An Emulator Toolbox to Approximate Radiative Transfer Models with Statistical Learning

Physically-based radiative transfer models (RTMs) help in understanding the processes occurring on the Earth’s surface and their interactions with vegetation and atmosphere. When it comes to studying vegetation properties, RTMs allows us to study light interception by plant canopies and are used in the retrieval of biophysical variables through model inversion. However, advanced RTMs can take a long computational time, which makes them unfeasible in many real applications. To overcome this problem, it has been proposed to substitute RTMs through so-called emulators. Emulators are statistical models that approximate the functioning of RTMs. Emulators are advantageous in real practice because of the computational efficiency and excellent accuracy and flexibility for extrapolation. We hereby present an “Emulator toolbox” that enables analysing multi-output machine learning regression algorithms (MO-MLRAs) on their ability to approximate an RTM. The toolbox is included in the free-access ARTMO’s MATLAB suite for parameter retrieval and model inversion and currently contains both linear and non-linear MO-MLRAs, namely partial least squares regression (PLSR), kernel ridge regression (KRR) and neural networks (NN). These MO-MLRAs have been evaluated on their precision and speed to approximate the soil vegetation atmosphere transfer model SCOPE (Soil Canopy Observation, Photochemistry and Energy balance). SCOPE generates, amongst others, sun-induced chlorophyll fluorescence as the output signal. KRR and NN were evaluated as capable of reconstructing fluorescence spectra with great precision. Relative errors fell below 0.5% when trained with 500 or more samples using cross-validation and principal component analysis to alleviate the underdetermination problem. Moreover, NN reconstructed fluorescence spectra about 50-times faster and KRR about 800-times faster than SCOPE. The Emulator toolbox is foreseen to open new opportunities in the use of advanced RTMs, in which both consistent physical assumptions and data-driven machine learning algorithms live together

Crane collision modelling using a neural network approach

The objective of the present work is to find a Collision Detection algorithm to be used in the Virtual Reality crane simulator (UVSim®), developed by the Robotics Institute of the University of Valencia for the Port of Valencia. The method is applicable to box-shaped objects and is based on the relationship between the colliding object positions and their impact points. The tool chosen to solve the problem is a neural network, the multilayer perceptron, which adapts to the characteristics of the problem, namely, non-linearity, a large amount of data, and no a priori knowledge. The results achieved by the neural network are very satisfactory for the case of box-shaped objects. Furthermore, the computational burden is independent from the object positions and how the surfaces are modelled; hence, it is suitable for the real-time requirements of the application and outperforms the computational burden of other classical methods. The model proposed is currently being used and validated in the UVSim Gantry Crane simulator

Novel Fast Catadioptric Objective with Wide Field of View

Using the Simultaneous Multiple Surface method in 2D (SMS2D), we present a fast catadioptric objective with a wide field of view (125°×96°designed for a microbolometer detector with 640×480 pixels and 25 microns pixel pitc

Spread of ST348 Klebsiella pneumoniae producing NDM-1 in a peruvian hospital

The aim of this study was to characterize carbapenem-resistant Klebsiella pneumoniae (CR-Kp) isolates recovered from adults and children with severe bacteremia in a Peruvian Hospital in June 2018. Antimicrobial susceptibility was determined by disc/gradient diffusion and broth microdilution when necessary. Antibiotic resistance mechanisms were evaluated by PCR and DNA sequencing. Clonal relatedness was assessed using pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). Plasmid typing was performed with a PCR-based method. Thirty CR-Kp isolates were recovered in June 2018. All isolates were non-susceptible to all -lactams, ciprofloxacin, gentamicin and trimethoprim-sulfamethoxazole, while mostly remaining susceptible to colistin, tigecycline, levofloxacin and amikacin. All isolates carried the blaNDM-1 gene and were extended spectrum -lactamase (ESBL) producers. PFGE showed four different pulsotypes although all isolates but two belonged to the ST348 sequence type, previously reported in Portugal. blaNDM-1 was located in an IncFIB-M conjugative plasmid. To our knowledge, this is the first report of an New Delhi metallo- -lactamase (NDM)-producing K. pneumoniae recovered from both children and adults in Lima, Peru, as well as the first time that the outbreak strain ST348 is reported in Peru and is associated with NDM. Studies providing epidemiological and molecular data on CR-Kp in Peru are essential to monitor their dissemination and prevent further spread

