A k-space method for nonlinear wave propagation

A k-space method for nonlinear wave propagation in absorptive media is presented. The Westervelt equation is first transferred into k-space via Fourier transformation, and is solved by a modified wave-vector time-domain scheme [Mast et al., IEEE Tran. Ultrason. Ferroelectr. Freq. Control 48, 341-354 (2001)]. The present approach is not limited to forward propagation or parabolic approximation. One- and two-dimensional problems are investigated to verify the method by comparing results to the finite element method. It is found that, in order to obtain accurate results in homogeneous media, the grid size can be as little as two points per wavelength, and for a moderately nonlinear problem, the Courant-Friedrichs-Lewy number can be as small as 0.4. As a result, the k-space method for nonlinear wave propagation is shown here to be computationally more efficient than the conventional finite element method or finite-difference time-domain method for the conditions studied here. However, although the present method is highly accurate for weakly inhomogeneous media, it is found to be less accurate for strongly inhomogeneous media. A possible remedy to this limitation is discussed

VARIOUS LEVELS OF ERYTHROMYCIN ON THE DEVELOPMENT OF ANTIBIOTIC RESISTANCE IN ESCHERICHIA COLI

Master'sMASTER OF ENGINEERIN

An Improved Histogram Based Boosting Detection Rate Video Watermarking Algorithm

The existing histogram based video watermarking algorithm with temporal modulated is robust to combined attacks, but the watermark detection rate is not high due to watermark cannot embedded to the smoothness and still areas effectively. To increase the watermark detection rate, in this paper, we proposed the improved algorithm of shot segmentation first and then propose an improved video watermarking algorithm which firstly construct the watermark template in each frame video in the same shot through computing block based histogram and selecting the position of the relative high variance. Then we embed the watermark template into the video frame by temporal modulation without changing the destination of the shot group of the consecutive frames. The watermark sequence is extracted by comparing the correlation distribution of video frame and corresponding watermark template in the time domain. Experimental results demonstrate that the proposed algorithm is robust to recording attacks and guarantee the watermarking video quality at the same time, besides the watermark sequences can embedded to the smoothness and still areas effectively, and the watermark detection rate can increase by about 10% than previous methods

Ovarian juvenile granulosa cell tumors with Ollier’s disease in children with IDH1 gene somatic mutation

ObjectiveThe aim of this study was to explore the symptoms, treatment, and pathogenesis of ovarian juvenile granulosa cell tumors with Ollier’s disease in children.MethodsFrom October 2019 to October 2020, clinical data were retrospectively analyzed for one case of ovarian juvenile granulosa cell tumors with Ollier’s disease. Whole-exome sequencing and Sanger sequencing were used to detect gene mutation in ovarian tumor and chondroma tissue. NADP-dependent isocitrate dehydrogenase-1 (IDH1) and S6 ribosomal protein expression levels in cells transfected with wild-type or mutant plasmid were analyzed by Western blot.ResultsThe 4-year-old female showed multiple skeletal deformities, bilateral breast development with chromatosis, and vulvar discharge. Sex hormone assay suggested that estradiol and prolactin were elevated, and the x-ray of limbs suggested enchondroma. Pelvic ultrasound and abdominal CT revealed a right ovarian solid mass. Pathologic examination of the right ovarian solid mass showed a juvenile granulosa cell type. A c.394C>T (p. Arg132Cys) mutation of the IDH1 gene was detected in both the ovarian juvenile granulosa cell tumors and enchondroma. Transfection of HeLa cells with either WT or Mut plasmid caused 4.46- or 3.77-fold overexpression of IDH1 gene compared to non-transfected control cells, respectively. R132C mutation inhibited the phosphorylation of S6 ribosomal protein, which is central to the mTOR pathway. Postoperatively, estradiol and prolactin levels fell to values normal for her age and bilateral breast gradual retraction.ConclusionThe incidence of ovarian juvenile granulosa cell tumors with Ollier’s disease in children may be caused by generalized mesodermal dysplasia; IDH1 gene mutation may play a facilitated role in this process. Surgical operation is the main treatment. We suggest that patients with ovarian juvenile granulosa cell tumors and Ollier’s disease should undergo regular investigation

