Intersected EMG heatmaps and deep learning based gesture recognition

Hand gesture recognition in myoelectric based prosthetic devices is a key challenge to offering effective solutions to hand/lower arm amputees. A novel hand gesture recognition methodology that employs the difference of EMG energy heatmaps as the input of a specific designed deep learning neural network is presented. Experimental results using data from real amputees indicate that the proposed design achieves 94.31% as average accuracy with best accuracy rate of 98.96%. A comparison of experimental results between the proposed novel hand gesture recognition methodology and other similar approaches indicates the superior effectiveness of the new design

A well-separated pairs decomposition algorithm for k-d trees implemented on multi-core architectures

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.Variations of k-d trees represent a fundamental data structure used in Computational Geometry with numerous applications in science. For example particle track tting in the software of the LHC experiments, and in simulations of N-body systems in the study of dynamics of interacting galaxies, particle beam physics, and molecular dynamics in biochemistry. The many-body tree methods devised by Barnes and Hutt in the 1980s and the Fast Multipole Method introduced in 1987 by Greengard and Rokhlin use variants of k-d trees to reduce the computation time upper bounds to O(n log n) and even O(n) from O(n2). We present an algorithm that uses the principle of well-separated pairs decomposition to always produce compressed trees in O(n log n) work. We present and evaluate parallel implementations for the algorithm that can take advantage of multi-core architectures.The Science and Technology Facilities Council, UK

Static Friction between Elastic Solids due to Random Asperities

Several workers have established that the Larkin domains for two three dimensional nonmetallic elastic solids in contact with each other at a disordered interface are enormously large. This implies that there should be negligible static friction per unit area in the macroscopic solid limit. The present work argues that the fluctuations in the heights of the random asperities at the interface that occur in the Greenwood-Williamson model can account for static friction.Comment: Contains some improvements in the treatment of the subjec

Extracardiac 18F-florbetapir imaging in patients with systemic amyloidosis: more than hearts and minds

PURPOSE: 18F-Florbetapir has been reported to show cardiac uptake in patients with systemic light-chain amyloidosis (AL). This study systematically assessed uptake of 18F-florbetapir in patients with proven systemic amyloidosis at sites outside the heart. METHODS: Seventeen patients with proven cardiac amyloidosis underwent 18F-florbetapir PET/CT imaging, 15 with AL and 2 with transthyretin amyloidosis (ATTR). Three patients had repeat scans. All patients had protocolized assessment at the UK National Amyloidosis Centre including imaging with 123I-serum amyloid P component (SAP). 18F-Florbetapir images were assessed for areas of increased tracer accumulation and time-uptake curves in terms of standardized uptake values (SUVmean) were produced. RESULTS: All 17 patients showed 18F-florbetapir uptake at one or more extracardiac sites. Uptake was seen in the spleen in 6 patients (35%; 6 of 9, 67%, with splenic involvement on 123I-SAP scintigraphy), in the fat in 11 (65%), in the tongue in 8 (47%), in the parotids in 8 (47%), in the masticatory muscles in 7 (41%), in the lungs in 3 (18%), and in the kidney in 2 (12%) on the late half-body images. The 18F-florbetapir spleen retention index (SRI) was calculated. SRI >0.045 had 100% sensitivity/sensitivity (in relation to 123I-SAP splenic uptake, the current standard) in detecting splenic amyloid on dynamic imaging and a sensitivity of 66.7% and a specificity of 100% on the late half-body images. Intense lung uptake was seen in three patients, one of whom had lung interstitial infiltration suggestive of amyloid deposition on previous high-resolution CT. Repeat imaging showed a stable appearance in all three patients suggesting no early impact of treatment response. CONCLUSION: 18F-Florbetapir PET/CT is a promising tool for the detection of extracardiac sites of amyloid deposition. The combination of uptake in the heart and uptake in the spleen on 18F-florbetapir PET/CT, a hallmark of AL, suggests that this tracer holds promise as a screening tool for AL

Decoupling algorithms from schedules for easy optimization of image processing pipelines

Using existing programming tools, writing high-performance image processing code requires sacrificing readability, portability, and modularity. We argue that this is a consequence of conflating what computations define the algorithm, with decisions about storage and the order of computation. We refer to these latter two concerns as the schedule, including choices of tiling, fusion, recomputation vs. storage, vectorization, and parallelism. We propose a representation for feed-forward imaging pipelines that separates the algorithm from its schedule, enabling high-performance without sacrificing code clarity. This decoupling simplifies the algorithm specification: images and intermediate buffers become functions over an infinite integer domain, with no explicit storage or boundary conditions. Imaging pipelines are compositions of functions. Programmers separately specify scheduling strategies for the various functions composing the algorithm, which allows them to efficiently explore different optimizations without changing the algorithmic code. We demonstrate the power of this representation by expressing a range of recent image processing applications in an embedded domain specific language called Halide, and compiling them for ARM, x86, and GPUs. Our compiler targets SIMD units, multiple cores, and complex memory hierarchies. We demonstrate that it can handle algorithms such as a camera raw pipeline, the bilateral grid, fast local Laplacian filtering, and image segmentation. The algorithms expressed in our language are both shorter and faster than state-of-the-art implementations.National Science Foundation (U.S.) (Grant 0964004)National Science Foundation (U.S.) (Grant 0964218)National Science Foundation (U.S.) (Grant 0832997)United States. Dept. of Energy (Award DE-SC0005288)Cognex CorporationAdobe System

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region\u27s water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah\u27s water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks

Remote Sensing of Ploidy Level in Quaking Aspen (Populus Tremuloides Michx.)

Ploidy level in plants may influence ecological functioning, demography and response to climate change. However, measuring ploidy level typically requires intensive cell or molecular methods. We map ploidy level variation in quaking aspen, a dominant North American tree species that can be diploid or triploid and that grows in spatially extensive clones. We identify the predictors and spatial scale of ploidy level variation using a combination of genetic and ground‐based and airborne remote sensing methods. We show that ground‐based leaf spectra and airborne canopy spectra can both classify aspen by ploidy level with a precision‐recall harmonic mean of 0.75–0.95 and Cohen\u27s kappa of c. 0.6–0.9. Ground‐based bark spectra cannot classify ploidy level better than chance. We also found that diploids are more common on higher elevation and steeper sites in a network of forest plots in Colorado, and that ploidy level distribution varies at subkilometer spatial scales. Synthesis. Our proof‐of‐concept study shows that remote sensing of ploidy level could become feasible in this tree species. Mapping ploidy level across landscapes could provide insights into the genetic basis of species\u27 responses to climate change

Simultaneous free-volume modeling of the self-diffusion coefficient and dynamic viscosity at high pressure

International audienceA free-volume model of the dynamic viscosity and the self-diffusion coefficients was discussed. The temperature-pressure variations of the dynamic viscosity and the self-diffusion coefficients of small molecules were predicted. The compounds, carbon tetrachloride, cyclohexane, benzene, chlorotrifluoromethane, tetramethylsilane and methylcyclohexane were used for the investigation. The relation between microstructure, free volume and different complex thermophysical properties were emphasized by the model