A MapReduce Algorithm for Polygon Retrieval in Geospatial Analysis

The proliferation of data acquisition devices like 3D laser scanners had led to the burst of large-scale spatial terrain data which imposes many challenges to spatial data analysis and computation. With the advent of several emerging cloud technologies, a natural and cost-effective approach to managing such large-scale data is to store and process such datasets in a publicly hosted cloud service using modern distributed computing paradigms such as MapReduce. For several key spatial data analysis and computation problems, polygon retrieval is a fundamental operation which is often computed under real-time constraints. However, existing sequential algorithms fail to meet this demand effectively given that terrain data in recent years have witnessed an unprecedented growth in both volume and rate. In this work, we present a MapReduce-based parallel polygon retrieval algorithm which aims at minimizing the IO and CPU loads of the map and reduce tasks during spatial data processing. Our proposed algorithm first hierarchically indexes the spatial terrain data using a quad-tree index, with the help of which, a significant amount of data is filtered out in the pre-processing stage based on the query object. In addition, a prefix tree based on the quad-tree index is built to query the relationship between the terrain data and query area in real time which leads to significant savings in both I/O load and CPU time. The performance of the proposed techniques is evaluated in a Hadoop cluster and the results demonstrate that the proposed techniques are scalable and lead to more than 35% reduction in execution time of the polygon retrieval operation over existing distributed algorithms

Migration patterns and winter population dynamics of rice planthoppers in Indochina: New perspectives from field surveys and atmospheric trajectories

This is the author accepted manuscript. The final version is available from Elsevier Masson via the DOI in this record.Rice planthoppers (RPH) are the most serious insect pests of rice production in East Asia, frequently out-breaking in China, Korea and Japan each summer. They are unable to overwinter in temperate East Asia, and summer populations arise anew each year via northward spring migration from south-east Asia. The annual migration cycle is generally believed to be a closed loop with mass returns to south-east Asia in the autumn, but this leg of the journey and the overwintering dynamics are much less studied than the spring immigrations. Previous studies have indicated that the north-central Vietnam (NCV) region is a key location for both the spring colonisation of China and for receiving return migrants from southern China each autumn. However, NCV experiences a three-month rice-free fallow period during mid-winter, and so it cannot be the principal over-wintering region for RPH populations. In this study, the continental-scale migration patterns of RPH in East Asia were explored using data from light trap catches, field surveys and atmospheric trajectory simulations. Our results confirmed that large numbers of return migrants arrive in NCV from southern China each autumn, but that they are unable to survive there over winter. The NCV region is recolonised in the early-spring (mid-February to mid-March) of each year by migrants from winter rice-growing regions in north-east Thailand, southern Laos and south-central coastal Vietnam, which are transported on favourable high-altitude synoptic winds. The following generation initiates the colonisation of East Asia from a large source population in NCV. Our results provide a new perspective on RPH migration patterns and over-wintering dynamics in East Asia, which is governed by crop production, environmental conditions and synoptic wind patterns at a continental scale.National Natural Science Foundation of China (NSFC)Natural Science Foundation of Jiangsu ProvinceBiotechnology and Biological Sciences Research Council (BBSRC)Science and Technology Facilities Council (STFC

Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices

The rapid development in representation learning techniques such as deep neural networks and the availability of large-scale, well-annotated medical imaging datasets have to a rapid increase in the use of supervised machine learning in the 3D medical image analysis and diagnosis. In particular, deep convolutional neural networks (D-CNNs) have been key players and were adopted by the medical imaging community to assist clinicians and medical experts in disease diagnosis and treatment. However, training and inferencing deep neural networks such as D-CNN on high-resolution 3D volumes of Computed Tomography (CT) scans for diagnostic tasks pose formidable computational challenges. This challenge raises the need of developing deep learning-based approaches that are robust in learning representations in 2D images, instead 3D scans. In this work, we propose for the first time a new strategy to train \emph{slice-level} classifiers on CT scans based on the descriptors of the adjacent slices along the axis. In particular, each of which is extracted through a convolutional neural network (CNN). This method is applicable to CT datasets with per-slice labels such as the RSNA Intracranial Hemorrhage (ICH) dataset, which aims to predict the presence of ICH and classify it into 5 different sub-types. We obtain a single model in the top 4% best-performing solutions of the RSNA ICH challenge, where model ensembles are allowed. Experiments also show that the proposed method significantly outperforms the baseline model on CQ500. The proposed method is general and can be applied to other 3D medical diagnosis tasks such as MRI imaging. To encourage new advances in the field, we will make our codes and pre-trained model available upon acceptance of the paper.Comment: Accepted for presentation at the 22nd IEEE Statistical Signal Processing (SSP) worksho

Pathogenic effect of interleukin-17A in induction of Sjogren's syndrome-like disease using adenovirus-mediated gene transfer

