Can managed grasslands enhance pollinators in intensively farmed areas?

Wild flower strips is a common agri-environmental scheme used by farmers and land managers in order to improve biodiversity of pollinators. However, managed grasslands may also provide flower resources for flower visiting insects in agricultural landscapes. Botanically diverse grasslands on arable farms may support a range of wild pollinators, enhancing pollination services of crops. Intensively managed leys, on the other hand, typically contain only a few high-yielding, competitively strong species. One of the aims of the Multiplant project (2014-2018) was to test perennial seed mixtures targeted for bio-energy, feed protein and biodiversity, in order to develop multi-functional seed mixtures for grasslands. In the current study, we specifically investigated if yield (biomass production) and floral resources for pollinators could be simultaneously optimized by varying botanical composition of mixtures and cutting frequency. We tested four different perennial seed mixtures (3-, 5-, 11- and 13-species mixtures) at three sites varying in surrounding environment using three cutting strategies (no cutting, two cuts per year, four cuts per year). We measured flower production during the season, composition of flower-visitors (in functional groups), and biomass production of all plant species in the seed mixtures. The 11- and 13-species mixtures, which were designed to enhance pollinators, produced similar or higher yield than the 3- and 5- species mixtures under certain cutting regimes. The 3- and 5- species mixtures had a high accumulated flower abundance due to excessive flowering of lucerne under the two-cut strategy and white clover under the four-cut strategy. However, the 11- and 13 species mixtures presented a higher diversity of flowers during the flowering season. Interestingly, accumulated flower abundance was not significantly reduced under the two-cut strategy compared to no cut. Pollinator profiles (visits by different functional groups of insects) were plant-species specific, i.e. at all sites, plant species attracted similar types of insects. Legume species mainly attracted large bees (honey bees and bumblebees), while herbs attracted other insect groups, in particular syrphids and other flies. Our results suggest that multi-species grassland mixtures can be designed to support a higher diversity of pollinators without compromising herbage yield. In particular, adding forbs to the grass-legume mixtures and using a two-cut strategy rather than four cuts per year, may increase flower resources available for a larger range of wild pollinators

Ab initio study of shock compressed oxygen

Quantum molecular dynamic simulations are introduced to study the shock compressed oxygen. The principal Hugoniot points derived from the equation of state agree well with the available experimental data. With the increase of pressure, molecular dissociation is observed. Electron spin polarization determines the electronic structure of the system under low pressure, while it is suppressed around 30 $\sim$ 50 GPa. Particularly, nonmetal-metal transition is taken into account, which also occurs at about 30 $\sim$ 50 GPa. In addition, the optical properties of shock compressed oxygen are also discussed.Comment: 5 pages, 5 figure

Effects of GATT/WTO on Asia's Trade Performance

Our review of the literature suggests that the effects of GATT/WTO are insignificant or relatively small for participants in general, but potentially very large for groups that make heavy use of it. Our empirical analysis suggests that these gains are disproportionately large for the Asia-Pacific countries—perhaps by reducing resistance to the rapid growth and change in trade patterns in the region. We also highlight a potentially important source of future gains through helping to restrain the costly growth of agricultural protection in rapidly-developing countries in the region.Asian trade growth, GATT commitments, WTO accession

Differential Phase-contrast Interior Tomography

Differential phase contrast interior tomography allows for reconstruction of a refractive index distribution over a region of interest (ROI) for visualization and analysis of internal structures inside a large biological specimen. In this imaging mode, x-ray beams target the ROI with a narrow beam aperture, offering more imaging flexibility at less ionizing radiation. Inspired by recently developed compressive sensing theory, in numerical analysis framework, we prove that exact interior reconstruction can be achieved on an ROI via the total variation minimization from truncated differential projection data through the ROI, assuming a piecewise constant distribution of the refractive index in the ROI. Then, we develop an iterative algorithm for the interior reconstruction and perform numerical simulation experiments to demonstrate the feasibility of our proposed approach

Reverse k Nearest Neighbor Search over Trajectories

GPS enables mobile devices to continuously provide new opportunities to improve our daily lives. For example, the data collected in applications created by Uber or Public Transport Authorities can be used to plan transportation routes, estimate capacities, and proactively identify low coverage areas. In this paper, we study a new kind of query-Reverse k Nearest Neighbor Search over Trajectories (RkNNT), which can be used for route planning and capacity estimation. Given a set of existing routes DR, a set of passenger transitions DT, and a query route Q, a RkNNT query returns all transitions that take Q as one of its k nearest travel routes. To solve the problem, we first develop an index to handle dynamic trajectory updates, so that the most up-to-date transition data are available for answering a RkNNT query. Then we introduce a filter refinement framework for processing RkNNT queries using the proposed indexes. Next, we show how to use RkNNT to solve the optimal route planning problem MaxRkNNT (MinRkNNT), which is to search for the optimal route from a start location to an end location that could attract the maximum (or minimum) number of passengers based on a pre-defined travel distance threshold. Experiments on real datasets demonstrate the efficiency and scalability of our approaches. To the best of our best knowledge, this is the first work to study the RkNNT problem for route planning.Comment: 12 page

On-line Quantum State Estimation Using Continuous Weak Measurement and Compressed Sensing

We propose a new protocol for on-line quantum system estimation on the basis of continuous weak-measurements with the help of compressive sensing and the optimization algorithm. By directly measuring the state of the probe system, we indirectly obtain the measurement operators of the estimated system. The continuous weak measurements for a dynamic evolution open quantum system enable us to derive the time-varying measurement operators of the estimated system. Compressed sensing is used to reduce the number of the measurements needed and to improve the efficiency of the estimation. This approach to the on-line state estimation provides a novel solution to the problem of closed-loop quantum feedback control.Comment: 4 figure

Validating Sample Average Approximation Solutions with Negatively Dependent Batches

Sample-average approximations (SAA) are a practical means of finding approximate solutions of stochastic programming problems involving an extremely large (or infinite) number of scenarios. SAA can also be used to find estimates of a lower bound on the optimal objective value of the true problem which, when coupled with an upper bound, provides confidence intervals for the true optimal objective value and valuable information about the quality of the approximate solutions. Specifically, the lower bound can be estimated by solving multiple SAA problems (each obtained using a particular sampling method) and averaging the obtained objective values. State-of-the-art methods for lower-bound estimation generate batches of scenarios for the SAA problems independently. In this paper, we describe sampling methods that produce negatively dependent batches, thus reducing the variance of the sample-averaged lower bound estimator and increasing its usefulness in defining a confidence interval for the optimal objective value. We provide conditions under which the new sampling methods can reduce the variance of the lower bound estimator, and present computational results to verify that our scheme can reduce the variance significantly, by comparison with the traditional Latin hypercube approach

Optical chirality from dark-field illumination of planar plasmonic nanostructures

Dark-field illumination is shown to make planar chiral nanoparticle arrangements exhibit circular dichroism in extinction analogous to true chiral scatterers. Circular dichrosim is experimentally observed at the maximum scattering of single oligomers consisting rotationally symmetric arrangements of gold nanorods, with strong agreement to numerical simulation. A dipole model is developed to show that this effect is caused by a difference in the geometric projection of a nanorod onto the handed orientation of electric fields created by a circularly polarized dark-field that is normally incident on a glass substrate. Owing to this geometric origin, the wavelength of the peak chiral response is also experimentally shown to shift depending on the separation between nanoparticles. All presented oligomers have physical dimensions less than the operating wavelength, and the applicable extension to closely packed planar arrays of oligomers is demonstrated to amplify the magnitude of circular dichroism. The realization of strong chirality in these oligomers demonstrates a new path to engineer optical chirality from planar devices using dark-field illumination