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https://www.readbyqxmd.com/read/28749344/giant-magnetoresistive-biosensor-array-for-detecting-magnetorelaxation
#1
Xiahan Zhou, Chih-Cheng Huang, Drew A Hall
In this paper, a time-domain magnetorelaxometry biosensing scheme is presented using giant magnetoresistive (GMR) sensors to measure the fast relaxation response of superparamagnetic magnetic nanoparticles (MNPs) in a pulsed magnetic field. The system consists of an 8 × 10 GMR sensor array, a Helmholtz coil, an electromagnet driver, and an integrator-based analog front-end needed to capture the fast relaxation dynamics of MNPs. A custom designed electromagnet driver and Helmholtz coil improve the switch-off speed to >5 Oe/μs, limiting the dead zone time to <10 μs, and thus enables the system to monitor fast relaxation processes of 30 nm MNPs...
August 2017: IEEE Transactions on Biomedical Circuits and Systems
https://www.readbyqxmd.com/read/28748930/neuromorphic-computing-with-nanoscale-spintronic-oscillators
#2
Jacob Torrejon, Mathieu Riou, Flavio Abreu Araujo, Sumito Tsunegi, Guru Khalsa, Damien Querlioz, Paolo Bortolotti, Vincent Cros, Kay Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Mark D Stiles, Julie Grollier
Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 10(8) oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way...
July 26, 2017: Nature
https://www.readbyqxmd.com/read/28748400/reconstructing-genetic-regulatory-networks-using-two-step-algorithms-with-the-differential-equation-models-of-neural-networks
#3
Chi-Kan Chen
BACKGROUND: The identification of genetic regulatory networks (GRNs) provides insights into complex cellular processes. A class of recurrent neural networks (RNNs) captures the dynamics of GRN. Algorithms combining the RNN and machine learning schemes were proposed to reconstruct small-scale GRNs using gene expression time series. RESULTS: We present new GRN reconstruction methods with neural networks. The RNN is extended to a class of recurrent multilayer perceptrons (RMLPs) with latent nodes...
July 26, 2017: Interdisciplinary Sciences, Computational Life Sciences
https://www.readbyqxmd.com/read/28745013/moving-alcohol-prevention-research-forward-part-ii-new-directions-grounded-in-community-based-system-dynamics-modeling
#4
Yorghos Apostolopoulos, Michael K Lemke, Adam E Barry, Kristen Hassmiller Lich
BACKGROUNDS AND AIMS: Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources, and model validation...
July 25, 2017: Addiction
https://www.readbyqxmd.com/read/28742041/admm-%C3%A2-projective-dynamics-fast-simulation-of-hyperelastic-models-with-dynamic-constraints
#5
Matthew Overby, George E Brown, Jie Li, Rahul Narain
We apply the alternating direction method of multipliers (ADMM) optimization algorithm to implicit time integration of elastic bodies, and show that the resulting method closely relates to the recently proposed projective dynamics algorithm. However, as ADMM is a general purpose optimization algorithm applicable to a broad range of objective functions, it permits the use of nonlinear constitutive models and hard constraints while retaining the speed, parallelizability, and robustness of projective dynamics...
July 24, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28741845/self-regulation-shift-theory-a-dynamic-systems-approach-to-traumatic-stress
#6
Charles C Benight, Kotaro Shoji, Douglas L Delahanty
Self-regulation shift theory (SRST) is a threshold theory explaining self-regulation following trauma that utilizes nonlinear dynamics to capture systemic shifts in trauma adaptation. Cusp catastrophe modeling tests nonlinear changes in an outcome (e.g., posttraumatic distress) based on an identified bifurcation factor under specific conditions (i.e., asymmetry variables). We evaluated two cusp models in a motor vehicle accident (MVA) database and then confirmed findings within a similar dataset. Based on SRST, we tested coping self-efficacy (CSE) as the bifurcation factor and a set of asymmetry controlling variables...
July 25, 2017: Journal of Traumatic Stress
https://www.readbyqxmd.com/read/28740090/chaotic-time-series-prediction-for-glucose-dynamics-in-type-1-diabetes-mellitus-using-regime-switching-models
#7
Mirela Frandes, Bogdan Timar, Romulus Timar, Diana Lungeanu
In patients with type 1 diabetes mellitus (T1DM), glucose dynamics are influenced by insulin reactions, diet, lifestyle, etc., and characterized by instability and nonlinearity. With the objective of a dependable decision support system for T1DM self-management, we aim to model glucose dynamics using their nonlinear chaotic properties. A group of patients was monitored via continuous glucose monitoring (CGM) sensors for several days under free-living conditions. We assessed the glycemic variability (GV) and chaotic properties of each time series...
