Effect Of Rear Leg Morphology On Energetics Of A Quadrupedal Robot

Many biomimetic legged robots exist, but their leg designs appear to be arbitrarily chosen. Here, we examine the performance difference between a canine-inspired rear leg in its normal configuration versus the same leg in a transverse-mirrored configuration. A quadrupedal robot was built to test this hypothesis; the robot was successfully able to walk in with both rear-leg configurations. Successful telemetry of energy and localization data was also demonstrated. Both experimental and simulation results confirm that the transverse-mirrored configuration is faster and more efficient. In experiment the robot achieved speeds of up to 0.4 m/s versus 0.33 m/s, and specific resistances of 3.9 versus 5.1 in transverse and normal experiments, respectively. It is suggested here that the transverse-mirrored configuration, which engages the knee spring more than the normal configuration, be used in designs which require higher speeds and greater efficiencies.

Effect Of Rear Leg Morphology On Energetics Of A Quadrupedal Robot

Many biomimetic legged robots exist, but their leg designs appear to be arbitrarily chosen. Here, we examine the performance difference between a canine-inspired rear leg in its normal configuration versus the same leg in a transverse-mirrored configuration. A quadrupedal robot was built to test this hypothesis; the robot was successfully able to walk in with both rear-leg configurations. Successful telemetry of energy and localization data was also demonstrated. Both experimental and simulation results confirm that the transverse-mirrored configuration is faster and more efficient. In experiment the robot achieved speeds of up to 0.4 m/s versus 0.33 m/s, and specific resistances of 3.9 versus 5.1 in transverse and normal experiments, respectively. It is suggested here that the transverse-mirrored configuration, which engages the knee spring more than the normal configuration, be used in designs which require higher speeds and greater efficiencies.

Understanding Social Behaviour in a Health-Care Facility from Localization Data: A Case Study

The most frequent form of dementia is Alzheimer’s Disease (AD), a severe progressive neurological pathology in which the main cognitive functions of an individual are compromised. Recent studies have found that loneliness and living in isolation are likely to cause an acceleration in the cognitive decline associated with AD. Therefore, understanding social behaviours of AD patients is crucial to promote sociability, thus delaying cognitive decline, preserving independence, and providing a good quality of life. In this work, we analyze the localization data of AD patients living in assisted care homes to gather insights about the social dynamics among them. We use localization data collected by a system based on iBeacon technology comprising two components: a network of antennas scattered throughout the facility and a Bluetooth bracelet worn by the patients. We redefine the Relational Index to capture wandering and casual encounters, these being common phenomena among AD patients, and use the notions of Relational and Popularity Indexes to model, visualize and understand the social behaviour of AD patients. We leverage the data analyses to build predictive tools and applications to enhance social activities scheduling and sociability monitoring and promotion, with the ultimate aim of providing patients with a better quality of life. Predictions and visualizations act as a support for caregivers in activity planning to maximize treatment effects and, hence, slow down the progression of Alzheimer’s disease. We present the Community Behaviour Prediction Table (CBPT), a tool to visualize the estimated values of sociability among patients and popularity of places within a facility. Finally, we show the potential of the system by analyzing the Coronavirus Disease 2019 (COVID-19) lockdown time-frame between February and June 2020 in a specific facility. Through the use of the indexes, we evaluate the effects of the pandemic on the behaviour of the residents, observing no particular impact on sociability even though social distancing was put in place.

Local conformal autoencoder for standardized data coordinates

We propose a local conformal autoencoder (LOCA) for standardized data coordinates. LOCA is a deep learning-based method for obtaining standardized data coordinates from scientific measurements. Data observations are modeled as samples from an unknown, nonlinear deformation of an underlying Riemannian manifold, which is parametrized by a few normalized, latent variables. We assume a repeated measurement sampling strategy, common in scientific measurements, and present a method for learning an embedding inRdthat is isometric to the latent variables of the manifold. The coordinates recovered by our method are invariant to diffeomorphisms of the manifold, making it possible to match between different instrumental observations of the same phenomenon. Our embedding is obtained using LOCA, which is an algorithm that learns to rectify deformations by using a local z-scoring procedure, while preserving relevant geometric information. We demonstrate the isometric embedding properties of LOCA in various model settings and observe that it exhibits promising interpolation and extrapolation capabilities, superior to the current state of the art. Finally, we demonstrate LOCA’s efficacy in single-site Wi-Fi localization data and for the reconstruction of three-dimensional curved surfaces from two-dimensional projections.

The Effect of Phi on the Perception of Attractiveness

The ratio Phi, equal to approximately 1.618, is an observable phenomenon that Greek mathematician Euclid defined this relationship as a line in two parts, in which the ratio of the longer part to the shorter part is equal to the ratio of the total length over the longer part. The ancient Greeks thought of Phi as a mathematical representation of physical beauty. Although many studies have shown a correlation between Phi and perceived attractiveness, other studies have displayed no/very weak, correlation. The question, “Does the expression of Phi play a significant role in the attractiveness of a face?” was investigated. It was hypothesized that if the features of a face closely fit the proportions of Phi, then survey respondents will give that face a higher attractiveness rating than a face whose features do not. Landmark localization data was calculated for images of 14 different faces. Individual and average facial ratios were calculated for each photograph, and a survey was conducted in which 100 participants were asked to rate the attractiveness of each face on a scale of 1-10. The average attractiveness rating of each face was then compared to the variance/distance of its average facial ratio away from the numerical value of Phi. Based on the analysis of the data, faces with features whose proportions closely fit the ratio of Phi are perceived as more attractive than faces with features that do not. Faces with average facial ratios closer to Phi received higher average attractiveness ratings.

Single Molecule Light Field Microscopy

We introduce single molecule light field microscopy (SMLFM), a novel 3D single molecule localization technique that is capable of up to 20 nm isotropic precision across a 6 μm depth of field. SMLFM can be readily implemented by installing a refractive microlens array into the conjugate back focal plane of any widefield single molecule localization system. We demonstrate that 3D localization can be performed by post-processing 2D localization data generated by common, widely-used, algorithms. In this work we benchmark the performance of SMLFM and finally showcase its capabilities by imaging fluorescently labeled membranes of fixed eukaryotic cells below the diffraction limit.

Bioenergetics of the Dictyostelium Kinesin-8 Motor Isoform

The functional organization of microtubules in eukaryotic cells requires a combination of their inherent dynamic properties, interactions with motor machineries, and interactions with accessory proteins to affect growth, shrinkage, stability, and architecture. In most organisms, the Kinesin-8 family of motors play an integral role in these organizations, well known for their mitotic activities in microtubule (MT) length control and kinetochore interactions. In Dictyostelium discoideum, the function of Kinesin-8 remains elusive. We present here some biochemical properties and localization data that indicate that this motor (DdKif10) shares some motility properties with other Kinesin-8s but also illustrates differences in microtubule localization and depolymerase action that highlight functional diversity.