A parallel implementation of sequential minimal optimization on FPGA

This paper proposes a parallel FPGA implementation of the training phase of a Support Vector Machine (SVM). The training phase of the SVM is implemented using Sequential Minimal Optimization (SMO), which enables the resolution of a complex convex optimization problem using simple steps. The SMO implementation is also highly parallel and uses some acceleration techniques, such as the error cache. Moreover, the Hardware Friendly Kernel (HFK) is used in order to reduce the kernel’s area, enabling an increase in the number of kernels per area. After the parallel implementation in hardware, the SVM is validated by bit-accurate simulation. Finally, analysis associated with the temporal performance of the proposed structure, as well as analysis associated with FPGAs area usage is performed

Muscle fiber conduction velocity is more affected after eccentric than concentric exercise

It has been shown that mean muscle fiber conduction velocity (CV) can be acutely impaired after eccentric exercise. However, it is not known whether this applies to other exercise modes. Therefore, the purpose of this experiment was to compare the effects of eccentric and concentric exercises on CV, and amplitude and frequency content of surface electromyography (sEMG) signals up to 24 h post-exercise. Multichannel sEMG signals were recorded from biceps brachii muscle of the exercised arm during isometric maximal voluntary contraction (MVC) and electrically evoked contractions induced by motor-point stimulation before, immediately after and 2 h after maximal eccentric (ECC group, N = 12) and concentric (CON group, N = 12) elbow flexor exercises. Isometric MVC decreased in CON by 21.7 ± 12.0% (± SD, p < 0.01) and by 30.0 ± 17.7% (p < 0.001) in ECC immediately post-exercise when compared to baseline. At 2 h post-exercise, ECC showed a reduction in isometric MVC by 24.7 ± 13.7% (p < 0.01) when compared to baseline, while no significant reduction (by 8.0 ± 17.0%, ns) was observed in CON. Similarly, reduction in CV was observed only in ECC both during the isometric MVC (from baseline of 4.16 ± 0.3 to 3.43 ± 0.4 m/s, p < 0.001) and the electrically evoked contractions (from baseline of 4.33 ± 0.4 to 3.82 ± 0.3 m/s, p < 0.001). In conclusion, eccentric exercise can induce a greater and more prolonged reduction in muscle force production capability and CV than concentric exercis

Rescaling quality of life values from discrete choice experiments for use as QALYs: a cautionary tale

Background: Researchers are increasingly investigating the potential for ordinal tasks such as ranking and discrete choice experiments to estimate QALY health state values. However, the assumptions of random utility theory, which underpin the statistical models used to provide these estimates, have received insufficient attention. In particular, the assumptions made about the decisions between living states and the death state are not satisfied, at least for some people. Estimated values are likely to be incorrectly anchored with respect to death (zero) in such circumstances. Methods: Data from the Investigating Choice Experiments for the preferences of older people CAPability instrument (ICECAP) valuation exercise were analysed. The values (previously anchored to the worst possible state) were rescaled using an ordinal model proposed previously to estimate QALY-like values. Bootstrapping was conducted to vary artificially the proportion of people who conformed to the conventional random utility model underpinning the analyses. Results: Only 26% of respondents conformed unequivocally to the assumptions of conventional random utility theory. At least 14% of respondents unequivocally violated the assumptions. Varying the relative proportions of conforming respondents in sensitivity analyses led to large changes in the estimated QALY values, particularly for lower-valued states. As a result these values could be either positive (considered to be better than death) or negative (considered to be worse than death). Conclusion: Use of a statistical model such as conditional (multinomial) regression to anchor quality of life values from ordinal data to death is inappropriate in the presence of respondents who do not conform to the assumptions of conventional random utility theory. This is clearest when estimating values for that group of respondents observed in valuation samples who refuse to consider any living state to be worse than death: in such circumstances the model cannot be estimated. Only a valuation task requiring respondents to make choices in which both length and quality of life vary can produce estimates that properly reflect the preferences of all respondents

Boreal forest floor greenhouse gas emissions across a Pleurozium schreberi-dominated, wildfire-disturbed chronosequence

