Elections, Ideology, and Turnover in the U.S. Federal Government

A defining feature of public sector employment is the regular change in elected leadership. Yet, we know little about how elections influence public sector careers. We describe how elections alter policy outputs and disrupt the influence of civil servants over agency decisions. These changes shape the career choices of employees motivated by policy, influence, and wages. Using new Office of Personnel Management data on the careers of millions of federal employees between 1988 and 2011, we evaluate how elections influence employee turnover decisions. We find that presidential elections increase departure rates of career senior employees, particularly in agencies with divergent views relative to the new president and at the start of presidential terms. We also find suggestive evidence that vacancies in high-level positions after elections may induce lower-level executives to stay longer in hopes of advancing. We conclude with implications of our findings for public policy, presidential politics, and public management

The Cost of Perfection for Matchings in Graphs

Perfect matchings and maximum weight matchings are two fundamental combinatorial structures. We consider the ratio between the maximum weight of a perfect matching and the maximum weight of a general matching. Motivated by the computer graphics application in triangle meshes, where we seek to convert a triangulation into a quadrangulation by merging pairs of adjacent triangles, we focus mainly on bridgeless cubic graphs. First, we characterize graphs that attain the extreme ratios. Second, we present a lower bound for all bridgeless cubic graphs. Third, we present upper bounds for subclasses of bridgeless cubic graphs, most of which are shown to be tight. Additionally, we present tight bounds for the class of regular bipartite graphs

Modelagem da hidrografia em planos de manejo e critérios para definição de árvores em APP pelo Modeflora.

Novas tecnologias, sendo advindas do geoprocessamento e do sensoriamento remoto, vêm sendo desenvolvidas a fim de auxiliar no processo de delimitação das APPs e demarcação das árvores. No entanto, faltam estudos para investigar e comprovar sua eficácia. Não há registro de trabalhos, publicados no Brasil, que utilizem diferentes metodologias na definição de APPs para avaliá-las. O presente trabalho teve como objetivo propor uma metodologia precisa para o mapeamento de áreas de preservação permanente e definição de árvores protegidas e exploráveis na região de influência das APPs, comprovando a sua aplicabilidade nos PMFS.bitstream/CPAF-AC-2010/23132/1/circtec-n50.pd

Going Further with Point Pair Features

Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce novel sampling and voting schemes that significantly reduces the influence of clutter and sensor noise. Our experiments show that with our improvements, PPFs become competitive against state-of-the-art methods as it outperforms them on several objects from challenging benchmarks, at a low computational cost.Comment: Corrected post-print of manuscript accepted to the European Conference on Computer Vision (ECCV) 2016; https://link.springer.com/chapter/10.1007/978-3-319-46487-9_5

Agricultural impacts of hydrobiogeochemical cycling in the Amazon: is there any solution?

Abstract: Expansion of agriculture in the Brazilian Amazon has been driven not just by demands from traditional, rural producers, but also large agriculture and cattle producers, both of whom have put considerable pressure on remaining forests and their watersheds. Monitoring of these watersheds has been a focus of intensive study for the past 20 years and although this work has greatly increased our understanding, considerable gaps still remain in our ability to provide adequate recommendations for land management and associated public policies. In this study we present a summary of findings from these previous results. For small properties, the use of fire to prepare land for cultivation remains controversial, while in large properties, forest conversion to pasture and/or crop production has had a meaningful and adverse effect on water quality. Riparian forest conservation can make a significant difference in reducing impacts of land-use change. Secondary vegetation can also play an important role in mitigating these impacts. New types of sustainable agricultural production systems, together with incentives such as payments for ecosystem service can also contribute. Continued monitoring of these changes, together with robust sustainable development plans, can help to preserve forest while still addressing the social and economic needs of Amazonian riverine inhabitants

Optimizing Connectivity through Network Gradients for the Restricted Boltzmann Machine

Leveraging sparse networks to connect successive layers in deep neural networks has recently been shown to provide benefits to large scale state-of-the-art models. However, network connectivity also plays a significant role on the learning performance of shallow networks, such as the classic Restricted Boltzmann Machines (RBM). Efficiently finding sparse connectivity patterns that improve the learning performance of shallow networks is a fundamental problem. While recent principled approaches explicitly include network connections as model parameters that must be optimized, they often rely on explicit penalization or have network sparsity as a hyperparameter. This work presents a method to find optimal connectivity patterns for RBMs based on the idea of network gradients (NCG): computing the gradient of every possible connection, given a specific connection pattern, and using the gradient to drive a continuous connection strength parameter that in turn is used to determine the connection pattern. Thus, learning RBM parameters and learning network connections is truly jointly performed, albeit with different learning rates, and without changes to the objective function. The method is applied to the MNIST and other datasets showing that better RBM models are found for the benchmark tasks of sample generation and input classification. Results also show that NCG is robust to network initialization, both adding and removing network connections while learning

Statistical models of mixtures with a biaxial nematic phase

We consider a simple Maier-Saupe statistical model with the inclusion of disorder degrees of freedom to mimic the phase diagram of a mixture of rod-like and disc-like molecules. A quenched distribution of shapes leads to the existence of a stable biaxial nematic phase, in qualitative agreement with experimental findings for some ternary lyotropic liquid mixtures. An annealed distribution, however, which is more adequate to liquid mixtures, precludes the stability of this biaxial phase. We then use a two-temperature formalism, and assume a separation of relaxation times, to show that a partial degree of annealing is already sufficient to stabilize a biaxial nematic structure.Comment: 11 pages, 2 figure

CO2-driven cation leaching after tropical forest clearing.

The objective of this study was to investigate the role of dissolved CO2 (H2CO3*) as a mechanism of cation removal from surface soils under secondary land uses in the tropics. Soil leachate columns were prepared with 0?10 cm soils from mature and secondary forest, and managed pastures, and extracted with H2CO3* from deionized water equilibrated with 0%, 0.5%, 1%, and 10% CO2 (g). Extraction of soil cations slowed over time following an exponential form for the cumulative data. The rate of cation concentration decline varied as a function of CO2 concentration with the 10% solution resulting in a greater percent decline with extraction volume. Potassium removal from the exchange sites of all soils and for all solutions was nearly complete ranging from 85% to 97% while removals of Mg (31% to 71%) and Ca (12% to 42%) were lower. The asymptotic patterns of cation loss observed in this study suggest that H2CO3* acid-driven losses of cations may become self-limiting over time. Other stronger acids from atmospheric deposition or organic sources may serve to perpetuate cation removal, and re-forestation on these cleared lands would certainly re-distribute cations from soils to vegetation