Non-linear oscillations assessment of the distribution static compensator operating in voltage control mode

This article deals with the non-linear oscillations assessment of a distribution static comensator ooperating in voltage control mode using the bifurcation theory. A mathematical model of the distribution static compensator in the voltage control mode to carry out the bifurcation analysis is derived. The stabiity regions in the Thevein equivalent plane are computed. In addition, the stability regions in the control gains space, as well as the contour lines for different Floquet multipliers are computed. The AC and DC capacitor impacts on the stability are analyzed through the bifurcation theory. The observations are verified through simulaation studies. The computation of the stability region allows the assessment of the stable operating zones for a power system that includes a distribution static compensator operating in the voltage mode.

Semantic oscillations : encoding context and structure in complex valued holographic vectors

In computational linguistics, information retrieval and applied cognition, words and concepts are often represented as vectors in high dimensional spaces computed from a corpus of text. These high dimensional spaces are often referred to as Semantic Spaces. We describe a novel and efficient approach to computing these semantic spaces via the use of complex valued vector representations. We report on the practical implementation of the proposed method and some associated experiments. We also briefly discuss how the proposed system relates to previous theoretical work in Information Retrieval and Quantum Mechanics and how the notions of probability, logic and geometry are integrated within a single Hilbert space representation. In this sense the proposed system has more general application and gives rise to a variety of opportunities for future research.

Impact of traffic oscillations on freeway crash occurrences

Traffic oscillations are typical features of congested traffic flow that are characterized by recurring decelerations followed by accelerations (stop-and-go driving). The negative environmental impacts of these oscillations are widely accepted, but their impact on traffic safety has been debated. This paper describes the impact of freeway traffic oscillations on traffic safety. This study employs a matched case-control design using high-resolution traffic and crash data from a freeway segment. Traffic conditions prior to each crash were taken as cases, while traffic conditions during the same periods on days without crashes were taken as controls. These were also matched by presence of congestion, geometry and weather. A total of 82 cases and about 80,000 candidate controls were extracted from more than three years of data from 2004 to 2007. Conditional logistic regression models were developed based on the case-control samples. To verify consistency in the results, 20 different sets of controls were randomly extracted from the candidate pool for varying control-case ratios. The results reveal that the standard deviation of speed (thus, oscillations) is a significant variable, with an average odds ratio of about 1.08. This implies that the likelihood of a (rear-end) crash increases by about 8% with an additional unit increase in the standard deviation of speed. The average traffic states prior to crashes were less significant than the speed variations in congestion.

Applications of wavelet transform for analysis of freeway traffic : bottlenecks, transient traffic, and traffic oscillations

This paper demonstrates the capabilities of wavelet transform (WT) for analyzing important features related to bottleneck activations and traffic oscillations in congested traffic in a systematic manner. In particular, the analysis of loop detector data from a freeway shows that the use of wavelet-based energy can effectively identify the location of an active bottleneck, the arrival time of the resulting queue at each upstream sensor location, and the start and end of a transition during the onset of a queue. Vehicle trajectories were also analyzed using WT and our analysis shows that the wavelet-based energies of individual vehicles can effectively detect the origins of deceleration waves and shed light on possible triggers (e.g., lane-changing). The spatiotemporal propagations of oscillations identified by tracing wavelet-based energy peaks from vehicle to vehicle enable analysis of oscillation amplitude, duration and intensity.

Freeway traffic oscillations : microscopic analysis of formations and propagations using Wavelet Transform

In this paper we identify the origins of stop-and-go (or slow-and-go) driving and measure microscopic features of their propagations by analyzing vehicle trajectories via Wavelet Transform. Based on 53 oscillation cases analyzed, we find that oscillations can be originated by either lane-changing maneuvers (LCMs) or car-following behavior (CF). LCMs were predominantly responsible for oscillation formations in the absence of considerable horizontal or vertical curves, whereas oscillations formed spontaneously near roadside work on an uphill segment. Regardless of the trigger, the features of oscillation propagations were similar in terms of propagation speed, oscillation duration, and amplitude. All observed cases initially exhibited a precursor phase, in which slow-and-go motions were localized. Some of them eventually transitioned into a well developed phase, in which oscillations propagated upstream in queue. LCMs were primarily responsible for the transition, although some transitions occurred without LCMs. Our findings also suggest that an oscillation has a regressive effect on car following behavior: a deceleration wave of an oscillation affects a timid driver (with larger response time and minimum spacing) to become less timid and an aggressive driver less aggressive, although this change may be short-lived. An extended framework of Newell’s CF is able to describe the regressive effects with two additional parameters with reasonable accuracy, as verified using vehicle trajectory data.

