Cells sense and predict their environment via energy-dissipating pathways. However, it is unclear whether dissipation helps or harms prediction. Here we study dissipation and prediction for a minimal sensory module of receptors that reversibly bind ligand. We find that the module performs short-term prediction optimally when operating in an adiabatic regime where dissipation vanishes. In contra...

The last few decades have witnessed rapid progress in the field of type-2 fuzzy systems and in particular interval type-2 fuzzy systems. Encouraged by this progress, we present in this paper some theoretical foundations and applications of interval-valued fuzzy morphological associative memories (IV-FMAMs) as a rule-based system. We perform simulations concerning the application of IV-FMAMs to ...

In recent years, more and people choose to travel by bus save time economic costs, but the problem of inaccurate arrival has become increasingly prominent. The reason is lack scientific planning departure time. This paper takes passenger flow as an important basis for interval, proposes a prediction method based on wavelet neural network, uses intelligent optimization algorithm study elastic in...

A new approach to solve Chance constrained Portfolio Optimization Problems (CPOPs) without using the Monte Carlo simulation is proposed. Specifically, according to Chebyshev inequality, the prediction interval of a stochastic function value included in CPOP is estimated from a set of samples. By using the prediction interval, CPOP is transformed into Lower-bound Portfolio Optimization Problem (...

We propose an ultra-short-term dynamic interval predictor (DIP) of solar irradiance. Our DIP relies on experimentally observed correlations between the derivative of the solar irradiance and the forecast error in the next time-step. The main originalities of this DIP are (i) its independence from the method used for the point forecast of solar irradiance, (ii) its independence from the error di...

This paper studies performance of both point and interval predictors of technical ine ciency in the stochastic production frontier model using a Monte Carlo experiment. In point prediction we use the Jondrow et al. (1980) results, while for interval prediction the Horrace and Schmidt (1996) and Hjalmarsson et al. (1996) results are used. When ML estimators are used we nd negative bias in point ...

In this paper, we show that prediction algorithms in the least mean square error sense prove better in a burst rather than in a packet switching network. For the latter, further information about the packet arrival distribution within the prediction interval is required. Regarding burst switching, we compare Optical Burst Switching networks with and without linear prediction to conclude that li...

BACKGROUND Sevoflurane may prolong the corrected QT (QTc) interval in healthy humans when administered for induction and maintenance of anesthesia. Little information is available about the dose-response relationship of sevoflurane on the QTc interval. We performed a pharmacodynamic analysis of the relationship between end-tidal sevoflurane concentration (CET) and the QTc. METHODS Twenty-one ...

The system for estimating days open for cows with no subsequent lactation was examined to determine if estimates should vary depending on pregnancy diagnosis. Pregnancy diagnosis information was unavailable when the original prediction system was developed, but collection was begun in 2002. New prediction equations were estimated from nearly 1.1 million Holstein lactations for 20-d intervals fr...