Using step width to compare locomotor biomechanics between extinct, non-avian theropod dinosaurs and modern obligate bipeds

How extinct, non-avian theropod dinosaurs locomoted is a subject of considerable interest, as is the manner in which it evolved on the line leading to birds. Fossil footprints provide the most direct evidence for answering these questions. In this study, step width—the mediolateral (transverse) distance between successive footfalls—was investigated with respect to speed (stride length) in non-avian theropod trackways of Late Triassic age. Comparable kinematic data were also collected for humans and 11 species of ground-dwelling birds. Permutation tests of the slope on a plot of step width against stride length showed that step width decreased continuously with increasing speed in the extinct theropods (p < 0.001), as well as the five tallest bird species studied (p < 0.01). Humans, by contrast, showed an abrupt decrease in step width at the walk–run transition. In the modern bipeds, these patterns reflect the use of either a discontinuous locomotor repertoire, characterized by distinct gaits (humans), or a continuous locomotor repertoire, where walking smoothly transitions into running (birds). The non-avian theropods are consequently inferred to have had a continuous locomotor repertoire, possibly including grounded running. Thus, features that characterize avian terrestrial locomotion had begun to evolve early in theropod history

Support Neighbor Loss for Person Re-Identification

Person re-identification (re-ID) has recently been tremendously boosted due to the advancement of deep convolutional neural networks (CNN). The majority of deep re-ID methods focus on designing new CNN architectures, while less attention is paid on investigating the loss functions. Verification loss and identification loss are two types of losses widely used to train various deep re-ID models, both of which however have limitations. Verification loss guides the networks to generate feature embeddings of which the intra-class variance is decreased while the inter-class ones is enlarged. However, training networks with verification loss tends to be of slow convergence and unstable performance when the number of training samples is large. On the other hand, identification loss has good separating and scalable property. But its neglect to explicitly reduce the intra-class variance limits its performance on re-ID, because the same person may have significant appearance disparity across different camera views. To avoid the limitations of the two types of losses, we propose a new loss, called support neighbor (SN) loss. Rather than being derived from data sample pairs or triplets, SN loss is calculated based on the positive and negative support neighbor sets of each anchor sample, which contain more valuable contextual information and neighborhood structure that are beneficial for more stable performance. To ensure scalability and separability, a softmax-like function is formulated to push apart the positive and negative support sets. To reduce intra-class variance, the distance between the anchor's nearest positive neighbor and furthest positive sample is penalized. Integrating SN loss on top of Resnet50, superior re-ID results to the state-of-the-art ones are obtained on several widely used datasets.Comment: Accepted by ACM Multimedia (ACM MM) 201

Intensity limits of the PSI Injector II cyclotron

We investigate limits on the current of the PSI Injector II high intensity separate-sector isochronous cyclotron, in its present configuration and after a proposed upgrade. Accelerator Driven Subcritical Reactors, neutron and neutrino experiments, and medical isotope production all benefit from increases in current, even at the ~ 10% level: the PSI cyclotrons provide relevant experience. As space charge dominates at low beam energy, the injector is critical. Understanding space charge effects and halo formation through detailed numerical modelling gives clues on how to maximise the extracted current. Simulation of a space-charge dominated low energy high intensity (9.5 mA DC) machine, with a complex collimator set up in the central region shaping the bunch, is not trivial. We use the OPAL code, a tool for charged-particle optics calculations in large accelerator structures and beam lines, including 3D space charge. We have a precise model of the present production) Injector II, operating at 2.2 mA current. A simple model of the proposed future (upgraded) configuration of the cyclotron is also investigated. We estimate intensity limits based on the developed models, supported by fitted scaling laws and measurements. We have been able to perform more detailed analysis of the bunch parameters and halo development than any previous study. Optimisation techniques enable better matching of the simulation set-up with Injector II parameters and measurements. We show that in the production configuration the beam current scales to the power of three with the beam size. However, at higher intensities, 4th power scaling is a better fit, setting the limit of approximately 3 mA. Currents of over 5 mA, higher than have been achieved to date, can be produced if the collimation scheme is adjusted