Search results for "quantitative"
showing 10 items of 2409 documents
Versatile optimization-based speed-up method for autofocusing in digital holographic microscopy
2021
We propose a speed-up method for the in-focus plane detection in digital holographic microscopy that can be applied to a broad class of autofocusing algorithms that involve repetitive propagation of an object wave to various axial locations to decide the in-focus position. The classical autofocusing algorithms apply a uniform search strategy, i.e., they probe multiple, uniformly distributed axial locations, which leads to heavy computational overhead. Our method substantially reduces the computational load, without sacrificing the accuracy, by skillfully selecting the next location to investigate, which results in a decreased total number of probed propagation distances. This is achieved by…
FPGA implementation of Spiking Neural Networks
2012
Abstract Spiking Neural Networks (SNN) have optimal characteristics for hardware implementation. They can communicate among neurons using spikes, which in terms of logic resources, means a single bit, reducing the logic occupation in a device. Additionally, SNN are similar in performance compared to other neural Artificial Neural Network (ANN) architectures such as Multilayer Perceptron, and others. SNN are very similar to those found in the biological neural system, having weights and delays as adjustable parameters. This work describes the chosen models for the implemented SNN: Spike Response Model (SRM) and temporal coding is used. FPGA implementation using VHDL language is also describe…
Simplified spiking neural network architecture and STDP learning algorithm applied to image classification
2015
Spiking neural networks (SNN) have gained popularity in embedded applications such as robotics and computer vision. The main advantages of SNN are the temporal plasticity, ease of use in neural interface circuits and reduced computation complexity. SNN have been successfully used for image classification. They provide a model for the mammalian visual cortex, image segmentation and pattern recognition. Different spiking neuron mathematical models exist, but their computational complexity makes them ill-suited for hardware implementation. In this paper, a novel, simplified and computationally efficient model of spike response model (SRM) neuron with spike-time dependent plasticity (STDP) lear…
Noise-assisted persistence and recovery of memory state in a memristive spiking neuromorphic network
2021
Abstract We investigate the constructive role of an external noise signal, in the form of a low-rate Poisson sequence of pulses supplied to all inputs of a spiking neural network, consisting in maintaining for a long time or even recovering a memory trace (engram) of the image without its direct renewal (or rewriting). In particular, this unique dynamic property is demonstrated in a single-layer spiking neural network consisting of simple integrate-and-fire neurons and memristive synaptic weights. This is carried out by preserving and even fine-tuning the conductance values of memristors in terms of dynamic plasticity, specifically spike-timing-dependent plasticity-type, driven by overlappi…
Self-assembly of a bioelastomeric structure: solution dynamics and the spinodal and coacervation lines.
1990
The stability, metastability, and instability regions of aqueous solutions of a representative synthetic bioelastomeric polymer, poly (Val-Pro-Gly-Val-Gly), were determined by a combined use of elastic and quasi-elastic light scattering experiments. The approach followed here offers the attractive advantage of singling out the relevant contributions to the total scattering even in the presence of traces of noninteracting larger sized impurities. Conclusions so reached were checked by means of independent experiments. The present results provide descriptions of the very early events in the physics of bioelastogenesis in terms of general polymer science and phase transitions, and in terms of …
Genome-wide association analysis identifies six new loci associated with forced vital capacity
2014
Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P <5 x 10(-8)) with FVC in or near EFEMP1, BMP6, MIR129-2-HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispani…
Quantitative analysis of chromite ores using glass discs in moderate dilutions of lithium tetraborate by x-ray fluorescence spectrometry
2006
A method for the quantitative analysis of chromite ores by x-ray fluorescence spectrometry using beads is proposed. The work concerned the serious problems caused by the refractory nature of these materials which prevents the use of glass discs in x-ray fluorescence. An in-depth study was done to optimise the variables which influence the glass disc formation process. Sufficiently homogeneous glass discs were obtained under the following experimental conditions: lithium tetraborate as flux with moderate sample dilution (1:40), with the addition of one or two drops of LiBr solution(250 g l−1), at a temperature of 1200 °C for 30 min. The qualitative and semiquantitative results for the chromi…
Non-Equilibrium Markov State Modeling of the Globule-Stretch Transition
2016
We describe a systematic approach to construct coarse-grained Markov state models from molecular dynamics data of systems driven into a nonequilibrium steady state. We apply this method to study the globule-stretch transition of a single tethered model polymer in shear flow. The folding and unfolding rates of the coarse-grained model agree with the original detailed model. We demonstrate that the folding and unfolding proceeds through the same narrow region of configuration space but along different cycles.
Unfolding dynamics of small peptides biased by constant mechanical forces
2018
We show how multi-ensemble Markov state models can be combined with constant-force equilibrium simulations. Besides obtaining the unfolding/folding rates, Markov state models allow gaining detailed insights into the folding dynamics and pathways through identifying folding intermediates and misfolded structures. For two specific peptides, we demonstrate that the end-to-end distance is an insufficient reaction coordinate. This problem is alleviated through constructing models with multiple collective variables, for which we employ the time-lagged independent component analysis requiring only minimal prior knowledge. Our results show that combining Markov state models with constant-force simu…
ANALYTICAL DETERMINATION OF INITIAL CONDITIONS LEADING TO FIRING IN NERVE FIBERS
2007
International audience; An analytical solution characterizing initial conditions leading to action potential firing in smooth nerve fibers is determined, using the bistable equation. In the first place, we present a nontrivial stationary solution wave, then, using the perturbative method, we analyze the stability of this stationary wave. We show that it corresponds to a frontier between the initiation of the travelling waves and a decay to the resting state. Eventually, this analytical approach is extended to FitzHugh-Nagumo model.