184 research outputs found
Dispersive wave runup on non-uniform shores
Historically the finite volume methods have been developed for the numerical
integration of conservation laws. In this study we present some recent results
on the application of such schemes to dispersive PDEs. Namely, we solve
numerically a representative of Boussinesq type equations in view of important
applications to the coastal hydrodynamics. Numerical results of the runup of a
moderate wave onto a non-uniform beach are presented along with great lines of
the employed numerical method (see D. Dutykh et al. (2011) for more details).Comment: 8 pages, 6 figures, 18 references. This preprint is submitted to
FVCA6 conference proceedings. Other author papers can be downloaded at
http://www.lama.univ-savoie.fr/~dutykh
Adaptive Evolutionary Clustering
In many practical applications of clustering, the objects to be clustered
evolve over time, and a clustering result is desired at each time step. In such
applications, evolutionary clustering typically outperforms traditional static
clustering by producing clustering results that reflect long-term trends while
being robust to short-term variations. Several evolutionary clustering
algorithms have recently been proposed, often by adding a temporal smoothness
penalty to the cost function of a static clustering method. In this paper, we
introduce a different approach to evolutionary clustering by accurately
tracking the time-varying proximities between objects followed by static
clustering. We present an evolutionary clustering framework that adaptively
estimates the optimal smoothing parameter using shrinkage estimation, a
statistical approach that improves a naive estimate using additional
information. The proposed framework can be used to extend a variety of static
clustering algorithms, including hierarchical, k-means, and spectral
clustering, into evolutionary clustering algorithms. Experiments on synthetic
and real data sets indicate that the proposed framework outperforms static
clustering and existing evolutionary clustering algorithms in many scenarios.Comment: To appear in Data Mining and Knowledge Discovery, MATLAB toolbox
available at http://tbayes.eecs.umich.edu/xukevin/affec
What has finite element analysis taught us about diabetic foot disease and its management?:a systematic review
Over the past two decades finite element (FE) analysis has become a popular tool for researchers seeking to simulate the biomechanics of the healthy and diabetic foot. The primary aims of these simulations have been to improve our understanding of the foot's complicated mechanical loading in health and disease and to inform interventions designed to prevent plantar ulceration, a major complication of diabetes. This article provides a systematic review and summary of the findings from FE analysis-based computational simulations of the diabetic foot.A systematic literature search was carried out and 31 relevant articles were identified covering three primary themes: methodological aspects relevant to modelling the diabetic foot; investigations of the pathomechanics of the diabetic foot; and simulation-based design of interventions to reduce ulceration risk.Methodological studies illustrated appropriate use of FE analysis for simulation of foot mechanics, incorporating nonlinear tissue mechanics, contact and rigid body movements. FE studies of pathomechanics have provided estimates of internal soft tissue stresses, and suggest that such stresses may often be considerably larger than those measured at the plantar surface and are proportionally greater in the diabetic foot compared to controls. FE analysis allowed evaluation of insole performance and development of new insole designs, footwear and corrective surgery to effectively provide intervention strategies. The technique also presents the opportunity to simulate the effect of changes associated with the diabetic foot on non-mechanical factors such as blood supply to local tissues.While significant advancement in diabetic foot research has been made possible by the use of FE analysis, translational utility of this powerful tool for routine clinical care at the patient level requires adoption of cost-effective (both in terms of labour and computation) and reliable approaches with clear clinical validity for decision making
The T2K ND280 Off-Axis Pi-Zero Detector
The Pi-Zero detector (P{\O}D) is one of the subdetectors that makes up the
off-axis near detector for the Tokai-to-Kamioka (T2K) long baseline neutrino
experiment. The primary goal for the P{\O}D is to measure the relevant cross
sections for neutrino interactions that generate pi-zero's, especially the
cross section for neutral current pi-zero interactions, which are one of the
dominant sources of background to the electron neutrino appearance signal in
T2K. The P{\O}D is composed of layers of plastic scintillator alternating with
water bags and brass sheets or lead sheets and is one of the first detectors to
use Multi-Pixel Photon Counters (MPPCs) on a large scale.Comment: 17 pages, submitted to NIM
Reports of the AAAI 2019 spring symposium series
Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic impact of machine learning is estimated in the trillions of dollars. But as autonomous machines become ubiquitous, recent problems have surfaced. Early on, and again in 2018, Judea Pearl warned AI scientists they must "build machines that make sense of what goes on in their environment," a warning still unheeded that may impede future development. For example, self-driving vehicles often rely on sparse data; self-driving cars have already been involved in fatalities, including a pedestrian; and yet machine learning is unable to explain the contexts within which it operates
Measurement of the Generalized Polarizabilities of the Proton in Virtual Compton Scattering
We propose to conduct a measurement of the Virtual Compton Scattering
reaction in Hall C that will allow the precise extraction of the two scalar
Generalized Polarizabilities (GPs) of the proton in the region of
to . The Generalized Polarizabilities
are fundamental properties of the proton, that characterize the system's
response to an external electromagnetic (EM) field. They describe how easily
the charge and magnetization distributions inside the system are distorted by
the EM field, mapping out the resulting deformation of the densities in the
proton. As such, they reveal unique information regarding the underlying system
dynamics and provide a key for decoding the proton structure in terms of the
theory of the strong interaction that binds its elementary quark and gluon
constituents together. Recent measurements of the proton GPs have challenged
the theoretical predictions, particularly in regard to the electric
polarizability. The magnetic GP, on the other hand, can provide valuable
insight to the competing paramagnetic and diamagnetic contributions in the
proton, but it is poorly known within the region where the interplay of these
processes is very dynamic and rapidly changing.The unique capabilities of Hall
C, namely the high resolution of the spectrometers combined with the ability to
place the spectrometers in small angles, will allow to pin down the dynamic
signature of the GPs through high precision measurements combined with a fine
mapping as a function of . The experimental setup utilizes standard Hall C
equipment, as was previously employed in the VCS-I (E12-15-001) experiment,
namely the HMS and SHMS spectrometers and a 10 cm liquid hydrogen target. A
total of 59 days of unpolarized 75 electron beam with energy of 1100
MeV (6 days) and 2200 MeV (53 days) is requested for this experiment
Ovine pedomics : the first study of the ovine foot 16S rRNA-based microbiome
We report the first study of the bacterial microbiome of ovine interdigital skin based on 16S rRNA by pyrosequencing and conventional cloning with Sanger-sequencing. Three flocks were selected, one a flock with no signs of footrot or interdigital dermatitis, a second flock with interdigital dermatitis alone and a third flock with both interdigital dermatitis and footrot. The sheep were classified as having either healthy interdigital skin (H), interdigital dermatitis (ID) or virulent footrot (VFR). The ovine interdigital skin bacterial community varied significantly by flock and clinical condition. The diversity and richness of operational taxonomic units was greater in tissue from sheep with ID than H or VFR affected sheep. Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria were the most abundant phyla comprising 25 genera. Peptostreptococcus, Corynebacterium and Staphylococcus were associated with H, ID and VFR respectively. Sequences of Dichelobacter nodosus, the causal agent of ovine footrot, were not amplified due to mismatches in the 16S rRNA universal forward primer (27F). A specific real time PCR assay was used to demonstrate the presence of D. nodosus which was detected in all samples including the flock with no signs of ID or VFR. Sheep with ID had significantly higher numbers of D. nodosus (104-109 cells/g tissue) than those with H or VFR feet
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