NEXT-100 Technical Design Report (TDR). Executive Summary

In this Technical Design Report (TDR) we describe the NEXT-100 detector that will search for neutrinoless double beta decay (bbonu) in Xe-136 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. The document formalizes the design presented in our Conceptual Design Report (CDR): an electroluminescence time projection chamber, with separate readout planes for calorimetry and tracking, located, respectively, behind cathode and anode. The detector is designed to hold a maximum of about 150 kg of xenon at 15 bar, or 100 kg at 10 bar. This option builds in the capability to increase the total isotope mass by 50% while keeping the operating pressure at a manageable level. The readout plane performing the energy measurement is composed of Hamamatsu R11410-10 photomultipliers, specially designed for operation in low-background, xenon-based detectors. Each individual PMT will be isolated from the gas by an individual, pressure resistant enclosure and will be coupled to the sensitive volume through a sapphire window. The tracking plane consists in an array of Hamamatsu S10362-11-050P MPPCs used as tracking pixels. They will be arranged in square boards holding 64 sensors (8 times8) with a 1-cm pitch. The inner walls of the TPC, the sapphire windows and the boards holding the MPPCs will be coated with tetraphenyl butadiene (TPB), a wavelength shifter, to improve the light collection.Comment: 32 pages, 22 figures, 5 table

Radon and material radiopurity assessment for the NEXT double beta decay experiment

The Neutrino Experiment with a Xenon TPC (NEXT), intended to investigate the neutrinoless double beta decay using a high-pressure xenon gas TPC filled with Xe enriched in 136Xe at the Canfranc Underground Laboratory in Spain, requires ultra-low background conditions demanding an exhaustive control of material radiopurity and environmental radon levels. An extensive material screening process is underway for several years based mainly on gamma-ray spectroscopy using ultra-low background germanium detectors in Canfranc but also on mass spectrometry techniques like GDMS and ICPMS. Components from shielding, pressure vessel, electroluminescence and high voltage elements and energy and tracking readout planes have been analyzed, helping in the final design of the experiment and in the construction of the background model. The latest measurements carried out will be presented and the implication on NEXT of their results will be discussed. The commissioning of the NEW detector, as a first step towards NEXT, has started in Canfranc; in-situ measurements of airborne radon levels were taken there to optimize the system for radon mitigation and will be shown too.Comment: Proceedings of the Low Radioactivity Techniques 2015 workshop (LRT2015), Seattle, March 201

Determinants of the current and future distribution of the West Nile virus mosquito vector Culex pipiens in Spain

Changes in environmental conditions, whether related or not to human activities, are continuously modifying the geographic distribution of vectors, which in turn affects the dynamics and distribution of vector-borne infectious diseases. Determining the main ecological drivers of vector distribution and how predicted changes in these drivers may alter their future distributions is therefore of major importance. However, the drivers of vector populations are largely specific to each vector species and region. Here, we identify the most important human-activity-related and bioclimatic predictors affecting the current distribution and habitat suitability of the mosquito Culex pipiens and potential future changes in its distribution in Spain. We determined the niche of occurrence (NOO) of the species, which considers only those areas lying within the range of suitable environmental conditions using presence data. Although almost ubiquitous, the distribution of Cx. pipiens is mostly explained by elevation and the degree of urbanization but also, to a lesser extent, by mean temperatures during the wettest season and temperature seasonality. The combination of these predictors highlights the existence of a heterogeneous pattern of habitat suitability, with most suitable areas located in the southern and northeastern coastal areas of Spain, and unsuitable areas located at higher altitude and in colder regions. Future climatic predictions indicate a net decrease in distribution of up to 29.55%, probably due to warming and greater temperature oscillations. Despite these predicted changes in vector distribution, their effects on the incidence of infectious diseases are, however, difficult to forecast since different processes such as local adaptation to temperature, vector-pathogen interactions, and human-derived changes in landscape may play important roles in shaping the future dynamics of pathogen transmission.info:eu-repo/semantics/acceptedVersio