591 research outputs found
Design of a passive hydraulic simulator for abnormal muscle behavior replication
Spasticity and rigidity are two abnormal hypertonic muscle behaviors commonly observed in passive joint flexion and extension evaluation. Clinical evaluation for spasticity and rigidity is done through in-person assessment using qualitative scales. Due to the subjective nature of this evaluation method, diagnostic results produced from these clinical assessments can have poor reliability and inconsistency. Incorrect diagnosis and treatment often result in worsening of the abnormal muscle behaviors, reducing the quality of life and leading to an increased cost of healthcare. Several programmable, robotic simulators had been developed to improve the accuracy of clinical evaluation by providing clinician practical training opportunities; however none of these training devices are commercially available due to technical and manufacturing limitations. For this reason, a novel, purely mechanical, hydraulic-based simulator design was proposed as an alternative approach to abnormal muscle behavior simulation. The original goal of the project presented in this thesis was to address both spasticity and rigidity in the elbow joint during flexion; however due to time constraints, the initial prototype can only mimic spasticity. The hydraulic-based simulator utilized a novel damper design using viscous fluid in combination with creative flow channel configurations to replicate different levels of spasticity behaviors depicted on a qualitative scale. The simulator was capable of generating a wide range of speed-dependent force feedbacks without need for any computational controls. Preliminary results obtained from evaluating the simulator suggested the possibility of using this novel design in replicating the speed-dependent characteristics of spasticity. The framework and method implemented in the current simulator prototype could be further developed and expanded to replicate spasticity or other types of abnormal behaviors, such as rigidity, in various human joints (not limiting the design to just the elbow joint)
Loan Loss Provisioning of UK Commercial Banks Pre- and Post-Global Financial Crisis
This paper undertook a research on 29 UK commercial banks between the periods of 2006 to 2012 for observing the loan loss provisioning of the selected banks pre- and post- global financial crisis. There are two models were applied for this research, which are X-efficiency model and GMM model. We tested four hypotheses: 1) Do UK commercial banks conduct their provisioning relying on the business cycle? 2) Does income smoothing behaviour exist in the UK commercial banks? 3) Does capital management exist in the UK commercial banks? 4) Is Bank efficiency endogenous to loan loss provisioning? If yes / no, how does it correlate with loan loss provisioning? Our results showed no evidence for UK banks to conduct income smoothing and capital management through loan loss provisioning. However, we found a negative relationship between bank efficiency and loan loss provisioning and market concentration problem for the selected banks. The result suggests that the FCA should pay more attention to the loan portfolios of high market power banks
Loan Loss Provisioning of UK Commercial Banks Pre- and Post-Global Financial Crisis
This paper undertook a research on 29 UK commercial banks between the periods of 2006 to 2012 for observing the loan loss provisioning of the selected banks pre- and post- global financial crisis. There are two models were applied for this research, which are X-efficiency model and GMM model. We tested four hypotheses: 1) Do UK commercial banks conduct their provisioning relying on the business cycle? 2) Does income smoothing behaviour exist in the UK commercial banks? 3) Does capital management exist in the UK commercial banks? 4) Is Bank efficiency endogenous to loan loss provisioning? If yes / no, how does it correlate with loan loss provisioning? Our results showed no evidence for UK banks to conduct income smoothing and capital management through loan loss provisioning. However, we found a negative relationship between bank efficiency and loan loss provisioning and market concentration problem for the selected banks. The result suggests that the FCA should pay more attention to the loan portfolios of high market power banks
Improving tensor regression by optimal model averaging
Tensors have broad applications in neuroimaging, data mining, digital
marketing, etc. CANDECOMP/PARAFAC (CP) tensor decomposition can effectively
reduce the number of parameters to gain dimensionality-reduction and thus plays
a key role in tensor regression. However, in CP decomposition, there is
uncertainty which rank to use. In this article, we develop a model averaging
method to handle this uncertainty by weighting the estimators from candidate
tensor regression models with different ranks. When all candidate models are
misspecified, we prove that the model averaging estimator is asymptotically
optimal. When correct models are included in the candidate models, we prove the
consistency of parameters and the convergence of the model averaging weight.
Simulations and empirical studies illustrate that the proposed method has
superiority over the competition methods and has promising applications
Joint Task Offloading and Resource Allocation in Aerial-Terrestrial UAV Networks with Edge and Fog Computing for Post-Disaster Rescue
Unmanned aerial vehicles (UAVs) play an increasingly important role in
assisting fast-response post-disaster rescue due to their fast deployment,
flexible mobility, and low cost. However, UAVs face the challenges of limited
battery capacity and computing resources, which could shorten the expected
flight endurance of UAVs and increase the rescue response delay during
performing mission-critical tasks. To address this challenge, we first present
a three-layer post-disaster rescue computing architecture by leveraging the
aerial-terrestrial edge capabilities of mobile edge computing (MEC) and vehicle
fog computing (VFC), which consists of a vehicle fog layer, a UAV client layer,
and a UAV edge layer. Moreover, we formulate a joint task offloading and
resource allocation optimization problem (JTRAOP) with the aim of maximizing
the time-average system utility. Since the formulated JTRAOP is proved to be
NP-hard, we propose an MEC-VFC-aided task offloading and resource allocation
(MVTORA) approach, which consists of a game theoretic algorithm for task
offloading decision, a convex optimization-based algorithm for MEC resource
allocation, and an evolutionary computation-based hybrid algorithm for VFC
resource allocation. Simulation results validate that the proposed approach can
achieve superior system performance compared to the other benchmark schemes,
especially under heavy system workloads.Comment: 18 pages, 6 figure
An Expanded Gene Catalog of Mouse Gut Metagenomes
High-quality and comprehensive reference gene catalogs are essential for metagenomic research. The rather low diversity of samples used to construct existing catalogs of the mouse gut metagenome limits the numbers of identified genes in existing catalogs. We therefore established an expanded catalog of genes in the mouse gut metagenome (EMGC) containing >5.8 million genes by integrating 88 newly sequenced samples, 86 mouse gut-related bacterial genomes, and 3 existing gene catalogs. EMGC increases the number of nonredundant genes by more than 1 million genes compared to the so-far most extensive catalog. More than 60% of the genes in EMGC were assigned to Bacteria, with 54.20% being assigned to a phylum and 35.33% to a genus, while 30.39% were annotated at the KEGG orthology level. Nine hundred two metagenomic species (MGS) assigned to 122 taxa are identified based on the EMGC. The EMGC-based analysis of samples from groups of mice originating from different animal providers, housing laboratories, and genetic strains substantiated that diet is a major contributor to differences in composition and functional potential of the gut microbiota irrespective of differences in environment and genetic background. We envisage that EMGC will serve as a valuable reference data set for future metagenomic studies in mice.publishedVersio
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