Statistical analysis of safety performance of displaced left-turn intersections: Case studies in San Marcos, Texas

Displaced left-turn (DLT) intersections are designed to increase the mobility of vehicles by relocating the left-turn lane (lanes) to the far-left side of the road upstream of the main signalized intersection. Since DLT is a relatively new design and very limited crash data are available, previous studies have focused mainly on the analysis of its operational performance rather than its safety performance. To fill this gap, in this study, we investigated the safety performance of two DLT intersections located in San Marcos, Texas. Crash data from 2011 to April 2018 were extracted from the TxDOT Crash Record Information System (CRIS). These crash data were analyzed using two different approaches, i.e., statistical analysis and collision diagram-based analysis. The results of this study indicated that DLT did not increase the overall crash frequencies at the studied intersections. Traffic crashes related to left turns and right turns were reduced significantly by DLT. Meanwhile, it also caused safety issues related to traffic signage, traffic signal, geometric design, and access management at DLT intersections. Thus, in the implementation of DLT intersections, traffic engineers need to carefully consider different aspects of the DLT intersection design, including access management, traffic signal coordination, and driver acceptance. As a result of these analyses, recommendations were provided for the safe implementation of the DLT design in the future

A Laser-Guided Spinal Cord Displacement Injury in Adult Mice

Mouse models are unique for studying molecular mechanisms of neurotrauma because of the availability of various genetic modified mouse lines. For spinal cord injury (SCI) research, producing an accurate injury is essential, but it is challenging because of the small size of the mouse cord and the inconsistency of injury production. The Louisville Injury System Apparatus (LISA) impactor has been shown to produce precise contusive SCI in adult rats. Here, we examined whether the LISA impactor could be used to create accurate and graded contusive SCIs in mice. Adult C57BL/6 mice received a T10 laminectomy followed by 0.2, 0.5, and 0.8 mm displacement injuries, guided by a laser, from the dorsal surface of the spinal cord using the LISA impactor. Basso Mouse Scale (BMS), grid-walking, TreadScan, and Hargreaves analyses were performed for up to 6 weeks post-injury. All mice were euthanized at the 7th week, and the spinal cords were collected for histological analysis. Our results showed that the LISA impactor produced accurate and consistent contusive SCIs corresponding to mild, moderate, and severe injuries to the cord. The degree of injury severities could be readily determined by the BMS locomotor, grid-walking, and TreadScan gait assessments. The cutaneous hyperalgesia threshold was also significantly increased as the injury severity increased. The terminal lesion area and the spared white matter of the injury epicenter were strongly correlated with the injury severities. We conclude that the LISA device, guided by a laser, can produce reliable graded contusive SCIs in mice, resulting in severity-dependent behavioral and histopathological deficits

Automated monitoring of early neurobehavioral changes in mice following traumatic brain injury

Traumatic brain injury often causes a variety of behavioral and emotional impairments that can develop into chronic disorders. Therefore, there is a need to shift towards identifying early symptoms that can aid in the prediction of traumatic brain injury outcomes and behavioral endpoints in patients with traumatic brain injury after early interventions. In this study, we used the SmartCage system, an automated quantitative approach to assess behavior alterations in mice during an early phase of traumatic brain injury in their home cages. Female C57BL/6 adult mice were subjected to moderate controlled cortical impact (CCI) injury. The mice then received a battery of behavioral assessments including neurological score, locomotor activity, sleep/wake states, and anxiety-like behaviors on days 1, 2, and 7 after CCI. Histological analysis was performed on day 7 after the last assessment. Spontaneous activities on days 1 and 2 after injury were significantly decreased in the CCI group. The average percentage of sleep time spent in both dark and light cycles were significantly higher in the CCI group than in the sham group. For anxiety-like behaviors, the time spent in a light compartment and the number of transitions between the dark/light compartments were all significantly reduced in the CCI group than in the sham group. In addition, the mice suffering from CCI exhibited a preference of staying in the dark compartment of a dark/light cage. The CCI mice showed reduced neurological score and histological abnormalities, which are well correlated to the automated behavioral assessments. Our findings demonstrate that the automated SmartCage system provides sensitive and objective measures for early behavior changes in mice following traumatic brain injury

A Tissue Displacement-based Contusive Spinal Cord Injury Model in Mice

Producing a consistent and reproducible contusive spinal cord injury (SCI) is critical to minimizing behavioral and histological variabilities between experimental animals. Several contusive SCI models have been developed to produce injuries using different mechanisms. The severity of the SCI is based on the height that a given weight is dropped, the injury force, or the spinal cord displacement. In the current study, we introduce a novel mouse contusive SCI device, the Louisville Injury System Apparatus (LISA) impactor, which can create a displacement-based SCI with high injury velocity and accuracy. This system utilizes laser distance sensors combined with advanced software to produce graded and highly-reproducible injuries. We performed a contusive SCI at the 10th thoracic vertebral (T10) level in mice to demonstrate the step-by-step procedure. The model can also be applied to the cervical and lumbar spinal levels

Descending motor circuitry required for NT-3 mediated locomotor recovery after spinal cord injury in mice

Locomotor function, mediated by lumbar neural circuitry, is modulated by descending spinal pathways. Spinal cord injury (SCI) interrupts descending projections and denervates lumbar motor neurons (MNs). We previously reported that retrogradely transported neurotrophin-3 (NT-3) to lumbar MNs attenuated SCI-induced lumbar MN dendritic atrophy and enabled functional recovery after a rostral thoracic contusion. Here we functionally dissected the role of descending neural pathways in response to NT-3-mediated recovery after a T9 contusive SCI in mice. We find that residual projections to lumbar MNs are required to produce leg movements after SCI. Next, we show that the spared descending propriospinal pathway, rather than other pathways (including the corticospinal, rubrospinal, serotonergic, and dopaminergic pathways), accounts for NT-3-enhanced recovery. Lastly, we show that NT-3 induced propriospino-MN circuit reorganization after the T9 contusion via promotion of dendritic regrowth rather than prevention of dendritic atrophy

A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals

As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals

Pressure Control of High-Pressure Oil Pipe

In this paper, to realize the pressure stability control of high-pressure oil pipe, the dynamic differential equation of fuel oil inlet and outlet is established based on the theory of mass conservation. According to the change of the pressure in the high-pressure tubing, an optimization model is established to achieve precise control of the working time of each part of the high-pressure oil pipe

Pressure Control of High-Pressure Oil Pipe

In this paper, to realize the pressure stability control of high-pressure oil pipe, the dynamic differential equation of fuel oil inlet and outlet is established based on the theory of mass conservation. According to the change of the pressure in the high-pressure tubing, an optimization model is established to achieve precise control of the working time of each part of the high-pressure oil pipe

A state-dependent approximation method for estimating truck queue length at marine terminals

As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals