True and False Foodplants of \u3ci\u3eCallosamia Promethea\u3c/i\u3e (Lepidoptera: Saturniidae) in Southern Michigan

A survey in 1980 of the associations of over 400 cocoons of Callosamia promethea Drury in vegetation along and adjacent to southern Michigan roadsides gave evidence for seven species of true larval foodplants (not including two others known in the area from other studies) and 17 species of false foodplants, the latter determined by the (1) rarity of their association with cocoons, (2) only one or two cocoons per plant, and (3) their proximity to a well known true foodplant. Three species, sassafras, black cherry, and buttonbush, are evidently the most important true foodplants in this area. Comparisons are made of the foodplants in terms of past literature, geography, and taxonomic relationships

Semi-supervised Eigenvectors for Large-scale Locally-biased Learning

In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks "nearby" that prespecified target region. For example, one might be interested in the clustering structure of a data graph near a prespecified "seed set" of nodes, or one might be interested in finding partitions in an image that are near a prespecified "ground truth" set of pixels. Locally-biased problems of this sort are particularly challenging for popular eigenvector-based machine learning and data analysis tools. At root, the reason is that eigenvectors are inherently global quantities, thus limiting the applicability of eigenvector-based methods in situations where one is interested in very local properties of the data. In this paper, we address this issue by providing a methodology to construct semi-supervised eigenvectors of a graph Laplacian, and we illustrate how these locally-biased eigenvectors can be used to perform locally-biased machine learning. These semi-supervised eigenvectors capture successively-orthogonalized directions of maximum variance, conditioned on being well-correlated with an input seed set of nodes that is assumed to be provided in a semi-supervised manner. We show that these semi-supervised eigenvectors can be computed quickly as the solution to a system of linear equations; and we also describe several variants of our basic method that have improved scaling properties. We provide several empirical examples demonstrating how these semi-supervised eigenvectors can be used to perform locally-biased learning; and we discuss the relationship between our results and recent machine learning algorithms that use global eigenvectors of the graph Laplacian

POWTEX Neutron Diffractometer at FRM II - new perspectives for in-situ rock deformation analysis

EGU2012-13521 In Geoscience quantitative texture analysis here defined as the quantitative analysis of the crystallographic preferred orientation (CPO), is a common tool for the investigation of fabric development in mono- and polyphase rocks, their deformation histories and kinematics. Bulk texture measurements also allow the quantitative characterisation of the anisotropic physical properties of rock materials. A routine tool to measure bulk sample volumes is neutron texture diffraction, as neutrons have large penetration capabilities of several cm in geological sample materials. The new POWTEX (POWder and TEXture) Diffractometer at the neutron research reactor FRM II in Garching, Germany is designed as a high-intensity diffractometer by groups from the RWTH Aachen, Forschungszentrum Jülich and the University of Göttingen. Complementary to existing neutron diffractometers (SKAT at Dubna, Russia; GEM at ISIS, UK; HIPPO at Los Alamos, USA; D20 at ILL, France; and the local STRESS-SPEC and SPODI at FRM II) the layout of POWTEX is focused on fast time-resolved experiments and the measurement of larger sample series as necessary for the study of large scale geological structures. POWTEX is a dedicated beam line for geoscientific research. Effective texture measurements without sample tilting and rotation are possible firstly by utilizing a range of neutron wavelengths simultaneously (Time-of-Flight technique) and secondly by the high detector coverage (9.8 sr) and a high flux (�~1x10 7 n/cm2s) at the sample. Furthermore the instrument and the angular detector resolution is designed also for strong recrystallisation textures as well as for weak textures of polyphase rocks. These instrument characteristics allow in-situ time-resolved texture measurements during deformation experiments on rocksalt, ice and other materials as large sample environments will be implemented at POWTEX. The in-situ deformation apparatus is operated by a uniaxial spindle drive with a maximum axial load of 250 kN, which will be redesigned to minimize shadowing effects inside the cylindrical detector. The HT deformatione experiments will be carried out in uniaxial compression or extension and an upgrade to triaxial deformation conditions is envisaged. The load frame can alternatively be used for ice deformation by inserting a cryostat cell for temperatures down to 77 K with a triaxial apparatus allowing also simple shear experiments on ice. Strain rates range between 10-8 and 10-3 s-1 reaching to at least 50% axial strain. The deformation apparatus is designed for continuous long-term deformation experiments and can be exchanged between in-situ and ex-situ placements during continuous operation inside and outside the neutron detector

Structure and dynamics of colloidal depletion gels: coincidence of transitions and heterogeneity

Transitions in structural heterogeneity of colloidal depletion gels formed through short-range attractive interactions are correlated with their dynamical arrest. The system is a density and refractive index matched suspension of 0.20 volume fraction poly(methyl methacyrlate) colloids with the non-adsorbing depletant polystyrene added at a size ratio of depletant to colloid of 0.043. As the strength of the short-range attractive interaction is increased, clusters become increasingly structurally heterogeneous, as characterized by number-density fluctuations, and dynamically immobilized, as characterized by the single-particle mean-squared displacement. The number of free colloids in the suspension also progressively declines. As an immobile cluster to gel transition is traversed, structural heterogeneity abruptly decreases. Simultaneously, the mean single-particle dynamics saturates at a localization length on the order of the short-range attractive potential range. Both immobile cluster and gel regimes show dynamical heterogeneity. Non-Gaussian distributions of single particle displacements reveal enhanced populations of dynamical trajectories localized on two different length scales. Similar dependencies of number density fluctuations, free particle number and dynamical length scales on the order of the range of short-range attraction suggests a collective structural origin of dynamic heterogeneity in colloidal gels.Comment: 14 pages, 10 figure

Theory and evidence

Indian outward foreign direct investment (FDI) has risen dramatically in recent years. This reflects that Indian multinational corporations (MNCs) are asserting an increasingly important role in the global economy, not only as resource and market seekers in less developed countries, but increasingly competing on par with western MNCs in their home markets. When we confront the Indian outward FDI path with theories of outward foreign direct investment from developing countries, a number of puzzles and anomalies becomes evident: Normally, we would expect strong inward FDI performance to precede strong outward FDI performance, however in India the rise in outward FDI has been almost simultaneous with the rise in inward FDI; Normally, we would expect developing country MNCs to invest in like or less developed countries, however Indian MNCs have in a rapid sequence moved into developed economies; Normally, we would expect developing country MNCs to be operating with less advanced technologies and business models, however Indian MNCs have moved directly into FDI in advanced sectors and technologies. This paper will offer a number of explanations for the unique Indian outward investment path, explanations that take their point of departure in the idiosyncratic nature of Indian industrialization

Linking seasonal forecasts into RiskView to enhance food security contingency planning

RiskView is a tool developed by the World Food Programme (WFP) to translate weather data (real-time and historical) and other spatial information (e.g., crops, drought risk, population, etc.) into food security needs and response costs. It serves as a swift way of estimating costs in advance of food insecurity outlooks for financial planning, and for facilitating better resource allocations to disasters before on-the-ground needs assessments are produced

Structure of a liquid crystalline fluid around a macroparticle: Density functional theory study

The structure of a molecular liquid, in both the nematic liquid crystalline and isotropic phases, around a cylindrical macroparticle, is studied using density functional theory. In the nematic phase the structure of the fluid is highly anisotropic with respect to the director, in agreement with results from simulation and phenomenological theories. On going into the isotropic phase the structure becomes rotationally invariant around the macroparticle with an oriented layer at the surface.Comment: 10 pages, 6 figues. Submitted to Phys. Rev.