241 research outputs found
Object-oriented stream programming using Aspects: a high-productivity programming paradigm for hybrid platforms
No full textThe move to massively parallel hybrid platforms, such as multicore CPUs accelerated with heterogeneous GPU co-processing systems, is significantly impacting software programmers because existing programs have to be properly parallelized before they can take advantage of these advanced processing architectures. However, using current programming frameworks such as CUDA leads to tangled source code that combines code for the core computation with that for device and computational kernel management, data transfers between memory spaces, and various optimizations. In this research, we propose a programming system based on the principles of Aspect-Oriented Programming, to un-clutter the code and to improve programmability of these heterogeneous parallel systems. Specifically, we use a standard Object-Oriented language to describe the core computations and aspects to encapsulate all other support functions, such as parallelization granularity and memory access optimization. An aspect-weaving compiler is then used to combine the core OO program with these aspects to generate parallelized programs. This approach modularizes concerns that are hard to manage using conventional programming frameworks such as CUDA, has a small impact on existing program structure as well as performance, and as a result, simplifies the programming of accelerator-based heterogeneous parallel systems. Studies on example programs suggest that programs written using this system can be successfully translated to CUDA programs for execution on a CPU + GPU co-processing system with comparable performance. The performance of the translated code achieved ~80% of the hand-coded CUDA programs. We also introduce a performance model based on Bulk Synchronous Parallel (BSP) to help with quick identification of performance bottlenecks and tuning programs for better performance. This model defines a machine parameter (Machine Characteristic Ratio) and an application parameter (Application Characteristic Ratio) to identify the principle factors that can be used to bound application performance for the hierarchical parallel execution in the GPU co-processing device.Ph.D.Includes bibliographical referencesIncludes vitaby Mingliang Wan
Supplemental Material - Higher Levels of Tumour-Infiltrating Lymphocytes (TILs) are Associated with a Better Prognosis, While CDK5 Plays a Different Role Between Nonmetastatic and Metastatic Colonic Carcinoma
No full textSupplemental Material for Higher Levels of Tumour-Infiltrating Lymphocytes (TILs) are Associated with a Better Prognosis, While CDK5 Plays a Different Role Between Nonmetastatic and Metastatic Colonic Carcinoma by Qinghua Wang, Ruihua Yin, Xiaoxiao Chen1, Bin Hu, Bingjing Jiang, Wanfen Tang, Xia Zhang, Xiayun Jin, Mingliang Ying, and Jianfei Fu in Cancer Control</p
Supplemental Material - Higher Levels of Tumour-Infiltrating Lymphocytes (TILs) are Associated with a Better Prognosis, While CDK5 Plays a Different Role Between Nonmetastatic and Metastatic Colonic Carcinoma
No full textSupplemental Material for Higher Levels of Tumour-Infiltrating Lymphocytes (TILs) are Associated with a Better Prognosis, While CDK5 Plays a Different Role Between Nonmetastatic and Metastatic Colonic Carcinoma by Qinghua Wang, Ruihua Yin, Xiaoxiao Chen1, Bin Hu, Bingjing Jiang, Wanfen Tang, Xia Zhang, Xiayun Jin, Mingliang Ying, and Jianfei Fu in Cancer Control</p
Size and shape-based separation using deterministic lateral displacement microfludic systems
No full textContinuous separation of particles of different sizes and shapes is important in both clinical diagnostics and industrial applications and a number of methods have been developed for such separations. In microfluidic systems, deterministic lateral displacement has proved its great potential in achieving the goal of high throughput and efficient separation. Although it was originally based on transporting the suspension in a convective flow, particles can be also driven with external force fields, thus force-driven DLD (f-DLD) devices were demonstrated. This thesis demonstrates the separation of suspended particles by shape and size using scaled-up macroscopic f-DLD devices, using gravity force and a centrifuge, respectively. In the first set of experiments and for the first time, we demonstrate the potential of gravity-driven DLD devices for the separation of particles of different shapes. Our results show that each type of particle moves in different directions within the array of obstacles in DLD systems, depending on the forcing direction. Interestingly, we show that the migration of the particles can be predicted by the diameter of the inscribed sphere, independent of shape. In the second set of experiments and also for the first time, we combined DLD devices with centrifugal force as the driving field. We show that spherical particles of different sizes are driven to different outlets. We show that at some specific angles this setup provides high separation resolution, but the resolution decreases as the concentration of particles increases.M.S.Includes bibliographical referencesby Mingliang JiangThis work was partially supported by the National Science Foundation Grant no. CBET-1339087
The Effect of Consistency on Short-Term Memory for Scenes
