The impact of columnar file formats on SQL‐on‐hadoop engine performance: A study on ORC and Parquet

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Agriculture is the main driver of deforestation in Tanzania

Reducing deforestation can generate multiple economic, social and ecological benefits by safeguarding the climate and other ecosystem services provided by forests. Understanding the relative contribution of different drivers of deforestation is needed to guide policies seeking to maintain natural forest cover. We assessed 119 randomly selected plots from areas deforested between 2010 and 2017, in Tanzania. Through ground surveys and stakeholder interviews we assessed the proximate deforestation drivers at each point. Crop cultivation was the most commonly observed driver occurring in 89% of plots, compared to livestock grazing (69%) and charcoal (35%). There was evidence of fire in 77% of plots. Most deforestation events involved multiple drivers, with 83% of plots showing signs of two or more drivers. Stakeholder interviews identified agriculture as the primary deforestation driver in 81% of plots, substantially more than charcoal production (12%), timber harvesting (1%) and livestock (1%). Policy-makers in Tanzania have sought to reduce deforestation by reducing demand for charcoal. However, our work demonstrates that agriculture, not charcoal, is the main driver of deforestation in Tanzania. Beyond protected areas, there is no clear policy limiting the conversion of forests to agricultural land. Reducing deforestation in Tanzania requires greater inter-sectoral coordination between the agriculture, livestock, land, energy and forest sectors

On the unification of dwarf and giant elliptical galaxies

The near orthogonal distributions of dwarf elliptical (dE) and giant elliptical (E) galaxies in the mu_e-Mag and mu_e-log(R_e) diagrams have been interpreted as evidence for two distinct galaxy formation processes. However, continuous, linear relationships across the alleged dE/E boundary at M_B = -18 mag - such as those between central surface brightness (mu_0) and (i) galaxy magnitude and (ii) light-profile shape (n) - suggest a similar, governing formation mechanism. Here we explain how these latter two linear trends necessitate a different behavior for dE and E galaxies, exactly as observed, in diagrams involving mu_e (and also _e). A natural consequence is that the distribution of dEs and Es in Fundamental Plane type analyses that use the associated intensity I_e, or _e, are expected to appear different. Together with other linear trends across the alleged dE/E boundary, such as those between luminosity and color, metallicity, and velocity dispersion, it appears that the dEs form a continuous extension to the E galaxies. The presence of partially depleted cores in luminous (M_B < -20.5 mag) Es does however signify the action of a different physical process at the centers (< ~300 pc) of these galaxies.Comment: 5 pages from the proceedings of the 2004 conference "Penetrating bars through masks of cosmic dust: the Hubble tuning fork strikes a new note". Edited by D. L. Block, I. Puerari, K. C. Freeman, R. Groess, and E. K. Bloc

CAR-Net: Clairvoyant Attentive Recurrent Network

We present an interpretable framework for path prediction that leverages dependencies between agents' behaviors and their spatial navigation environment. We exploit two sources of information: the past motion trajectory of the agent of interest and a wide top-view image of the navigation scene. We propose a Clairvoyant Attentive Recurrent Network (CAR-Net) that learns where to look in a large image of the scene when solving the path prediction task. Our method can attend to any area, or combination of areas, within the raw image (e.g., road intersections) when predicting the trajectory of the agent. This allows us to visualize fine-grained semantic elements of navigation scenes that influence the prediction of trajectories. To study the impact of space on agents' trajectories, we build a new dataset made of top-view images of hundreds of scenes (Formula One racing tracks) where agents' behaviors are heavily influenced by known areas in the images (e.g., upcoming turns). CAR-Net successfully attends to these salient regions. Additionally, CAR-Net reaches state-of-the-art accuracy on the standard trajectory forecasting benchmark, Stanford Drone Dataset (SDD). Finally, we show CAR-Net's ability to generalize to unseen scenes.Comment: The 2nd and 3rd authors contributed equall

Shifting Attention From Theory to Practice in Philosophy of Biology

Traditional approaches in philosophy of biology focus attention on biological concepts, explanations, and theories, on evidential support and inter-theoretical relations. Newer approaches shift attention from concepts to conceptual practices, from theories to practices of theorizing, and from theoretical reduction to reductive retooling. In this article, I describe the shift from theory-focused to practice-centered philosophy of science and explain how it is leading philosophers to abandon fundamentalist assumptions associated with traditional approaches in philosophy of science and to embrace scientific pluralism. This article comes in three parts, each illustrating the shift from theory-focused to practice-centered epistemology. The first illustration shows how shifting philosophical attention to conceptual practice reveals how molecular biologists succeed in identifying coherent causal strands within systems of bewildering complexity. The second illustration suggests that analyzing how a multiplicity of alternative models function in practice provides an illuminating approach for understanding the nature of theoretical knowledge in evolutionary biology. The third illustration demonstrates how framing reductionism in terms of the reductive retooling of practice offers an informative perspective for understanding why putting DNA at the center of biological research has been incredibly productive throughout much of biology. Each illustration begins by describing how traditional theory-focused philosophical approaches are laden with fundamentalist assumptions and then proceeds to show that shifting attention to practice undermines these assumptions and motivates a philosophy of scientific pluralism

