Gaussian process for ground-motion prediction and emulation of systems of computer models

In this thesis, several challenges in both ground-motion modelling and the surrogate modelling, are addressed by developing methods based on Gaussian processes (GP). The first chapter contains an overview of the GP and summarises the key findings of the rest of the thesis. In the second chapter, an estimation algorithm, called the Scoring estimation approach, is developed to train GP-based ground-motion models with spatial correlation. The Scoring estimation approach is introduced theoretically and numerically, and it is proven to have desirable properties on convergence and computation. It is a statistically robust method, producing consistent and statistically efficient estimators of spatial correlation parameters. The predictive performance of the estimated ground-motion model is assessed by a simulation-based application, which gives important implications on the seismic risk assessment. In the third chapter, a GP-based surrogate model, called the integrated emulator, is introduced to emulate a system of multiple computer models. It generalises the state-of-the-art linked emulator for a system of two computer models and considers a variety of kernels (exponential, squared exponential, and two key Matérn kernels) that are essential in advanced applications. By learning the system structure, the integrated emulator outperforms the composite emulator, which emulates the entire system using only global inputs and outputs. Furthermore, its analytic expressions allow a fast and efficient design algorithm that could yield significant computational and predictive gains by allocating different runs to individual computer models based on their heterogeneous functional complexity. The benefits of the integrated emulator are demonstrated in a series of synthetic experiments and a feed-back coupled fire-detection satellite model. Finally, the developed method underlying the integrated emulator is used to construct a non-stationary Gaussian process model based on deep Gaussian hierarchy

Linked Deep Gaussian Process Emulation for Model Networks

Modern scientific problems are often multi-disciplinary and require integration of computer models from different disciplines, each with distinct functional complexities, programming environments, and computation times. Linked Gaussian process (LGP) emulation tackles this challenge through a divide-and-conquer strategy that integrates Gaussian process emulators of the individual computer models in a network. However, the required stationarity of the component Gaussian process emulators within the LGP framework limits its applicability in many real-world applications. In this work, we conceptualize a network of computer models as a deep Gaussian process with partial exposure of its hidden layers. We develop a method for inference for these partially exposed deep networks that retains a key strength of the LGP framework, whereby each model can be emulated separately using a DGP and then linked together. We show in both synthetic and empirical examples that our linked deep Gaussian process emulators exhibit significantly better predictive performance than standard LGP emulators in terms of accuracy and uncertainty quantification. They also outperform single DGPs fitted to the network as a whole because they are able to integrate information from the partially exposed hidden layers. Our methods are implemented in an R package $\texttt{dgpsi}$ that is freely available on CRAN

Linked Gaussian Process Emulation for Systems of Computer Models Using Matérn Kernels and Adaptive Design

The state-of-the-art linked Gaussian process offers a way to build analytical emulators for systems of computer models. We generalize the closed form expressions for the linked Gaussian process under the squared exponential kernel to a class of Mat\'ern kernels, that are essential in advanced applications. An iterative procedure to construct linked Gaussian processes as surrogate models for any feed-forward systems of computer models is presented and illustrated on a feed-back coupled satellite system. We also introduce an adaptive design algorithm that could increase the approximation accuracy of linked Gaussian process surrogates with reduced computational costs on running expensive computer systems, by allocating runs and refining emulators of individual sub-models based on their heterogeneous functional complexity

Deep Gaussian Process Emulation using Stochastic Imputation

We propose a novel deep Gaussian process (DGP) inference method for computer model emulation using stochastic imputation. By stochastically imputing the latent layers, the approach transforms the DGP into the linked GP, a state-of-the-art surrogate model formed by linking a system of feed-forward coupled GPs. This transformation renders a simple while efficient DGP training procedure that only involves optimizations of conventional stationary GPs. In addition, the analytically tractable mean and variance of the linked GP allows one to implement predictions from DGP emulators in a fast and accurate manner. We demonstrate the method in a series of synthetic examples and real-world applications, and show that it is a competitive candidate for efficient DGP surrogate modeling in comparison to the variational inference and the fully-Bayesian approach. A $\texttt{Python}$ package $\texttt{dgpsi}$ implementing the method is also produced and available at https://github.com/mingdeyu/DGP

Viia-hand: a Reach-and-grasp Restoration System Integrating Voice interaction, Computer vision and Auditory feedback for Blind Amputees

Visual feedback plays a crucial role in the process of amputation patients completing grasping in the field of prosthesis control. However, for blind and visually impaired (BVI) amputees, the loss of both visual and grasping abilities makes the "easy" reach-and-grasp task a feasible challenge. In this paper, we propose a novel multi-sensory prosthesis system helping BVI amputees with sensing, navigation and grasp operations. It combines modules of voice interaction, environmental perception, grasp guidance, collaborative control, and auditory/tactile feedback. In particular, the voice interaction module receives user instructions and invokes other functional modules according to the instructions. The environmental perception and grasp guidance module obtains environmental information through computer vision, and feedbacks the information to the user through auditory feedback modules (voice prompts and spatial sound sources) and tactile feedback modules (vibration stimulation). The prosthesis collaborative control module obtains the context information of the grasp guidance process and completes the collaborative control of grasp gestures and wrist angles of prosthesis in conjunction with the user's control intention in order to achieve stable grasp of various objects. This paper details a prototyping design (named viia-hand) and presents its preliminary experimental verification on healthy subjects completing specific reach-and-grasp tasks. Our results showed that, with the help of our new design, the subjects were able to achieve a precise reach and reliable grasp of the target objects in a relatively cluttered environment. Additionally, the system is extremely user-friendly, as users can quickly adapt to it with minimal training

