Profile-based Maximum Penalised Likelihood Trajectory Estimation from Space-borne LOS Measurements

Estimating the boost-phase trajectory of a ballistic missile using line of sight measurements from space-borne passive sensors is an important issue in missile defense. A well-known difficulty of this issue is the poor-observability of the target motion. A profile-based maximum penalised likelihood estimator is presented, which is expected to work in poor-observability scenarios. Firstly, a more adaptable boost-phase profile is proposed by introducing unknown parameters. Then, the estimator is given based on the Bayesian paradigm. After that, a special penalty for box constraint is constructed based on a mixed distribution. Numerical results for some typical scenarios and sensitivity with respect to a priori information are reported to show that the proposed estimator is promising

Development of Automated Incident Detection System Using Existing ATMS CCTV

Indiana Department of Transportation (INDOT) has over 300 digital cameras along highways in populated areas in Indiana. These cameras are used to monitor traffic conditions around the clock, all year round. Currently, the videos from these cameras are observed by human operators. The main objective of this research is to develop an automatic real-time system to monitor traffic conditions using the INDOT CCTV video feeds by a collaborative research team of the Transportation Active Safety Institute (TASI) at Indiana University-Purdue University Indianapolis (IUPUI) and the Traffic Management Center (TMC) of INDOT. In this project, the research team developed the system architecture based on a detailed system requirement analysis. The first prototype of major system components of the system has been implemented. Specifically, the team has successfully accomplished the following: An AI based deep learning algorithm provided in YOLO3 is selected for vehicle detection which generates the best results for daytime videos. The tracking information of moving vehicles is used to derive the locations of roads and lanes. A database is designed as the center place to gather and distribute the information generated from all camera videos. The database provides all information for the traffic incident detection. A web-based Graphical User Interface (GUI) was developed. The automatic traffic incident detection will be implemented after the traffic flow information being derived accurately. The research team is currently in the process of integrating the prototypes of all components of the system together to establish a complete system prototype

Impingement and Mixing Dynamics of Micro-Droplets on a Solid Surface

Supported from National Natural Science Foundation of China (No.22078008) and the Fundamental Research Funds for the Central Universities (XK1802-1). Acknowledgement The authors gratefully acknowledge the financial support from National Natural Science Foundation of China (No.22078008) and the Fundamental Research Funds for the Central Universities (XK1802-1).Peer reviewedPostprin

Droplet impingement and wetting behavior on a chemically heterogeneous surface in the Beyond-Cassie-Baxter regime

Peer reviewedPostprin

Analysis of environmental conditions and characteristics of convective system evolution of a Mei-Yu Front heavy rainstorm in southern Jiangsu

Affected by the Mei-Yu Front and the mesoscale vortex on the Mei-Yu Front, a heavy rain event occurred in Suzhou on 6 July, 2020, and caused disasters such as urban waterlogging. In this paper, by using ERA5 reanalysis data from the European Center for Medium-Range Weather Forecasts, as well as various observational data from ground meteorological stations, Doppler weather radar, and wind profile radar, we analyze the weather background, environmental characteristics, convective system evolution, and maintenance mechanism of this heavy rain process. The results show that: (1) The upper westerly trough moved eastward, the cold shear line at the middle and lower levels pressed southward, the convergence of cold and warm air over southern Jiangsu enhanced the convergence at the lower level, the strengthening of the southwest jet at the middle and lower levels and the maintenance of the ground quasi stationary front provided favorable weather background conditions for the heavy rainstorm process. (2) During the strongest rainfall period, the intensity of the radar echo center is 60 dBz and the top height exceeds 14 km. The strong reflectivity factor area corresponds to a differential propagation phase shift of 7°·km-1. The average vertical extension height of the strong echo is below 6 km, making it a typical low center of mass warm area rainfall. (3) The moderate levels of convective availble potential energy, strong vertical wind shear in the middle and lower levels, and convective instability stratification, and the low lifting condensation level over Suzhou provide favorable environmental conditions for the generation of heavy rainstorm. The continuously increasing low-level jet propagates downwards, to forming an superultra low-level jet. The strong convergence and uplift in the jet exitoutflow area, combined with the rising branches of the secondary circulation above the shear line, provide dynamic uplift and triggering conditions for the generation of heavy precipitation. The strong frontogenesis of the Mei-Yu Front in both horizontal and vertical directions enables the maintenance of heavy precipitation

