Stiffness of the human foot and evolution of the transverse arch

The stiff human foot enables an efficient push-off when walking or running, and was critical for the evolution of bipedalism(1-6). The uniquely arched morphology of the human midfoot is thought to stiffen it(5-9), whereas other primates have flat feet that bend severely in the midfoot(7,10,11). However, the relationship between midfoot geometry and stiffness remains debated in foot biomechanics(12,13), podiatry(14,15) and palaeontology(4-6). These debates centre on the medial longitudinal arch(5,6) and have not considered whether stiffness is affected by the second, transverse tarsal arch of the human foot(16). Here we show that the transverse tarsal arch, acting through the inter-metatarsal tissues, is responsible for more than 40% of the longitudinal stiffness of the foot. The underlying principle resembles a floppy currency note that stiffens considerably when it curls transversally. We derive a dimensionless curvature parameter that governs the stiffness contribution of the transverse tarsal arch, demonstrate its predictive power using mechanical models of the foot and find its skeletal correlate in hominin feet. In the foot, the material properties of the inter-metatarsal tissues and the mobility of the metatarsals may additionally influence the longitudinal stiffness of the foot and thus the curvature-stiffness relationship of the transverse tarsal arch. By analysing fossils, we track the evolution of the curvature parameter among extinct hominins and show that a human-like transverse arch was a key step in the evolution of human bipedalism that predates the genus Homo by at least 1.5 million years. This renewed understanding of the foot may improve the clinical treatment of flatfoot disorders, the design of robotic feet and the study of foot function in locomotion

GWTC-2.1: Deep extended catalog of compact binary coalescences observed by LIGO and Virgo during the first half of the third observing run

The second Gravitational-Wave Transient Catalog, GWTC-2, reported on 39 compact binary coalescences observed by the Advanced LIGO and Advanced Virgo detectors between 1 April 2019 15 ∶ 00 UTC and 1 October 2019 15 ∶ 00 UTC. Here, we present GWTC-2.1, which reports on a deeper list of candidate events observed over the same period. We analyze the final version of the strain data over this period with improved calibration and better subtraction of excess noise, which has been publicly released. We employ three matched-filter search pipelines for candidate identification, and estimate the probability of astrophysical origin for each candidate event. While GWTC-2 used a false alarm rate threshold of 2 per year, we include in GWTC-2.1, 1201 candidates that pass a false alarm rate threshold of 2 per day. We calculate the source properties of a subset of 44 high-significance candidates that have a probability of astrophysical origin greater than 0.5. Of these candidates, 36 have been reported in GWTC-2. We also calculate updated source properties for all binary black hole events previously reported in GWTC-1. If the eight additional high-significance candidates presented here are astrophysical, the mass range of events that are unambiguously identified as binary black holes (both objects ≥ 3 M⊙ ) is increased compared to GWTC-2, with total masses from ∼ 14 M ⊙ for GW190924_021846 to ∼ 182 M⊙ for GW190426_190642. Source properties calculated using our default prior suggest that the primary components of two new candidate events (GW190403_051519 and GW190426_190642) fall in the mass gap predicted by pair-instability supernova theory. We also expand the population of binaries with significantly asymmetric mass ratios reported in GWTC-2 by an additional two events (the mass ratio is less than 0.65 and 0.44 at 90% probability for GW190403_051519 and GW190917_114630 respectively), and find that two of the eight new events have effective inspiral spins χeff > 0 (at 90% credibility), while no binary is consistent with χeff < 0 at the same significance. We provide updated estimates for rates of binary black hole and binary neutron star coalescence in the local Universe

All-sky, all-frequency directional search for persistent gravitational waves from Advanced LIGO’s and Advanced Virgo’s first three observing runs

We present the first results from an all-sky all-frequency (ASAF) search for an anisotropic stochastic gravitational-wave background using the data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. Upper limit maps on broadband anisotropies of a persistent stochastic background were published for all observing runs of the LIGO-Virgo detectors. However, a broadband analysis is likely to miss narrowband signals as the signal-to-noise ratio of a narrowband signal can be significantly reduced when combined with detector output from other frequencies. Data folding and the computationally efficient analysis pipeline, {\tt PyStoch}, enable us to perform the radiometer map-making at every frequency bin. We perform the search at 3072 {\tt{HEALPix}} equal area pixels uniformly tiling the sky and in every frequency bin of width $1/32$~Hz in the range $20-1726$~Hz, except for bins that are likely to contain instrumental artefacts and hence are notched. We do not find any statistically significant evidence for the existence of narrowband gravitational-wave signals in the analyzed frequency bins. Therefore, we place $95\%$ confidence upper limits on the gravitational-wave strain for each pixel-frequency pair, the limits are in the range $(0.030 - 9.6) \times10^{-24}$. In addition, we outline a method to identify candidate pixel-frequency pairs that could be followed up by a more sensitive (and potentially computationally expensive) search, e.g., a matched-filtering-based analysis, to look for fainter nearly monochromatic coherent signals. The ASAF analysis is inherently independent of models describing any spectral or spatial distribution of power. We demonstrate that the ASAF results can be appropriately combined over frequencies and sky directions to successfully recover the broadband directional and isotropic results

Search for gravitational waves associated with gamma-ray bursts detected by Fermi and Swift during the LIGO–Virgo run O3b

We search for gravitational-wave signals associated with gamma-ray bursts (GRBs) detected by the Fermi and Swift satellites during the second half of the third observing run of Advanced LIGO and Advanced Virgo (2019 November 1 15:00 UTC–2020 March 27 17:00 UTC). We conduct two independent searches: a generic gravitational-wave transients search to analyze 86 GRBs and an analysis to target binary mergers with at least one neutron star as short GRB progenitors for 17 events. We find no significant evidence for gravitational-wave signals associated with any of these GRBs. A weighted binomial test of the combined results finds no evidence for subthreshold gravitational-wave signals associated with this GRB ensemble either. We use several source types and signal morphologies during the searches, resulting in lower bounds on the estimated distance to each GRB. Finally, we constrain the population of low-luminosity short GRBs using results from the first to the third observing runs of Advanced LIGO and Advanced Virgo. The resulting population is in accordance with the local binary neutron star merger rate

Prediction of Cyclists Movement in Different Terrain Conditions

In Malaysia, most of the accidents involving a bicycle and another vehicle are due to either the driver or rider ‘failing to look properly’. This is more significant with the government initiatives to support the use of bicycle making the carbon-free environment, a vision of TN50. This research addresses the safety aspect of the cyclists in terms of the driver’s point of view which improves cyclist visibility during driving. The proposed helmet system implements a rule-based algorithm which predicts the turning and braking movement of the cyclists. With this system, additional illumination and signaling are provided for the cyclists. The major challenge faced is the implementation of an algorithm for various situations of cycling. To ensure the system could be used on the road, the accuracy and speed of the automatic signaling system need to adhere. Situations that affects the output of the indicators include bicycle speed, the angle of turning, body tilt, duration of turn and random body movements. This paper implements a 3-axis accelerometer and a microcontroller in a data logger to acquire the required data which are analyzed in MATLAB. Using filtering technique, the acquired data are then be cleaned to remove noise due to vibration during cycling. The characteristics of braking and turning are then analyzed in the time domain as well as frequency domain to ensure the optimum algorithm used for gesture recognition and movement prediction. The algorithm is based on sliding window, FFT and threshold-based rule algorithm. The output based on the rule-based algorithm then illuminate the corresponding signals which provide the safety feature of the system