An Electrodynamics Solver for Moving Sources

An Electrodynamics solver for moving sources is introduced. The main challenges and formulation are highlighted. The solver enables the simulation of fields for sources undergoing arbitrary motion. Two examples of uniformly moving current sources are provided to correlate the numerical solver computations with theory, based on the solution of Maxwell's equations and the relativistic transformation of the electromagnetic fields

Action recognition using Kinematics Posture Feature on 3D skeleton joint locations

Action recognition is a very widely explored research area in computer vision and related fields. We propose Kinematics Posture Feature (KPF) extraction from 3D joint positions based on skeleton data for improving the performance of action recognition. In this approach, we consider the skeleton 3D joints as kinematics sensors. We propose Linear Joint Position Feature (LJPF) and Angular Joint Position Feature (AJPF) based on 3D linear joint positions and angles between bone segments. We then combine these two kinematics features for each video frame for each action to create the KPF feature sets. These feature sets encode the variation of motion in the temporal domain as if each body joint represents kinematics position and orientation sensors. In the next stage, we process the extracted KPF feature descriptor by using a low pass filter, and segment them by using sliding windows with optimized length. This concept resembles the approach of processing kinematics sensor data. From the segmented windows, we compute the Position-based Statistical Feature (PSF). These features consist of temporal domain statistical features (e.g., mean, standard deviation, variance, etc.). These statistical features encode the variation of postures (i.e., joint positions and angles) across the video frames. For performing classification, we explore Support Vector Machine (Linear), RNN, CNNRNN, and ConvRNN model. The proposed PSF feature sets demonstrate prominent performance in both statistical machine learning- and deep learning-based models. For evaluation, we explore five benchmark datasets namely UTKinect-Action3D, Kinect Activity Recognition Dataset (KARD), MSR 3D Action Pairs, Florence 3D, and Office Activity Dataset (OAD). To prevent overfitting, we consider the leave-one-subject-out framework as the experimental setup and perform 10-fold cross-validation. Our approach outperforms several existing methods in these benchmark datasets and achieves very promising classification performance

First Measurements of Electron Temperature Fluctuations by Correlation ECE on Tore Supra

Electron temperature fluctuation studies can help to understand the nature of the turbulent transport in to-kamak plasmas. At Tore Supra, a 32-channel heterodyne ECE radiometer has been upgraded with two chan-nels of 100 MHz bandwidth and tunable central frequencies allowing the shift of the plasma sample volume in the radial direction. With the sufficiently large video bandwidth and the long sampling time, it is possible to reduce significantly the thermal noise and to identify "true" high frequency components up to 200 kHz from the cross-correlation between these channels. First results of temperature fluctuation measurements on Tore Supra are reported in this paper.Comment: 12th International Congress on Plasma Physics, 25-29 October 2004, Nice (France

Deep Pipeline Architecture for Fast Fractal Color Image Compression Utilizing Inter-Color Correlation

Fractal compression technique is a well-known technique that encodes an image by mapping the image into itself and this requires performing a massive and repetitive search. Thus, the encoding time is too long, which is the main problem of the fractal algorithm. To reduce the encoding time, several hardware implementations have been developed. However, they are generally developed for grayscale images, and using them to encode colour images leads to doubling the encoding time 3× at least. Therefore, in this paper, new high-speed hardware architecture is proposed for encoding RGB images in a short time. Unlike the conventional approach of encoding the colour components similarly and individually as a grayscale image, the proposed method encodes two of the colour components by mapping them directly to the most correlated component with a searchless encoding scheme, while the third component is encoded with a search-based scheme. This results in reducing the encoding time and also in increasing the compression rate. The parallel and deep-pipelining approaches have been utilized to improve the processing time significantly. Furthermore, to reduce the memory access to the half, the image is partitioned in such a way that half of the matching operations utilize the same data fetched for processing the other half of the matching operations. Consequently, the proposed architecture can encode a 1024×1024 RGB image within a minimal time of 12.2 ms, and a compression ratio of 46.5. Accordingly, the proposed architecture is further superior to the state-of-the-art architectures.©2022 The Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

