prior report with low specific activity [(11)C]Iomazenil. Kinetic modeling using the three compartment model with PET and high specific activity [(11)C]Iomazenil provides a reliable measure of benzodiazepine receptor binding. Synapse 35:68-77, 2000. Published 2000 Wiley-Liss, Inc.

Visual privacy by context: proposal and evaluation of a level-based visualisation scheme.

PubMed

Padilla-López, José Ramón; Chaaraoui, Alexandros Andre; Gu, Feng; Flórez-Revuelta, Francisco

2015-06-04

Privacy in image and video data has become an important subject since cameras are being installed in an increasing number of public and private spaces. Specifically, in assisted living, intelligent monitoring based on computer vision can allow one to provide risk detection and support services that increase people's autonomy at home. In the present work, a level-based visualisation scheme is proposed to provide visual privacy when human intervention is necessary, such as at telerehabilitation and safety assessment applications. Visualisation levels are dynamically selected based on the previously modelled context. In this way, different levels of protection can be provided, maintaining the necessary intelligibility required for the applications. Furthermore, a case study of a living room, where a top-view camera is installed, is presented. Finally, the performed survey-based evaluation indicates the degree of protection provided by the different visualisation models, as well as the personal privacy preferences and valuations of the users.

Using Transmural Regularization and Dynamic Modeling for Non-Invasive Cardiac Potential Imaging of Endocardial Pacing with Imprecise Thoracic Geometry

PubMed Central

Erem, Burak; Coll-Font, Jaume; Orellana, Ramon Martinez; Štóvíček, Petr; Brooks, Dana H.

2014-01-01

Cardiac electrical imaging from body surface potential measurements is increasingly being seen as a technology with the potential for use in the clinic, for example for pre-procedure planning or during-treatment guidance for ventricular arrhythmia ablation procedures. However several important impediments to widespread adoption of this technology remain to be effectively overcome. Here we address two of these impediments: the difficulty of reconstructing electric potentials on the inner (endocardial) as well as outer (epicardial) surfaces of the ventricles, and the need for full anatomical imaging of the subject’s thorax to build an accurate subject-specific geometry. We introduce two new features in our reconstruction algorithm: a non-linear low-order dynamic parameterization derived from the measured body surface signals, and a technique to jointly regularize both surfaces. With these methodological innovations in combination, it is possible to reconstruct endocardial activation from clinically acquired measurements with an imprecise thorax geometry. In particular we test the method using body surface potentials acquired from three subjects during clinical procedures where the subjects’ hearts were paced on their endocardia using a catheter device. Our geometric models were constructed using a set of CT scans limited in axial extent to the immediate region near the heart. The catheter system provides a reference location to which we compare our results. We compare our estimates of pacing site localization, in terms of both accuracy and stability, to those reported in a recent clinical publication [1], where a full set of CT scans were available and only epicardial potentials were reconstructed. PMID:24595345

Reconfiguration of the upper extremity relative to the pushrim affects load distribution during wheelchair propulsion.

PubMed

Munaretto, Joseph M; McNitt-Gray, Jill L; Flashner, Henryk; Requejo, Philip S

2013-08-01

Repetitive loading during manual wheelchair propulsion (WCP) is associated with overuse injury to the upper extremity (UE). The aim of this study was to determine how RF redirection and load distribution are affected by changes upper extremity kinematic modifications associated with modifications in seat positions during a WCP task. The aim of this study was to determine how RF redirection and load distribution are affected by upper extremity kinematic changes associated with seat position adjustment during a WCP task. Dynamic simulations using an experiment-based multi-link inverse dynamics model were used to generate solutions for redistributing UE mechanical load in different seating positions without decrements in WCP task performance. Experimental RF and kinematic data were collected for one subject propelling at a self-selected speed and used as input into the model. Shoulder/axle distance, wrist angular position, and RF direction were systematically modified to simulate how the mechanical demand imposed on the upper extremity (elbow and shoulder net joint moments (NJMs) and net joint forces) may vary. Load distribution depended on UE orientation relative to the wheel. At peak force, lower shoulder/axle distances and more anterior wrist positions on the pushrim allowed for more extended elbow positions and reduced total NJM load. Simulation results incorporating subject-specific data may provide mechanically based information to guide clinical interventions that aim to maintain WCP performance and redistribute load by modifying RF direction, seat configuration and hand/rim interaction. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Message survival and decision dynamics in a class of reactive complex systems subject to external fields

NASA Astrophysics Data System (ADS)

Rodriguez Lucatero, C.; Schaum, A.; Alarcon Ramos, L.; Bernal-Jaquez, R.

2014-07-01

In this study, the dynamics of decisions in complex networks subject to external fields are studied within a Markov process framework using nonlinear dynamical systems theory. A mathematical discrete-time model is derived using a set of basic assumptions regarding the convincement mechanisms associated with two competing opinions. The model is analyzed with respect to the multiplicity of critical points and the stability of extinction states. Sufficient conditions for extinction are derived in terms of the convincement probabilities and the maximum eigenvalues of the associated connectivity matrices. The influences of exogenous (e.g., mass media-based) effects on decision behavior are analyzed qualitatively. The current analysis predicts: (i) the presence of fixed-point multiplicity (with a maximum number of four different fixed points), multi-stability, and sensitivity with respect to the process parameters; and (ii) the bounded but significant impact of exogenous perturbations on the decision behavior. These predictions were verified using a set of numerical simulations based on a scale-free network topology.

