Innovation, R&D Investment and Productivity in Chile

This paper uses two sources of information and different methodologies to analyze the causal effect of product and process innovation on productivity in the Chilean manufacturing industry during the past decade. In general, the evidence suggests there is not a contemporaneous effect of product innovation on productivity, but there is a positive effect of process innovation. This notsignificant effect of product innovation contrasts with evidence of studies for other countries. However, the results show the presence of lagged effects product innovation on productivity two years after innovation. Compared with the case of developed countries, this evidence might be consistent with a very slow process of “learning by doing” on the part of Chilean firms with regard to mastering new technologies. These slow and frequently uncertain gains in productivity could help to explain the low levels of investment in research and development (R&D) activities by Chilean firms.Productivity, Innovation, Investment, Research and development, Chile

Object Distribution Networks for World-wide Document Circulation

This paper presents an Object Distribution System (ODS), a distributed system inspired by the ultra-large scale distribution models used in everyday life (e.g. food or newspapers distribution chains). Beyond traditional mechanisms of approaching information to readers (e.g. caching and mirroring), this system enables the publication, classification and subscription to volumes of objects (e.g. documents, events). Authors submit their contents to publication agents. Classification authorities provide classification schemes to classify objects. Readers subscribe to topics or authors, and retrieve contents from their local delivery agent (like a kiosk or library, with local copies of objects). Object distribution is an independent process where objects circulate asynchronously among distribution agents. ODS is designed to perform specially well in an increasingly populated, widespread and complex Internet jungle, using weak consistency replication by object distribution, asynchronous replication, and local access to objects by clients. ODS is based on two independent virtual networks, one dedicated to the distribution (replication) of objects and the other to calculate optimised distribution chains to be applied by the first network

Performance evaluation over HW/SW co-design SoC memory transfers for a CNN accelerator

Many FPGAs vendors have recently included embedded processors in their devices, like Xilinx with ARM-Cortex A cores, together with programmable logic cells. These devices are known as Programmable System on Chip (PSoC). Their ARM cores (embedded in the processing system or PS) communicates with the programmable logic cells (PL) using ARM-standard AXI buses. In this paper we analyses the performance of exhaustive data transfers between PS and PL for a Xilinx Zynq FPGA in a co-design real scenario for Convolutional Neural Networks (CNN) accelerator, which processes, in dedicated hardware, a stream of visual information from a neuromorphic visual sensor for classification. In the PS side, a Linux operating system is running, which recollects visual events from the neuromorphic sensor into a normalized frame, and then it transfers these frames to the accelerator of multi-layered CNNs, and read results, using an AXI-DMA bus in a per-layer way. As these kind of accelerators try to process information as quick as possible, data bandwidth becomes critical and maintaining a good balanced data throughput rate requires some considerations. We present and evaluate several data partitioning techniques to improve the balance between RX and TX transfer and two different ways of transfers management: through a polling routine at the userlevel of the OS, and through a dedicated interrupt-based kernellevel driver. We demonstrate that for longer enough packets, the kernel-level driver solution gets better timing in computing a CNN classification example. Main advantage of using kernel-level driver is to have safer solutions and to have tasks scheduling in the OS to manage other important processes for our application, like frames collection from sensors and their normalization.Ministerio de Economía y Competitividad TEC2016-77785-

SketchZooms: Deep Multi-view Descriptors for Matching Line Drawings

Finding point-wise correspondences between images is a long-standing problem in image analysis. This becomes particularly challenging for sketch images, due to the varying nature of human drawing style, projection distortions and viewport changes. In this paper, we present the first attempt to obtain a learned descriptor for dense registration in line drawings. Based on recent deep learning techniques for corresponding photographs, we designed descriptors to locally match image pairs where the object of interest belongs to the same semantic category, yet still differ drastically in shape, form, and projection angle. To this end, we have specifically crafted a data set of synthetic sketches using non-photorealistic rendering over a large collection of part-based registered 3D models. After training, a neural network generates descriptors for every pixel in an input image, which are shown togeneralize correctly in unseen sketches hand-drawn by humans. We evaluate our method against a baseline of correspondences data collected from expert designers, in addition to comparisons with other descriptors that have been proven effective in sketches. Code, data and further resources will be publicly released by the time of publication.Fil: Navarro, Jose Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentina. Universidad Nacional de la Patagonia "San Juan Bosco". Facultad de Ingeniería - Sede Puerto Madryn. Departamento de Informática; ArgentinaFil: Orlando, José Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; ArgentinaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Iarussi, Emmanuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentin

