Dependence of transient dynamics in a class-C laser upon variation of inversion with time

The transient statistics of a gain-switched coherently pumped class-C laser displays a linear correlation between the first passage time and subsequent peak intensity. Measurements are reported showing a positive or negative sign of this linear correlation, controlled through the switching time and the laser detuning. Further measurements of the small-signal laser gain combined with calculations involving a three-level laser model indicate that this sign fundamentally depends upon the way the laser inversion varies during the gain switching, despite the added dynamics of the laser polarization in the class-C laser. [S1050-2947(97)07112-6].

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Capillary network models for transport in packed beds: Considerations of pore aspect ratio

The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Chronic ethanol treatment leads to increased ornithine decarboxylase activity: Implications for a role of polyamines in ethanol dependence and withdrawal

Recent research has focused on the N-methyl-D-aspartate receptor system as a major site of ethanol action in the brain and specifically on compensatory changes in the expression of the polyamine-sensitive NR2B subunit. Therefore, we examined the effects of chronic ethanol treatment on polyamine homeostasis in the rat brain. Wistar rats were made dependent by ethanol vapor inhalation. This caused a rise in hippocampal ornithine decarboxylase (ODC) activity that was correlated with the appearance of physiological dependence. ODC activity returned to control levels within 3 days of ethanol withdrawal. Enzyme activity also increased in the cerebral cortex, striatum, and cerebellum of the ethanol-dependent rats. The concentration of the polyamines (putrescine, spermidine, and spermine) in the hippocampus was increased in ethanol-dependent rats. Injection of the ODC inhibitor, gamma-difluoromethylornithine (500 mg/kg) at the onset of withdrawal resulted in a significant reduction in the severity of withdrawal behaviors. The level of ODC activity and the severity of withdrawal behaviors were positively correlated. Perturbed polyamine homeostasis may represent an important molecular component in the initiation of ethanol withdrawal behaviors in the ethanol-dependent rat.

Patient matching in treatment for alcohol dependence: is the null hypothesis still alive and well?

In the light of Project MATCH, is it reasonable to accept the null hypothesis that there are no clinically signi® cant matching effects between patient characteristics and cognitive± behaviour therapy (CBT), motivational enhancement therapy (MET) and Twelve-Step facilitation therapy (TSF)? The Project MATCH investigators considered the null hypothesis but preferred the alternative hypothesis that further analysis may reveal combinations of patient and therapist characteristics that show more substantial matching effects than any of the variables that they have examined to date.1

Role of maintenance treatment in opioid dependence

Methadone maintenance treatment (MMT) involves the daily administration of the oral opioid agonist methadone as a treatment for opioid dependence-a persistent disorder with a substantial risk of premature death. MMT improves health and reduces illicit heroin use, infectious-disease transmission, and overdose death. However, its effectiveness is compromised if low maintenance doses of methadone (

Asymmetry and duration dependence in Australian GDP and unemployment

The per iodic structure of business cycles suggests that significant asymmetries are present over different phases of the cycle. This paper uses markov regime-switching models with fixed and duration dependent transition probabilities to directly model expansions, contractions and durations in Australian GDP growth and unemployment growth. Evidence is found of significant asymmetry in growth rates across expansions and contractions for both series. GDP contractions exhibit duration dependence implying that as output recessions age the likelihood of switching into an expansion phase increases. Unemployment growth does not exhibit duration dependence in either phase. Evidence is also presented that non-linearities in unemployment growth are well explained by the asymmetries in the GDP growth cycle. The analysis suggests that recessions are periods of rapid and intense job destruction, that Australian unemployment tends to ratchet up in recessionary periods and, in contrast to US and UK studies, that shocks to Australian unemployment growth are more persistent in recessions than expansions. [E37 C5 C41].

Self-efficacy for refusal mediated by outcome expectancies in the prediction of alcohol-dependence amongst young adults

The present study examined the relative importance of outcome expectancies and self-efficacy [1] in the prediction of alcohol dependence [2] and alcohol consumption in a sample of young adult drinkers drawn from a milieu previously reported as supportive of risky drinking. In predicting alcohol dependence, outcome expectancies were found to mediate self-efficacy and the same pattern was found for both males and females. This suggests that male and female drinkers may become more similar as they progress along the drinking continuum from risky drinking to dependent drinking. However, in women, in comparison to men, a greater array of expectancies and self-efficacy scales were found to predict heavy drinking, as measured by quantity and frequency. These results suggest that heavy drinking women are particularly at risk of developing drinking related complications and that preventative education needs to take into account gender differences.

An evaluation of the time dependence of the anisotropy of the water diffusion tensor in acute human ischemia

We have performed MRI examinations to determine the water diffusion tensor in the brain of six patients who were admitted to the hospital within 12 h after the onset of cerebral ischemic symptoms. The examinations have been carried out immediately after admission, and thereafter at varying intervals up to 90 days post admission. Maps of the trace of the diffusion tensor, the fractional anisotropy and the lattice index, as well as maps of cerebral blood perfusion parameters, were generated to quantitatively assess the character of the water diffusion tensor in the infarcted area. In patients with significant perfusion deficits and substantial lesion volume changes, four of six cases, our measurements show a monotonic and significant decrease in the diffusion anisotropy within the ischemic lesion as a function of time. We propose that retrospective analysis of this quantity, in combination with brain tissue segmentation and cerebral perfusion maps, may be used in future studies to assess the severity of the ischemic event. (C) 1999 Elsevier Science Inc.

Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

Is naltrexone a cure for heroin dependence? [Editorial]

No Abstract