Atherogenic Factors and Their Epigenetic Relationships

Hypercholesterolemia, homocysteine, oxidative stress, and hyperglycemia have been recognized as the major risk factors for atherogenesis. Their impact on the physiology and biochemistry of vascular cells has been widely demonstrated for the last century. However, the recent discovery of the role of epigenetics in human disease has opened up a new field in the study of atherogenic factors. Thus, epigenetic tags in endothelial, smooth muscle, and immune cells seem to be differentially affected by similar atherogenic stimuli. This paper summarizes some recent works on expression of histone-modifying enzymes and DNA methylation directly linked to the presence of risk factors that could lead to the development or prevention of the atherosclerotic process

A polynomial texture extraction with application in dynamic texture classification

International audienceGeometry and texture image decomposition is an important paradigm in image processing. Following to Yves Meyer works based on Total Variation (VT), the decomposition model has known a renewed interest. In this paper , we propose an algorithm which decomposes color image into geometry and texture component by projecting the image in a bivariate polynomial basis and considering the geometry component as the partial reconstruction and the texture component as the remaining part. The experimental results show the adequacy of using our method as a texture extraction tool. Furthermore, we integrate it into a dynamic texture classification process

Assessment of STEM e-Learning in an Immersive Virtual Reality (VR) Environment

This paper shows the early research findings of utilizing a virtual reality environment as an educational tool for the operation of a computerized numerical control (CNC) milling machine. Based off of a previous work, the Advanced Virtual Machining Lab (AVML), this project features a virtual environment in which a virtual CNC machine is fully operable, designed to allow STEM students and training professionals to learn the use of the CNC machine without the need to be in a physical lab. Users operate in the virtual environment using an immersive virtual reality headset (i.e. Oculus Rift) and standard input devices (i.e. mouse and keyboard), both of which combined make for easy movement and realistic visuals. On-screen tutorials allow users to learn about what they need to do to operate the machine without the need for outside instruction. While designing and perfecting this environment has been the primary focus of this project thus far, the research goal is to test the ease of use and the pedagogical effectiveness of the immersive technology as it relates to education in STEM fields. Initial usability studies for this environment featured students from the graduate level CAD/CAM-Theory and Advanced Applications (ME 54600) course at IUPUI. Results from the study were tabulated with a survey using a four-point Likert scale and several open-ended questions. Findings from the survey indicate that the majority of users found the environment realistic and easy to navigate, in addition to finding the immersive technology to be beneficial. Many also indicated that they felt comfortable navigating the environment without the need for additional assistance from the survey proctors. Full details on the first usability study, including data and discussion, can be found in this paper. The general consensus from the study was that, while some features needed refinement, the immersive environment helped them learn about the operation of a CNC machine. Additional usability studies will need to be undergone to refine said features before beginning the final study, in which students learning from the immersive virtual environment will be tested against students learning from traditional methods. Details on this last study will be discussed in the final paper, which will also discuss the methods used for preparing the environment, full results and detailed discussion on each of the usability studies, and conclusions on the usability and educational effectiveness of the immersive virtual reality technology in STEM education

Spatial image polynomial decomposition with application to video classification

International audienceThis paper addresses the use of orthogonal polynomial basis transform in video classification due to its multiple advantages, especially for multiscale and multiresolution analysis similar to the wavelet transform. In our approach, we benefit from these advantages to reduce the resolution of the video by using a multiscale/multiresolution decomposition to define a new algorithm that decomposes a color image into geometry and texture component by projecting the image on a bivariate polynomial basis and considering the geometry component as the partial reconstruction and the texture component as the remaining part, and finally to model the features (like motion and texture) extracted from reduced image sequences by projecting them into a bivariate polynomial basis in order to construct a hybrid polynomial motion texture video descriptor. To evaluate our approach, we consider two visual recognition tasks, namely the classification of dynamic textures and recognition of human actions. The experimental section shows that the proposed approach achieves a perfect recognition rate in the Weizmann database and highest accuracy in the Dyntex++ database compared to existing methods

