Image based human body rendering via regression & MRF energy minimization

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A machine learning method for synthesising human images is explored to create new images without relying on 3D modelling. Machine learning allows the creation of new images through prediction from existing data based on the use of training images. In the present study, image synthesis is performed at two levels: contour and pixel. A class of learning-based methods is formulated to create object contours from the training image for the synthetic image that allow pixel synthesis within the contours in the second level. The methods rely on applying robust object descriptions, dynamic learning models after appropriate motion segmentation, and machine learning-based frameworks. Image-based human image synthesis using machine learning is a research focus that has recently gained considerable attention in the field of computer graphics. It makes use of techniques from image/motion analysis in computer vision. The problem lies in the estimation of methods for image-based object configuration (i.e. segmentation, contour outline). Using the results of these analysis methods as bases, the research adopts the machine learning approach, in which human images are synthesised by executing the synthesis of contour and pixels through the learning from training image. Firstly, thesis shows how an accurate silhouette is distilled using developed background subtraction for accuracy and efficiency. The traditional vector machine approach is used to avoid ambiguities within the regression process. Images can be represented as a class of accurate and efficient vectors for single images as well as sequences. Secondly, the framework is explored using a unique view of machine learning methods, i.e., support vector regression (SVR), to obtain the convergence result of vectors for contour allocation. The changing relationship between the synthetic image and the training image is expressed as a vector and represented in functions. Finally, a pixel synthesis is performed based on belief propagation. This thesis proposes a novel image-based rendering method for colour image synthesis using SVR and belief propagation for generalisation to enable the prediction of contour and colour information from input colour images. The methods rely on using appropriately defined and robust input colour images, optimising the input contour images within a sparse SVR framework. Firstly, the thesis shows how contour can effectively and efficiently be predicted from small numbers of input contour images. In addition, the thesis exploits the sparse properties of SVR efficiency, and makes use of SVR to estimate regression function. The image-based rendering method employed in this study enables contour synthesis for the prediction of small numbers of input source images. This procedure avoids the use of complex models and geometry information. Secondly, the method used for human body contour colouring is extended to define eight differently connected pixels, and construct a link distance field via the belief propagation method. The link distance, which acts as the message in propagation, is transformed by improving the low-envelope method in fast distance transform. Finally, the methodology is tested by considering human facial and human body clothing information. The accuracy of the test results for the human body model confirms the efficiency of the proposed method

Study of Automatic Fiber Placement Manipulator's Robotic Kinematics Manipulability Based on Volume Element

Abstract: The method is proposed based on volume element in order to measure the manipulator's robotic kinematics manipulability. Then studied the series redundant automatic fiber placement robotic manipulator's operation space, draw the conclusion that the greater of the robotic manipulator's operation space volume, the better of the robotic manipulator's manipulability, volume element based on redundant robotic manipulator's kinematics is proposed as an operational performance index. n-DOF serial robotic manipulator's operation space is n-dimensional Riemannian manifold, the n-dimensional Riemannian manifold volume is calculated using the moving coordinate system and the exterior product definition in differential geometry and get the robotic manipulator's operation space volume then compared the obtained results with the operation space volume using inner product determinant in the literature, it shows that the volume element as a kinematics operational performance index is feasible

FPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture

Neural Network (NN) accelerators with emerging ReRAM (resistive random access memory) technologies have been investigated as one of the promising solutions to address the \textit{memory wall} challenge, due to the unique capability of \textit{processing-in-memory} within ReRAM-crossbar-based processing elements (PEs). However, the high efficiency and high density advantages of ReRAM have not been fully utilized due to the huge communication demands among PEs and the overhead of peripheral circuits. In this paper, we propose a full system stack solution, composed of a reconfigurable architecture design, Field Programmable Synapse Array (FPSA) and its software system including neural synthesizer, temporal-to-spatial mapper, and placement & routing. We highly leverage the software system to make the hardware design compact and efficient. To satisfy the high-performance communication demand, we optimize it with a reconfigurable routing architecture and the placement & routing tool. To improve the computational density, we greatly simplify the PE circuit with the spiking schema and then adopt neural synthesizer to enable the high density computation-resources to support different kinds of NN operations. In addition, we provide spiking memory blocks (SMBs) and configurable logic blocks (CLBs) in hardware and leverage the temporal-to-spatial mapper to utilize them to balance the storage and computation requirements of NN. Owing to the end-to-end software system, we can efficiently deploy existing deep neural networks to FPSA. Evaluations show that, compared to one of state-of-the-art ReRAM-based NN accelerators, PRIME, the computational density of FPSA improves by 31x; for representative NNs, its inference performance can achieve up to 1000x speedup.Comment: Accepted by ASPLOS 201

Epigenetic regulation of CD271, a potential cancer stem cell marker associated with chemoresistance and metastatic capacity.