July 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28737487/task-dependent-recurrent-dynamics-in-visual-cortex
#8
Satohiro Tajima, Kowa Koida, Chihiro I Tajima, Hideyuki Suzuki, Kazuyuki Aihara, Hidehiko Komatsu
The capacity for flexible sensory-action association in animals has been related to context-dependent attractor dynamics outside the sensory cortices. Here we report a line of evidence that flexibly modulated attractor dynamics during task switching are already present in the higher visual cortex in macaque monkeys. With a nonlinear decoding approach, we can extract the particular aspect of the neural population response that reflects the task-induced emergence of bistable attractor dynamics in a neural population, which could be obscured by standard unsupervised dimensionality reductions such as PCA...
July 24, 2017: ELife
https://www.readbyqxmd.com/read/28734500/a-new-online-delay-estimation-based-robust-adaptive-stabilizer-for-multi-input-neutral-systems-with-unknown-actuator-nonlinearities
#9
A H Tahoun
This paper studies the problem of actuator-nonlinearities compensation in the multi-input uncertain neutral systems. The neutral systems with different unknown time-varying delays, unmodeled dynamics, nonlinear perturbations and disturbances are considered. A new methodology based on the online estimation of the delays to compensate for the effects generated by dead-zone and saturation, acting in series on a system's input are presented. The online estimations of the unknown delays are accomplished by adaptive laws that guarantee the exponential stabilities of the estimated delays...
July 19, 2017: ISA Transactions
https://www.readbyqxmd.com/read/28731795/plant-size-and-competitive-dynamics-along-nutrient-gradients
#10
Deborah E Goldberg, Jason P Martina, Kenneth J Elgersma, William S Currie
Resource competition theory in plants has focused largely on resource acquisition traits that are independent of size, such as traits of individual leaves or roots or proportional allocation to different functions. However, plants also differ in maximum potential size, which could outweigh differences in module-level traits. We used a community ecosystem model called mondrian to investigate whether larger size inevitably increases competitive ability and how size interacts with nitrogen supply. Contrary to the conventional wisdom that bigger is better, we found that invader success and competitive ability are unimodal functions of maximum potential size, such that plants that are too large (or too small) are disproportionately suppressed by competition...
August 2017: American Naturalist
https://www.readbyqxmd.com/read/28730355/charge-transport-in-dna-model-with-vibrational-and-rotational-coupling-motions
#11
H Ngoubi, G H Ben-Bolie, T C Kofané
The dynamics of the Peyrard-Bishop model for vibrational motion of DNA dynamics, which has been extended by taking into account the rotational motion for the nucleotides (Silva et al., J. Biol. Phys. 34, 511-519, 2018) is studied. We report on the presence of the modulational instability (MI) of a plane wave for charge migration in DNA and the generation of soliton-like excitations in DNA nucleotides. We show that the original differential-difference equation for the DNA dynamics can be reduced in the continuum approximation to a set of three coupled nonlinear equations...
July 20, 2017: Journal of Biological Physics
https://www.readbyqxmd.com/read/28729748/on-flare-cme-characteristics-from-sun-to-earth-combining-remote-sensing-image-data-with-in-situ-measurements-supported-by-modeling
#12
Manuela Temmer, Julia K Thalmann, Karin Dissauer, Astrid M Veronig, Johannes Tschernitz, Jürgen Hinterreiter, Luciano Rodriguez
We analyze the well-observed flare and coronal mass ejection (CME) from 1 October 2011 (SOL2011-10-01T09:18) covering the complete chain of effects - from Sun to Earth - to better understand the dynamic evolution of the CME and its embedded magnetic field. We study in detail the solar surface and atmosphere associated with the flare and CME using the Solar Dynamics Observatory (SDO) and ground-based instruments. We also track the CME signature off-limb with combined extreme ultraviolet (EUV) and white-light data from the Solar Terrestrial Relations Observatory (STEREO)...
2017: Solar Physics
https://www.readbyqxmd.com/read/28729160/echo-time-dependence-of-the-bold-response-transients-a-window-into-brain-functional-physiology
#13
Martin Havlicek, Dimo Ivanov, Benedikt A Poser, Kamil Uludag
The blood oxygenation level-dependent (BOLD) fMRI response to neuronal activation results from a complex interplay of induced metabolic and vascular changes. Thus, its transients, such as initial overshoot and post-stimulus undershoot, provide a window into the dynamic relationships of the underlying physiological variables. In this study, we propose multi-echo fMRI as a tool to investigate the physiological underpinnings of the BOLD signal, in particular, and brain functional physiology, in general. In the human visual cortex at 3 T, we observed that the BOLD response is nonlinearly dependent on echo-time (TE) and the amount of nonlinearity varies during the entire time-course...
July 17, 2017: NeuroImage
https://www.readbyqxmd.com/read/28727850/hybrid-cubature-kalman-filtering-for-identifying-nonlinear-models-from-sampled-recording-estimation-of-neuronal-dynamics
#14
Mahmoud K Madi, Fadi N Karameh
Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled...
