Development of a GIS-based safety analysis system

The objective of this study is to develop a safety analysis system that integrates crash data and roadway related information. This system is developed in a Geographic Information System (GIS) environment. It includes customized user interfaces to support queries to analyze data and to display results either in graphical or tabular formats. The system also affords the capabilities to export such results. The system permits analyses to be performed either at individual locations such as intersections, or for roadway segments. These analyses are based on data fields included in the crash database. The queries may be based on individual attributes recorded in the crash database or by combining multiple attributes from the database. The system also contains a module to identify high crash locations based on methods identified from the published literature. The methods range from those based on simple crash frequency to more complex methods which incorporate different weights for crashed based on the crash outcomes. An application of the system is illustrated using data from the Las Vegas metropolitan are in the state of Nevada; The system can be used to identify safety issues in a region, and to plan and deploy appropriate countermeasures to enhance safety. It also can be used to monitor the effectiveness of traffic safety programs. Such a system could also be used to screen projects and operational strategies to be funded in through appropriate funding processes

Modeling Long Term Impacts of Freeway Traffic Incidents on Travel Time Reliability

The objective of this study is to calibrate models of relationships between Travel Time Reliability measures and incident and traffic characteristics for a given highway segment

Modeling of Short Term and Long Term Impacts of Freeway Traffic Incidents using Historical Data

Traffic incidents are major contributors to non-recurring traffic congestion in most urban areas in United States. In addition to losses in terms of injury and property damage, freeway incidents also produce negative effects on the system including increased travel delays, fuel consumption and vehicle emissions. Incident management strategies are aimed at reducing the impacts caused by such incidents. Development of guidelines or models to quantify the impacts of these incidents on the society can aid in analyzing the effectiveness and economic feasibility of such incident management strategies. The first objective of this study is to calibrate models that relate the short term marginal impacts caused by freeway incidents with incident characteristics such as incident duration and the number of lanes blocked. These models will help in quantifying the impacts of freeway incidents on the system as a part of the evaluation of incident management strategies or other related freeway operation projects. Historical incident data from a Las Vegas freeway is used to calibrate these statistical models. Additionally, freeway operation-related information is obtained from the web-based Dashboard system maintained by the Regional Transportation Commission of Southern Nevada (RTC). Different statistical regression models calibrated relate freeway travel times, fuel consumption and emissions as functions of incident characteristics including incident duration, number of lanes blocked and time of day. Statistical measures of performance are used to evaluate the models and appropriate models are selected for recommendation. An additional component included in the impacts is the effect of the incident on the opposing direction of flow (rubbernecking). The second objective of this research is to calibrate the influence of incidents and their corresponding impacts. In this study, various travel time reliability indices are used in quantifying the long term impacts of freeway incidents. Travel time reliability is an important planning tool both from the user point of view as well as transportation planners. The findings of this part of the research can help in operational and economic evaluation of freeway safety and incident management projects from the point of travel time reliability. The models can also be used to quantify system-wide impacts of incident to provide economic justification for acquisition of funding for such projects. This contribution of this research is two-fold. First, statistical models are calibrated for quantifying the short-term impacts of freeway incidents on travel time, fuel consumption and vehicular emissions exclusively from field data as opposed to simulation and/or mathematical models. These marginal impacts can be used by transportation agencies and public organizations in the evaluation of incident management strategies. Also, given that these models are based on historical field data, accuracy is improved over existing models that are based on computer simulation. The second contribution of this research is in providing models that quantify the long-term impacts of incidents in terms of travel time reliability. This quantification is a principal benefit since models specific to traffic incident impacts and travel time reliability have rarely been explored previously. In addition, this analysis is also based on field data unlike the very few previous studies and is therefore an improvement in the understanding of relationships between travel time reliability and incident characteristics

