Freeway Incident Likelihood Prediction and Response Decision-Making

This research project consisted of two parts. The first part developed a set of real-time incident likelihood prediction models. The second part developed a freeway incident response decision-making methodology based on sequential hypothesis testing methods. The freeway incident likelihoods predicted by the real-time prediction models act as prior probabilities for the freeway incident response decision-making system. The products of this research project will be incorporated in the Advanced Traffic Management System that is being implemented on the Borman Expressway, a 16-mile segment of I-80 in northwest Indiana. The decision-making system can be used by traffic management personnel to assist in responding to various freeway incidents in a near optimal manner to minimize traffic delays and reduce the number of secondary incidents

Impact of river discharge on hydrodynamics and sedimentary processes at Yellow River Delta

During the Anthropocene, regulating river discharge by high dams may have met the need for water demands in river basins, but resulted in carrying less freshwater and sediment to the sea, inducing land degradation and shoreline retreat in worldwide mega-river deltas. In land-ocean interaction, tide response to water discharge changes plays an important role and is crucial for the river-laden sediment transfer and dispersal, affecting both nearshore and estuarine deposits. The Yellow River Delta (YRD), which is under an increasing pressure of the new discharge regime of the Yellow River, has undergone drastic changes in terms of sediment dynamics and morphologic evolution. To gain a better understanding of the overall fluvial and marine hydrodynamics and morphodynamic processes in the YRD, in this study, a full-scale numerical model is built to investigate the interaction and impacts of changing environmental forcing and dynamics on flow and sediment transport in the estuary of YRD and its adjacent coasts. The results show that the river discharge strongly affects the tidal dynamics and morphology of the delta, particularly in the close vicinity of the outlet and the intertidal zone. Tidal constituents M2 and K1, which are the most significant ones in the YRD, are found to be noticeably affected with a decreasing trend when the river discharge increases. The model results also indicate that river discharge affects the location and intensity of the shear front that occurs in the nearshore areas of the YRD. Increasing the river discharge can induce a seaward movement of the shear front, reduce its width and concentrate its shear intensity. It is found that the reverse of the flow direction at each side of the shear front and strong longshore tidal current can act as a barrier for the sediment dispersal process by keeping suspended sediment in the inner zone, thus to form a particular sediment deposition zone and the depo-center

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s)

Solvent-Induced Crystallization Method for High-Performance and Long-Term Stability Flexible Perovskite Photodetectors

Herein, we report a novel solvent-induced fabrication method to synthesize a perovskite thin film on flexible substrates. The high-quality CH3NH3PbI3 (MAPbI3) thin film is successfully fabricated, which is applied to prepare the stable flexible photodetector (PD). Compared with the reported results, this method achieved a low-temperature and low-cost perovskite thin film fabrication process on a flexible substrate. The constructed MAPbI3 layer possesses the advantages of being highly crystalline, uniform, and compact in a large area. The flexible PD based on the as-prepared perovskite thin film exhibits excellent performance and long-term stability. The EQE and R of the flexible PDs reached 8 × 102% and 3.6 A/W, respectively. At the same time, the flexible PDs still showed superior stability and high performance after 15 days of continuous working. The presented high-quality perovskite thin-film fabrication method and high-performance flexible perovskite PDs are expected for application in the development of novel optoelectronic devices

Impact of storm surge on the Yellow River Delta: Simulation and analysis

Storm surges can lead to serious natural hazards and pose great threats to coastal areas, especially developed deltas. Assessing the risk of storm surges on coastal infrastructures is crucial for regional economic development and disaster mitigation. Combining in situ observations, remote sensing retrievals, and numerical simulation, storm surge floods in the Yellow River Delta (YRD) were calculated in different scenarios. The results showed that NE wind can cause the largest flooding area of 630 km2, although the overall storm surge risk in the delta is at lower levels under various conditions. The coastal oilfields are principally at an increasing storm surge risk level. E and NE winds would result in storm surges of 0.9–1.4 m, increasing the risk of flooding in the coastal oilfields. Nearshore seabed erosion in storm events resulted in a decrease in inundation depths and inundation areas. To prevent and control storm surge disasters, we should adapt to local conditions. Different measures should be taken to prevent the disaster of storm surges on different seashores, such as planting saltmarsh vegetation to protect seawalls, while the key point is to construct and maintain seawalls on high-risk shorelines

INT: Towards Infinite-frames 3D Detection with An Efficient Framework

It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their systems due to the dramatically increased computational and memory cost. To address these issues, we propose a novel on-stream training and prediction framework that, in theory, can employ an infinite number of frames while keeping the same amount of computation as a single-frame detector. This infinite framework (INT), which can be used with most existing detectors, is utilized, for example, on the popular CenterPoint, with significant latency reductions and performance improvements. We've also conducted extensive experiments on two large-scale datasets, nuScenes and Waymo Open Dataset, to demonstrate the scheme's effectiveness and efficiency. By employing INT on CenterPoint, we can get around 7% (Waymo) and 15% (nuScenes) performance boost with only 2~4ms latency overhead, and currently SOTA on the Waymo 3D Detection leaderboard.Comment: accepted by ECCV202