Effective Use of Multimedia Presentations to Maximize Learning within High School Science Classrooms

ERIC Educational Resources Information Center

Rapp, Eric

2013-01-01

This research used an evidenced-based experimental 2 x 2 factorial design General Linear Model with Repeated Measures Analysis of Covariance (RMANCOVA). For this analysis, time served as the within-subjects factor while treatment group (i.e., static and signaling, dynamic and signaling, static without signaling, and dynamic without signaling)…

Injury risk functions based on population-based finite element model responses: Application to femurs under dynamic three-point bending.

PubMed

Park, Gwansik; Forman, Jason; Kim, Taewung; Panzer, Matthew B; Crandall, Jeff R

2018-02-28

The goal of this study was to explore a framework for developing injury risk functions (IRFs) in a bottom-up approach based on responses of parametrically variable finite element (FE) models representing exemplar populations. First, a parametric femur modeling tool was developed and validated using a subject-specific (SS)-FE modeling approach. Second, principal component analysis and regression were used to identify parametric geometric descriptors of the human femur and the distribution of those factors for 3 target occupant sizes (5th, 50th, and 95th percentile males). Third, distributions of material parameters of cortical bone were obtained from the literature for 3 target occupant ages (25, 50, and 75 years) using regression analysis. A Monte Carlo method was then implemented to generate populations of FE models of the femur for target occupants, using a parametric femur modeling tool. Simulations were conducted with each of these models under 3-point dynamic bending. Finally, model-based IRFs were developed using logistic regression analysis, based on the moment at fracture observed in the FE simulation. In total, 100 femur FE models incorporating the variation in the population of interest were generated, and 500,000 moments at fracture were observed (applying 5,000 ultimate strains for each synthesized 100 femur FE models) for each target occupant characteristics. Using the proposed framework on this study, the model-based IRFs for 3 target male occupant sizes (5th, 50th, and 95th percentiles) and ages (25, 50, and 75 years) were developed. The model-based IRF was located in the 95% confidence interval of the test-based IRF for the range of 15 to 70% injury risks. The 95% confidence interval of the developed IRF was almost in line with the mean curve due to a large number of data points. The framework proposed in this study would be beneficial for developing the IRFs in a bottom-up manner, whose range of variabilities is informed by the population-based FE model responses. Specifically, this method mitigates the uncertainties in applying empirical scaling and may improve IRF fidelity when a limited number of experimental specimens are available.

Predictive accuracy of particle filtering in dynamic models supporting outbreak projections.

PubMed

Safarishahrbijari, Anahita; Teyhouee, Aydin; Waldner, Cheryl; Liu, Juxin; Osgood, Nathaniel D

2017-09-26

While a new generation of computational statistics algorithms and availability of data streams raises the potential for recurrently regrounding dynamic models with incoming observations, the effectiveness of such arrangements can be highly subject to specifics of the configuration (e.g., frequency of sampling and representation of behaviour change), and there has been little attempt to identify effective configurations. Combining dynamic models with particle filtering, we explored a solution focusing on creating quickly formulated models regrounded automatically and recurrently as new data becomes available. Given a latent underlying case count, we assumed that observed incident case counts followed a negative binomial distribution. In accordance with the condensation algorithm, each such observation led to updating of particle weights. We evaluated the effectiveness of various particle filtering configurations against each other and against an approach without particle filtering according to the accuracy of the model in predicting future prevalence, given data to a certain point and a norm-based discrepancy metric. We examined the effectiveness of particle filtering under varying times between observations, negative binomial dispersion parameters, and rates with which the contact rate could evolve. We observed that more frequent observations of empirical data yielded super-linearly improved accuracy in model predictions. We further found that for the data studied here, the most favourable assumptions to make regarding the parameters associated with the negative binomial distribution and changes in contact rate were robust across observation frequency and the observation point in the outbreak. Combining dynamic models with particle filtering can perform well in projecting future evolution of an outbreak. Most importantly, the remarkable improvements in predictive accuracy resulting from more frequent sampling suggest that investments to achieve efficient reporting mechanisms may be more than paid back by improved planning capacity. The robustness of the results on particle filter configuration in this case study suggests that it may be possible to formulate effective standard guidelines and regularized approaches for such techniques in particular epidemiological contexts. Most importantly, the work tentatively suggests potential for health decision makers to secure strong guidance when anticipating outbreak evolution for emerging infectious diseases by combining even very rough models with particle filtering method.

Musculoskeletal model-based control interface mimics physiologic hand dynamics during path tracing task

NASA Astrophysics Data System (ADS)

Crouch, Dustin L.; (Helen Huang, He

2017-06-01

Objective. We investigated the feasibility of a novel, customizable, simplified EMG-driven musculoskeletal model for estimating coordinated hand and wrist motions during a real-time path tracing task. Approach. A two-degree-of-freedom computational musculoskeletal model was implemented for real-time EMG-driven control of a stick figure hand displayed on a computer screen. After 5-10 minutes of undirected practice, subjects were given three attempts to trace 10 straight paths, one at a time, with the fingertip of the virtual hand. Able-bodied subjects completed the task on two separate test days. Main results. Across subjects and test days, there was a significant linear relationship between log-transformed measures of accuracy and speed (Pearson’s r  =  0.25, p  <  0.0001). The amputee subject could coordinate movement between the wrist and MCP joints, but favored metacarpophalangeal joint motion more highly than able-bodied subjects in 8 of 10 trials. For able-bodied subjects, tracing accuracy was lower at the extremes of the model’s range of motion, though there was no apparent relationship between tracing accuracy and fingertip location for the amputee. Our result suggests that, unlike able-bodied subjects, the amputee’s motor control patterns were not accustomed to the multi-joint dynamics of the wrist and hand, possibly as a result of post-amputation cortical plasticity, disuse, or sensory deficits. Significance. To our knowledge, our study is one of very few that have demonstrated the real-time simultaneous control of multi-joint movements, especially wrist and finger movements, using an EMG-driven musculoskeletal model, which differs from the many data-driven algorithms that dominate the literature on EMG-driven prosthesis control. Real-time control was achieved with very little training and simple, quick (~15 s) calibration. Thus, our model is potentially a practical and effective control platform for multifunctional myoelectric prostheses that could restore more life-like hand function for individuals with upper limb amputation.

