Trade, Technology and the Great Divergence

This paper develops a model that captures the key features of the Industrial Revolution and the Great Divergence between the industrializing \North" and the lagging \South." In particular, a convincing story is needed for why North-South divergence occurred so dramatically during the late 19th Century, a good hundred years after the beginnings of the Industrial Revolution. To this end we construct a trade/growth model that includes both endogenous biased technologies and intercontinental trade. The Industrial Revolution began as a sequence of unskilled-labor intensive innovations which initially incited fertil- ity increases and limited human capital formation in both the North and the South. The subsequent co-evolution of trade and technological growth however fostered an inevitable di- vergence in living standards - the South increasingly specialized in production that worsened their terms of trade and spurred even greater fertility increases and educational declines. Biased technological changes in both regions only reinforced this pattern. The model high- lights how pronounced divergence ultimately arose from interactions between specialization from trade and technological forces.

Bee-Friendly Beef: Developing Biodiverse Pastures to Increase Ecosystem Services

The capacity of grasslands to provide ecosystem services, such as pollinator resources, is often limited by lack of plant biodiversity. This is true of grasslands in the eastern US that are dominated by tall fescue (Festuca arundinacea) a non-native, cool-season grass that is typically toxic to cattle. This paper summarizes a research project in Virginia, USA exploring the idea that ecosystem services provided by tall fescue-dominated grasslands can be improved by increasing the plant biodiversity available to beef cattle and bees. Within three 6.5 ha tall fescue grasslands, we established 0.8 ha plots with a 17 species mix of native warm-season grasses (NWSGs) and wildflowers. Beginning in 2018, we measured grass and wildflower establishment, attractiveness of wildflowers to bees, abundance and diversity of bee communities in biodiverse pastures and adjacent tall fescue pastures. Many of the 18 species sown established well expect for NWSGs. Competition from wildflowers likely suppressed native grasses and limited forage availability for beef cattle. Cattle largely ignored the wildflowers. This finding suggests that cattle and pollinators can share this biodiverse grassland as their primary foods are mutually exclusive. The total number of bees was almost double in wildflower-enhanced grasslands compared with more typical tall fescue grasslands. We observed most bee landings on purple coneflower (Echinacea purpurea) and anise hyssop (Agastache foeniculum). Several weedy species such as milkweed (Asclepias syriaca) and musk thistle (Carduus nutans) were also attractive to bees. Preliminary analyses identified at least 28 bee morphospecies and a distinct bee community present in wildflower pastures. While these results were promising, more research is needed on ways to establish biodiverse grasslands so that a more optimal balance of grasses and wildflowers can be sustained to benefit both cattle production and pollinators

A Characterization of Visibility Graphs for Pseudo-Polygons

In this paper, we give a characterization of the visibility graphs of pseudo-polygons. We first identify some key combinatorial properties of pseudo-polygons, and we then give a set of five necessary conditions based off our identified properties. We then prove that these necessary conditions are also sufficient via a reduction to a characterization of vertex-edge visibility graphs given by O'Rourke and Streinu

Facets for Art Gallery Problems

The Art Gallery Problem (AGP) asks for placing a minimum number of stationary guards in a polygonal region P, such that all points in P are guarded. The problem is known to be NP-hard, and its inherent continuous structure (with both the set of points that need to be guarded and the set of points that can be used for guarding being uncountably infinite) makes it difficult to apply a straightforward formulation as an Integer Linear Program. We use an iterative primal-dual relaxation approach for solving AGP instances to optimality. At each stage, a pair of LP relaxations for a finite candidate subset of primal covering and dual packing constraints and variables is considered; these correspond to possible guard positions and points that are to be guarded. Particularly useful are cutting planes for eliminating fractional solutions. We identify two classes of facets, based on Edge Cover and Set Cover (SC) inequalities. Solving the separation problem for the latter is NP-complete, but exploiting the underlying geometric structure, we show that large subclasses of fractional SC solutions cannot occur for the AGP. This allows us to separate the relevant subset of facets in polynomial time. We also characterize all facets for finite AGP relaxations with coefficients in {0, 1, 2}. Finally, we demonstrate the practical usefulness of our approach. Our cutting plane technique yields a significant improvement in terms of speed and solution quality due to considerably reduced integrality gaps as compared to the approach by Kr\"oller et al.Comment: 29 pages, 18 figures, 1 tabl

Simulations of slow positron production using a low energy electron accelerator

Monte Carlo simulations of slow positron production via energetic electron interaction with a solid target have been performed. The aim of the simulations was to determine the expected slow positron beam intensity from a low energy, high current electron accelerator. By simulating (a) the fast positron production from a tantalum electron-positron converter and (b) the positron depth deposition profile in a tungsten moderator, the slow positron production probability per incident electron was estimated. Normalizing the calculated result to the measured slow positron yield at the present AIST LINAC the expected slow positron yield as a function of energy was determined. For an electron beam energy of 5 MeV (10 MeV) and current 240 $\mu$A (30 $\mu$A) production of a slow positron beam of intensity 5 $\times$ 10$^{6}$ s$^{-1}$ is predicted. The simulation also calculates the average energy deposited in the converter per electron, allowing an estimate of the beam heating at a given electron energy and current. For low energy, high-current operation the maximum obtainable positron beam intensity will be limited by this beam heating.Comment: 11 pages, 15 figures, submitted to Review of Scientific Instrument

Medication Adherence in Renal Transplant Recipients: A Latent Variable Model of Psychosocial and Neurocognitive Predictors

