452 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, Supplementary_tables_and_figures - Prediction of Target Genes and Pathways Associated With Cetuximab Insensitivity in Colorectal Cancer
No full textSupplemental Material, Supplementary_tables_and_figures for Prediction of Target Genes and Pathways Associated With Cetuximab Insensitivity in Colorectal Cancer by Chaoran Yu, Hiju Hong, Jiaoyang Lu, Xuan Zhao, Wenjun Hu, Sen Zhang, Yaping Zong, Zhihai Mao, Jianwen Li, Mingliang Wang, Bo Feng, Jing Sun, and Minhua Zheng in Technology in Cancer Research & Treatment</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
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
MicroRNA-181a Regulates the Proliferation and Differentiation of Hu Sheep Skeletal Muscle Satellite Cells and Targets the YAP1 Gene
No full textMicroRNA (miRNA) is of great importance to muscle growth and development, including
the regulation of the proliferation and differentiation of skeletal muscle satellite cells (SMSCs). In our
research group’s previous study, we found that miR-181a is differentially expressed in the longissimus
dorsi muscle of Hu sheep at different stages. We speculated that miR-181a may participate in the
growth and development process of Hu sheep. To understand the mechanism of miR-181a regulating
the growth and development of Hu sheep skeletal muscle, we extracted skeletal muscle satellite
cells from the longissimus dorsi muscle of 3-month-old Hu sheep fetuses and performed a series of
experiments. Our results showed that miR-181a suppressed SMSCs’ proliferation using QRT-PCR,
Western blot, CCK-8, EDU, and Flow cytometry cycle tests. In addition, QRT-PCR, Western blot,
and immunofluorescence indicated that miR-181a facilitated the differentiation of SMSCs. Then, we
used dual-luciferase reporter gene detection, QRT-PCR, and Western blot to find that the Yes1-related
transcription regulator (YAP1) is the target gene of miR-181a. Our study supplies a research basis for
understanding the regulation mechanism of miR-181a on the growth of Hu sheep skeletal muscle
Visual tracking via incremental Log-Euclidean Riemannian subspace learning
No full textRecently, a novel Log-Euclidean Riemannian metric is proposed for statistics on symmetric positive definite (SPD) matrices. Under this metric, distances and Riemannian means take a much simpler form than the widely used affine-invariant Riemannian metric. Based on the Log-Euclidean Riemannian metric, we develop a tracking framework in this paper. In the framework, the covariance matrices of image features in the five modes are used to represent object appearance. Since a nonsingular covariance matrix is a SPD matrix lying on a connected Riemannian manifold, the Log-Euclidean Riemannian metric is used for statistics on the covariance matrices of image features. Further, we present an effective online Log-Euclidean Riemannian subspace learning algorithm which models the appearance changes of an object by incrementally learning a low-order Log-Euclidean eigenspace representation through adaptively updating the sample mean and eigenbasis. Tracking is then led by the Bayesian state inference framework in which a particle filter is used for propagating sample distributions over the time. Theoretic analysis and experimental evaluations demonstrate the promise and effectiveness of the proposed framework.Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, Mingliang Zhu, Jian Chen
Rank aggregation based text feature selection
No full textFiltering feature selection method (filtering method, for short) is a well-known feature selection strategy in pattern recognition and data mining. Filtering method outperforms other feature selection methods in many cases when the dimension of features is large. There are so many filtering methods proposed in previous work leading to the “selection trouble” that how to select an appropriate filtering method for a given text data set. Since to find the best filtering method is usually intractable in real application, this paper takes an alternative path. We propose a feature selection framework that fuses the results obtained by different filtering methods. In fact, deriving a better rank list from different rank lists, known as rank aggregation, is a hot topic studied in many disciplines. Based on the proposed framework and Markov chains rank aggregation techniques, in this paper, we present two new feature selection methods: FR-MC1 and FR-MC4. We also introduce a perturbation algorithm to alleviate the drawbacks of Markov chains rank aggregation techniques. Empirical evaluation on two public text data sets shows that the two new feature selection methods achieve better or comparable results than classical filtering methods, which also demonstrate the effectiveness of our framework.Ou Wu, Haiqiang Zuo, Mingliang Zhu, Weiming Hu, Jun Gao and Hanzi Wan
Performance evaluation of urea injection on the emission reduction of dioxins and furans in a commercial municipal solid waste incinerator
No full textPolychlorinated dibenzo-p-furans and dioxins (PCDD/Fs) that pose a great threat to human health are commonly found during the incineration of municipal solid waste. In this study, industrial urea was injected into a commercial MSW incinerator flue gas to evaluate the suppression performances of PCDD/Fs, and the possible inhibition mechanisms were proposed. The results show that the use of urea dramatically reduced the PCDD/Fs emission concentration from 8.87 to 0.63 ng/Nm3, along with a significant decrease in the I-TEQ value (0.26 → 0.047 ng I-TEQ/Nm3), below the Chinese national standard of 0.1 ng I-TEQ/Nm3. The emission reduction cost of the industrial urea was over 41 % lower than that of using activated carbon. Urea molecule poisoned the metal ions, thus seriously inhibiting the de novo synthesis of PCDD/Fs. Furthermore, the decomposition products of urea reduced the concentration of HCl in the flue gas, thereby reducing the formation of Cl2 and hindering the chlorination reaction, which was identified from the reduction of chlorination degree and lower distribution of high-chlorinated PCDD/Fs. This research provided some practice basis and experience to reduce the emission of PCDD/Fs from municipal solid waste incineration for future commercial promotion and application
The Role of <i>BMP7</i> in the Proliferation of Hu Sheep Dermal Papilla Cells Is Influenced by DNA Methylation
No full textPrevious studies have shown that the BMP7 gene is differentially expressed in Hu sheep lamb skin of different pattern types, and its expression level is significantly correlated with hair follicle indices of different pattern types, but the molecular mechanism of the differential expression of the BMP7 gene remains unclear. This study investigated the effect of DNA methylation on the transcriptional expression of BMP7. Firstly, we found that the mRNA expression of the BMP7 gene and the activity of the core promoter of the BMP7 gene were upregulated after 5-Aza-Deoxycytidine-induced demethylation treatment using qRT-PCR and double luciferase reporter assay. Then, we found that the proliferation of Hu sheep DPCs in vitro was promoted after 5-Aza-Deoxycytidine-induced demethylation treatment through qRT-PCR, CCK-8, and EdU assay, and that the overexpression of DNMT1 in DPCs induced the opposite effect. In addition, the results of the cell cycle assay reveal that the percentage of cells in the S phase was increased after 5-Aza-Deoxycytidine-induced demethylation treatment, and that the percentage of cells in the S phase was decreased after overexpression of DNMT1 in DPCs. This study indicated that the differential expression of the BMP7 gene in different patterns of Hu sheep lamb skin may be regulated by DNA methylation modification. In addition, DNA methylation can regulate the proliferation and cell cycle of DPCs in Hu sheep
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
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