Why Do Woodpeckers Resist Head Impact Injury: A Biomechanical Investigation

Head injury is a leading cause of morbidity and death in both industrialized and developing countries. It is estimated that brain injuries account for 15% of the burden of fatalities and disabilities, and represent the leading cause of death in young adults. Brain injury may be caused by an impact or a sudden change in the linear and/or angular velocity of the head. However, the woodpecker does not experience any head injury at the high speed of 6–7 m/s with a deceleration of 1000 g when it drums a tree trunk. It is still not known how woodpeckers protect their brain from impact injury. In order to investigate this, two synchronous high-speed video systems were used to observe the pecking process, and the force sensor was used to measure the peck force. The mechanical properties and macro/micro morphological structure in woodpecker's head were investigated using a mechanical testing system and micro-CT scanning. Finite element (FE) models of the woodpecker's head were established to study the dynamic intracranial responses. The result showed that macro/micro morphology of cranial bone and beak can be recognized as a major contributor to non-impact-injuries. This biomechanical analysis makes it possible to visualize events during woodpecker pecking and may inspire new approaches to prevention and treatment of human head injury

Strategies for Searching Video Content with Text Queries or Video Examples

The large number of user-generated videos uploaded on to the Internet everyday has led to many commercial video search engines, which mainly rely on text metadata for search. However, metadata is often lacking for user-generated videos, thus these videos are unsearchable by current search engines. Therefore, content-based video retrieval (CBVR) tackles this metadata-scarcity problem by directly analyzing the visual and audio streams of each video. CBVR encompasses multiple research topics, including low-level feature design, feature fusion, semantic detector training and video search/reranking. We present novel strategies in these topics to enhance CBVR in both accuracy and speed under different query inputs, including pure textual queries and query by video examples. Our proposed strategies have been incorporated into our submission for the TRECVID 2014 Multimedia Event Detection evaluation, where our system outperformed other submissions in both text queries and video example queries, thus demonstrating the effectiveness of our proposed approaches

Toll‐like receptor‐mediated IRE1α activation as a therapeutic target for inflammatory arthritis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/1/embj2013183-sup-0004-SourceData-S4.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/2/embj2013183-sup-0001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/3/embj2013183-sup-0008-SourceData-S8.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/4/embj2013183-sup-0005-SourceData-S5.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/5/embj2013183-sup-0001-SourceData-S1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/6/embj2013183-sup-0009-SourceData-S9.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/7/embj2013183-sup-0006-SourceData-S6.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/8/embj2013183-sup-0002-SourceData-S2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/9/embj2013183-sup-0010-SourceData-S10.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/10/embj2013183-sup-0007-SourceData-S7.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/11/embj2013183-sup-0003-SourceData-S3.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/12/embj2013183.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/13/embj2013183.reviewer_comments.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102185/14/embj2013183-sup-0011-SourceData-S11.pd

Synthesis and antibacterial activity against ralstonia solanacearum for novel hydrazone derivatives containing a pyridine moiety

<p>Abstract</p> <p>Background</p> <p><it>Ralstonia solanacearum</it>, one of the most important bacterial diseases on plants, is a devastating, soil-borne plant pathogen with a global distribution and an unusually wide host range. In order to discover new bioactive molecules and pesticides acting on tobacco bacterial wilt, we sought to combine the active structure of hydrazone and pyridine together to design and synthesize a series of novel hydrazone derivatives containing a pyridine moiety.</p> <p>Results</p> <p>A series of hydrazone derivatives containing a pyridine moiety were synthesized. Their structures were characterized by ¹H-NMR, ¹³C-NMR, IR, and elemental analysis. The preliminary biological activity tests showed that compound 3e and 3g exhibited more than 80% activity against <it>Ralstonia solanacearum </it>at 500 mg/L, especially compound 3g displayed relatively good activity to reach 57.0% at 200 mg/L.</p> <p>Conclusion</p> <p>A practical synthetic route to hydrazone derivatives containing a pyridine moiety by the reaction of intermediates 2 with different aldehydes in ethanol at room temperature using 2-chloronicotinic acid and 2-amino-5-chloro-3-methylbenzoic acid as start materials is presented. This study suggests that the hydrazone derivatives containing a substituted pyridine ring could inhibit the growth of <it>Ralstonia solanacearum</it>.</p

Clinical use of zinc in viral warts: a systematic review of the clinical trials

Background Zinc has shown promise in the treatment of patients with viral warts in several clinical trials, but there is no consensus on its effectiveness. Objective To investigate the efficacy of various formulations of zinc on cutaneous warts. Data sources We searched the Cochrane Central Register of Controlled Trials, EMBASE, PUBMED, and Web of Science without publishing-time restriction. Trials examining zinc in the treatment of warts were collected. Results Out of 265 articles, a total of 16 met inclusion criteria. Six clinical trials investigated the clinical effectiveness of oral zinc supplementation alone in treating viral warts, two trials evaluated the efficacy of oral zinc in combination with other therapy, five trials investigated the efficacy of intralesional zinc sulfate, and three trials investigated topical zinc treatment efficacy. Zinc therapy was found to be beneficial in 13 of 16 studies evaluating its effects on warts. Conclusions The use of zinc is a simple, safe, and cost-effective treatment in viral warts based on some preliminary evidence. However, more well-designed studies need to be performed to further evaluate the effect of zinc on warts