Neuronal nicotinic acetylcholine receptors as pharmacotherapeutic targets for the treatment of alcohol use disorders

Alcohol use disorders (AUDs) are complex and developing effective treatments will require the combination of novel medications and cognitive behavioral therapy approaches. Epidemiological studies have shown there is a high correlation between alcohol consumption and tobacco use, and the prevalence of smoking in alcoholics is as high as 80% compared to about 30% for the general population. Both preclinical and clinical data provide evidence that nicotine administration increases alcohol intake and nonspecific nicotinic receptor antagonists reduce alcohol-mediated behaviors. As nicotine interacts specifically with the neuronal nicotinic acetylcholine receptor (nAChR) system, this suggests that nAChRs play an important role in the behavioral effects of alcohol. In this review, we discuss the importance of nAChRs for the treatment of AUDs and argue that the use of FDA approved nAChR ligands, such as varenicline and mecamylamine, approved as smoking cessation aids may prove to be valuable treatments for AUDs. We also address the importance of combining effective medications with behavioral therapy for the treatment of alcohol dependent individuals.

Partial agonists of the [alpha]3[beta]4[ast] neuronal nicotinic acetylcholine receptor reduce ethanol consumption and seeking in rats

Alcohol use disorders (AUDs) impact millions of individuals and there remain few effective treatment strategies. Despite evidence that neuronal nicotinic acetylcholine receptors (nAChRs) have a role in AUDs, it has not been established which subtypes of the nAChR are involved. Recent human genetic association studies have implicated the gene cluster CHRNA3-CHRNA5-CHRNB4 encoding the α3, α5, and β4 subunits of the nAChR in susceptibility to develop nicotine and alcohol dependence; however, their role in ethanol-mediated behaviors is unknown due to the lack of suitable and selective research tools. To determine the role of the α3, and β4 subunits of the nAChR in ethanol self-administration, we developed and characterized high-affinity partial agonists at α3β4 nAChRs, CP-601932, and PF-4575180. Both CP-601932 and PF-4575180 selectively decrease ethanol but not sucrose consumption and operant self-administration following long-term exposure. We show that the functional potencies of CP-601932 and PF-4575180 at α3β4 nAChRs correlate with their unbound rat brain concentrations, suggesting that the effects on ethanol self-administration are mediated via interaction with α3β4 nAChRs. Also varenicline, an approved smoking cessation aid previously shown to decrease ethanol consumption and seeking in rats and mice, reduces ethanol intake at unbound brain concentrations that allow functional interactions with α3β4 nAChRs. Furthermore, the selective α4β2(*) nAChR antagonist, DHβE, did not reduce ethanol intake. Together, these data provide further support for the human genetic association studies, implicating CHRNA3 and CHRNB4 genes in ethanol-mediated behaviors. CP-601932 has been shown to be safe in humans and may represent a potential novel treatment for AUDs.

A behavioural car-following model that captures traffic oscillations

This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.

Neuronal nicotinic acetylcholine receptors : neuroplastic changes underlying alcohol and nicotine addictions

Addictive drugs can activate systems involved in normal reward-related learning, creating long-lasting memories of the drug's reinforcing effects and the environmental cues surrounding the experience. These memories significantly contribute to the maintenance of compulsive drug use as well as cue-induced relapse which can occur even after long periods of abstinence. Synaptic plasticity is thought to be a prominent molecular mechanism underlying drug-induced learning and memories. Ethanol and nicotine are both widely abused drugs that share a common molecular target in the brain, the neuronal nicotinic acetylcholine receptors (nAChRs). The nAChRs are ligand-gated ion channels that are vastly distributed throughout the brain and play a key role in synaptic neurotransmission. In this review, we will delineate the role of nAChRs in the development of ethanol and nicotine addiction. We will characterize both ethanol and nicotine's effects on nAChR-mediated synaptic transmission and plasticity in several key brain areas that are important for addiction. Finally, we will discuss some of the behavioral outcomes of drug-induced synaptic plasticity in animal models. An understanding of the molecular and cellular changes that occur following administration of ethanol and nicotine will lead to better therapeutic strategies.