A preliminary study of patient-specific mechanical properties of diabetic and healthy plantar soft tissue from gated magnetic resonance imaging.

PubMed

Williams, Evan D; Stebbins, Michael J; Cavanagh, Peter R; Haynor, David R; Chu, Baocheng; Fassbind, Michael J; Isvilanonda, Vara; Ledoux, William R

2017-07-01

Foot loading rate, load magnitude, and the presence of diseases such as diabetes can all affect the mechanical properties of the plantar soft tissues of the human foot. The hydraulic plantar soft tissue reducer instrument was designed to gain insight into which variables are the most significant in determining these properties. It was used with gated magnetic resonance imaging to capture three-dimensional images of feet under dynamic loading conditions. Custom electronics controlled by LabVIEW software simultaneously recorded system pressure, which was then translated to applied force values based on calibration curves. Data were collected for two subjects, one without diabetes (Subject A) and one with diabetes (Subject B). For a 0.2-Hz loading rate, and strains 0.16, 0.18, 0.20, and 0.22, Subject A's average tangential heel pad stiffness was 10 N/mm and Subject B's was 24 N/mm. Maximum test loads were approximately 200 N. Loading rate and load magnitude limitations (both were lower than physiologic values) will continue to be addressed in the next version of the instrument. However, the current hydraulic plantar soft tissue reducer did produce a data set for healthy versus diabetic tissue stiffness that agrees with previous trends. These data are also being used to improve finite element analysis models of the foot as part of a related project.

Self: an adaptive pressure arising from self-organization, chaotic dynamics, and neural Darwinism.

PubMed

Bruzzo, Angela Alessia; Vimal, Ram Lakhan Pandey

2007-12-01

In this article, we establish a model to delineate the emergence of "self" in the brain making recourse to the theory of chaos. Self is considered as the subjective experience of a subject. As essential ingredients of subjective experiences, our model includes wakefulness, re-entry, attention, memory, and proto-experiences. The stability as stated by chaos theory can potentially describe the non-linear function of "self" as sensitive to initial conditions and can characterize it as underlying order from apparently random signals. Self-similarity is discussed as a latent menace of a pathological confusion between "self" and "others". Our test hypothesis is that (1) consciousness might have emerged and evolved from a primordial potential or proto-experience in matter, such as the physical attractions and repulsions experienced by electrons, and (2) "self" arises from chaotic dynamics, self-organization and selective mechanisms during ontogenesis, while emerging post-ontogenically as an adaptive pressure driven by both volume and synaptic-neural transmission and influencing the functional connectivity of neural nets (structure).

From medical images to minimally invasive intervention: Computer assistance for robotic surgery.

PubMed

Lee, Su-Lin; Lerotic, Mirna; Vitiello, Valentina; Giannarou, Stamatia; Kwok, Ka-Wai; Visentini-Scarzanella, Marco; Yang, Guang-Zhong

2010-01-01

Minimally invasive surgery has been established as an important way forward in surgery for reducing patient trauma and hospitalization with improved prognosis. The introduction of robotic assistance enhances the manual dexterity and accuracy of instrument manipulation. Further development of the field in using pre- and intra-operative imaging guidance requires the integration of the general anatomy of the patient with clear pathologic indications and geometrical information for preoperative planning and intra-operative manipulation. It also requires effective visualization and the recreation of haptic and tactile sensing with dynamic active constraints to improve consistency and safety of the surgical procedures. This paper describes key technical considerations of tissue deformation tracking, 3D reconstruction, subject-specific modeling, image guidance and augmented reality for robotic assisted minimally invasive surgery. It highlights the importance of adapting preoperative surgical planning according to intra-operative data and illustrates how dynamic information such as tissue deformation can be incorporated into the surgical navigation framework. Some of the recent trends are discussed in terms of instrument design and the usage of dynamic active constraints and human-robot perceptual docking for robotic assisted minimally invasive surgery. Copyright 2009 Elsevier Ltd. All rights reserved.

Photoinduced electron transfer and fluorophore motion as a probe of the conformational dynamics of membrane proteins: application to the influenza a M2 proton channel.

PubMed

Rogers, Julie M G; Polishchuk, Alexei L; Guo, Lin; Wang, Jun; DeGrado, William F; Gai, Feng

2011-04-05

The structure and function of the influenza A M2 proton channel have been the subject of intensive investigations in recent years because of their critical role in the life cycle of the influenza virus. Using a truncated version of the M2 proton channel (i.e., M2TM) as a model, here we show that fluctuations in the fluorescence intensity of a dye reporter that arise from both fluorescence quenching via the mechanism of photoinduced electron transfer (PET) by an adjacent tryptophan (Trp) residue and local motions of the dye molecule can be used to probe the conformational dynamics of membrane proteins. Specifically, we find that the dynamics of the conformational transition between the N-terminal open and C-terminal open states of the M2TM channel occur on a timescale of about 500 μs and that the binding of either amantadine or rimantadine does not inhibit the pH-induced structural equilibrium of the channel. These results are consistent with the direct occluding mechanism of inhibition which suggests that the antiviral drugs act by sterically occluding the channel pore.