Cancer stem cells (CSCs) are considered to be the cause of tumor initiation, metastasis and recurrence. Additionally, CSCs are responsible for the failure of chemotherapy and radiotherapy. The isolation and identification of CSCs is crucial for facilitating the monitoring, therapy or prevention of cancer. We aimed to identify esophageal squamous cell carcinoma (ESCC) stem-like cells, the epigenetic mechanism and identify novel biomarkers for targeting ESCC CSCs. Sixty-three paired ESCC tissues and adjacent non-cancerous tissues were included in this study. CD271, which was identified as the CSC marker for melanoma, was assessed using quantitative PCR (qPCR). Using flow cytometry, we isolated CD271+ cells comprising 7.5% of cancer cells from the KYSE70 cell line. Sphere formation and anchorage-independent growth were analyzed in CD271+ and CD271- cancer cells, respectively. qPCR was used to detect stem-related genes and CCK-8 was performed to analyze the sensitivity to chemotherapy in the two groups. Bisulfite genomic sequencing was used to analyze the methylation status. CD271 expression was significantly higher in ESCC tissues than in adjacent non-cancerous tissues. Compared with CD271- cancer cells, CD271+ cancer cells showed a higher ability of sphere and colony formation, a high level expression of stem-related gene, and resistance to chemotherapy. The expression of CD271 was induced by a demethylation agent. In conclusion, CD271+ ESCC cells possess stem-like properties. CD271 can potentially act as a prognostic marker for ESCC, whose expression is regulated epigenetically

Beyond Universal Transformer: block reusing with adaptor in Transformer for automatic speech recognition

Transformer-based models have recently made significant achievements in the application of end-to-end (E2E) automatic speech recognition (ASR). It is possible to deploy the E2E ASR system on smart devices with the help of Transformer-based models. While these models still have the disadvantage of requiring a large number of model parameters. To overcome the drawback of universal Transformer models for the application of ASR on edge devices, we propose a solution that can reuse the block in Transformer models for the occasion of the small footprint ASR system, which meets the objective of accommodating resource limitations without compromising recognition accuracy. Specifically, we design a novel block-reusing strategy for speech Transformer (BRST) to enhance the effectiveness of parameters and propose an adapter module (ADM) that can produce a compact and adaptable model with only a few additional trainable parameters accompanying each reusing block. We conducted an experiment with the proposed method on the public AISHELL-1 corpus, and the results show that the proposed approach achieves the character error rate (CER) of 9.3%/6.63% with only 7.6M/8.3M parameters without and with the ADM, respectively. In addition, we also make a deeper analysis to show the effect of ADM in the general block-reusing method

Pleural effusion adenosine deaminase: a candidate biomarker to discriminate between Gram-negative and Gram-positive bacterial infections of the pleural space

OBJECTIVES: Delay in the treatment of pleural infection may contribute to its high mortality. In this retrospective study, we aimed to evaluate the diagnostic accuracy of pleural adenosine deaminase in discrimination between Gram-negative and Gram-positive bacterial infections of the pleural space prior to selecting antibiotics. METHODS: A total of 76 patients were enrolled and grouped into subgroups according to Gram staining: 1) patients with Gram-negative bacterial infections, aged 53.2±18.6 years old, of whom 44.7% had empyemas and 2) patients with Gram-positive bacterial infections, aged 53.5±21.5 years old, of whom 63.1% had empyemas. The pleural effusion was sampled by thoracocentesis and then sent for adenosine deaminase testing, biochemical testing and microbiological culture. The Mann-Whitney U test was used to examine the differences in adenosine deaminase levels between the groups. Correlations between adenosine deaminase and specified variables were also quantified using Spearman’s correlation coefficient. Moreover, receiver operator characteristic analysis was performed to evaluate the diagnostic accuracy of pleural effusion adenosine deaminase. RESULTS: Mean pleural adenosine deaminase levels differed significantly between Gram-negative and Gram-positive bacterial infections of the pleural space (191.8±32.1 U/L vs 81.0±16.9 U/L,

