A Quantum-mechanical description of ion motion within the confining potentials of voltage gated ion channels

Voltage gated channel proteins cooperate in the transmission of membrane potentials between nerve cells. With the recent progress in atomic-scaled biological chemistry it has now become established that these channel proteins provide highly correlated atomic environments that may maintain electronic coherences even at warm temperatures. Here we demonstrate solutions of the Schr\"{o}dinger equation that represent the interaction of a single potassium ion within the surrounding carbonyl dipoles in the Berneche-Roux model of the bacterial \textit{KcsA} model channel. We show that, depending on the surrounding carbonyl derived potentials, alkali ions can become highly delocalized in the filter region of proteins at warm temperatures. We provide estimations about the temporal evolution of the kinetic energy of ions depending on their interaction with other ions, their location within the oxygen cage of the proteins filter region and depending on different oscillation frequencies of the surrounding carbonyl groups. Our results provide the first evidence that quantum mechanical properties are needed to explain a fundamental biological property such as ion-selectivity in trans-membrane ion-currents and the effect on gating kinetics and shaping of classical conductances in electrically excitable cells.Comment: 12 pages, 8 figure

Forecasting Time-Series with Correlated Seasonality

A new approach is proposed for forecasting a time series with multiple seasonal patterns. A state space model is developed for the series using the single source of error approach which enables us to develop explicit models for both additive and multiplicative seasonality. Parameter estimates may be obtained using methods adapted from general exponential smoothing, although the Kalman filter may also be used. The proposed model is used to examine hourly and daily patterns in hourly data for both utility loads and traffic flows. Our formulation provides a model for several existing seasonal methods and also provides new options, which result in superior forecasting performance over a range of prediction horizons. The approach is likely to be useful in a wide range of applications involving both high and low frequency data, and it handles missing values in a straightforward manner.Exponential smoothing; Holt-Winters; Seasonality; Structural time series model

R-modes in the ocean of a magnetic neutron star

We study the dynamics of r-modes in the ocean of a magnetic neutron star. We modeled the star's ocean with a spherical rotating thin shell and assumed that the magnetic field symmetry axis is not aligned to the shell's spin axis. In the magnetohydrodynamic approximation, we calculate the frequency of $\ell=m$ r-modes in the shell of an incompressible fluid. Different r-modes with $\ell$ and $\ell\pm2$ are coupled by the {\it inclined} magnetic field. Kinematical secular effects for the motion of a fluid element in the shell undergoing $\ell=m=2$ r-mode are studied. The magnetic corrected drift velocity of a given fluid element undergoing the $\ell=m$ r-mode oscillations is obtained. The magnetic field increases the magnitude of the fluid drift produced by the r-mode drift velocity, the high-$\ell$ modes in the ocean fluid will damp faster than the low-$\ell$ ones.Comment: 24 pages, 5 figures, to appear in ApJ, v574 n2 August 1, 2002 issu

One-transit paths and steady-state of a non-equilibrium process in a discrete-time update

We have shown that the partition function of the Asymmetric Simple Exclusion Process with open boundaries in a sublattice-parallel updating scheme is equal to that of a two-dimensional one-transit walk model defined on a diagonally rotated square lattice. It has been also shown that the physical quantities defined in these systems are related through a similarity transformation.Comment: 8 pages, 2 figure

Cognitive Neuroscience of Pain

Non peer reviewe

Influence of particle size of the main cereal of the diet on egg production of brown laying hens

The influence of the screen size used to grind the main cereal of the diet on egg production, gastrointestinal tract (GIT) development, and body measurements was studied in hens from 17 to 49 wk of age. Diets formed a 2 × 5 factorial with 2 main cereals (corn vs. barley) and 5 screen sizes of the cereal (4, 6, 8, 10, and 12 mm). Each treatment was replicated 5 times. No interactions between main cereal and screen size were observed for any of the traits studied. Cereal type and screen size did not affect feed intake, egg production, BW gain, or quality traits of the eggs. Eggs tended to be larger (P = 0.092) in hens fed the barley diet than in hens fed the corn diet. Also, feed conversion ratio tended to increase (P = 0.081) when the cereal of the diet was ground with a 4-mm screen as compared with the average of the other diets. At 49 wk of age, the relative weight (% BW) of the GIT and gizzard was greater (P < 0.05) in hens fed barley than in hens fed corn. An increase in the screen size increased linearly the relative weight of the GIT (P = 0.089), gizzard (P < 0.01), and liver (P = 0.056). None of the other GIT traits or body measurements was affected by the main cereal or the screen size. In summary, barley can substitute up to 45% of the corn in diets for laying hens without any adverse effect on egg production. Therefore, the use of one or other cereal will depend on their relative cost. An increase in screen size improved gizzard development but had little effect on hen productivity. Within the range studied, the size of the screen used for grinding the cereal had little effect on hen productivity, although the use of a 4-mm screen might increase feed conversion ratio and gizzard development

Evaluation of SIP Signalling and QoS for VoIP over OLSR MANET Routing Protocol

Abstract: This paper evaluates the SIP based VoIP applications over the Optimized Link State Routing protocol (OLSR) as a proactive routing protocol for Mobile Ad Hoc Networks (MANET) using Static, Uniform, and Random mobility models. The evaluation considered PCM, LQS, IPTelephony, and GSM voice codecs to study the SIP signaling performance and the voice Quality of Service (QoS) for VoIP calls over OLSR MANET. The simulation efforts performed in OPNET Modeler 17.1. The results show that VoIP over OLSR MANET has good performance over Static and Uniform mobility models while it has variable performance with Random models. SIP signaling has large delays compared with the voice signaling which reduce the VoIP performance and increases the call's duration. In addition, GSM and LQS based VoIP calls have an acceptable level of QoS while PCM and IP-Telephony based VoIP calls have a low level of QoS over different types of mobility models. Furthermore, the location and the mobility of SIP server affect the number of hops and the SIP signaling performance between the different parties of the VoIP call

Estimating oil and gas recovery factors via machine learning: Database-dependent accuracy and reliability

With recent advances in artificial intelligence, machine learning (ML) approaches have become an attractive tool in petroleum engineering, particularly for reservoir characterizations. A key reservoir property is hydrocarbon recovery factor (RF) whose accurate estimation would provide decisive insights to drilling and production strategies. Therefore, this study aims to estimate the hydrocarbon RF for exploration from various reservoir characteristics, such as porosity, permeability, pressure, and water saturation via the ML. We applied three regression-based models including the extreme gradient boosting (XGBoost), support vector machine (SVM), and stepwise multiple linear regression (MLR) and various combinations of three databases to construct ML models and estimate the oil and/or gas RF. Using two databases and the cross-validation method, we evaluated the performance of the ML models. In each iteration 90 and 10% of the data were respectively used to train and test the models. The third independent database was then used to further assess the constructed models. For both oil and gas RFs, we found that the XGBoost model estimated the RF for the train and test datasets more accurately than the SVM and MLR models. However, the performance of all the models were unsatisfactory for the independent databases. Results demonstrated that the ML algorithms were highly dependent and sensitive to the databases based on which they were trained. Statistical tests revealed that such unsatisfactory performances were because the distributions of input features and target variables in the train datasets were significantly different from those in the independent databases (p-value < 0.05)