No full textWhich is more detectable, the change of a consistent or an inconsistent object in a scene? This question has been debated for decades. We noted that the change of objects in scenes might simultaneously be accompanied with gist changes. In the present study we aimed to examine how the alteration of gist, as well as the consistency of the changed objects, modulated change detection. In Experiment 1, we manipulated the semantic content by either keeping or changing the consistency of the scene. Results showed that the changes of consistent and inconsistent scenes were equally detected. More importantly, the changes were more accurately detected when scene consistency changed than when the consistency remained unchanged, regardless of the consistency of the memory scenes. A phase-scrambled version of stimuli was adopted in Experiment 2 to decouple the possible confounding effect of low-level factors. The results of Experiment 2 demonstrated that the effect found in Experiment 1 was indeed due to the change of high-level semantic consistency rather than the change of low-level physical features. Together, the study suggests that the change of consistency plays an important role in scene short-term memory, which might be attributed to the sensitivity to the change of semantic content
DeepHMap plus plus : Combined Projection Grouping and Correspondence Learning for Full DoF Pose Estimation
No full textIn recent years, estimating the 6D pose of object instances with convolutional neural network (CNN) has received considerable attention. Depending on whether intermediate cues are used, the relevant literature can be roughly divided into two broad categories: direct methods and two-stage pipelines. For the latter, intermediate cues, such as 3D object coordinates, semantic keypoints, or virtual control points instead of pose parameters are regressed by CNN in the first stage. Object pose can then be solved by correspondence constraints constructed with these intermediate cues. In this paper, we focus on the postprocessing of a two-stage pipeline and propose to combine two learning concepts for estimating object pose under challenging scenes: projection grouping on one side, and correspondence learning on the other. We firstly employ a local-patch based method to predict projection heatmaps which denote the confidence distribution of projection of 3D bounding box's corners. A projection grouping module is then proposed to remove redundant local maxima from each layer of heatmaps. Instead of directly feeding 2D-3D correspondences to the perspective-n-point (PnP) algorithm, multiple correspondence hypotheses are sampled from local maxima and its corresponding neighborhood and ranked by a correspondence-evaluation network. Finally, correspondences with higher confidence are selected to determine object pose. Extensive experiments on three public datasets demonstrate that the proposed framework outperforms several state of the art methods
Solving the Pose Ambiguity via a Simple Concentric Circle Constraint
No full textEstimating the pose of objects with circle feature from images is a basic and important question in computer vision community. This paper is focused on the ambiguity problem in pose estimation of circle feature, and a new method is proposed based on the concentric circle constraint. The pose of a single circle feature, in general, can be determined from its projection in the image plane with a pre-calibrated camera. However, there are generally two possible sets of pose parameters. By introducing the concentric circle constraint, interference from the false solution can be excluded. On the basis of element at infinity in projective geometry and the Euclidean distance invariant, cases that concentric circles are coplanar and non-coplanar are discussed respectively. Experiments on these two cases are performed to validate the proposed method
Quantitative proteomic and phosphoproteomic studies reveal novel 5-fluorouracil resistant targets in hepatocellular carcinoma
No full textThe development of chemoresistance remains the major obstacles to successful chemotherapy of hepatocellular carcinoma. The molecular mechanisms of drug resistance are complex. Identifying the key markers is crucial for development of therapeutic strategies to overcome resistance. In this study, we employed a cell-line model consisting of the 5-fluorouracil resistant Bel/5-Fu cell line and its parental Bel cell line. Using stable isotope dimethyl labeling combined with high-resolution mass spectrometry, in total, 8272 unique proteins and 22,095 phosphorylation sites with high localization confidence were identified. Our data indicated that the GnRH signaling pathway was involved in acquiring drug resistance, which has not been well elucidated. The western blotting results confirmed that the expression levels of PLC beta 3 and PLC beta 3 pS1105 in Bel/5-Fu cells were increased as compared to Bel cells. Furthermore, the protein levels of SRC and PKG delta, which could phosphorylate PLC beta 3 at ser1105, were higher in Bel/5-Fu cells than in Bel cells. The knockdown of SRC, PKC delta and PLC beta 3 increased the susceptibility of Bel/5-Fu cells to 5-Fu. Besides, the increased transcription levels of PLC beta 3, PRC delta and SRC were significantly associated with decreased overall survival. Together, our deep proteomic and phosphoproteomic data reveal novel therapeutic targets for attenuating 5-Fu resistance in anti-cancer therapy.
Significance: It was reported that many hepatocellular carcinoma patients are resistance to 5-Fu. Although some studies related to drug resistance have been reported, the underlying mechanisms were not well elucidated. Unlike many single molecular studies, we focused on the global proteome and phosphoproteome analysis of Bel and Be15-/Fu cell line using stable isotope dimethyl labeling to identify the previously unrecognized signaling pathway for causing 5-Fu resistance. Our results showed that the phosphorylation levels of PLC beta 3 pS1105 and the protein levels of PLC beta 3, PKC delta and SRC, which are major components of GnRH signaling pathway were higher in Bel/5-Fu cells than in Bel cells. Furthermore, knockdown of PLC beta 3, PKC delta and SRC increased the susceptibility of Bel/5-Fu cells to 5-Fu. Overall, this is the first comprehensive proteomic and phosphoproteomic studies on 5-Fu resistant cell line Bel/5-Fu to identify the potential targets of attenuating chemoresistance in hepatocellular carcinoma
Non-rigid point set registration via mixture of asymmetric Gaussians with integrated local structures
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