INTERCULTURATION AND INYERCULTURAL SENSITIVITY: IMPLEMENTATION OF THE MAJOR CONCEPTS FOR A BETTER MANAGEMENT OF CULTURAL OTHERNESS

This study aimed to explore the relationship between intercultural sensitivity, namely, the ability to apprehend cultural difference, and interculturation. Specifically, this study investigated the effect of nationality (French, Brazilian, Bolivian, Sri Lankan) and individual characteristics (e.g., number of spoken foreign languages, socioeconomic status, age and gender) on intercultural sensitivity and interculturation. An intercultural sensitivity scale and demographic questions about individual characteristics were administered to a sample of 434 participants. The results showed that intercultural sensitivity depends on the number of spoken foreign languages, which is a strong asset for a better understanding of cultural otherness. Nationality, socioeconomic status and gender had significant effects on ethnocentrism and ethnorelativism aspects of intercultural sensitivity

Signal level comparison between TerraSAR-X and COSMO-SkyMed SAR Sensors

International audienceSoil and vegetation biophysical parameter retrieval using synthetic-aperture-radar images requires radiometrically well-calibrated sensors. In this letter, a comparison of signal levels between TerraSAR-X (TSX) and the COSMO-SkyMed (CSK) constellation (CSK1, CSK2, CSK3, and CSK4) was carried out in order to analyze the ability to use jointly all current X-band sensors. The analysis of the X-band signal over forest stands showed a stable signal (variation lower than 1 dB) over time for each of the studied sensors, but a significant difference was observed between the different X-band sensors. Differences between radar signals were higher in HH than in HV polarization. TSX and CSK4 showed similar backscatter signals, with signal level differences of 0.6 dB in HH and 1.4 dB in HV. The CSK3 signal was observed to be lower than those from TSX and CSK4 by about 2.1 dB and 1.5 dB in HH against 3.2 dB and 1.8 dB in HV, respectively. Moreover, CSK2 and CSK1 which showed slightly different backscatter signals (within 1.1 dB in HH and 1.9 dB in HV) had signal levels lower than those obtained from TSX (2.2-3.3 dB in HH and 3.2-5.1 dB in HV for about 29° incidence angle). These results show that it is currently difficult to use jointly the available X-band satellites (CSK and TSX) for estimating the biophysical parameters of soil or vegetation. This is due to the significant difference in the radar signal level between some of the analyzed satellites, which will cause a high overor underestimation of biophysical parameters

Benchmarking a New Paradigm: An Experimental Analysis of a Real Processing-in-Memory Architecture

Many modern workloads, such as neural networks, databases, and graph processing, are fundamentally memory-bound. For such workloads, the data movement between main memory and CPU cores imposes a significant overhead in terms of both latency and energy. A major reason is that this communication happens through a narrow bus with high latency and limited bandwidth, and the low data reuse in memory-bound workloads is insufficient to amortize the cost of main memory access. Fundamentally addressing this data movement bottleneck requires a paradigm where the memory system assumes an active role in computing by integrating processing capabilities. This paradigm is known as processing-in-memory (PIM). Recent research explores different forms of PIM architectures, motivated by the emergence of new 3D-stacked memory technologies that integrate memory with a logic layer where processing elements can be easily placed. Past works evaluate these architectures in simulation or, at best, with simplified hardware prototypes. In contrast, the UPMEM company has designed and manufactured the first publicly-available real-world PIM architecture. This paper provides the first comprehensive analysis of the first publicly-available real-world PIM architecture. We make two key contributions. First, we conduct an experimental characterization of the UPMEM-based PIM system using microbenchmarks to assess various architecture limits such as compute throughput and memory bandwidth, yielding new insights. Second, we present PrIM, a benchmark suite of 16 workloads from different application domains (e.g., linear algebra, databases, graph processing, neural networks, bioinformatics).Comment: Our open source software is available at https://github.com/CMU-SAFARI/prim-benchmark