Shear vibration of a crystal plate carrying an array of microbeams

We study shear vibration of a rotated Y-cut quartz crystal plate carrying an array of microbeams with their bottoms fixed to the top surface of the plate. The beams undergo flexural vibrations when the plate is in shear motion. The plate is modeled by the theory of anisotropic elasticity. The beams are modeled by the Euler–Bernoulli theory for beam bending. A frequency equation that determines the resonant frequencies of the structure is derived. An analytical solution on beam-induced frequency shift is obtained using a perturbation procedure. It is shown that the frequency shift may be used to measure geometric/physical properties of the beam array. A vibrating crystal plate carrying a beam array may also be considered for application as an ultrasonic brush.     

Band-edge states in ultrasmall silicon quantum boxes: Calculations of electronic states and oscillator strengths

Band-edge states and oscillator strengths in four configurations of ultrasmall Si quantum boxes (QBs) with (100) planes saturated by H have been calculated using the extended Hückel-type non-orthogonal tight-binding method. It is found that, while the valence-band edge states are always bulk like, both bulk-like and surface-like states occur at the conduction-band (CB) edge, depending on the atom configuration of the QB studied. An analysis shows that the surface-like CB edge states are caused by an interhydride interaction between trihydride units on the hydrogenated QB surface and there is significant correlation of oscillator strength with the CB edge states.     

Whispering gallery mode sensor for phase transformation and solidification studies

Whispering gallery mode (WGM) sensors are created by coupling a dielectric microresonator with the evanescent field of an optical fiber. Since the sensor is created by two separate entities, most of the existing studies are limited to using them in fluid environments, such as air or water, for the ease of manipulation and placement in the optimum configuration. This work is focused on studying the possibility of using WGM sensors inside a solid material. The sensor is immersed in water, which is cooled to solid state and the sensor survival is monitored. In subsequent studies, three remelting cycles are carried out and temperature measurements are obtained through the sensor. The sensor output is calibrated with the temperature data obtained from a thermocouple. The results show that a linear relationship exists between temperature and WGM shift, which enables application of these sensors in temperature measurement. Considering that the sensitivity of WGM sensors is very high (10^?6 N force and 10^?5 K temperature), they can be used for high resolution studies on solidification in cryogenic environments.     

Recognizing upper limb movements with wrist worn inertial sensors using k-means clustering classification

In this paper we present a methodology for recognizing three fundamental movements of the human forearm (extension, flexion and rotation) using pattern recognition applied to the data from a single wrist-worn, inertial sensor. We propose that this technique could be used as a clinical tool to assess rehabilitation progress in neurodegenerative pathologies such as stroke or cerebral palsy by tracking the number of times a patient performs specific arm movements (e.g. prescribed exercises) with their paretic arm throughout the day. We demonstrate this with healthy subjects and stroke patients in a simple proof of concept study in which these arm movements are detected during an archetypal activity of daily-living (ADL) – ‘making-a-cup-of-tea’. Data is collected from a tri-axial accelerometer and a tri-axial gyroscope located proximal to the wrist. In a training phase, movements are initially performed in a controlled environment which are represented by a ranked set of 30 time-domain features. Using a sequential forward selection technique, for each set of feature combinations three clusters are formed using k-means clustering followed by 10 runs of 10-fold cross validation on the training data to determine the best feature combinations. For the testing phase, movements performed during the ADL are associated with each cluster label using a minimum distance classifier in a multi-dimensional feature space, comprised of the best ranked features, using Euclidean or Mahalanobis distance as the metric. Experiments were performed with four healthy subjects and four stroke survivors and our results show that the proposed methodology can detect the three movements performed during the ADL with an overall average accuracy of 88% using the accelerometer data and 83% using the gyroscope data across all healthy subjects and arm movement types. The average accuracy across all stroke survivors was 70% using accelerometer data and 66% using gyroscope data. We also use a Linear Discriminant Analysis (LDA) classifier and a Support Vector Machine (SVM) classifier in association with the same set of features to detect the three arm movements and compare the results to demonstrate the effectiveness of our proposed methodology.     

Simultaneous determination of thin-film inertia and shear stiffness using thickness-twist and face-shear modes of an AT-cut quartz resonator

We propose the use of thickness-twist (TT) and face-shear (FS) vibration modes of an AT-cut quartz crystal plate resonator for simultaneous determination of the inertia and stiffness of a thin film deposited on a crystal surface. A theoretical analysis using Mindlin's first-order theory for crystal plates is performed to demonstrate the idea. Expressions for the stiffness ratio and mass ratio between the thin film and the resonator are presented in terms of frequency shifts of FS and TT modes, which are experimentally measurable. A numerical example is given.     