Antibody responses to bacteriophage phi X-174 in human subjects exposed to the antarctic winter-over model of spaceflight

NASA Technical Reports Server (NTRS)

Shearer, W. T.; Lugg, D. J.; Rosenblatt, H. M.; Nickolls, P. M.; Sharp, R. M.; Reuben, J. M.; Ochs, H. D.

2001-01-01

BACKGROUND: It has been proposed that exposure to long-term spaceflight conditions (stress, isolation, sleep disruption, containment, microbial contamination, and solar radiation) or to ground-based models of spaceflight will alter human immune responses, but specific antibody responses have not been fully evaluated. OBJECTIVE: We sought to determine whether exposure to the 8-month Antarctic winter-over model of spaceflight would alter human antibody responses. METHODS: During the 1999 Australian National Antarctic Research Expeditions, 11 adult study subjects at Casey, Antarctica, and 7 control subjects at Macquarie Island, sub-Antarctica, received primary and secondary immunizations with the T cell-dependent neoantigen bacteriophage phi X-174. Periodic plasma samples were analyzed for specific antibody function. RESULTS: All of the subjects from Casey, Antarctica, cleared bacteriophage phi X-174 normally by 1 week after primary immunization, and all had normal primary and secondary antibody responses, including immunologic memory amplification and switch from IgM to IgG antibody production. One subject showed a high normal pattern, and one subject had a low normal pattern. The control subjects from Macquarie Island also had normal immune responses to bacteriophage phi X-174. CONCLUSIONS: These data do not support the hypothesis that de novo specific antibody responses of subjects become defective during the conditions of the Antarctic winter-over. Because the Antarctic winter-over model of spaceflight lacks the important factors of microgravity and solar radiation, caution must be used in interpreting these data to anticipate normal antibody responses in long-term spaceflight.

Patient-specific modeling and analysis of dynamic behavior of individual sickle red blood cells under hypoxic conditions

NASA Astrophysics Data System (ADS)

Li, Xuejin; Du, E.; Li, Zhen; Tang, Yu-Hang; Lu, Lu; Dao, Ming; Karniadakis, George

2015-11-01

Sickle cell anemia is an inherited blood disorder exhibiting heterogeneous morphology and abnormal dynamics under hypoxic conditions. We developed a time-dependent cell model that is able to simulate the dynamic processes of repeated sickling and unsickling of red blood cells (RBCs) under physiological conditions. By using the kinetic cell model with parameters derived from patient-specific data, we present a mesoscopic computational study of the dynamic behavior of individual sickle RBCs flowing in a microfluidic channel with multiple microgates. We investigate how individual sickle RBCs behave differently from healthy ones in channel flow, and analyze the alteration of cellular behavior and response to single-cell capillary obstruction induced by cell rheologic rigidification and morphological change due to cell sickling under hypoxic conditions. We also simulate the flow dynamics of sickle RBCs treated with hydroxyurea (HU) and quantify the relative enhancement of hemodynamic performance of HU. This work was supported by the National Institutes of Health (NIH) Grant U01HL114476.

Quantum and classical dynamics of water dissociation on Ni(111): A test of the site-averaging model in dissociative chemisorption of polyatomic molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Bin; Department of Chemical Physics, University of Science and Technology of China, Hefei 230026; Guo, Hua, E-mail: hguo@unm.edu

Recently, we reported the first highly accurate nine-dimensional global potential energy surface (PES) for water interacting with a rigid Ni(111) surface, built on a large number of density functional theory points [B. Jiang and H. Guo, Phys. Rev. Lett. 114, 166101 (2015)]. Here, we investigate site-specific reaction probabilities on this PES using a quasi-seven-dimensional quantum dynamical model. It is shown that the site-specific reactivity is largely controlled by the topography of the PES instead of the barrier height alone, underscoring the importance of multidimensional dynamics. In addition, the full-dimensional dissociation probability is estimated by averaging fixed-site reaction probabilities with appropriatemore » weights. To validate this model and gain insights into the dynamics, additional quasi-classical trajectory calculations in both full and reduced dimensions have also been performed and important dynamical factors such as the steering effect are discussed.« less

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

"My Future Doesn't Know ME": Time and Subjectivity in Poetry by Young People

ERIC Educational Resources Information Center

Conrad, Rachel

2012-01-01

This article explores children's imaginative representations of time in relation to self-experience. Poems published in a young poets' anthology edited by Naomi Shihab Nye are analyzed in order to discern models of temporality and subjectivity imagined by young writers. A "dynamic temporality" is seen in a subset of poems which manipulate time…

Ahead of the Curve: Implementation Challenges in Personalized Learning School Models

ERIC Educational Resources Information Center

Bingham, Andrea J.; Pane, John F.; Steiner, Elizabeth D.; Hamilton, Laura S.

