Halo ratio from ground based all-sky imaging

© Author(s) 2019.The halo ratio (HR) is a quantitative measure characterizing the occurrence of the 22 halo peak associated with cirrus. We propose to obtain it from an approximation to the scattering phase function (SPF) derived from allsky imaging. Ground-based fisheye cameras are used to retrieve the SPF by implementing the necessary image transformations and corrections. These consist of geometric camera characterization by utilizing positions of known stars in a camera image, transforming the images from the zenithcentred to the light-source-centred system of coordinates and correcting for the air mass and for vignetting, the latter using independent measurements from a sun photometer. The SPF is then determined by averaging the image brightness over the azimuth angle and the HR by calculating the ratio of the SPF at two scattering angles in the vicinity of the 22° halo peak. In variance from previous suggestions we select these angles to be 20 and 23°, on the basis of our observations. HR time series have been obtained under various cloud conditions, including halo cirrus, non-halo cirrus and scattered cumuli. While the HR measured in this way is found to be sensitive to the halo status of cirrus, showing values typically > 1 under halo-producing clouds, similar HR values, mostly artefacts associated with bright cloud edges, can also be occasionally observed under scattered cumuli. Given that the HR is an ice cloud characteristic, a separate cirrus detection algorithm is necessary to screen out non-ice clouds before deriving reliable HR statistics. Here we propose utilizing sky brightness temperature from infrared radiometry: Both its absolute value and the magnitude of fluctuations obtained through detrended fluctuation analysis. The brightness temperature data permit the detection of cirrus in most but not all instances.Peer reviewe

Highly Stretchable MoS2_2 Kirigami

We report the results of classical molecular dynamics simulations focused on studying the mechanical properties of MoS$_{2}$ kirigami. Several different kirigami structures were studied based upon two simple non-dimensional parameters, which are related to the density of cuts, as well as the ratio of the overlapping cut length to the nanoribbon length. Our key finding is significant enhancements in tensile yield (by a factor of four) and fracture strains (by a factor of six) as compared to pristine MoS$_{2}$ nanoribbons. These results in conjunction with recent results on graphene suggest that the kirigami approach may be a generally useful one for enhancing the ductility of two-dimensional nanomaterials

Polarization and valley switching in monolayer group-IV monochalcogenides

Group-IV monochalcogenides are a family of two-dimensional puckered materials with an orthorhombic structure that is comprised of polar layers. In this article, we use first principles calculations to show the multistability of monolayer SnS and GeSe, two prototype materials where the direction of the puckering can be switched by application of tensile stress or electric field. Furthermore, the two inequivalent valleys in momentum space, which are dictated by the puckering orientation, can be excited selectively using linearly polarized light, and this provides an additional tool to identify the polarization direction. Our findings suggest that SnS and GeSe monolayers may have observable ferroelectricity and multistability, with potential applications in information storage

Revitalizing African Languages for Transformation

Local languages are the repositories of the indigenous knowledge base of societies.  Marginalization of certain languages is a form of devaluing not only the languages but the knowledge and culture embodied in those languages.  This paper explores the effects the devaluation of African languages have had on the indigenous knowledge base and culture of African countries and considers possibilities for the transformation of Africa through re-valuing African languages

Accelerated search and design of stretchable graphene kirigami using machine learning

Making kirigami-inspired cuts into a sheet has been shown to be an effective way of designing stretchable materials with metamorphic properties where the 2D shape can transform into complex 3D shapes. However, finding the optimal solutions is not straightforward as the number of possible cutting patterns grows exponentially with system size. Here, we report on how machine learning (ML) can be used to approximate the target properties, such as yield stress and yield strain, as a function of cutting pattern. Our approach enables the rapid discovery of kirigami designs that yield extreme stretchability as verified by molecular dynamics (MD) simulations. We find that convolutional neural networks, commonly used for classification in vision tasks, can be applied for regression to achieve an accuracy close to the precision of the MD simulations. This approach can then be used to search for optimal designs that maximize elastic stretchability with only 1000 training samples in a large design space of ∼4×106 candidate designs. This example demonstrates the power and potential of ML in finding optimal kirigami designs at a fraction of iterations that would be required of a purely MD or experiment-based approach, where no prior knowledge of the governing physics is known or available.P. Z. H. developed the codes, performed the simulations and data analysis, and wrote the manuscript with input from all authors. P. Z. H. and E. D. C. developed the machine learning methods. P. Z. H., D. K. C. and H. S. P. acknowledge the Hariri Institute Research Incubation Grant No. 2018-02-002 and the Boston University High Performance Shared Computing Cluster. P. Z. H. is grateful for the Hariri Graduate Fellowship. P. Z. H. thank Grace Gu and Adrian Yi for helpful discussions. (2018-02-002 - Hariri Graduate Fellowship)Published versio

Mode-Locked Two-Photon States

The concept of mode locking in laser is applied to a two-photon state with frequency entanglement. Cavity enhanced parametric down-conversion is found to produce exactly such a state. The mode-locked two-photon state exhibits a comb-like correlation function. An unbalanced Hong-Ou-Mandel type interferometer is used to measure the correlation function. A revival of the typical interference dip is observed. We will discuss schemes for engineering of quantum states in time domain.Comment: 4 pages, 5 figure

Strain-induced gauge and Rashba fields in ferroelectric Rashba lead chalcogenide PbX monolayers (X = S, Se, Te)

One of the exciting features of two-dimensional (2D) materials is their electronic and optical tunability through strain engineering. Previously, we found a class of 2D ferroelectric Rashba semiconductors PbX (X = S, Se, Te) with tunable spin-orbital properties. In this work, based on our previous tight-binding (TB) results, we derive an effective low-energy Hamiltonian around the symmetry points that captures the effects of strain on the electronic properties of PbX. We find that strains induce gauge fields which shift the Rashba point and modify the Rashba parameter. This effect is equivalent to the application of in-plane magnetic fields. The out-of-plane strain, which is proportional to the electric polarization, is also shown to modify the Rashba parameter. Overall, our theory connects strain and spin splitting in ferroelectric Rashba materials, which will be important to understand the strain-induced variations in local Rashba parameters that will occur in practical applications

An Unfinished Canvas: Allocating Funding and Instructional Time for Elementary Arts Education

An Unfinished Canvas found that California's elementary schools face unique challenges inproviding all students with sequential, standards-based arts education. In particular, elementary principals identified inadequate funding and insufficient instructional time as significant barriers to the provision of arts education. For this study, we sought to further understand the impact of funding and time on elementary arts education. To do so, we examined the allocation of funding and instructional time in 10 schools across five states (Kentucky, Massachusetts, Minnesota, New Jersey, and California)