Characterization of lower-limbs inter-segment coordination during the take-off extension in ski jumping

Take-off, the most important phase in ski jumping, has been primarily studied in terms of spatio-temporal parameters; little is known about its motor control aspects. This study aims to assess the inter-segment coordination of the shank-thigh and thigh-sacrum pairs using the continuous relative phase (CRP). In total 87 jumps were recorded from 33 athletes with an inertial sensor-based system. The CRP curves indicated that the thighs lead the shanks during the first part of take-off extension and that the shanks rotated faster at the take-off extension end. The thighs and sacrum first rotated synchronously, with the sacrum then taking lead, with finally the thighs rotating faster. Five characteristic features were extracted from the CRP and their relationship with jump length was tested. Three features of the shank-thigh pair and one of the thigh-sacrum pair reported a significant association with jump length. It was observed that athletes who achieved longer jumps had their thighs leading their shanks during a longer time, with these athletes also having a more symmetric movement between thighs and sacrum. This study shows that inter-segment coordination during the take-off extension is related to performance and further studies are necessary to contrast its importance with other ski jumping aspects.     

Physiological responses to urban design during bicycling: A naturalistic investigation

The current research set out to measure the moderating effect that urban design may have on bicyclist physiology while in transition. Focusing on the hilly City of Wuppertal, Germany, we harnessed bicyclists with mobile sensors to measure their responses to urban design metrics obtained from space syntax, while also adjusting for known traffic, terrain, and contextual factors. The empirical strategy consisted of exploratory data analysis (EDA), ordinary least squares (OLS), and a local regression model to account for spatial autocorrelation. The latter model was robust (R² = 68%), and showed that two statistically significant (p < 0.05) urban design factors influenced bicyclist physiology. Controllability, a measure of how spatially dominated a space is, increased bicyclist responses (i.e., decreased comfortability); while integration, which is related to accessibility and connectivity, had the opposite effect. Other noteworthy covariates included one-way streets and density of parked automobiles: these exerted a negative influence on bicyclist physiology. The results of this research ultimately showed that nuanced urban designs have a moderate influence on bicycling comfort. These outcomes could be utilized by practitioners focused on implementing appropriate interventions to increase bicyclist comfort levels and this mode share.     

Sensoring the Future: Complex Geographies of Connectivity and Communication

Visions of an interconnected future are on the rise that foresee technologies moving toward ubiquitous “everywhere” computing and the rise of the “Internet of Things.” This article examines emerging trends in informational connectivity that indicates shifts toward upcoming scenarios of re-imagined geographies and spatial landscapes that are sensored and networked. I examine how the relationships, processes, and flows between people, physical objects, and the environment will make implicit information explicit and engagement between the physical and the digital more commonplace. These are the scenarios presented by emerging applications of location-specific, informationally augmented objects: a real-time sensored future.     

Multiple liquid impact of single-crystal lithium fluoride

Lithium fluoride in its single-crystal form is an interesting material for investigating the development of fracture by multiple liquid impact owing to its well characterized crystal structure. The development of fracture during liquid impact is attributed to the extension of short circumferential cracks produced around the loaded area by the passing Rayleigh stress wave after the impact event. The damage threshold of single-crystal lithium fluoride is developed using the Cavendish Laboratory's multiple impact jet apparatus as a result of identifying the characteristic fracture annulus associated with liquid impact during a controlled experimental procedure. The observation of damage produced in solids by liquid impact has practical significance in the problems with supersonic aircraft flying through rain and in the erosion of turbine blades moving at high speeds through wet steam.     

Perspective on “in the wild” movement analysis using machine learning

Recent advances in wearable sensing and machine learning have created ample opportunities for “in the wild” movement analysis in sports, since the combination of both enables real-time feedback to be provided to athletes and coaches, as well as long-term monitoring of movements. The potential for real-time feedback is useful for performance enhancement or technique analysis, and can be achieved by training efficient models and implementing them on dedicated hardware. Long-term monitoring of movement can be used for injury prevention, among others. Such applications are often enabled by training a machine learned model from large datasets that have been collected using wearable sensors. Therefore, in this perspective paper, we provide an overview of approaches for studies that aim to analyze sports movement “in the wild” using wearable sensors and machine learning. First, we discuss how a measurement protocol can be set up by answering six questions. Then, we discuss the benefits and pitfalls and provide recommendations for effective training of machine learning models from movement data, focusing on data pre-processing, feature calculation, and model selection and tuning. Finally, we highlight two application domains where “in the wild” data recording was combined with machine learning for injury prevention and technique analysis, respectively.