An Automated tool to detect variable sources in the Vista Variables in the Vía Láctea Survey. The VVV Variables (V^4) catalog of tiles d001 and d002

27 pages, 19 figuresTime-varying phenomena are one of the most substantial sources of astrophysical information, and their study has led to many fundamental discoveries in modern astronomy. We have developed an automated tool to search for and analyze variable sources in the near-infrared K s band using the data from the VISTA Variables in the Vía Láctea (VVV) ESO Public Large Survey. This process relies on the characterization of variable sources using different variability indices calculated from time series generated with point-spread function (PSF) photometry of sources under analysis. In particular, we used two main indices, the total amplitude and the eta index η, to identify variable sources. Once the variable objects are identified, periods are determined with generalized Lomb-Scargle periodograms and the information potential metric. Variability classes are assigned according to a compromise between comparisons with VVV templates and the period of the variability. The automated tool is applied on VVV tiles d001 and d002 and led to the discovery of 200 variable sources. We detected 70 irregular variable sources and 130 periodic ones. In addition, nine open-cluster candidates projected in the region are analyzed, and the infrared variable candidates found around these clusters are further scrutinized by cross-matching their locations against emission star candidates from VPHAS+ survey H α color cuts.Peer reviewedFinal Accepted Versio

The acetyl xylan esterase II gene from Penicillium purpurogenum is differentially expressed in several carbon sources, and tightly regulated by pH

http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602004000100011&lng=es&nrm=isoThe expression of the acetyl xylan esterase II (axeII) gene from Penicillium purpurogenum is repressed by glucose and induced by xylan, as well as to a small degree by xylose and xylitol. This gene is expressed at neutral pH, but not under alkaline or acidic conditions, in agreement with previous findings for other xylanolytic genes of this organism. This is the first report showing pH regulation of an axe gene

Subjective symptoms related to GSM radiation from mobile phone base stations : a cross-sectional study

Objectives: We performed a reanalysis of the data from Navarro et al., 2003, in which health symptoms related to microwave exposure from mobile phone base stations (BS) were explored, including data obtained in a retrospective inquiry about fear of exposure from BS. Design: Cross-sectional study. Setting: La Ñora (Murcia), Spain. Participants: Participants with known illness in 2003 were subsequently disregarded: 88 participants instead of 101 (in 2003) were analysed. Since weather circumstances can influence exposure, we restricted data to measurements made under similar weather conditions. Outcomes and methods: A statistical method indifferent to the assumption of normality was employed: namely, binary logistic regression for modelling a binary response (e.g. suffering fatigue (1) or not (0)), and so exposure was introduced as a predictor variable. This analysis was carried out on a regular basis and bootstrapping [95% percentile method] was used to provide more accurate confidence intervals. Main outcome measures Results: The symptoms most related to exposure were: lack of appetite [odds ratio (OR)] = 1.58, 95% confidence interval (95%CI) = 1.23-2.03; lack of concentration [OR = 1.54, 95% CI = 1.25- 1.89]; irritability [OR = 1.51, 95% CI = 1.23-1.85]; and trouble sleeping [OR = 1.49, 95% CI = 1.20-1.84]. Changes in -2 log likelihood showed similar results. Concerns about the BS were strongly related with trouble sleeping [OR = 3.12, 95% CI = 1.10-8.86]. The exposure variable remained statistically significant in the multivariate analysis. The bootstrapped values were similar to the asymptotic confidence intervals. Conclusion: This study confirms our preliminary results. We observed that the incidence of most of the symptoms was related to exposure levels ¿ independently of the demographic variables and some possible risk factors. Concerns about adverse effects from exposure, despite being strongly related with sleep disturbances, do not influence the direct association between exposure and sleep