Intelligent single switch wheelchair navigation

We have developed an intelligent single switch scanning interface and wheelchair navigation assistance system, called intelligent single switch wheelchair navigation (ISSWN), to improve driving safety, comfort and efficiency for individuals who rely on single switch scanning as a control method. ISSWN combines a standard powered wheelchair with a laser rangefinder, a single switch scanning interface and a computer. It provides the user with context sensitive and task specific scanning options that reduce driving effort based on an interpretation of sensor data together with user input. Trials performed by 9 able-bodied participants showed that the system significantly improved driving safety and efficiency in a navigation task by significantly reducing the number of switch presses to 43.5% of traditional single switch wheelchair navigation (p < 0.001). All participants made a significant improvement (39.1%; p < 0.001) in completion time after only two trials. Implications for Rehabilitation Intelligent navigation algorithm helps investigators develop smart wheelchair technology that may ultimately provide independent mobility to a segment of the population that currently finds it difficult or impossible to operate a conventional wheelchair. intelligent single switch wheelchair navigation improves the driving safety, comfort, and efficiency for individuals who rely on single switch scanning as a wheelchair control method by significantly reducing the number of switch presses and completion time. © 2012 Informa UK, Ltd

POCS-based reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE): A general algorithm for reducing motion-related artifacts.

PURPOSE: A projection onto convex sets reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE) is developed to reduce motion-related artifacts, including respiration artifacts in abdominal imaging and aliasing artifacts in interleaved diffusion-weighted imaging. THEORY: Images with reduced artifacts are reconstructed with an iterative projection onto convex sets (POCS) procedure that uses the coil sensitivity profile as a constraint. This method can be applied to data obtained with different pulse sequences and k-space trajectories. In addition, various constraints can be incorporated to stabilize the reconstruction of ill-conditioned matrices. METHODS: The POCSMUSE technique was applied to abdominal fast spin-echo imaging data, and its effectiveness in respiratory-triggered scans was evaluated. The POCSMUSE method was also applied to reduce aliasing artifacts due to shot-to-shot phase variations in interleaved diffusion-weighted imaging data corresponding to different k-space trajectories and matrix condition numbers. RESULTS: Experimental results show that the POCSMUSE technique can effectively reduce motion-related artifacts in data obtained with different pulse sequences, k-space trajectories and contrasts. CONCLUSION: POCSMUSE is a general post-processing algorithm for reduction of motion-related artifacts. It is compatible with different pulse sequences, and can also be used to further reduce residual artifacts in data produced by existing motion artifact reduction methods

Musculoskeletal strength, balance performance and self-efficacy in elderly Ving Tsun Chinese martial art practitioners: Implications for fall prevention

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The effects of a 6-month Tai Chi Qigong training program on temporomandibular, cervical and shoulder joint mobility and sleep problems in nasopharyngeal cancer survivors

Introduction. Nasopharyngeal cancer (NPC) survivors often sustain head–neck–shoulder impairments from conventional treatments, which could disturb sleep. This novel study aimed to examine the efficacy of Tai Chi (TC) Qigong in optimizing temporomandibular joint (TMJ), cervical, and shoulder joint mobility and reducing sleep problems in NPC survivors. Methods. Fifty-two NPC survivors participated in the study. The experimental group (n = 25) received 6 months of TC Qigong training (1.5 h/session; 4 sessions/wk including self-practice) while the control group (n = 27) received no training. Cervical side flexion and rotation, shoulder flexion and horizontal flexion range of motion (ROM), mouth opening capacity (interincisor distance), and sleep problems (Medical Outcomes Study Sleep Scale) were assessed at baseline, mid-intervention (3 months), immediately after TC Qigong training, and at 6-month follow-up. Results. Intention-to-treat analysis revealed improvement in cervical side flexion ROM only (P .008) after the TC Qigong training. Deterioration was observed in shoulder flexion ROM and mouth opening capacity in the no-training controls over time (P < .008). Sleep problems also decreased in the TC Qigong group (P < .008), and this effect was most profound during the follow-up period. In addition, improvement in cervical side flexion ROM was associated with a reduction in sleep problems in the experimental group after TC Qigong training (P < .05). Conclusions. The 6-month TC Qigong intervention improved neck mobility, maintained TMJ and shoulder joint mobility, and reduced sleep problems for NPC survivors. TC Qigong could be an effective nonpharmacological intervention for managing progressive trismus, chronic neck and shoulder hypomobility, and reducing sleep problems among NPC survivors.postprin

Discovering monotonic stemness marker genes from time-series stem cell microarray data

