Minimizing Stimulus Current in a Wearable Pudendal Nerve Stimulator Using Computational Models.

After spinal cord injury, functions of the lower urinary tract may be disrupted. A wearable device with surface electrodes which can effectively control the bladder functions would be highly beneficial to the patients. A trans-rectal pudendal nerve stimulator may provide such a solution. However, the major limiting factor in such a stimulator is the high level of current it requires to recruit the nerve fibers. Also, the variability of the trajectory of the nerve in different individuals should be considered. Using computational models and an approximate trajectory of the nerve derived from an MRI study, it is demonstrated in this paper that it may be possible to considerably reduce the required current levels for trans-rectal stimulation of the pudendal nerve compared to the values previously reported in the literature. This was corroborated by considering an ensemble of possible and probable variations of the trajectory. The outcome of this study suggests that trans-rectal stimulation of the pudendal nerve is a plausible long term solution for treating lower urinary tract dysfunctions after spinal cord injury

Dictionary selection for Compressed Sensing of EEG signals using sparse binary matrix and spatiotemporal sparse Bayesian learning

Online monitoring of electroencephalogram (EEG) signals is challenging due to the high volume of data and power requirements. Compressed sensing (CS) may be employed to address these issues. Compressed sensing using sparse binary matrix, owing to its low power features, and reconstruction/decompression using spatiotemporal sparse Bayesian learning have been shown to constitute a robust framework for fast, energy efficient and accurate multichannel bio-signal monitoring. EEG signal, however, does not show a strong temporal correlation. Therefore, the use of sparsifying dictionaries has been proposed to exploit the sparsity in a transformed domain instead. Assuming sparsification adds values, a challenge, therefore, in employing this CS framework for the EEG signal is to identify the suitable dictionary. Using real multichannel EEG data from 15 subjects, in this paper, we systematically evaluated the performance of the framework when using various wavelet bases while considering their key attributes of number of vanishing moments and coherence with sensing matrix. We identified Beylkin as the wavelet dictionary leading to the best performance. Using the same dataset, we then compared the performance of Beylkin with discrete cosine basis, often used in the literature, and the case of using no sparsifying dictionary. We further demonstrate that using dictionaries (Beylkin and DCT) may improve performance tangibly only for a high compression ratio (CR) of 80% and with smaller block sizes; as compared to when using no dictionaries

Quantum algorithms and the power of forgetting

The so-called welded tree problem provides an example of a black-box problem that can be solved exponentially faster by a quantum walk than by any classical algorithm. Given the name of a special ENTRANCE vertex, a quantum walk can find another distinguished EXIT vertex using polynomially many queries, though without finding any particular path from ENTRANCE to EXIT. It has been an open problem for twenty years whether there is an efficient quantum algorithm for finding such a path, or if the path-finding problem is hard even for quantum computers. We show that a natural class of efficient quantum algorithms provably cannot find a path from ENTRANCE to EXIT. Specifically, we consider algorithms that, within each branch of their superposition, always store a set of vertex labels that form a connected subgraph including the ENTRANCE, and that only provide these vertex labels as inputs to the oracle. While this does not rule out the possibility of a quantum algorithm that efficiently finds a path, it is unclear how an algorithm could benefit by deviating from this behavior. Our no-go result suggests that, for some problems, quantum algorithms must necessarily forget the path they take to reach a solution in order to outperform classical computation.Comment: 49 pages, 9 figure

Quantum Algorithms and the Power of Forgetting

The so-called welded tree problem provides an example of a black-box problem that can be solved exponentially faster by a quantum walk than by any classical algorithm [Andrew M. Childs et al., 2003]. Given the name of a special entrance vertex, a quantum walk can find another distinguished exit vertex using polynomially many queries, though without finding any particular path from entrance to exit. It has been an open problem for twenty years whether there is an efficient quantum algorithm for finding such a path, or if the path-finding problem is hard even for quantum computers. We show that a natural class of efficient quantum algorithms provably cannot find a path from entrance to exit. Specifically, we consider algorithms that, within each branch of their superposition, always store a set of vertex labels that form a connected subgraph including the entrance, and that only provide these vertex labels as inputs to the oracle. While this does not rule out the possibility of a quantum algorithm that efficiently finds a path, it is unclear how an algorithm could benefit by deviating from this behavior. Our no-go result suggests that, for some problems, quantum algorithms must necessarily forget the path they take to reach a solution in order to outperform classical computation

