Search results for "PROCESSES"
showing 10 items of 3831 documents
Enhancing formability of aluminium alloys by superimposing hydrostatic pressure
2003
Publisher Summary One of the strategic topics in manufacturing engineering is represented by the reduction of components weight. This aim is pursued by utilizing accurate and effective design tools and using lightweight metals such as aluminum, magnesium, and titanium alloys. Unfortunately, such materials often show a poor ductility, and thus enhancing formability is nowadays one of the most relevant research focus, as well as the development of effective and reliable predictive models of defects insurgence during forming processes. In this scenario, forming by means of superimposed hydrostatic pressure represents a promising alternative manufacturing technique. The chapter discusses the si…
First Characterization of Novel Silicon Carbide Detectors with Ultra-High Dose Rate Electron Beams for FLASH Radiotherapy
2023
Ultra-high dose rate (UHDR) beams for FLASH radiotherapy present significant dosimetric challenges. Although novel approaches for decreasing or correcting ion recombination in ionization chambers are being proposed, applicability of ionimetric dosimetry to UHDR beams is still under investigation. Solid-state sensors have been recently investigated as a valuable alternative for real-time measurements, especially for relative dosimetry and beam monitoring. Among them, Silicon Carbide (SiC) represents a very promising candidate, compromising between the maturity of Silicon and the robustness of diamond. Its features allow for large area sensors and high electric fields, required to avoid ion r…
A neoepitope generated by an FLT3 internal tandem duplication (FLT3-ITD) is recognized by leukemia-reactive autologous CD8+ T cells.
2006
Abstract The FLT3 receptor tyrosine kinase is expressed in more than 90% of acute myelogeneous leukemias (AMLs), up to 30% of which carry an internal tandem duplication (ITD) within the FLT3 gene. Although varying duplication sites exist, most FLT3-ITDs affect a single protein domain. We analyzed the FLT3-ITD of an AML patient for encoding HLA class I–restricted immunogenic peptides. One of the tested peptides (YVDFREYEYY) induced in vitro autologous T-cell responses restricted by HLA-A*0101 that were also detectable ex vivo. These peptide-reactive T cells recognized targets transfected with the patient's FLT3-ITD, but not wild-type FLT3, and recognized the patient's AML cells. Our results …
Spectral band selection for vegetation properties retrieval using Gaussian processes regression
2020
Abstract With current and upcoming imaging spectrometers, automated band analysis techniques are needed to enable efficient identification of most informative bands to facilitate optimized processing of spectral data into estimates of biophysical variables. This paper introduces an automated spectral band analysis tool (BAT) based on Gaussian processes regression (GPR) for the spectral analysis of vegetation properties. The GPR-BAT procedure sequentially backwards removes the least contributing band in the regression model for a given variable until only one band is kept. GPR-BAT is implemented within the framework of the free ARTMO's MLRA (machine learning regression algorithms) toolbox, w…
A perspective on Gaussian processes for Earth observation
2019
Earth observation (EO) by airborne and satellite remote sensing and in-situ observations play a fundamental role in monitoring our planet. In the last decade, machine learning and Gaussian processes (GPs) in particular has attained outstanding results in the estimation of bio-geo-physical variables from the acquired images at local and global scales in a time-resolved manner. GPs provide not only accurate estimates but also principled uncertainty estimates for the predictions, can easily accommodate multimodal data coming from different sensors and from multitemporal acquisitions, allow the introduction of physical knowledge, and a formal treatment of uncertainty quantification and error pr…
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method
2020
Abstract Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past, empirical algorithms have been widely employed to retrieve information on this biochemical plant component from canopy reflectance. However, these approaches do not seek for a cause-effect relationship based on physical laws. Moreover, most studies solely relied on the correlation of chlorophyll content with nitrogen, and thus neglected the fact that most N is bound in proteins. Our study presents a hybrid retrieval method using a physically-base…
Multiscale analysis of information dynamics for linear multivariate processes.
2016
In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving aver…
Resolving gas bubbles ascending in liquid metal from low-SNR neutron radiography images
2021
We demonstrate a new image processing methodology for resolving gas bubbles travelling through liquid metal from dynamic neutron radiography images with an intrinsically low signal-to-noise ratio. Image pre-processing, denoising and bubble segmentation are described in detail, with practical recommendations. Experimental validation is presented—stationary and moving reference bodies with neutron-transparent cavities are radiographed with imaging conditions representative of the cases with bubbles in liquid metal. The new methods are applied to our experimental data from previous and recent imaging campaigns, and the performance of the methods proposed in this paper is compared against our p…
A multi-scale area-interaction model for spatio-temporal point patterns
2018
Models for fitting spatio-temporal point processes should incorporate spatio-temporal inhomogeneity and allow for different types of interaction between points (clustering or regularity). This paper proposes an extension of the spatial multi-scale area-interaction model to a spatio-temporal framework. This model allows for interaction between points at different spatio-temporal scales and the inclusion of covariates. We fit the proposed model to varicella cases registered during 2013 in Valencia, Spain. The fitted model indicates small scale clustering and regularity for higher spatio-temporal scales.
Tick size and price diffusion
2010
A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature on the role of tick size on market microstructure. However, tick size can also affect price properties at longer time scales, and relatively less is known about the effect of tick size on the statistical properties of prices. The present paper is divided in two parts. In the first we review the effect of tick size change on the market microstructure and the diffusion properties…