2018-01-01

In the current educational context, school models that leverage technology to personalize instruction have proliferated, as has student enrollment in, and funding of, such school models. However, even the best laid plans are subject to challenges in design and practice, particularly in the dynamic context of a school. In this collective case…

Multiscale Analysis of a Collapsible Respiratory Airway

NASA Astrophysics Data System (ADS)

Ghadiali, Samir; Bell, E. David; Swarts, J. Douglas

2006-11-01

The Eustachian tube (ET) is a collapsible respiratory airway that connects the nasopharynx with the middle ear (ME). The ET normally exists in a collapsed state and must be periodically opened to maintain a healthy and sterile ME. Although the inability to open the ET (i.e. ET dysfunction) is the primary etiology responsible for several common ME diseases (i.e. Otitis Media), the mechanisms responsible for ET dysfunction are not well established. To investigate these mechanisms, we developed a multi-scale model of airflow in the ET and correlated model results with experimental data obtained in healthy and diseased subjects. The computational models utilized finite-element methods to simulate fluid-structure interactions and molecular dynamics techniques to quantify the adhesive properties of mucus glycoproteins. Results indicate that airflow in the ET is highly sensitive to both the dynamics of muscle contraction and molecular adhesion forces within the ET lumen. In addition, correlation of model results with experimental data obtained in diseased subjects was used to identify the biomechanical mechanisms responsible for ET dysfunction.

Composite quantum collision models

NASA Astrophysics Data System (ADS)

Lorenzo, Salvatore; Ciccarello, Francesco; Palma, G. Massimo

2017-09-01

A collision model (CM) is a framework to describe open quantum dynamics. In its memoryless version, it models the reservoir R as consisting of a large collection of elementary ancillas: the dynamics of the open system S results from successive collisions of S with the ancillas of R . Here, we present a general formulation of memoryless composite CMs, where S is partitioned into the very open system under study S coupled to one or more auxiliary systems {Si} . Their composite dynamics occurs through internal S -{Si} collisions interspersed with external ones involving {Si} and the reservoir R . We show that important known instances of quantum non-Markovian dynamics of S —such as the emission of an atom into a reservoir featuring a Lorentzian, or multi-Lorentzian, spectral density or a qubit subject to random telegraph noise—can be mapped on to such memoryless composite CMs.

Application of uniform design to improve dental implant system.

PubMed

Cheng, Yung-Chang; Lin, Deng-Huei; Jiang, Cho-Pei

2015-01-01

This paper introduces the application of uniform experimental design to improve dental implant systems subjected to dynamic loads. The dynamic micromotion of the Zimmer dental implant system is calculated and illustrated by explicit dynamic finite element analysis. Endogenous and exogenous factors influence the success rate of dental implant systems. Endogenous factors include: bone density, cortical bone thickness and osseointegration. Exogenous factors include: thread pitch, thread depth, diameter of implant neck and body size. A dental implant system with a crest module was selected to simulate micromotion distribution and stress behavior under dynamic loads using conventional and proposed methods. Finally, the design which caused minimum micromotion was chosen as the optimal design model. The micromotion of the improved model is 36.42 μm, with an improvement is 15.34% as compared to the original model.

Real time closed loop control of an Ar and Ar/O2 plasma in an ICP

NASA Astrophysics Data System (ADS)

Faulkner, R.; Soberón, F.; McCarter, A.; Gahan, D.; Karkari, S.; Milosavljevic, V.; Hayden, C.; Islyaikin, A.; Law, V. J.; Hopkins, M. B.; Keville, B.; Iordanov, P.; Doherty, S.; Ringwood, J. V.

2006-10-01

Real time closed loop control for plasma assisted semiconductor manufacturing has been the subject of academic research for over a decade. However, due to process complexity and the lack of suitable real time metrology, progress has been elusive and genuine real time, multi-input, multi-output (MIMO) control of a plasma assisted process has yet to be successfully implemented in an industrial setting. A Splasma parameter control strategy T is required to be adopted whereby process recipes which are defined in terms of plasma properties such as critical species densities as opposed to input variables such as rf power and gas flow rates may be transferable between different chamber types. While PIC simulations and multidimensional fluid models have contributed considerably to the basic understanding of plasmas and the design of process equipment, such models require a large amount of processing time and are hence unsuitable for testing control algorithms. In contrast, linear dynamical empirical models, obtained through system identification techniques are ideal in some respects for control design since their computational requirements are comparatively small and their structure facilitates the application of classical control design techniques. However, such models provide little process insight and are specific to an operating point of a particular machine. An ideal first principles-based, control-oriented model would exhibit the simplicity and computational requirements of an empirical model and, in addition, despite sacrificing first principles detail, capture enough of the essential physics and chemistry of the process in order to provide reasonably accurate qualitative predictions. This paper will discuss the development of such a first-principles based, control-oriented model of a laboratory inductively coupled plasma chamber. The model consists of a global model of the chemical kinetics coupled to an analytical model of power deposition. Dynamics of actuators including mass flow controllers and exhaust throttle are included and sensor characteristics are also modelled. The application of this control-oriented model to achieve multivariable closed loop control of specific species e.g. atomic Oxygen and ion density using the actuators rf power, Oxygen and Argon flow rates, and pressure/exhaust flow rate in an Ar/O2 ICP plasma will be presented.

Particle-gas dynamics in the protoplanetary nebula

NASA Technical Reports Server (NTRS)

Cuzzi, Jeffrey N.; Champney, Joelle M.; Dobrovolskis, Anthony R.

1991-01-01

In the past year we made significant progress in improving our fundamental understanding of the physics of particle-gas dynamics in the protoplanetary nebula. Having brought our code to a state of fairly robust functionality, we devoted significant effort to optimizing it for running long cases. We optimized the code for vectorization to the extent that it now runs eight times faster than before. The following subject areas are covered: physical improvements to the model; numerical results; Reynolds averaging of fluid equations; and modeling of turbulence and viscosity.