The α5 neuronal nicotinic acetylcholine receptor subunits plays an important role in the sedative effects of ethanol but does not modulate consumption in mice

Alcohol use disorders (AUDs) are a major public health problem, and the few treatment options available to those seeking treatment offer only modest success rates. There remains a need to identify novel targets for the treatment of AUDs. The neuronal nicotinic acetylcholine receptors (nAChRs) represent a potential therapeutic target in the brain, as recent human genetic studies have implicated gene variants in the α5 nAChR subunit as high risk factors for developing alcohol dependence. Here, we evaluate the role of 5* nAChR for ethanol-mediated behaviors using α5+/+ and α5-/- mice. We characterized the effect of hypnotic doses of ethanol and investigated drinking behavior using an adapted Drinking-in-the Dark (DID) paradigm that has been shown to induce high ethanol consumption in mice. We found the α5 subunit to be critical in mediating the sedative effects of ethanol. The α5-/- mice showed slower recovery from ethanol-induced sleep, as measured by loss of righting reflex. Additionally the α5-/- mice showed enhanced impairment to ethanol-induced ataxia. We found the initial sensitivity to ethanol and ethanol metabolism to be similar in both α5+/+ and α5-/- mice. Hence the enhanced sedation is likely due to a difference in the acute tolerance of ethanol in mice deficient of the α5 subunit. However the α5 subunit did not play a role in ethanol consumption for ethanol concentrations ranging from 5% to 30% in the DID paradigm. Additionally, varenicline (Chantix®) was effective in reducing ethanol intake in α5-/- mice. Together, our data suggest that the α5 nAChR subunit is important for the sedative hypnotic doses of ethanol but does not play a role in ethanol consumption. Varenicline can be a treatment option even when there is loss of function of the α5 nAChR subunit.

Microscopic traffic hysteresis in traffic oscillations : a behavioral perspective

This paper studies traffic hysteresis arising in traffic oscillations from a behavioral perspective. It is found that the occurrence and type of traffic hysteresis is closely correlated with driver behavior when experiencing traffic oscillations and with the time driver reaction begins relative to the starting deceleration wave. Statistical results suggest that driver behavior is different depending on its position along the oscillation. This suggests that different car-following models should be used inside the different stages of an oscillation in order to replicate realistic congestion features.

Investigation of a neuronal nitric oxide synthase gene (NOS1) polymorphism in a multiple sclerosis population

Multiple Sclerosis (MS) is a chronic neurological disease characterized by demyelination associated with infiltrating white blood cells in the central nervous system (CNS). Nitric oxide synthases (NOS) are a family of enzymes that control the production of nitric oxide. It is possible that neuronal NOS could be involved in MS pathophysiology and hence the nNOS gene is a potential candidate for involvement in disease susceptibility. The aim of this study was to determine whether allelic variation at the nNOS gene locus is associated with MS in an Australian cohort. DNA samples obtained from a Caucasian Australian population affected with MS and an unaffected control population, matched for gender, age and ethnicity, were genotyped for a microsatellite polymorphism in the promoter region of the nNOS gene. Allele frequencies were compared using chi-squared based statistical analyses with significance tested by Monte Carlo simulation. Allelic analysis of MS cases and controls produced a chi-squared value of 5.63 with simulated P = 0.96 (OR(max) = 1.41, 95% CI: 0.926-2.15). Similarly, a Mann-Whitney U analysis gave a non-significant P-value of 0.377 for allele distribution. No differences in allele frequencies were observed for gender or clinical course subtype (P > 0.05). Statistical analysis indicated that there is no association of this nNOS variant and MS and hence the gene does not appear to play a genetically significant role in disease susceptibility.

Fluorescence detection of plant extracts that affect neuronal voltage-gated Ca2+ channels

Structurally novel compounds able to block voltage-gated Ca2+ channels (VGCCs) are currently being sought for the development of new drugs directed at neurological disorders. Fluorescence techniques have recently been developed to facilitate the analysis of VGCC blockers in a multi-well format. By utilising the small cell lung carcinoma cell line, NCI-H146, we were able to detect changes in intracellular Ca2+ concentration ([Ca2+]i) using a fluorescence microplate reader. NCI-H146 cells have characteristics resembling those of neuronal cells and express multiple VGCC subtypes, including those of the L-, N- and P-type. We found that K+-depolarisation of fluo-3 loaded NCI-H146 cells causes a rapid and transient increase in fluorescence, which was readily detected in a 96-well plate. Extracts of Australian plants, including those used traditionally as headache or pain treatments, were tested in this study to identify those affecting Ca2+ influx following membrane depolarisation of NCI-H146 cells. We found that E. bignoniiflora, A. symphyocarpa and E. vespertilio caused dose-dependent inhibition of K+-depolarised Ca2+ influx, with IC50 values calculated to be 234, 548 and 209 μg/ml, respectively. This data suggests an effect of these extracts on the function of VGCCs in these cells. Furthermore, we found similar effects using a fluorescence laser imaging plate reader (FLIPR) that allows simultaneous measurement of real-time fluorescence in a multi-well plate. Our results indicate that the dichloromethane extract of E. bignoniiflora and the methanolic extract of E. vespertilio show considerable promise as antagonists of neuronal VGCCs. Further analysis is required to characterise the function of the bioactive constituents in these extracts and determine their selectivity on VGCC subtypes.