Introduction Sjögren's syndrome (SS) involves a chronic, progressive inflammation primarily of the salivary and lacrimal glands leading to decreased levels of saliva and tears resulting in dry mouth and dry eye diseases. Seminal findings regarding TH17 cell populations that secrete predominantly interleukin (IL)-17A have been shown to play an important role in an increasing number of autoimmune diseases, including SS. In the present study, we investigated the function of IL-17A on the development and onset of SS. Methods Adenovirus serotype 5 (Ad5) vectors expressing either IL-17A or LacZ were infused via retrograde cannulation into the salivary glands of C57BL/6J mice between 6 and 8 weeks of age or between 15 and 17 weeks of age. The mice were characterized for SS phenotypes. Results Disease profiling indicated that SS-non-susceptible C57BL/6J mice whose salivary glands received the Ad5-IL17A vector developed a SS-like disease profile, including the appearance of lymphocytic foci, increased cytokine levels, changes in antinuclear antibody profiles, and temporal loss of saliva flow. Conclusions Induction of SS pathology by IL-17A in SS-non-susceptible mice strongly suggests that IL-17A is an important inflammatory cytokine in salivary gland dysfunction. Thus, localized anti-IL17 therapy may be effective in preventing glandular dysfunction.National Institute of Dental and Craniofacial Research (U.S.) (PHS Grants K99DE018958)National Institute of Allergy and Infectious Diseases (U.S.) (R21AI081952)Sjogren's Syndrome FoundationUniversity of Florida. Center for Orphaned Autoimmune DisordersNational Institute of Dental and Craniofacial Research (U.S.) (Intramural research grant)National Institutes of Health (U.S.

Exact dynamical structure factor of the degenerate Haldane-Shastry model

The dynamical structure factor $S(q,\omega)$ of the K-component (K = 2,3,4) spin chain with the 1/r^2 exchange is derived exactly at zero temperature for arbitrary size of the system. The result is interpreted in terms of a free quasi-particle picture which is generalization of the spinon picture in the SU(2) case; the excited states consist of K quasi-particles each of which is characterized by a set of K-1 quantum numbers. Divergent singularities of $S(q,\omega)$ at the spectral edges are derived analytically. The analytic result is checked numerically for finite systems.Comment: 4 pages, 1 figure, accepted for publication in Phys. Rev. Let

Effect of hemicellulose liquid phase on the enzymatic hydrolysis of autohydrolyzed Eucalyptus globulus wood

In this work, Eucalyptus globulus wood was pretreated under non-isothermal autohydrolysis process at 210, 220, and 230 °C, obtaining a pretreated solid with high cellulose content and a hemicellulosic liquid phase (HLP) containing mainly xylose, acetic acid, furfural, xylooligosaccharides, and phenolic compounds. The maximum concentration of xylooligosaccharides (8.97 g/L) and phenolic compounds (2.66 g/L) was obtained at 210 and 230 °C, respectively. To evaluate the effect of HLP addition on the enzymatic hydrolysis using unwashed pretreated solid as substrate, different proportions of HLP were studied. Also, in order to use the whole slurry on enzymatic hydrolysis, the supplementation of xylanases was evaluated. Glucose concentration of 107.49 g/L (corresponding to 74.65 % of conversion) was obtained using pretreated solid at 220 °C liquid/solid ratio (LSR) of 4 g/g and enzyme solid ratio (ESR) of 25 FPU/gwithout the addition of HLP. Thus, it was shown that the unwashed pretreated solids are susceptible to enzymatic hydrolysis contributing to reduce operational cost (water consumption). Additionally, the influence of the inhibitory compounds in the HLP was shown to affect the enzymatic hydrolysis. Results indicated that 82.52 g/L of glucose (59.37 % of conversion) was obtained, using 100 % of HLP at LSR of 4 g/g and ESR of 16 FPU/g at 210 °C of pretreated solid. However, a positive effect was shown on the enzymatic hydrolysis when the xylanases were added using 100 % of HLP, increasing to 35 and 27 % in the glucose production with respect to whole slurry without addition of xylanases.The authors A. Romani and F. B. Pereira thank to the Portuguese Foundation for Science and Technology (FCT, Portugal) for their fellowships (grant number, SFRH/BPD/77995/2011 and SFRH/BD/64776/2009, respectively)

Mach's Principle and the Origin of Inertia

The current status of Mach's principle is discussed within the context of general relativity. The inertial properties of a particle are determined by its mass and spin, since these characterize the irreducible unitary representations of the inhomogeneous Lorentz group. The origin of the inertia of mass and intrinsic spin are discussed and the inertia of intrinsic spin is studied via the coupling of intrinsic spin with rotation. The implications of spin-rotation coupling and the possibility of history dependence and nonlocality in relativistic physics are briefly mentioned.Comment: 14 pages. Dedicated to Carl Brans in honor of his 80th birthday. To appear in the Brans Festschrift; v2: typo corrected, published in: At the Frontier of Spacetime, edited by T. Asselmeyer-Maluga (Springer, 2016), Chapter 10, pp. 177-18