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Multiple Time Scales in Diffraction Measurements of Diffusive Surface Relaxation

We grew SrTiO3 on SrTiO3 (001) by pulsed laser deposition, using x-ray scattering to monitor the growth in real time. The time-resolved small angle scattering exhibits a well-defined length scale associated with the spacing between unit cell high surface features. This length scale imposes a discrete spectrum of Fourier components and rate constants upon the diffusion equation solution, evident in multiple exponential relaxation of the "anti-Bragg" diffracted intensity. An Arrhenius analysis of measured rate constants confirms that they originate from a single activation energy.Comment: 4 pages, 3 figure

EFFECTS OF AGE, GENDER AND ACTIVITY LEVEL ON COUNTER-MOVEMENT JUMP PERFORMANCE AND VARIABILITY IN CHILDREN AND ADOLESCENTS

The aim of this study was to investigate counter-movement jump performance and variability in a large population of children and adolescents with respect to age, gender, and activity level. 1835 subjects performed three counter-movement jumps with arms akimbo on a force platform. The subjects were divided into 6 age groups and three activity level groups. Jump height and maximum rate of force development were calculated for all jumps. The best trial out of three was considered for further calculations. Variability of both parameters was indicated by the coefficient of variation over three jumps. Both parameters increased with increasing age while their variability decreased. Boys jumped higher than girls. Regarding maximum rate of force development female subjects showed higher values. The active subjects jumped higher and with less variability than the sedentary group. Jump height and maximum rate of force development are good parameters to describe the development of jumping performance regarding age, gender and activity aspects. Due to the high variability of maximum force rate development, however, this parameter has to be interpreted with caution in subject-specific assessments

Measurements of Surface Diffusivity and Coarsening During Pulsed Laser Deposition

Pulsed Laser Deposition (PLD) of homoepitaxial SrTiO3 was studied with in-situ x-ray specular reflectivity and surface diffuse x-ray scattering. Unlike prior reflectivity-based studies, these measurements access both the time- and the length-scales of the evolution of the surface morphology during growth. In particular, we show that this technique allows direct measurements of the diffusivity for both inter- and intra-layer transport. Our results explicitly limit the possible role of island break-up, demonstrate the key roles played by nucleation and coarsening in PLD, and place an upper bound on the Ehrlich-Schwoebel (ES) barrier for downhill diffusion

Revestimiento de canales

La maquinaria moderna alemana empleada para el revestimiento de canales de gran sección, presenta grandes ventajas de economía, rendimiento, regularidad e impermeabilidad de la construcción. Para la aplicación de esta maquinaria —inicialmente se ha procedido a la excavación del canal mediante el empleo de maquinaria ordinaria de desmonte y la maquinaria especial— comienza su trabajo con el enrase de las cotas previstas

Machine Learning for Enhancing Dementia Screening in Ageing Deaf Signers of British Sign Language

Real-time hand movement trajectory tracking based on machine learning approaches may assist the early identification of dementia in ageing deaf individuals who are users of British Sign Language (BSL), since there are few clinicians with appropriate communication skills, and a shortage of sign language interpreters. In this paper, we introduce an automatic dementia screening system for ageing Deaf signers of BSL, using a Convolutional Neural Network (CNN) to analyse the sign space envelope and facial expression of BSL signers recorded in normal 2D videos from the BSL corpus. Our approach involves the introduction of a sub-network (the multi-modal feature extractor) which includes an accurate real-time hand trajectory tracking model and a real-time landmark facial motion analysis model. The experiments show the effectiveness of our deep learning based approach in terms of sign space tracking, facial motion tracking and early stage dementia performance assessment tasks