Neurosteroid Actions in Memory and Neurologic/Neuropsychiatric Disorders

Memory dysfunction is a symptomatic feature of many neurologic and neuropsychiatric disorders; however, the basic underlying mechanisms of memory and altered states of circuitry function associated with disorders of memory remain a vast unexplored territory. The initial discovery of endogenous neurosteroids triggered a quest to elucidate their role as neuromodulators in normal and diseased brain function. In this review, based on the perspective of our own research, the advances leading to the discovery of positive and negative neurosteroid allosteric modulators of GABA type-A (GABAA), NMDA, and non-NMDA type glutamate receptors are brought together in a historical and conceptual framework. We extend the analysis toward a state-of-the art view of how neurosteroid modulation of neural circuitry function may affect memory and memory deficits. By aggregating the results from multiple laboratories using both animal models for disease and human clinical research on neuropsychiatric and age-related neurodegenerative disorders, elements of a circuitry level view begins to emerge. Lastly, the effects of both endogenously active and exogenously administered neurosteroids on neural networks across the life span of women and men point to a possible underlying pharmacological connectome by which these neuromodulators might act to modulate memory across diverse altered states of mind

Prodromal dysfunction of a5GABA-A receptor modulated hippocampal ripples occurs prior to neurodegeneration in the TgF344-AD rat model of Alzheimer's disease

Decades of research attempting to slow the onset of Alzheimer's disease (AD) indicates that a better understanding of memory will be key to the discovery of effective therapeutic approaches. Here, we ask whether prodromal neural network dysfunction might occur in the hippocampal trisynaptic circuit by using α5IA (an established memory enhancer and selective negative allosteric modulator of extrasynaptic tonically active α5GABA-A receptors) as a probe drug in TgF344-AD transgenic rats, a model for β-amyloid induced early onset AD. The results demonstrate that orally bioavailable α5IA increases CA1 pyramidal cell mean firing rates during foraging and peak ripple amplitude during wakeful immobility in wild type F344 rats in a familiar environment. We further demonstrate that CA1 ripples in TgF344-AD rats are nonresponsive to α5IA by 9 months of age, prior to the onset of AD-like pathology and memory dysfunction. TgF344-AD rats express human β-amyloid precursor protein (with the Swedish mutation) and human presenilin-1 (with a Δ exon 9 mutation) and we found high serum Aβ42 and Aβ40 levels by 3 months of age. When taken together, this demonstrates, to the best of our knowledge, the first evidence for prodromal α5GABA-A receptor dysfunction in the ripple-generating hippocampal trisynaptic circuit of AD-like transgenic rats. As α5GABA-A receptors are found at extrasynaptic and synaptic contacts, we posit that negative modulation of α5GABA-A receptor mediated tonic as well as phasic inhibition augments CA1 ripples and memory consolidation but that this modulatory mechanism is lost at an early stage of AD onset.Published versio

Abstinence from Escalation of Cocaine Intake Changes the microRNA Landscape in the Cortico-Accumbal Pathway

Cocaine administration alters the microRNA (miRNA) landscape in the cortico-accumbal pathway. These changes in miRNA can play a major role in the posttranscriptional regulation of gene expression during withdrawal. This study aimed to investigate the changes in microRNA expression in the cortico-accumbal pathway during acute withdrawal and protracted abstinence following escalated cocaine intake. Small RNA sequencing (sRNA-seq) was used to profile miRNA transcriptomic changes in the cortico-accumbal pathway [infralimbic- and prelimbic-prefrontal cortex (IL and PL) and nucleus accumbens (NAc)] of rats with extended access to cocaine self-administration followed by an 18-h withdrawal or a 4-week abstinence. An 18-h withdrawal led to differential expression (fold-change > 1.5 and p < 0.05) of 21 miRNAs in the IL, 18 miRNAs in the PL, and two miRNAs in the NAc. The mRNAs potentially targeted by these miRNAs were enriched in the following pathways: gap junctions, neurotrophin signaling, MAPK signaling, and cocaine addiction. Moreover, a 4-week abstinence led to differential expression (fold-change > 1.5 and p < 0.05) of 23 miRNAs in the IL, seven in the PL, and five miRNAs in the NAc. The mRNAs potentially targeted by these miRNAs were enriched in pathways including gap junctions, cocaine addiction, MAPK signaling, glutamatergic synapse, morphine addiction, and amphetamine addiction. Additionally, the expression levels of several miRNAs differentially expressed in either the IL or the NAc were significantly correlated with addiction behaviors. Our findings highlight the impact of acute and protracted abstinence from escalated cocaine intake on miRNA expression in the cortico-accumbal pathway, a key circuit in addiction, and suggest developing novel biomarkers and therapeutic approaches to prevent relapse by targeting abstinence-associated miRNAs and their regulated mRNAs