Multiple-image encryption by compressive holography

We present multiple-image encryption (MIE) based on compressive holography. In the encryption, a holographic technique is employed to record multiple images simultaneously to form a hologram. The two-dimensional Fourier data of the hologram are then compressed by nonuniform sampling, which gives rise to compressive encryption. Decryption of individual images is cast into a minimization problem. The minimization retains the sparsity of recovered images in the wavelet basis. Meanwhile, total variation regularization is used to preserve edges in the reconstruction. Experiments have been conducted using holograms acquired by optical scanning holography as an example. Computer simulations of multiple images are subsequently demonstrated to illustrate the feasibility of the MIE scheme.published_or_final_versio

Radial Growth of Qilian Juniper on the Northeast Tibetan Plateau and Potential Climate Associations

There is controversy regarding the limiting climatic factor for tree radial growth at the alpine treeline on the northeastern Tibetan Plateau. In this study, we collected 594 increment cores from 331 trees, grouped within four altitude belts spanning the range 3550 to 4020 m.a.s.l. on a single hillside. We have developed four equivalent ring-width chronologies and shown that there are no significant differences in their growth-climate responses during 1956 to 2011 or in their longer-term growth patterns during the period AD 1110–2011. The main climate influence on radial growth is shown to be precipitation variability. Missing ring analysis shows that tree radial growth at the uppermost treeline location is more sensitive to climate variation than that at other elevations, and poor tree radial growth is particularly linked to the occurrence of serious drought events. Hence water limitation, rather than temperature stress, plays the pivotal role in controlling the radial growth of Sabina przewalskii Kom. at the treeline in this region. This finding contradicts any generalisation that tree-ring chronologies from high-elevation treeline environments are mostly indicators of temperature changes

Will all scientists working on snails and the diseases they transmit please stand up?

Copyright © 2012 Adema et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.No abstract available

On acceleration of Krylov-subspace-based Newton and Arnoldi iterations for incompressible CFD: replacing time steppers and generation of initial guess

We propose two techniques aimed at improving the convergence rate of steady state and eigenvalue solvers preconditioned by the inverse Stokes operator and realized via time-stepping. First, we suggest a generalization of the Stokes operator so that the resulting preconditioner operator depends on several parameters and whose action preserves zero divergence and boundary conditions. The parameters can be tuned for each problem to speed up the convergence of a Krylov-subspace-based linear algebra solver. This operator can be inverted by the Uzawa-like algorithm, and does not need a time-stepping. Second, we propose to generate an initial guess of steady flow, leading eigenvalue and eigenvector using orthogonal projection on a divergence-free basis satisfying all boundary conditions. The approach, including the two proposed techniques, is illustrated on the solution of the linear stability problem for laterally heated square and cubic cavities

Deletion of vascular endothelial growth factor in myeloid cells accelerates tumorigenesis.

Angiogenesis and the development of a vascular network are required for tumour progression, and they involve the release of angiogenic factors, including vascular endothelial growth factor (VEGF-A), from both malignant and stromal cell types. Infiltration by cells of the myeloid lineage is a hallmark of many tumours, and in many cases the macrophages in these infiltrates express VEGF-A. Here we show that the deletion of inflammatory-cell-derived VEGF-A attenuates the formation of a typical high-density vessel network, thus blocking the angiogenic switch in solid tumours in mice. Vasculature in tumours lacking myeloid-cell-derived VEGF-A was less tortuous, with increased pericyte coverage and decreased vessel length, indicating vascular normalization. In addition, loss of myeloid-derived VEGF-A decreases the phosphorylation of VEGF receptor 2 (VEGFR2) in tumours, even though overall VEGF-A levels in the tumours are unaffected. However, deletion of myeloid-cell VEGF-A resulted in an accelerated tumour progression in multiple subcutaneous isograft models and an autochthonous transgenic model of mammary tumorigenesis, with less overall tumour cell death and decreased tumour hypoxia. Furthermore, loss of myeloid-cell VEGF-A increased the susceptibility of tumours to chemotherapeutic cytotoxicity. This shows that myeloid-derived VEGF-A is essential for the tumorigenic alteration of vasculature and signalling to VEGFR2, and that these changes act to retard, not promote, tumour progression

An edge-from-focus approach to 3D inspection and metrology

Best Paper Award 2015We propose an edge-based depth-from-focus technique for high-precision non-contact industrial inspection and metrology applications. In our system, an objective lens with a large numerical aperture is chosen to resolve the edge details of the measured object. By motorizing this imaging system, we capture the high-resolution edges within every narrow depth of field. We can therefore extend the measured range and keep a high resolution at the same time. Yet, on the surfaces with a large depth variation, a significant amount of data around each measured point are out of focus within the captured images. Then, it is difficult to extract the valuable information from these out-of-focus data due to the depth-variant blur. Moreover, these data impede the extraction of continuous contours for the measurement objects in high-level machine vision applications. The proposed approach however makes use of the out-of-focus data to synthesize a depth-invariant smoothed image, and then robustly locates the positions of high contrast edges based on non-maximum suppression and hysteresis thresholding. Furthermore, by focus analysis of both the in-focus and the out-of-focus data, we reconstruct the high-precision 3D edges for metrology applications

Optogenetics and deep brain stimulation neurotechnologies

Brain neural network is composed of densely packed, intricately wired neurons whose activity patterns ultimately give rise to every behavior, thought, or emotion that we experience. Over the past decade, a novel neurotechnique, optogenetics that combines light and genetic methods to control or monitor neural activity patterns, has proven to be revolutionary in understanding the functional role of specific neural circuits. We here briefly describe recent advance in optogenetics and compare optogenetics with deep brain stimulation technology that holds the promise for treating many neurological and psychiatric disorders