2017: PloS One
https://www.readbyqxmd.com/read/28727566/model-free-adaptive-control-for-unknown-nonlinear-zero-sum-differential-game
#15
Xiangnan Zhong, Haibo He, Ding Wang, Zhen Ni
In this paper, we present a new model-free globalized dual heuristic dynamic programming (GDHP) approach for the discrete-time nonlinear zero-sum game problems. First, the online learning algorithm is proposed based on the GDHP method to solve the Hamilton-Jacobi-Isaacs equation associated with H∞ optimal regulation control problem. By setting backward one step of the definition of performance index, the requirement of system dynamics, or an identifier is relaxed in the proposed method. Then, three neural networks are established to approximate the optimal saddle point feedback control law, the disturbance law, and the performance index, respectively...
July 17, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28727547/designing-and-implementation-of-stable-sinusoidal-rough-neural-identifier
#16
Ghasem Ahmadi, Mohammad Teshnehlab
A rough neuron is defined as a pair of conventional neurons that are called the upper and lower bound neurons. In this paper, the sinusoidal rough-neural networks (SR-NNs) are used to identify the discrete dynamic nonlinear systems (DDNSs) with or without noise in series-parallel configuration. In the identification of periodic nonlinear systems, sinusoidal activation functions provide more efficient neural networks than the sigmoidal activation functions. Based on the Lyapunov stability theory, an online learning algorithm is developed to train the SR-NNs...
August 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28723910/estimating-mono-and-bi-phasic-regression-parameters-using-a-mixture-piecewise-linear-bayesian-hierarchical-model
#17
Rui Zhao, Paul Catalano, Victor G DeGruttola, Franziska Michor
The dynamics of tumor burden, secreted proteins or other biomarkers over time, is often used to evaluate the effectiveness of therapy and to predict outcomes for patients. Many methods have been proposed to investigate longitudinal trends to better characterize patients and to understand disease progression. However, most approaches assume a homogeneous patient population and a uniform response trajectory over time and across patients. Here, we present a mixture piecewise linear Bayesian hierarchical model, which takes into account both population heterogeneity and nonlinear relationships between biomarkers and time...
2017: PloS One
https://www.readbyqxmd.com/read/28716060/nonlinear-joint-models-for-individual-dynamic-prediction-of-risk-of-death-using-hamiltonian-monte-carlo-application-to-metastatic-prostate-cancer
#18
Solène Desmée, France Mentré, Christine Veyrat-Follet, Bernard Sébastien, Jérémie Guedj
BACKGROUND: Joint models of longitudinal and time-to-event data are increasingly used to perform individual dynamic prediction of a risk of event. However the difficulty to perform inference in nonlinear models and to calculate the distribution of individual parameters has long limited this approach to linear mixed-effect models for the longitudinal part. Here we use a Bayesian algorithm and a nonlinear joint model to calculate individual dynamic predictions. We apply this approach to predict the risk of death in metastatic castration-resistant prostate cancer (mCRPC) patients with frequent Prostate-Specific Antigen (PSA) measurements...
July 17, 2017: BMC Medical Research Methodology
https://www.readbyqxmd.com/read/28715007/the-covalently-bound-diazo-group-as-an-infrared-probe-for-hydrogen-bonding-environments
#19
Min You, Liyuan Liu, Wenkai Zhang
Covalently bound diazo groups are frequently found in biomolecular substrates. The C[double bond, length as m-dash]N[double bond, length as m-dash]N asymmetric stretching vibration (νas) of the diazo group has a large extinction coefficient and appears in an uncongested spectral region. To evaluate the solvatochromism of the C[double bond, length as m-dash]N[double bond, length as m-dash]N νas band for studying biomolecules, we recorded the infrared (IR) spectra of a diazo model compound, 2-diazo-3-oxo-butyric acid ethyl ester, in different solvents...
July 26, 2017: Physical Chemistry Chemical Physics: PCCP
https://www.readbyqxmd.com/read/28714094/selective-high-frequency-mechanical-actuation-driven-by-the-vo2-electronic-instability
#20
Nicola Manca, Luca Pellegrino, Teruo Kanki, Warner J Venstra, Giordano Mattoni, Yoshiyuki Higuchi, Hidekazu Tanaka, Andrea D Caviglia, Daniele Marré
Relaxation oscillators consist of periodic variations of a physical quantity triggered by a static excitation. They are a typical consequence of nonlinear dynamics and can be observed in a variety of systems. VO2 is a correlated oxide with a solid-state phase transition above room temperature, where both electrical resistance and lattice parameters undergo a drastic change in a narrow temperature range. This strong nonlinear response allows to realize spontaneous electrical oscillations in the megahertz range under a DC voltage bias...
July 17, 2017: Advanced Materials
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