Hidden upwelling systems associated with major western boundary currents

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Liao, F., Liang, X., Li, Y., & Spall, M. Hidden upwelling systems associated with major western boundary currents. Journal of Geophysical Research: Oceans. 127, (2022): e2021JC017649, https://doi.org/10.1029/2021jc017649.Western boundary currents (WBCs) play an essential role in regulating global climate. In contrast to their widely examined horizontal motions, less attention has been paid to vertical motions associated with WBCs. Here, we examine vertical motions associated with the major WBCs by analyzing vertical velocity from five ocean synthesis products and one eddy-resolving ocean simulation. These data reveal robust and intense subsurface upwelling systems, which are primarily along isopycnal surfaces, in five major subtropical WBC systems. These upwelling systems are part of basin-scale overturning circulations and are likely driven by meridional pressure gradients along the western boundary. Globally, the WBC upwelling contributes significantly to the vertical transport of water mass and ocean properties and is an essential yet overlooked branch of the global ocean circulation. In addition, the WBC upwelling intersects the oceanic euphotic and mixed layers, and thus likely plays an important role in ocean biological and chemical processes by transporting nutrients, carbon and other tracers vertically inside the ocean. This study calls for more research into the dynamics of the WBC upwelling and their role in the ocean and climate systems.X. Liang is supported by the National Science Foundation through Grants OCE-2021274, OCE-2122507, and the Alfred P. Sloan Foundation through Grant FG-2019-12536. M. Spall is supported through the National Science Foundation Grants OCE-1947290 and OCE-2122633

Laminoplasty versus laminectomy for multi-level cervical spondylotic myelopathy: a systematic review of the literature

BACKGROUND: There is considerable controversy as to which posterior technique is best for the treatment of multi-level cervical spondylotic myelopathy. The aim of this study was to compare the clinical and radiographic results and complications of laminoplasty (LAMP) and laminectomy (LAMT) in the treatment of multi-level cervical spondylotic myelopathy. METHODS: We reviewed and analyzed papers published from January 1966 and June 2013 regarding the comparison of LAMP and LAMT for multi-level cervical spondylotic myelopathy. Statistical comparisons were made when appropriate. RESULTS: Fifteen studies were included in this systematic review. There was no significant difference in the incidence of surgical complications between LAMP and LAMT. Compared to conventional LAMT and skip LAMT, postoperative ROM was more limited in LAMP, but this was still superior to postoperative ROM following LAMT with fusion. Postoperative kyphosis occurred in 8/180 (4.44%) in LAMP and 13/205 (6.34%) in LAMT, whereas no cases of kyphosis were reported for skip LAMT. Skip LAMT appears to have better clinical outcomes than LAMP, while the outcome was similar between LAMP and LAMT with fusion. CONCLUSIONS: Based on these results, a claim of superiority for laminoplasty or laminectomy was not justified. In deciding between the two procedures, the risks of surgical and neurological complications, and radiologic and clinical outcome, must be taken into consideration if both options are available in multi-level cervical spondylotic myelopathy

Inhibition of HSP90 promotes neural stem cell survival from oxidative stress through attenuating NF-κB/p65 activation

Stem cell survival post transplantation determines the efficiency of stem cell treatment, which develops as a novel potential therapy for several central nervous system (CNS) diseases in recent decades of yeas. The engrafted stem cells face the damage of oxidative stress, inflammation and immune response at the lesion point in host. Among the pathology, oxidative stress directs stem cells to apoptosis and even death through several signalling pathways and DNA damage. However, the in detail mechanism of stem cell survival from oxidative stress has not revealed clearly. Here in this study, we used hydrogen peroxide (H2O2) to induced the oxidative damage on neural stem cells (NSCs). The damage was in consequence demonstrated involving the activation of heat shock protein 90 (HSP90) and NF-κB/p65 signalling pathways. Further application of the pharmacological inhibitors respectively targeting at each signalling indicated an upper streaming role of HSP90 upon NF-κB/p65 on NSCs survival. Pre-inhibition of HSP90 with the specific inhibitor displayed a significant protection on NSCs against oxidative stress. In conclusion, inhibition of HSP90 would attenuate NF-κB/p65 activation by oxidative induction and promote NSCs survival from oxidative damage. The HSP90/NF-κB mechanism provides a new evidence on rescuing NSCs from oxidative stress, and also promotes the stem cell application on CNS pathologies