Developmental potential of aneuploid human embryos cultured beyond implantation

Funder: Weston Havens Foundation; doi: https://doi.org/10.13039/100011223Abstract: Aneuploidy, the presence of an abnormal number of chromosomes, is a major cause of early pregnancy loss in humans. Yet, the developmental consequences of specific aneuploidies remain unexplored. Here, we determine the extent of post-implantation development of human embryos bearing common aneuploidies using a recently established culture platform. We show that while trisomy 15 and trisomy 21 embryos develop similarly to euploid embryos, monosomy 21 embryos exhibit high rates of developmental arrest, and trisomy 16 embryos display a hypo-proliferation of the trophoblast, the tissue that forms the placenta. Using human trophoblast stem cells, we show that this phenotype can be mechanistically ascribed to increased levels of the cell adhesion protein E-CADHERIN, which lead to premature differentiation and cell cycle arrest. We identify three cases of mosaicism in embryos diagnosed as full aneuploid by pre-implantation genetic testing. Our results present the first detailed analysis of post-implantation development of aneuploid human embryos

The role of SHIP2 in suppressing inflammatory signaling induced by LPS in immortalized murine macrophage cell line

Inflammation is an important step in the body’s defense against pathogen infection. However, it must be tightly regulated and appropriately terminated to prevent pathological consequences. Interleukin-10 (IL10) is one of the body’s most important anti-inflammatory cytokine that can inhibit many molecular events necessary for promoting inflammation including production of pro-inflammatory cytokines such as Tumor Necrosis Factor α (TNFα). Our laboratory has recently shown that SH2-domain containing Inositol 5ʹ phosphatase (SHIP1) is involved in IL10 signaling in macrophages, and although the mechanism of how this occurs is not well studied, our laboratory have obtained data suggesting SHIP1 mediates IL10 signalling through its phosphatase activity or interaction with other signalling proteins. SHIP2 is the only other known homologue of SHIP1 with approximately 38% amino acid sequence identity, yet they possess several similar functions including mediating FcγIIB signaling and phagocytosis. Because of their similarities and SHIP1’s involvement in IL10 signaling, we sought to investigate whether SHIP2 is also involved in inhibiting inflammatory response in macrophage by knocking it out using CRISPR/Cas9-mediated genome editing. Overall, we were unable to determine whether SHIP2 plays a role in macrophage anti-inflammatory response due to the large variation in cell sensitivity to IL10 and we also observed that transduction of macrophages with CRISPR/Cas9 virus alters the cellular response to IL10 which confounded our investigation of SHIP2 function.Medicine, Faculty ofBiochemistry and Molecular Biology, Department ofGraduat

Machine Learning on Terrain Data and Logged Vehicle Data to Gain Insights into Operating Conditions for an Articulated Hauler : Machine Learning on Terrain Data and Logged Vehicle Data to Gain Insights into Operating Conditions for an Articulated Hauler

Manufacturers can develop next-generation production and service for their customers by the data gathered and analyzed from customers’ usage conditions. In this research, the operating condition of articular haulers is collected and analyzed through machine learning algorithms to predict the type of operational topographies and road surface. To achieve that, elevation data and satellite images, which were gathered from Microsoft Azure Maps, are used as data sources to identify the topography and road surface on which machines operated. In the end, two machine learning models are trained with machines’ inclination records and road roughness records, respectively, to classify the topography and road surface. For the topography classifier, the topography is categorized into four terrain labels, including "Low Hills", "Mountains", "Plains", and "Tablelands & High Hills". The road surface is classified into "Paved" and "Unpaved". A Convolutional Neural Network (CNN) image classification model is built for labeling satellite images instead of labeling manually. The results indicate that the prediction for topography labels "Plains" and "Tablelands & High Hills" has superior performance, which accounts for the majority of the raw dataset; on the contrary, the road surface classifier still needs further improvement in the future. In addition, an analysis and discussion regarding the imbalanced dataset are included, and it shows the limited effect on an extremely imbalanced dataset. Finally, the conclusion and future work are given