Zebu Cattle Are an Exclusive Legacy of the South Asia Neolithic

Animal domestication was a major step forward in human prehistory, contributing to the emergence of more complex societies. At the time of the Neolithic transition, zebu cattle (Bos indicus) were probably the most abundant and important domestic livestock species in Southern Asia. Although archaeological evidence points toward the domestication of zebu cattle within the Indian subcontinent, the exact geographic origins and phylogenetic history of zebu cattle remains uncertain. Here, we report evidence from 844 zebu mitochondrial DNA (mtDNA) sequences surveyed from 19 Asiatic countries comprising 8 regional groups, which identify 2 distinct mitochondrial haplogroups, termed I1 and I2. The marked increase in nucleotide diversity (P < 0.001) for both the I1 and I2 haplogroups within the northern part of the Indian subcontinent is consistent with an origin for all domestic zebu in this area. For haplogroup I1, genetic diversity was highest within the Indus Valley among the three hypothesized domestication centers (Indus Valley, Ganges, and South India). These data support the Indus Valley as the most likely center of origin for the I1 haplogroup and a primary center of zebu domestication. However, for the I2 haplogroup, a complex pattern of diversity is detected, preventing the unambiguous pinpointing of the exact place of origin for this zebu maternal lineage. Our findings are discussed with respect to the archaeological record for zebu domestication within the Indian subcontinent.

Distinctive Paleo-Indian Migration Routes from Beringia Marked by Two Rare mtDNA Haplogroups

Background: It is widely accepted that the ancestors of Native Americans arrived in the New World via Beringia approximately 10 to 30 thousand years ago (kya). However, the arrival time(s), number of expansion events, and migration routes into the Western

Effect of bend orientation on life and puncture point location due to solid particle erosion of a high concentration flow in pneumatic conveyors

An investigation into predicting failure of pneumatic conveyor pipe bends due to hard solid particle impact erosion has been carried out on an industrial scale test rig. The bend puncture point locations may vary with many factors. However, bend orientation was suspected of being a main factor due to the biased particle distribution pattern of a high concentration flow. In this paper, puncture point locations have been studied with different pipe bend orientations and geometry (a solids loading ratio of 10 being used for the high concentration flow). Test results confirmed that the puncture point location is indeed most significantly influenced by the bend orientation (especially for a high concentration flow) due to the biased particle distribution and biased particle flux distribution. © 2004 Elsevier B.V. All rights reserved.

Effect of particle concentration on erosion rate of mild steel bends in a pneumatic conveyor

Particle concentration is known as a main factor that affects erosion rate of pipe bends in pneumatic conveyors. With consideration of different bend radii, the effect of particle concentration on weight loss of mild steel bends has been investigated in an industrial scale test rig. Experimental results show that there was a significant reduction of the specific erosion rate for high particle concentrations. This reduction was considered to be as a result of the shielding effect during the particle impacts. An empirical model is given. Also a theoretical study of scaling on the shielding effect, and comparisons with some existing models, are presented. It is found that the reduction in specific erosion rate (relative to particle concentration) has a stronger relationship in conveying pipelines than has been found in the erosion tester. © 2004 Elsevier B.V. All rights reserved.

An advanced multi-configuration stator well cooling test facility

Optimisation of cooling systems within gas turbine engines is of great interest to engine manufacturers seeking gains in performance, efficiency and component life. The effectiveness of coolant delivery is governed by complex flows within the stator wells and the interaction of main annulus and cooling air in the vicinity of the rim seals. This paper reports the development of a test facility which allows the interaction of cooling air and main gas paths to be measured at conditions representative of those found in modern gas turbine engines. The test facility features a two stage turbine with an overall pressure ratio of approximately 2.6:1. Hot air is supplied to the main annulus using a Rolls-Royce Dart compressor driven by an aero-derivative engine plant. Cooling air can be delivered to the stator wells at multiple locations and at a range of flow rates which cover bulk ingestion through to bulk egress. The facility has been designed with adaptable geometry to enable rapid changes of cooling air path configuration. The coolant delivery system allows swift and accurate changes to the flow settings such that thermal transients may be performed. Particular attention has been focused on obtaining high accuracy data, using a radio telemetry system, as well as thorough through-calibration practices. Temperature measurements can now be made on both rotating and stationary discs with a long term uncertainty in the region of 0.3 K. A gas concentration measurement system has also been developed to obtain direct measurement of re-ingestion and rim seal exchange flows. High resolution displacement sensors have been installed in order to measure hot running geometry. This paper documents the commissioning of a test facility which is unique in terms of rapid configuration changes, non-dimensional engine matching and the instrumentation density and resolution. Example data for each of the measurement systems is presented. This includes the effect of coolant flow rate on the metal temperatures within the upstream cavity of the turbine stator well, the axial displacement of the rotor assembly during a commissioning test, and the effect of coolant flow rate on mixing in the downstream cavity of the stator well. Copyright © 2010 by ASME.