© 2015 Wang et al.; licensee BioMed Central Ltd. Background: Identification of genes with ascending or descending monotonic expression patterns over time or stages of stem cells is an important issue in time-series microarray data analysis. We propose a method named Monotonic Feature Selector (MFSelector) based on a concept of total discriminating error (DEtotal) to identify monotonic genes. MFSelector considers various time stages in stage order (i.e., Stage One vs. other stages, Stages One and Two vs. remaining stages and so on) and computes DEtotal of each gene. MFSelector can successfully identify genes with monotonic characteristics.Results: We have demonstrated the effectiveness of MFSelector on two synthetic data sets and two stem cell differentiation data sets: embryonic stem cell neurogenesis (ESCN) and embryonic stem cell vasculogenesis (ESCV) data sets. We have also performed extensive quantitative comparisons of the three monotonic gene selection approaches. Some of the monotonic marker genes such as OCT4, NANOG, BLBP, discovered from the ESCN dataset exhibit consistent behavior with that reported in other studies. The role of monotonic genes found by MFSelector in either stemness or differentiation is validated using information obtained from Gene Ontology analysis and other literature. We justify and demonstrate that descending genes are involved in the proliferation or self-renewal activity of stem cells, while ascending genes are involved in differentiation of stem cells into variant cell lineages.Conclusions: We have developed a novel system, easy to use even with no pre-existing knowledge, to identify gene sets with monotonic expression patterns in multi-stage as well as in time-series genomics matrices. The case studies on ESCN and ESCV have helped to get a better understanding of stemness and differentiation. The novel monotonic marker genes discovered from a data set are found to exhibit consistent behavior in another independent data set, demonstrating the utility of the proposed method. The MFSelector R function and data sets can be downloaded from: http://microarray.ym.edu.tw/tools/MFSelector/

Risk management strategy based on price swap for generation companies in electricity market environment

Author name used in this publication: 李晓军Author name used in this publication: 颜汉荣Author name used in this publication: 余志伟Author name used in this publication: 钟志勇, C Y ChungAuthor name used in this publication: K P WongTitle in Traditional Chinese: 電力市場環境下基於電價互換的發電公司風險管理策略Journal title in Traditional Chinese: 電力科學與技術學報2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

k is the Magic Number -- Inferring the Number of Clusters Through Nonparametric Concentration Inequalities

Most convex and nonconvex clustering algorithms come with one crucial parameter: the $k$ in $k$-means. To this day, there is not one generally accepted way to accurately determine this parameter. Popular methods are simple yet theoretically unfounded, such as searching for an elbow in the curve of a given cost measure. In contrast, statistically founded methods often make strict assumptions over the data distribution or come with their own optimization scheme for the clustering objective. This limits either the set of applicable datasets or clustering algorithms. In this paper, we strive to determine the number of clusters by answering a simple question: given two clusters, is it likely that they jointly stem from a single distribution? To this end, we propose a bound on the probability that two clusters originate from the distribution of the unified cluster, specified only by the sample mean and variance. Our method is applicable as a simple wrapper to the result of any clustering method minimizing the objective of $k$-means, which includes Gaussian mixtures and Spectral Clustering. We focus in our experimental evaluation on an application for nonconvex clustering and demonstrate the suitability of our theoretical results. Our \textsc{SpecialK} clustering algorithm automatically determines the appropriate value for $k$, without requiring any data transformation or projection, and without assumptions on the data distribution. Additionally, it is capable to decide that the data consists of only a single cluster, which many existing algorithms cannot

Practical Dosimetry of 131I in Patients with Thyroid Carcinoma

Radioiodine treatments of patients with well-differentiated thyroid carcinoma have generally been safe and beneficial. Safety can be ensured while efficacy is increased through practical methods of dosimetry that measure body retention of 131I. Prescriptions for therapeutic 131I can be decreased when the retention level is high and increased when the level is low. Assays of serum free T4 will alert the physician to possible increased radiation to blood and bone marrow, and appreciable concentrations of free T4 are indications to reduce the therapeutic 131I. Carcinomas ≥1 cm in diameter that are not visible on diagnostic scintigraphy are unlikely to respond to the commonly prescribed mCi of 131I. Biologic responses to commonly prescribed levels of therapeutic 131I, as seen in toxic changes of normal tissues and in indices of tumor size, will be the final dosimeters. With lower levels of prescribed diagnostic 131I, stunning should not impair dosimetry. Thus, readily obtained measurements make dosimetry a practical method for improving carcinoma therapy with 131I.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63166/1/10849780252824118.pd

Addressing robustness in time-critical, distributed, task allocation algorithms.

The aim of this work is to produce and test a robustness module (ROB-M) that can be generally applied to distributed, multi-agent task allocation algorithms, as robust versions of these are scarce and not well-documented in the literature. ROB-M is developed using the Performance Impact (PI) algorithm, as this has previously shown good results in deterministic trials. Different candidate versions of the module are thus bolted on to the PI algorithm and tested using two different task allocation problems under simulated uncertain conditions, and results are compared with baseline PI. It is shown that the baseline does not handle uncertainty well; the task-allocation success rate tends to decrease linearly as degree of uncertainty increases. However, when PI is run with one of the candidate robustness modules, the failure rate becomes very low for both problems, even under high simulated uncertainty, and so its architecture is adopted for ROB-M and also applied to MIT’s baseline Consensus Based Bundle Algorithm (CBBA) to demonstrate its flexibility. Strong evidence is provided to show that ROB-M can work effectively with CBBA to improve performance under simulated uncertain conditions, as long as the deterministic versions of the problems can be solved with baseline CBBA. Furthermore, the use of ROB-M does not appear to increase mean task completion time in either algorithm, and only 100 Monte Carlo samples are required compared to 10,000 in MIT’s robust version of the CBBA algorithm. PI with ROB-M is also tested directly against MIT’s robust algorithm and demonstrates clear superiority in terms of mean numbers of solved tasks.N/