Genome-Wide Profiling of Prognostic Alternative Splicing Signature in Colorectal Cancer

Background: This study was to explore differential RNA splicing patterns and elucidate the function of the splice variants served as prognostic biomarkers in colorectal cancer (CRC).Methods: Genome-wide profiling of prognostic alternative splicing (AS) events using RNA-seq data from The Cancer Genome Atlas (TCGA) program was conducted to evaluate the roles of seven AS patterns in 330 colorectal cancer cohort. The prognostic predictors models were assessed by integrated Cox proportional hazards regression. Based on the correlations between survival associated AS events and splicing factors, splicing networks were built.Results: A total of 2,158 survival associated AS events in CRC were identified. Interestingly, most of these top 20 survival associated AS events were adverse prognostic factors. The prognostic models were built by each type of splicing patterns, performing well for risk stratification in CRC patients. The area under curve (AUC) of receiver operating characteristic (ROC) for the combined prognostic predictors model could reach 0.963. Splicing network also suggested distinguished correlation between the expression of splicing factors and AS events in CRC patients.Conclusion: The ideal prognostic predictors model for risk stratification in CRC patients was constructed by differential splicing patterns of 13 genes. Our findings enriched knowledge about differential RNA splicing patterns and the regulation of splicing, providing generous biomarker candidates and potential targets for the treatment of CRC

Exploration characteristics of coal and rock boundary in horizontal well with Azimuth electromagnetic wave instrument PeriScope

In coal mine production, advance and precise identification of coal-rock interface can improve recovery and reduce mining risk, which is one of the bottleneck technologies to realize intelligent coal mining. Azimuth electromagnetic wave logging instrument has larger detecting depth and the azimuth resolution ability, which has a certain advantage in coal-rock interface detection, in order to study the oil the applicability of the azimuth electromagnetic wave instrument Periscope in coalfield well logging, coal log level layered formation model was established, using the generalized reflection coefficient method and finite element numerical simulation method, Taking Periscope as an example, the detection characteristics of coal seam boundary are investigated. Application of Periscope instrument transmitting frequency and spacing, set its instrument radius drill pipe radius of the commonly used for coal mine, the simulation results show that the geological response in line with the typical characteristics of signals in the interface, geological signal change with instrument rotation Angle with periodic response, frequency and delineation of distance is not a simple positive correlation, spaced and offset distance have positive correlation, The geological signal amplitude increases with the increase of coal layer thickness, but when the thickness increases to a certain value, the geological signal does not change with the thickness. When the eccentricity is large, the geological signal is affected by the eccentricity, and the azimuth electromagnetic wave measurement response can reflect the resistivity change of the goaf. Results show that the geological signal detection ability of the coal rock boundary by frequency resistivity contrast, layer thickness, spacing, and a variety of factors, such as electromagnetic wave instrument Periscope bearing geological signal has the azimuth resolution, can be used to set of coal rock interface detection model and identification of mined-out area, but in the case of surrounding rock and coal seam resistivity are high, It is necessary to increase the source distance of the instrument or select the appropriate transmission frequency to meet the requirements of the measurement signal intensity

Proteomic analyses in diverse populations improved risk prediction and identified new drug targets for type 2 diabetes

Objective: Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction and discover novel protein drug targets for T2D. Research Design and Methods: We measured plasma levels of 2923 proteins using OLINK Explore among ~2000 randomly selected participants from CKB without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n=92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using AUC, calibration plots and NRI, respectively. Two-sample MR analyses using cis-pQTLs identified in GWAS of CKB and UKB for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D. Results: Overall 33 proteins were significantly associated (FDR0.6) of shared genetic variants of LPL and PON3 with T2D. Conclusion: Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D