Model based learning of sigma points in unscented Kalman filtering

The unscented Kalman filter (UKF) is a widely used method in control and time series applications. The UKF suffers from arbitrary parameters necessary for sigma point placement, potentially causing it to perform poorly in nonlinear problems. We show how to treat sigma point placement in a UKF as a learning problem in a model based view. We demonstrate that learning to place the sigma points correctly from data can make sigma point collapse much less likely. Learning can result in a significant increase in predictive performance over default settings of the parameters in the UKF and other filters designed to avoid the problems of the UKF, such as the GP-ADF. At the same time, we maintain a lower computational complexity than the other methods. We call our method UKF-L. © 2011 Elsevier B.V.

Assessment of computational fluid dynamics and experimental data for shock boundary-layer interactions

A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop, numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric, and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and, in general, it was difficult to discern clear trends in the data. For the Reynolds-averaged Navier-Stokes (RANS) methods, the choice of turbulence model appeared to be the largest factor in solution accuracy. Scale-resolving methods, such as large-eddy simulation (LES), hybrid RANS/LES, and direct numerical simulation, produced error levels similar to RANS methods but provided superior predictions of normal stresses. Copyright © 2012 by Daniella E. Raveh and Michael Iovnovich.

Physical modelling of flexible retaining walls under seismic actions

A series of dynamic centrifuge tests on reduced scale models of flexible retaining structures were conducted on the Turner beam centrifuge at the Schofield Centre of the University of Cambridge. The paper illustrates the main results of the experimental work in terms of observed amplifications of ground motion and mobilised shear stiffness and damping ratio for all tests. The experimental results for one test on a pair of cantilevered walls in dense sand are also presented in terms of measured bending moments and horizontal displacements of the walls during (maximum values) and at the end of (residual values) each seismic event. Finally, the experimental data are discussed in the light of the results obtained from dynamic numerical analyses of the behaviour of cantilevered walls under real seismic actions. © 2010 Taylor & Francis Group, London.

Probabilistic amplitude and frequency demodulation

A number of recent scientific and engineering problems require signals to be decomposed into a product of a slowly varying positive envelope and a quickly varying carrier whose instantaneous frequency also varies slowly over time. Although signal processing provides algorithms for so-called amplitude-and frequency-demodulation (AFD), there are well known problems with all of the existing methods. Motivated by the fact that AFD is ill-posed, we approach the problem using probabilistic inference. The new approach, called probabilistic amplitude and frequency demodulation (PAFD), models instantaneous frequency using an auto-regressive generalization of the von Mises distribution, and the envelopes using Gaussian auto-regressive dynamics with a positivity constraint. A novel form of expectation propagation is used for inference. We demonstrate that although PAFD is computationally demanding, it outperforms previous approaches on synthetic and real signals in clean, noisy and missing data settings.

A population perspective on mobile phone related tasks

Chapter 6 A Population Perspective on Mobile Phone Related Tasks M. Bradley, S. Waller, J. Goodman-Deane, l. Hosking, R. Tenneti, PM Langdon and PJ Clarkson 6.1 Introduction For design to be truly inclusive, it needs to take into ...

State-space inference and learning with Gaussian processes

State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We apply the expectation maximization algorithm to iterate between inference in the latent state-space and learning the parameters of the underlying GP dynamics model. Copyright 2010 by the authors.

Robust filtering and smoothing with gaussian processes

We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of system identification is more robust than finding point estimates of a parametric function representation. Our principled filtering/smoothing approach for GP dynamic systems is based on analytic moment matching in the context of the forward-backward algorithm. Our numerical evaluations demonstrate the robustness of the proposed approach in situations where other state-of-the-art Gaussian filters and smoothers can fail. © 2011 IEEE.