Fish community reassembly after a coral mass mortality: higher trophic groups are subject to increased rates of extinction.

PubMed

Alonso, David; Pinyol-Gallemí, Aleix; Alcoverro, Teresa; Arthur, Rohan

2015-05-01

Since Gleason and Clements, our understanding of community dynamics has been influenced by theories emphasising either dispersal or niche assembly as central to community structuring. Determining the relative importance of these processes in structuring real-world communities remains a challenge. We tracked reef fish community reassembly after a catastrophic coral mortality in a relatively unfished archipelago. We revisited the stochastic model underlying MacArthur and Wilson's Island Biogeography Theory, with a simple extension to account for trophic identity. Colonisation and extinction rates calculated from decadal presence-absence data based on (1) species neutrality, (2) trophic identity and (3) site-specificity were used to model post-disturbance reassembly, and compared with empirical observations. Results indicate that species neutrality holds within trophic guilds, and trophic identity significantly increases overall model performance. Strikingly, extinction rates increased clearly with trophic position, indicating that fish communities may be inherently susceptible to trophic downgrading even without targeted fishing of top predators. © 2015 John Wiley & Sons Ltd/CNRS.

Knee medial and lateral contact forces in a musculoskeletal model with subject-specific contact point trajectories.

PubMed

Zeighami, A; Aissaoui, R; Dumas, R

2018-03-01

Contact point (CP) trajectory is a crucial parameter in estimating medial/lateral tibio-femoral contact forces from the musculoskeletal (MSK) models. The objective of the present study was to develop a method to incorporate the subject-specific CP trajectories into the MSK model. Ten healthy subjects performed 45 s treadmill gait trials. The subject-specific CP trajectories were constructed on the tibia and femur as a function of extension-flexion using low-dose bi-plane X-ray images during a quasi-static squat. At each extension-flexion position, the tibia and femur CPs were superimposed in the three directions on the medial side, and in the anterior-posterior and proximal-distal directions on the lateral side to form the five kinematic constraints of the knee joint. The Lagrange multipliers associated to these constraints directly yielded the medial/lateral contact forces. The results from the personalized CP trajectory model were compared against the linear CP trajectory and sphere-on-plane CP trajectory models which were adapted from the commonly used MSK models. Changing the CP trajectory had a remarkable impact on the knee kinematics and changed the medial and lateral contact forces by 1.03 BW and 0.65 BW respectively, in certain subjects. The direction and magnitude of the medial/lateral contact force were highly variable among the subjects and the medial-lateral shift of the CPs alone could not determine the increase/decrease pattern of the contact forces. The suggested kinematic constraints are adaptable to the CP trajectories derived from a variety of joint models and those experimentally measured from the 3D imaging techniques. Copyright © 2018 Elsevier Ltd. All rights reserved.

Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

NASA Technical Reports Server (NTRS)

Brain, Thomas A.; Kovel, Erik B.; MacLean, John R.; Quiocho, Leslie J.

2017-01-01

Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

New optomechanical approach to quantitative characterization of fatigue behavior of dynamically loaded structures

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1995-06-01

The basic relationships between stress and strain under cyclic conditions of loading are not at present well understood. It would seem that information of this type is vital for a fundamental approach to understand the fatigue behavior of dynamically loaded structures. In this paper, experimental and computational methods are utilized to study the fatigue behavior of a thin aluminum cantilever plate subjected to dynamic loading. The studies are performed by combining optomechanical and finite element methods. The cantilever plate is loaded periodically by excitation set at a fixed amplitude and at a specific resonance frequency of the plate. By continuously applying this type of loading and using holographic interferometry, the behavior of the plate during a specific period of time is investigated. Quantitative information is obtained from laser vibrometry data which are utilized by a finite element program to calculate strains and stresses assuming a homogeneous and isotropic material and constant strain elements. It is shown that the use of experimental and computational hybrid methodologies allows identification of different zones of the plate that are fatigue critical. This optomechanical approach proves to be a viable tool for understanding of fatigue behavior of mechanical components and for performing optimization of structures subjected to fatigue conditions.

Initial state-specific photodissociation dynamics of pyrrole via 1 π σ ∗/ S 0 conical intersection initiated with optimally controlled UV-laser pulses

NASA Astrophysics Data System (ADS)

Nandipati, K. R.; Kanakati, Arun Kumar; Singh, H.; Lan, Z.; Mahapatra, S.

2017-09-01

Optimal initiation of quantum dynamics of N-H photodissociation of pyrrole on the S0-1πσ∗(1A2) coupled electronic states by UV-laser pulses in an effort to guide the subsequent dynamics to dissociation limits is studied theoretically. Specifically, the task of designing optimal laser pulses that act on initial vibrational states of the system for an effective UV-photodissociation is considered by employing optimal control theory. The associated control mechanism(s) for the initial state dependent photodissociation dynamics of pyrrole in the presence of control pulses is examined and discussed in detail. The initial conditions determine implicitly the variation in the dissociation probabilities for the two channels, upon interaction with the field. The optimal pulse corresponds to the objective fixed as maximization of overall reactive flux subject to constraints of reasonable fluence and quantum dynamics. The simple optimal pulses obtained by the use of genetic algorithm based optimization are worth an experimental implementation given the experimental relevance of πσ∗-photochemistry in recent times.

Kinetics of the Tau PET Tracer 18F-AV-1451 (T807) in Subjects with Normal Cognitive Function, Mild Cognitive Impairment, and Alzheimer Disease.

