UK Large-scale Wind Power Programme from 1970 to 1990: the Carmarthen Bay experiments and the Musgrove Vertical-Axis Turbines

This article describes the development of the Musgrove Vertical Axis Wind Turbine (VAWT) concept, the UK ‘Carmarthen Bay’ wind turbine test programme, and UK government’s wind power programme to 1990. One of the most significant developments in the story of British wind power occurred during the 1970s, 1980s, and 1990s, with the development of the Musgrove vertical axis wind turbine and its inclusion within the UK Government’s wind turbine test programme. Evolving from a supervisor’s idea for an undergraduate project at Reading University, the Musgrove VAWT was once seen as an able competitor to the horizontal axis wind systems that were also being encouraged at the time by both the UK government and the Central Electricity Generating Board, the then nationalised electricity utility for England and Wales. During the 1980s and 1990s the most developed Musgrove VAWT system, along with three other commercial turbine designs was tested at Carmarthen Bay, South Wales as part of a national wind power test programme. From these developmental tests, operational data was collected and lessons learnt, which were incorporated into subsequent wind power operations.http://dx.doi.org/10.1260/03095240677860621

Coarse-to-fine autoencoder networks (CFAN) for real-time face alignment

Abstract. Accurate face alignment is a vital prerequisite step for most face perception tasks such as face recognition, facial expression analysis and non-realistic face re-rendering. It can be formulated as the nonlinear inference of the facial landmarks from the detected face region. Deep network seems a good choice to model the nonlinearity, but it is nontrivial to apply it directly. In this paper, instead of a straightforward application of deep network, we propose a Coarse-to-Fine Auto-encoder Networks (CFAN) approach, which cascades a few successive Stacked Auto-encoder Networks (SANs). Specifically, the first SAN predicts the landmarks quickly but accurately enough as a preliminary, by taking as input a low-resolution version of the detected face holistically. The following SANs then progressively refine the landmark by taking as input the local features extracted around the current landmarks (output of the previous SAN) with higher and higher resolution. Extensive experiments conducted on three challenging datasets demonstrate that our CFAN outperforms the state-of-the-art methods and performs in real-time(40+fps excluding face detection on a desktop)

Extended Supervised Descent Method for Robust Face Alignment

Abstract. Supervised Descent Method (SDM) is a highly efficient and accurate approach for facial landmark locating/face alignment. It learns a sequence of descent directions that minimize the difference between the estimated shape and the ground truth in HOG feature space during training, and utilize them in testing to predict shape increment itera-tively. In this paper, we propose to modify SDM in three respects: 1) Multi-scale HOG features are applied orderly as a coarse-to-fine feature detector; 2) Global to local constraints of the facial features are con-sidered orderly in regression cascade; 3) Rigid Regularization is applied to obtain more stable prediction results. Extensive experimental result-s demonstrate that each of the three modifications could improve the accuracy and robustness of the traditional SDM methods. Furthermore, enhanced by the three-fold improvements, the extended SDM compares favorably with other state-of-the-art methods on several challenging face data sets, including LFPW, HELEN and 300 Faces in-the-wild.

Co-located wind and wave energy farms: Uniformly distributed arrays

publisher: Elsevier articletitle: Co-located wind and wave energy farms: Uniformly distributed arrays journaltitle: Energy articlelink: http://dx.doi.org/10.1016/j.energy.2016.07.069 content_type: article copyright: © 2016 Elsevier Ltd. All rights reserved

Regulation of abscisic acid concentration in leaves of field-grown pearl millet (Pennisetum americanum (L.) Leeke): the role of abscisic acid export

Diurnal changes in the ABA concn. in leaves of droughted, field-grown plants of P. americanum were not always correlated with changes in bulk leaf water potential. A rapid decline in ABA content of the leaves following its rise to a peak level in mid-morning, was observed in several time-course studies despite continued water stress. The possibility that the reduction in ABA in leaves was due to an elevated rate of its export was examined by measuring ABA concn. in developing panicles (possible sinks for leaf-produced ABA) and in leaves, and by comparing the amounts of ABA in ungirdled leaves and in leaves heat-girdled at the base of the lamina to block export. ABA concn. in panicles generally paralleled those in leaves, though the peak concn. of ABA in the morning in panicles occurred later than in the leaves in some samplings. Although girdling initially increased ABA concn., it did not prevent a subsequent fall which generally paralleled the decline observed in untreated leaves. The decrease in ABA that occurred despite the block to export and despite continuing stress was attributed to changes in the synthesis or metabolism of ABA within the leaf. The probable rate of export of ABA from leaves, calculated from the changes in its concn. due to girdling, was highest at the time of most rapid ABA accumulation and declined thereafter. The percentage export of recently assimilated C declined similarly. However, the probable absolute rate of export of photosynthate, computed from stomatal conductance and [14C]-export measurements, was not uniquely related to that of AB