The mechanism of psychiatric drugs (stimulant and non-stimulant) is still unclear. Precision medication of psychiatric disorders faces challenges in pharmacogenetics and pharmacodynamics research due to difficulties in recruiting human subjects because of possibility of substance abuse and relatively small sample sizes. Drosophila is a powerful animal model for large-scale studies of drug effects based on the precise quantification of behavior. However, a user-friendly system for high-throughput simultaneous tracking and analysis of drug-treated individual adult flies is still lacking. It is critical to quickly setup a working environment including both the hardware and software at a reasonable cost. Thus, we have developed EasyFlyTracker, an open-source Python package that can track single fruit fly in each arena and analyze Drosophila locomotor and sleep activity based on video recording to facilitate revealing the psychiatric drug effects. The current version does not support multiple fruit fly tracking. Compared with existing software, EasyFlyTracker has the advantages of low cost, easy setup and scaling, rich statistics of movement trajectories, and compatibility with different video recording systems. Also, it accepts multiple video formats such as common MP4 and AVI formats. EasyFlyTracker provides a cross-platform and user-friendly interface combining command line and graphic configurations, which allows users to intuitively understand the process of tracking and downstream analyses and automatically generates multiple files, especially plots. Users can install EasyFlyTracker, go through tutorials, and give feedback on http://easyflytracker.cibr.ac.cn. Moreover, we tested EasyFlyTracker in a study of Drosophila melanogaster on the hyperactivity-like behavior effects of two psychiatric drugs, methylphenidate and atomoxetine, which are two commonly used drugs treating attention-deficit/hyperactivity disorder (ADHD) in human. This software has the potential to accelerate basic research on drug effect studies with fruit flies.

Graphics, uncertainty, and semantics are three approaches to building models. The combination of the three approaches is a way to develop a stronger modeling method.This article surveys the research efforts toward combining these aspects, which can be divided into two routes: One is to combine graphics and uncertainty as probabilistic graphical models and then incorporate semantics, and the other is to combine graphics and semantics and then incorporate probability to handle uncertainty. The models and methods involved in these efforts are introduced and their expressiveness, pros, and cons are discussed.

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The Block 3/7 of Sudan Oilfield has been in the period of high water production. The water cut of many wells is more than 80%, and still rising. Besides, there are many sandy wells in this area. In order to reduce the water cut, the conventional technique involves two string trips—water detection primarily, and then water shutoff treatment according to the result of testing. Obviously, high cost and low efficiency restrict its application. Therefore, based on the conventional technique, a new integrated technique for servo adjustable water detection and water shutoff has been researched by Daqing Oilfield Limited Company, which is mainly made up of drillable packers to divide layers, intelligent controlled piezoelectric valves, inserted seal sections and releasing subs. With the integrated technique, dynamic adjustment and water shutoff treatment can be achieved at any layer without pulling the string upward or downward. Applying casing pressure signals can open the appointed position’s valve when detecting water, then get its single layer’s production, meanwhile record and test on the ground to confirm this layer’s production and water cut. Applying casing pressure signals closes the appointed position valve after testing. Repeating the above steps can get all the layers water production and water cut. According to the result of water detection test, open the intelligent controlled piezoelectric valves of the lower water cut layers to stabilize the oil production. This new technique has been successfully applied to 8 wells in the Block 3/7 of Sudan Oilfield, which features low cost and high efficiency. It could meet the requirements of water detection and water shutoff for the remaining 30 wells of high water production. Similarly, it could apply to many wells of high water production in Daqing Oilfield.

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The finite element calculation method was used and the principal stresses distribution in the asphalt pavement was analyzed. The damage index of the pavement structure is defined as asphalt pavement potential damage index(APPDI) based on the Drucker-Prager criterion, and the APPDI as the pavement structure damage index are applied. The results show that: (1) The most dangerous nodes of this example model appeared between rounds from the edge of round about 0 to 2cm and the place beneath the tire. The composition of the principal stresses are tensile and compression stress.(2) Failure modes are rutting and Bottom-up which are caused by tension-compression composite shear stress.

This thesis discusses approaches and techniques to convert Sparsely- Sampled Light Fields (SSLFs) into Densely-Sampled Light Fields (DSLFs), which can be used for visualization on 3DTV and Virtual Reality (VR) de- vices. Exemplarily, a movable 1D large-scale light field acquisition system for capturing SSLFs in real-world environments is evaluated. This system consists of 24 sparsely placed RGB cameras and two Kinect V2 sensors. The real-world SSLF data captured with this setup can be leveraged to reconstruct real-world DSLFs. To this end, three challenging problems require to be solved for this system: (i) how to estimate the rigid trans- formation from the coordinate system of a Kinect V2 to the coordinate system of an RGB camera; (ii) how to register the two Kinect V2 sensors with a large displacement; (iii) how to reconstruct a DSLF from a SSLF with moderate and large disparity ranges. To overcome these three challenges, we propose: (i) a novel self- calibration method, which takes advantage of the geometric constraints from the scene and the cameras, for estimating the rigid transformations from the camera coordinate frame of one Kinect V2 to the camera coordi- nate frames of 12-nearest RGB cameras; (ii) a novel coarse-to-fine approach for recovering the rigid transformation from the coordinate system of one Kinect to the coordinate system of the other by means of local color and geometry information; (iii) several novel algorithms that can be categorized into two groups for reconstructing a DSLF from an input SSLF, including novel view synthesis methods, which are inspired by the state-of-the-art video frame interpolation algorithms, and Epipolar-Plane Image (EPI) in- painting methods, which are inspired by the Shearlet Transform (ST)-based DSLF reconstruction approaches.