PubMed

Shcherbinin, Sergey; Schwarz, Adam J; Joshi, Abhinay; Navitsky, Michael; Flitter, Matthew; Shankle, William R; Devous, Michael D; Mintun, Mark A

2016-10-01

We report kinetic modeling results of dynamic acquisition data from 0 to 100 min after injection with the tau PET tracer 18 F-AV-1451 in 19 subjects. Subjects were clinically diagnosed as 4 young cognitively normal, 5 old cognitively normal, 5 mild cognitive impairment, and 5 Alzheimer disease (AD). Kinetic modeling was performed using Logan graphical analysis with the cerebellum crus as a reference region. Voxelwise binding potential ([Formula: see text]) and SUV ratio ([Formula: see text]) images were compared. In AD subjects, slower and spatially nonuniform clearance from cortical regions was observed as compared with the controls, which led to focal uptake and elevated retention in the imaging data from 80 to 100 min after injection. BP from the dynamic data from 0 to 100 min correlated strongly (R 2 > 0.86) with corresponding regional [Formula: see text] values. In the putamen, the observed kinetics (positive [Formula: see text] at the tracer delivery stage and plateauing time-SUVR curves for all diagnostic categories) may suggest either additional off-target binding or a second binding site with different kinetics. The kinetics of the 18 F-AV-1451 tracer in cortical areas, as examined in this small group of subjects, differed by diagnostic stage. A delayed 80- to 100-min scan provided a reasonable substitute for a dynamic 0- to 100-min acquisition for cortical regions although other windows (e.g., 75-105 min) may be useful to evaluate. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Influence of solute charge and pyrrolidinium ionic liquid alkyl chain length on probe rotational reorientation dynamics.

PubMed

Guo, Jianchang; Mahurin, Shannon M; Baker, Gary A; Hillesheim, Patrick C; Dai, Sheng; Shaw, Robert W

2014-01-30

In recent years, the effect of molecular charge on the rotational dynamics of probe solutes in room-temperature ionic liquids (RTILs) has been a subject of growing interest. For the purpose of extending our understanding of charged solute behavior within RTILs, we have studied the rotational dynamics of three illustrative xanthene fluorescent probes within a series of N-alkylpyrrolidinium bis(trifluoromethylsulfonyl)imide ([Cnmpyr][Tf2N]) RTILs with different n-alkyl chain lengths (n = 3, 4, 6, 8, or 10) using time-resolved fluorescence anisotropy decay. The rotational dynamics of the neutral probe rhodamine B (RhB) dye lies between the stick and slip boundary conditions due to the influence of specific hydrogen bonding interactions. The rotation of the negatively charged sulforhodamine 640 (SR640) is slower than that of its positively charged counterpart rhodamine 6G (R6G). An analysis based upon Stokes-Einstein-Debye hydrodynamics indicates that SR640 adheres to stick boundary conditions due to specific interactions, whereas the faster rotation of R6G is attributed to weaker electrostatic interactions. No significant dependence of the rotational dynamics on the solvent alkyl chain length was observed for any of the three dyes, suggesting that the specific interactions between dyes and RTILs are relatively independent of this solvent parameter.

Nitrogen dynamics in flooded soil systems: an overview on concepts and performance of models

PubMed Central

Nurulhuda, Khairudin; Gaydon, Donald S; Jing, Qi; Zakaria, Mohamad P; Struik, Paul C

2017-01-01

Abstract Extensive modelling studies on nitrogen (N) dynamics in flooded soil systems have been published. Consequently, many N dynamics models are available for users to select from. With the current research trend, inclined towards multidisciplinary research, and with substantial progress in understanding of N dynamics in flooded soil systems, the objective of this paper is to provide an overview of the modelling concepts and performance of 14 models developed to simulate N dynamics in flooded soil systems. This overview provides breadth of knowledge on the models, and, therefore, is valuable as a first step in the selection of an appropriate model for a specific application. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:28940491

Electromotile hearing: Acoustic tones mask psychophysical response to high-frequency electrical stimulation of intact guinea pig cochleaea)

PubMed Central

Le Prell, Colleen G.; Kawamoto, Kohei; Raphael, Yehoash; Dolan, David F.

2011-01-01

When sinusoidal electric stimulation is applied to the intact cochlea, a frequency-specific acoustic emission can be recorded in the ear canal. Acoustic emissions are produced by basilar membrane motion, and have been used to suggest a corresponding acoustic sensation termed “electromotile hearing.” Electromotile hearing has been specifically attributed to electric stimulation of outer hair cells in the intact organ of Corti. To determine the nature of the auditory perception produced by electric stimulation of a cochlea with intact outer hair cells, we tested guinea pigs in a psychophysical task. First, subjects were trained to report detection of sinusoidal acoustic stimuli and dynamic range was assessed using response latency. Subjects were then implanted with a ball electrode placed into scala tympani. Following the surgical implant procedure, subjects were transferred to a task in which acoustic signals were replaced by sinusoidal electric stimulation, and dynamic range was assessed again. Finally, the ability of acoustic pure-tone stimuli to mask the detection of the electric signals was assessed. Based on the masking effects, we conclude that sinusoidal electric stimulation of the intact cochlea results in perception of a tonal (rather than a broad-band or noisy) sound at a frequency of 8 kHz or above. PMID:17225416

Preliminary Exploration of Adaptive State Predictor Based Human Operator Modeling

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2012-01-01

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to quantify the effects of changing aircraft dynamics on an operator s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. A gradient descent estimator and a least squares estimator with exponential forgetting used these data to predict pilot stick input. The results indicate that individual pilot characteristics and vehicle dynamics did not affect the accuracy of either estimator method to estimate pilot stick input. These methods also were able to predict pilot stick input during changing aircraft dynamics and they may have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot.