Development of complexity induced frameworks for charged cylindrical polytropes

The main theme of this work is the development of complexity induced generalized frameworks for static cylindrical polytropes. We consider two different definitions of generalized polytopes with charged anisotropic inner fluid distribution. A new methodology based on complexity factor for the generation of consistent sets of differential equations will be presented. We conclude our work by carrying out graphical analysis of developed frameworks.Comment: 21 pages, 6 figure

Assessing the efficacy and safety of pitavastatin compared to atorvastatin in dyslipidemic patients: a double blind randomized controlled trial

Background: Statins are the first choice in the treatment of dyslipidemia, commonly atorvastatin. Pitavastatin is a newer statin with more potency, less drug interactions and many added advantages considering the longevity of treatment required for dyslipidemia. The objective of this study was to evaluate the efficacy and safety of pitavastatin versus atorvastatin in dyslipidemic patients associated with hypertension, diabetes and/or coronary artery disease.Methods: A prospective, comparative, randomized, controlled, double blind, clinical trial was designed. Total 100 eligible subjects were randomised into 1:1 ratio to receive pitavastatin 4 mg once daily and atorvastatin 20 mg once daily for period of 8 weeks. Evaluation was scheduled at 4 week and 8 week. The efficacy assessment included percentage change from baseline in various lipid parameters like low density lipoprotein cholesterol (LDLC), total cholesterol (TC), high density lipoprotein cholesterol (HDLC), triglycerides (TG), and LDLC/HDLC ratio.Results: Analysis of data showed a significant improvement in all lipid parameters within both therapeutic groups. The difference in LDLC, TC and TG levels was not statistically significant between the two treatment groups after 8 weeks of therapy. However, significant improvement was seen in HDLC and LDLC/HDLC ratio with pitavastatin as compared to atorvastatin at the end of the study. Both were well tolerated.Conclusions: With better HDLC levels, in addition to comparable efficacy and good tolerability of pitavastatin, as compared to atorvastatin, could be considered as good alternative for treatment of dyslipidemia

Emotional Intelligence on Organizational Performance with the Moderating Effect of Organizational Culture in the Banking Sector in Sri Lanka: A Systematic Review

This is a conceptual paper based on a systematic literature review. For many years, the topic of emotional intelligence and organizational performance has caught the interest of researchers and practitioners. Much of the interest in these two areas is motivated by explicit and implicit assumptions that both the emotional intelligence of individuals and organizational culture are associated with organizational performance. While the associations between emotional intelligence and organizational performance and organizational culture have been studied independently, few studies have examined the relationship between the three variables. This paper aims to advance understanding of the effects of emotional intelligence on organizational performance with the moderating role of organizational culture by reviewing the literature of previous studies. This study reviewed 52 journal articles from the Scopus database and other sources. The study culminates with the development of a conceptual framework that can be used in future empirical studies. Key Words: Emotional Intelligence, Organizational Performance, Organizational Culture, Banking Secto

Coverage and predictors of vaccination among children of 1-4 years of age in a rural sub-district of Sindh

OBJECTIVE: To estimate the proportion of children 1-4 years of age vaccinated in the first year of their life and determine socio-demographic factors associated with vaccination in the rural sub-district Khairpur, Sindh, Pakistan.STUDY DESIGN: Cross-sectional study.PLACE AND DURATION OF STUDY: The study was conducted in 9 Union Councils of sub-district Gambat, district Khairpur, Sindh, from August to October 2008.METHODOLOGY: A questionnaire based representative multi-stage cluster survey was conducted. A total of 549 children aged 1-4 years were assessed for coverage and predictors of vaccination. Univariate and multivariate analysis was done using logistic regression to determine the unadjusted and adjusted relationship between socio-demographic predictor and outcome (vaccination status).RESULTS: The coverage for complete vaccination was 71.9% (95%CI=68.1%-75.7%). Educational level of mother (p=0.042), father (p=0.001) and child birth at hospital (p=0.006) were significantly associated with the vaccination status. Mother\u27s educational level of intermediate and above was the strongest predictor (OR=12.19, 95%CI=1.57-94.3) for vaccination.CONCLUSION: Education of parents, particularly mother\u27s education was important determinant of vaccination status of the children. In addition, distance from taluka health facility and misconception of parents were among the main reasons of not getting the children vaccinated. There is a need to educate the parents especially mothers about the importance of vaccination and organize EPI services at Basic Health Unit level to improve the vaccination coverage in rural areas of Pakistan