It is demonstrated that any realistic model of quintessence should be based on Supergravity since, when the scalar field is on tracks today, Q ≈ m Pl. This improves the agreement between theoretical predictions and the current observations. In particular, a generic property is that ratio ωQ ≡ pQ/ρQ is pushed towards −1. A string-inspired model is proposed where the potential is given by V (Q) =...

-An array of sigmoidal tension gashes from the Idaho-Wyoming thrust belt changes laterally into a continuous vein. Detailed mechanical twin analysis was used to determine the strain variation in the optically and chemically homogeneous blocky calcite filling. In the continuous portion of the vein complex, the shortening axes are parallel to the vein boundary. However, the orientation of the sho...

This paper demonstrates how the sigmoid activation function of neural-mass models can be understood in terms of the variance or dispersion of neuronal states. We use this relationship to estimate the probability density on hidden neuronal states, using non-invasive electrophysiological (EEG) measures and dynamic casual modelling. The importance of implicit variance in neuronal states for neural...

Buffer space in packet switching nodes is an important network resource. Shared buffer switches are prone to high packet losses and unfair use of buffer space. The use of a buffer management scheme is necessary to overcome these problems. This paper investigates the performance of Sigmoid Function Threshold scheme by means of simulations. This scheme regulates the usage of shared buffer space b...

In this paper, is proposed a method to implement in FPGA (Field Programmable Gate Array) circuits different approximation of the sigmoid function. Three previously published piecewise linear and one piecewise second-order approximation are analyzed from point of view of hardware resources utilization, induced errors caused by the approximation function and bits representation, power consumption...

Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of MVN is not differentiable. Therefore, we can not apply backpropagation when constructing multilayer structures. In this paper, we propose a new neuron model, MVN-sig, to simulate ...

This paper proposes a tone-reproduction method that uses a neural network and modified sigmoid function to perceptually compensate the characteristics of an output device. An inkjet printer was used as the output device the characteristics of which were analyzed by colorimetric measurement. The measured device-characteristic data for primary inks were then used to model the I/O characteristics ...

We present a multi-agent collaboration algorithm to recruit an approximate number of individually simple robots with controllable variance. We propose a sigmoid response threshold function motivated by task allocation in social insects, and describe macro-level models backed by micro-level simulations to predict the resulting team sizes and their variance. We show that the slope of the response...