TSAPA: identification of tissue-specific alternative polyadenylation sites in plants.

PubMed

Ji, Guoli; Chen, Moliang; Ye, Wenbin; Zhu, Sheng; Ye, Congting; Su, Yaru; Peng, Haonan; Wu, Xiaohui

2018-06-15

Alternative polyadenylation (APA) is now emerging as a widespread mechanism modulated tissue-specifically, which highlights the need to define tissue-specific poly(A) sites for profiling APA dynamics across tissues. We have developed an R package called TSAPA based on the machine learning model for identifying tissue-specific poly(A) sites in plants. A feature space including more than 200 features was assembled to specifically characterize poly(A) sites in plants. The classification model in TSAPA can be customized by selecting desirable features or classifiers. TSAPA is also capable of predicting tissue-specific poly(A) sites in unannotated intergenic regions. TSAPA will be a valuable addition to the community for studying dynamics of APA in plants. https://github.com/BMILAB/TSAPA. Supplementary data are available at Bioinformatics online.

Shedding Synchrotron Light on a Puzzle of Glasses

ScienceCinema

Chumakov, Aleksandr [European Synchrotron Radiation Facility, Grenoble, France

2017-12-09

Vibrational dynamics of glasses remains a point of controversial discussions. In particular, the density of vibrational states (DOS) reveals an excess of states above the Debye model called "boson peak." Despite the fact that this universal feature for all glasses has been known for more than 35 years, the nature of the boson peak is still not understood. The application of nuclear inelastic scattering via synchrotron radiation perhaps provides a clearer, more consistent picture of the subject. The distinguishing features of nuclear inelastic scattering relative to, e.g., neutron inelastic scattering, are ideal momentum integration and exact scaling of the DOS in absolute units. This allows for reliable comparison to data from other techniques such as Brillouin light scattering. Another strong point is ideal isotope selectivity: the DOS is measured for a single isotope with a specific low-energy nuclear transition. This allows for special "design" of an experiment to study, for instance, the dynamics of only center-of-mass motions. Recently, we have investigated the transformation of the DOS as a function of several key parameters such as temperature, cooling rate, and density. In all cases the transformation of the DOS is sufficiently well described by a transformation of the continuous medium, in particular, by changes of the macroscopic density and the sound velocity. These results suggest a collective sound-like nature of vibrational dynamics in glasses and cast doubts on microscopic models of glass dynamics. Further insight can be obtained in combined studies of glass with nuclear inelastic and inelastic neutron scattering. Applying two techniques, we have measured the energy dependence of the characteristic correlation length of atomic motions. The data do not reveal localization of atomic vibrations at the energy of the boson peak. Once again, the results suggest that special features of glass dynamics are related to extended motions and not to local models.

Collaborative Research. Damage and Burst Dynamics in Failure of Complex Geomaterials. A Statistical Physics Approach to Understanding the Complex Emergent Dynamics in Near Mean-Field Geological Materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rundle, John B.; Klein, William

We have carried out research to determine the dynamics of failure in complex geomaterials, specifically focusing on the role of defects, damage and asperities in the catastrophic failure processes (now popularly termed “Black Swan events”). We have examined fracture branching and flow processes using models for invasion percolation, focusing particularly on the dynamics of bursts in the branching process. We have achieved a fundamental understanding of the dynamics of nucleation in complex geomaterials, specifically in the presence of inhomogeneous structures.

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands

PubMed Central

Miller, Brian W.; Breckheimer, Ian; McCleary, Amy L.; Guzmán-Ramirez, Liza; Caplow, Susan C.; Jones-Smith, Jessica C.; Walsh, Stephen J.

2010-01-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands – tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps. PMID:20539752

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands.

PubMed

Miller, Brian W; Breckheimer, Ian; McCleary, Amy L; Guzmán-Ramirez, Liza; Caplow, Susan C; Jones-Smith, Jessica C; Walsh, Stephen J

2010-05-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.

Approach to equilibrium of a quantum system and generalization of the Montroll-Shuler equation for vibrational relaxation of a molecular oscillator

NASA Astrophysics Data System (ADS)

Kenkre, V. M.; Chase, M.

2017-08-01

The approach to equilibrium of a quantum mechanical system in interaction with a bath is studied from a practical as well as a conceptual point of view. Explicit memory functions are derived for given models of bath couplings. If the system is a harmonic oscillator representing a molecule in interaction with a reservoir, the generalized master equation derived becomes an extension into the coherent domain of the well-known Montroll-Shuler equation for vibrational relaxation and unimolecular dissociation. A generalization of the Bethe-Teller result regarding energy relaxation is found for short times. The theory has obvious applications to relaxation dynamics at ultra-short times as in observations on the femtosecond time scale and to the investigation of quantum coherence at those short times. While vibrational relaxation in chemical physics is a primary target of the study, another system of interest in condensed matter physics, an electron or hole in a lattice subjected to a strong DC electric field that gives rise to well-known Wannier-Stark ladders, is naturally addressed with the theory. Specific system-bath interactions are explored to obtain explicit details of the dynamics. General phenomenological descriptions of the reservoir are considered rather than specific microscopic realizations.