Objective Estimates indicate that 20–70% of renal transplant recipients are medication non-adherent, significantly increasing the risk of organ rejection. Medication adherence is negatively impacted by lower everyday problem solving ability, and associations between depressive symptoms, self-efficacy, and adherence are reported in renal transplant recipients. Nonetheless, to date, these associations have not been examined concurrently. Given the relationship between non-adherence and organ rejection, it is critical to gain a better understanding of the predictors of adherence in renal transplant recipients. To this end, we modeled relationships among cognitive abilities, depressive symptoms, self-efficacy, and adherence in this group. Methods Participants (N = 211) underwent renal transplant at least one year prior to participation. Adherence was measured via self-report, medication possession ratio, and immunosuppressant blood-level. Traditionally-measured neurocognitive and everyday problem-solving abilities were assessed. Depressive symptoms were measured via self-report, as were general and medication adherence related self-efficacy. Structural equation modeling was used to assess the fit of the model to available data. ResultsEveryday problem solving and self-efficacy had direct positive associations with adherence. Depressive symptoms were negatively associated with self-efficacy, but not adherence. Traditionally-measured neurocognitive abilities were positively associated with self-efficacy, and negatively associated with depressive symptoms. Conclusions We present a comprehensive investigation of relationships between cognitive and psychosocial factors and adherence in medically stable renal transplant recipients. Findings confirm the importance of everyday problem solving and self-efficacy in predicting adherence and suggest that influences of depressive symptoms and neurocognitive abilities are indirect. Findings have important implications for future development of interventions to improve medication adherence in renal transplant recipients

A Novel Approach for Ellipsoidal Outer-Approximation of the Intersection Region of Ellipses in the Plane

In this paper, a novel technique for tight outer-approximation of the intersection region of a finite number of ellipses in 2-dimensional (2D) space is proposed. First, the vertices of a tight polygon that contains the convex intersection of the ellipses are found in an efficient manner. To do so, the intersection points of the ellipses that fall on the boundary of the intersection region are determined, and a set of points is generated on the elliptic arcs connecting every two neighbouring intersection points. By finding the tangent lines to the ellipses at the extended set of points, a set of half-planes is obtained, whose intersection forms a polygon. To find the polygon more efficiently, the points are given an order and the intersection of the half-planes corresponding to every two neighbouring points is calculated. If the polygon is convex and bounded, these calculated points together with the initially obtained intersection points will form its vertices. If the polygon is non-convex or unbounded, we can detect this situation and then generate additional discrete points only on the elliptical arc segment causing the issue, and restart the algorithm to obtain a bounded and convex polygon. Finally, the smallest area ellipse that contains the vertices of the polygon is obtained by solving a convex optimization problem. Through numerical experiments, it is illustrated that the proposed technique returns a tighter outer-approximation of the intersection of multiple ellipses, compared to conventional techniques, with only slightly higher computational cost

Effects of salt water on the ballistic protective performance of bullet-resistant body armour

Bullet-resistant body armour is used by law enforcement agencies and military personnel worldwide, often in inclement weather. Some fibre types used in body armour perform poorly when wet, resulting in a reduced level of protection; this is why most body armour protective elements are water-repellent treated and/or protected by a water-resistant cover. Some of the users operate in the maritime environment. The effect of salt water on body armour performance has not been previously reported. In this work the effect of soaking body armour in salt water and exposing body armour for up to 10 soaking and drying cycles in salt water was investigated. The effectiveness of the water-resistant cover was investigated by considering three cover conditions: (i) intact, (ii) cut and (iii) removed. Wet armour was heavier and provided significantly less protection from 9 mm Luger FMJ ammunition when compared to not-exposed armour irrespective of cover condition. A degradation in performance of armours exposed to soaking and drying cycles was noted, but this was similar across all regimes considered (one, three, five and ten cycles) and not as great as for wet armours

Engineering Art Galleries

The Art Gallery Problem is one of the most well-known problems in Computational Geometry, with a rich history in the study of algorithms, complexity, and variants. Recently there has been a surge in experimental work on the problem. In this survey, we describe this work, show the chronology of developments, and compare current algorithms, including two unpublished versions, in an exhaustive experiment. Furthermore, we show what core algorithmic ingredients have led to recent successes

Rates of convergence for empirical spectral measures: a soft approach

Understanding the limiting behavior of eigenvalues of random matrices is the central problem of random matrix theory. Classical limit results are known for many models, and there has been significant recent progress in obtaining more quantitative, non-asymptotic results. In this paper, we describe a systematic approach to bounding rates of convergence and proving tail inequalities for the empirical spectral measures of a wide variety of random matrix ensembles. We illustrate the approach by proving asymptotically almost sure rates of convergence of the empirical spectral measure in the following ensembles: Wigner matrices, Wishart matrices, Haar-distributed matrices from the compact classical groups, powers of Haar matrices, randomized sums and random compressions of Hermitian matrices, a random matrix model for the Hamiltonians of quantum spin glasses, and finally the complex Ginibre ensemble. Many of the results appeared previously and are being collected and described here as illustrations of the general method; however, some details (particularly in the Wigner and Wishart cases) are new. Our approach makes use of techniques from probability in Banach spaces, in particular concentration of measure and bounds for suprema of stochastic processes, in combination with more classical tools from matrix analysis, approximation theory, and Fourier analysis. It is highly flexible, as evidenced by the broad list of examples. It is moreover based largely on "soft" methods, and involves little hard analysis