Quantum enhanced positioning and clock synchronization

A wide variety of positioning and ranging procedures are based on repeatedly sending electromagnetic pulses through space and measuring their time of arrival. This paper shows that quantum entanglement and squeezing can be employed to overcome the classical power/bandwidth limits on these procedures, enhancing their accuracy. Frequency entangled pulses could be used to construct quantum positioning systems (QPS), to perform clock synchronization, or to do ranging (quantum radar): all of these techniques exhibit a similar enhancement compared with analogous protocols that use classical light. Quantum entanglement and squeezing have been exploited in the context of interferometry, frequency measurements, lithography, and algorithms. Here, the problem of positioning a party (say Alice) with respect to a fixed array of reference points will be analyzed.Comment: 4 pages, 2 figures. Accepted for publication by Natur

Extracellular electrical signals in a neuron-surface junction: model of heterogeneous membrane conductivity

Signals recorded from neurons with extracellular planar sensors have a wide range of waveforms and amplitudes. This variety is a result of different physical conditions affecting the ion currents through a cellular membrane. The transmembrane currents are often considered by macroscopic membrane models as essentially a homogeneous process. However, this assumption is doubtful, since ions move through ion channels, which are scattered within the membrane. Accounting for this fact, the present work proposes a theoretical model of heterogeneous membrane conductivity. The model is based on the hypothesis that both potential and charge are distributed inhomogeneously on the membrane surface, concentrated near channel pores, as the direct consequence of the inhomogeneous transmembrane current. A system of continuity equations having non-stationary and quasi-stationary forms expresses this fact mathematically. The present work performs mathematical analysis of the proposed equations, following by the synthesis of the equivalent electric element of a heterogeneous membrane current. This element is further used to construct a model of the cell-surface electric junction in a form of the equivalent electrical circuit. After that a study of how the heterogeneous membrane conductivity affects parameters of the extracellular electrical signal is performed. As the result it was found that variation of the passive characteristics of the cell-surface junction, conductivity of the cleft and the cleft height, could lead to different shapes of the extracellular signals

A particle swarm optimization based memetic algorithm for dynamic optimization problems

Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic algorithm is robust and adaptable in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 70431003 and Grant No. 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, the National Support Plan of China under Grant No. 2006BAH02A09 and the Ministry of Education, science, and Technology in Korea through the Second-Phase of Brain Korea 21 Project in 2009, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and the Hong Kong Polytechnic University Research Grants under Grant G-YH60

Mathematics difficulties in extremely preterm children : evidence of a specific deficit in basic mathematics processing

Background: Extremely preterm (EP, <26 wk gestation) children have been observed to have poor academic achievement in comparison to their term-born peers, especially in mathematics. This study investigated potential underlying causes of this difficulty. Methods: A total of 219 EP participants were compared with 153 term-born control children at 11 y of age. All children were assessed by a psychologist on a battery of standardized cognitive tests and a number estimation test assessing children’s numerical representations. Results: EP children underperformed in all tests in comparison with the term controls (the majority of Ps < 0.001). Different underlying relationships between performance on the number estimation test and mathematical achievement were found in EP as compared with control children. That is, even after controlling for cognitive ability, a relationship between number representations and mathematical performance persisted for EP children only (EP: r = 0.346, n = 186, P < 0.001; control: r = 0.095, n = 146, P = 0.256). Conclusion: Interventions for EP children may target improving children’s numerical representations in order to subsequently remediate their mathematical skills

Nuclear receptors in vascular biology

Nuclear receptors sense a wide range of steroids and hormones (estrogens, progesterone, androgens, glucocorticoid, and mineralocorticoid), vitamins (A and D), lipid metabolites, carbohydrates, and xenobiotics. In response to these diverse but critically important mediators, nuclear receptors regulate the homeostatic control of lipids, carbohydrate, cholesterol, and xenobiotic drug metabolism, inflammation, cell differentiation and development, including vascular development. The nuclear receptor family is one of the most important groups of signaling molecules in the body and as such represent some of the most important established and emerging clinical and therapeutic targets. This review will highlight some of the recent trends in nuclear receptor biology related to vascular biology