The boreal forest is a globally critical biome for carbon cycling. Its forests are shaped by wildfire events that affect ecosystem properties and climate feedbacks including greenhouse gas (GHG) emissions. Improved understanding of boreal forest floor processes is needed to predict the impacts of anticipated increases in fire frequency, severity, and extent. In this study, we examined relationships between time since last wildfire (TSF), forest floor soil properties, and GHG emissions (CO2, CH4, N2O) along a Pleurozium schreberi-dominated chronosequence in mid- to late succession located in northern Sweden. Over three growing seasons in 2012–2014, GHG flux measurements were made in situ and samples were collected for laboratory analyses. We predicted that P. schreberi-covered forest floor GHG fluxes would be related to distinct trends in the soil properties and microbial community along the wildfire chronosequence. Although we found no overall effect of TSF on GHG emissions, there was evidence that soil C/N, one of the few properties to show a trend with time, was inversely linked to ecosystem respiration. We also found that local microclimatic conditions and site-dependent properties were better predictors of GHG fluxes than TSF. This shows that site-dependent co-variables (that is, forest floor climate and plant-soil properties) need to be considered as well as TSF to predict GHG emissions as wildfires become more frequent, extensive and severe

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes

Experimental Design

AbstractThis chapter covers various issues related to the experimental design, a statistical technique at the core of a discrete choice experiment. Specifically, it focuses on the dimensionality of a choice experiment and the statistical techniques used to allocate attribute levels to choice tasks. Among others, the pros and cons of orthogonal designs, optimal orthogonal in the differences designs as well as efficient designs are addressed. The last section shows how a simulation exercise can help to test the appropriateness of the experimental design

Improving antibiotic prescribing for adults with community acquired pneumonia: Does a computerised decision support system achieve more than academic detailing alone? – a time series analysis

BACKGROUND: The ideal method to encourage uptake of clinical guidelines in hospitals is not known. Several strategies have been suggested. This study evaluates the impact of academic detailing and a computerised decision support system (CDSS) on clinicians' prescribing behaviour for patients with community acquired pneumonia (CAP). METHODS: The management of all patients presenting to the emergency department over three successive time periods was evaluated; the baseline, academic detailing and CDSS periods. The rate of empiric antibiotic prescribing that was concordant with recommendations was studied over time comparing pre and post periods and using an interrupted time series analysis. RESULTS: The odds ratio for concordant therapy in the academic detailing period, after adjustment for age, illness severity and suspicion of aspiration, compared with the baseline period was OR = 2.79 [1.88, 4.14], p < 0.01, and for the computerised decision support period compared to the academic detailing period was OR = 1.99 [1.07, 3.69], p = 0.02. During the first months of the computerised decision support period an improvement in the appropriateness of antibiotic prescribing was demonstrated, which was greater than that expected to have occurred with time and academic detailing alone, based on predictions from a binary logistic model. CONCLUSION: Deployment of a computerised decision support system was associated with an early improvement in antibiotic prescribing practices which was greater than the changes seen with academic detailing. The sustainability of this intervention requires further evaluation

Development and evaluation of a web-based breast cancer cultural competency course for primary healthcare providers

<p>Abstract</p> <p>Background</p> <p>To develop and evaluate a continuing medical education (CME) course aimed at improving healthcare provider knowledge about breast cancer health disparities and the importance of cross-cultural communication in provider-patient interactions about breast cancer screening.</p> <p>Methods</p> <p>An interactive web-based CME course was developed and contained information about breast cancer disparities, the role of culture in healthcare decision making, and demonstrated a model of cross-cultural communication. A single group pre-/post-test design was used to assess knowledge changes. Data on user satisfaction was also collected.</p> <p>Results</p> <p>In all, 132 participants registered for the CME with 103 completing both assessments. Differences between pre-/post-test show a significant increase in knowledge (70% vs. 94%; p < .001). Ninety-five percent of participants agreed that the web based training was an appropriate tool to train healthcare providers about cultural competency and health disparities.</p> <p>Conclusion</p> <p>There was an overall high level of satisfaction among all users. Users felt that learning objectives were met and the web-based format was appropriate and easy to use and suggests that web-based CME formats are an appropriate tool to teach cultural competency skills. However, more information is needed to understand how the CME impacted practice behaviors.</p