Ablations of Ghrelin and Ghrelin Receptor Exhibit Differential Metabolic Phenotypes and Thermogenic Capacity during Aging

mice are adaptive. mice.Our data therefore suggest that GHS-R ablation activates adaptive thermogenic function(s) in BAT and increases EE, thereby enabling the retention of a lean phenotype. This is the first direct evidence that the ghrelin signaling pathway regulates fat-burning BAT to affect energy balance during aging. This regulation is likely mediated through an as-yet-unidentified new ligand of GHS-R

Epigenetic Characterization of the FMR1 Gene and Aberrant Neurodevelopment in Human Induced Pluripotent Stem Cell Models of Fragile X Syndrome

Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. In addition to cognitive deficits, FXS patients exhibit hyperactivity, attention deficits, social difficulties, anxiety, and other autistic-like behaviors. FXS is caused by an expanded CGG trinucleotide repeat in the 5′ untranslated region of the Fragile X Mental Retardation (FMR1) gene leading to epigenetic silencing and loss of expression of the Fragile X Mental Retardation protein (FMRP). Despite the known relationship between FMR1 CGG repeat expansion and FMR1 silencing, the epigenetic modifications observed at the FMR1 locus, and the consequences of the loss of FMRP on human neurodevelopment and neuronal function remain poorly understood. To address these limitations, we report on the generation of induced pluripotent stem cell (iPSC) lines from multiple patients with FXS and the characterization of their differentiation into post-mitotic neurons and glia. We show that clones from reprogrammed FXS patient fibroblast lines exhibit variation with respect to the predominant CGG-repeat length in the FMR1 gene. In two cases, iPSC clones contained predominant CGG-repeat lengths shorter than measured in corresponding input population of fibroblasts. In another instance, reprogramming a mosaic patient having both normal and pre-mutation length CGG repeats resulted in genetically matched iPSC clonal lines differing in FMR1 promoter CpG methylation and FMRP expression. Using this panel of patient-specific, FXS iPSC models, we demonstrate aberrant neuronal differentiation from FXS iPSCs that is directly correlated with epigenetic modification of the FMR1 gene and a loss of FMRP expression. Overall, these findings provide evidence for a key role for FMRP early in human neurodevelopment prior to synaptogenesis and have implications for modeling of FXS using iPSC technology. By revealing disease-associated cellular phenotypes in human neurons, these iPSC models will aid in the discovery of novel therapeutics for FXS and other autism-spectrum disorders sharing common pathophysiology.FRAXA Research FoundationHarvard Stem Cell Institute (seed grant)Stanley Medical Research InstituteNational Institute of Mental Health (U.S.) (grant #R33MH087896

Analysis of the TGFβ functional pathway in epithelial ovarian carcinoma

Epithelial ovarian carcinoma is often diagnosed at an advanced stage of disease and is the leading cause of death from gynaecological neoplasia. The genetic changes that occur during the development of this carcinoma are poorly understood. It has been proposed that IGFIIR, TGFβ1 and TGFβRII act as a functional unit in the TGFβ growth inhibitory pathway, and that somatic loss-of-function mutations in any one of these genes could lead to disruption of the pathway and subsequent loss of cell cycle control. We have examined these 3 genes in 25 epithelial ovarian carcinomas using single-stranded conformational polymorphism analysis and DNA sequence analysis. A total of 3 somatic missense mutations were found in the TGFβRII gene, but none in IGFRII or TGFβ1. An association was found between TGFβRII mutations and histology, with 2 out of 3 clear cell carcinomas having TGFβRII mutations. This data supports other evidence from mutational analysis of the PTEN and β-catenin genes that there are distinct developmental pathways responsible for the progression of different epithelial ovarian cancer histologic subtypes. © 2001 Cancer Research Campaign http://www.bjcancer.co

Global economic burden of unmet surgical need for appendicitis

Background: There is a substantial gap in provision of adequate surgical care in many low-and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods: Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results: Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion: For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially