Accelerating the Lawson-Hanson NNLS solver for large-scale Tchakaloff regression designs

We deal with the problem of computing near G-optimal compressed designs for high-degree polynomial regression on fine discretizations of 2d and 3d regions of arbitrary shape. The key tool is Tchakaloff-like compression of discrete probability measures, via an improved version of the Lawson-Hanson NNLS solver for the corresponding full and large-scale underdetermined moment system, that can have for example a size order of 10\u2c63 (basis polynomials) x 10\u2c64 (nodes)

Filtering out Outliers in Learning to Rank

Outlier data points are known to affect negatively the learning process of regression or classification models, yet their impact in the learning-to-rank scenario has not been thoroughly investigated so far. In this work we propose SOUR, a learning-to-rank method that detects and removes outliers before building an effective ranking model. We limit our analysis to gradient boosting decision trees, where SOUR searches for outlier instances that are incorrectly ranked in several iterations of the learning process. Extensive experiments show that removing a limited number of outlier data instances before re-training a new model provides statistically significant improvements, and that SOUR outperforms state-of-the-art de-noising and outlier detection methods

SOUR: an Outliers Detection Algorithm in Learning to Rank (Abstract)

Outlier data points are known to affect negatively the learning process of regression or classification models, yet their impact in the learning-to-rank scenario has not been thoroughly investigated so far. In this talk we present our effort to solve this research problem. The full version of this work will appear at ICTIR 2022 [1]. We designed SOUR, a learning-to-rank method that detects and removes outliers before building an effective ranking model. We limit our analysis to gradient boosting decision trees, but our algorithm can be easily adapted to handle different learning strategy, such as artificial Neural Network. SOUR searches for outlier instances that are consistently incorrectly ranked in several consecutive iterations of the learning process. We performed an extensive evaluation analysis on three publicly available datasets and we empirically demonstrated that i) removing a limited number of outlier data instances before re-training a new model, provides statistically significant improvements in term of effectiveness ii) SOUR outperforms state-of-the-art de-noising and outlier detection methods such as [2]. Finally, we investigated how the removal of the outliers affects the ensemble structure and we found that the ensemble leaves were purer when trained without the presence of the outliers

Hemoglobin is present as a canonical \u3b12\u3b22 tetramer in dopaminergic neurons

Hemoglobin is the oxygen carrier in blood erythrocytes. Oxygen coordination is mediated by \u3b12\u3b22 tetrameric structure via binding of the ligand to the heme iron atom. This structure is essential for hemoglobin function in the blood. In the last few years, expression of hemoglobin has been found in atypical sites, including the brain. Transcripts for \u3b1 and \u3b2 chains of hemoglobin as well as hemoglobin immunoreactivity have been shown in mesencephalic A9 dopaminergic neurons, whose selective degeneration leads to Parkinson's disease. To gain further insights into the roles of hemoglobin in the brain, we examined its quaternary structure in dopaminergic neurons in vitro and in vivo. Our results indicate that (i) in mouse dopaminergic cell line stably over-expressing \u3b1 and \u3b2 chains, hemoglobin exists as an \u3b12\u3b22 tetramer; (ii) similarly to the over-expressed protein, endogenous hemoglobin forms a tetramer of 64kDa; (iii) hemoglobin also forms high molecular weight insoluble aggregates; and (iv) endogenous hemoglobin retains its tetrameric structure in mouse mesencephalon in vivo. In conclusion, these results suggest that neuronal hemoglobin may be endowed with some of the biochemical activities and biological function associated to its role in erythroid cells. This article is part of a Special Issue entitled: Oxygen Binding and Sensing Proteins. \ua9 2013 The Authors. Published by Elsevier B.V. All rights reserved

Design optimization of RF lines in vacuum environment for the MITICA experiment

This contribution regards the Radio Frequency (RF) transmission line of the Megavolt ITER Injector and Concept Advancement (MITICA) experiment. The original design considered copper coaxial lines of 1″ 5/8, but thermal simulations under operating conditions showed maximum temperatures of the lines at regime not compatible with the prescription of the component manufacturer. Hence, an optimization of the design was necessary. Enhancing thermal radiation and increasing the conductor size were considered for design optimization: thermal analyses were carried out to calculate the temperature of MITICA RF lines during operation, as a function of the emissivity value and of other geometrical parameters. Five coating products to increase the conductor surface emissivity were tested, measuring the outgassing behavior of the selected products and the obtained emissivity values

Overview of the design of the ITER heating neutral beam injectors

The heating neutral beam injectors (HNBs) of ITER are designed to deliver 16.7MWof 1 MeVD0 or 0.87 MeVH0 to the ITER plasma for up to 3600 s. They will be the most powerful neutral beam\uf0a0(NB) injectors ever, delivering higher energy NBs to the plasma in a tokamak for longer than any previous systems have done. The design of the HNBs is based on the acceleration and neutralisation of negative ions as the efficiency of conversion of accelerated positive ions is so low at the required energy that a realistic design is not possible, whereas the neutralisation ofH 12 andD 12 remains acceptable ( 4856%). The design of a long pulse negative ion based injector is inherently more complicated than that of short pulse positive ion based injectors because: \u2022 negative ions are harder to create so that they can be extracted and accelerated from the ion source; \u2022 electrons can be co-extracted from the ion source along with the negative ions, and their acceleration must be minimised to maintain an acceptable overall accelerator efficiency; \u2022 negative ions are easily lost by collisions with the background gas in the accelerator; \u2022 electrons created in the extractor and accelerator can impinge on the extraction and acceleration grids, leading to high power loads on the grids; \u2022 positive ions are created in the accelerator by ionisation of the background gas by the accelerated negative ions and the positive ions are back-accelerated into the ion source creating a massive power load to the ion source; \u2022 electrons that are co-accelerated with the negative ions can exit the accelerator and deposit power on various downstream beamline components. The design of the ITER HNBs is further complicated because ITER is a nuclear installation which will generate very large fluxes of neutrons and gamma rays. Consequently all the injector components have to survive in that harsh environment. Additionally the beamline components and theNBcell, where the beams are housed, will be activated and all maintenance will have to be performed remotely. This paper describes the design of theHNBinjectors, but not the associated power supplies, cooling system, cryogenic system etc, or the high voltage bushingwhich separates the vacuum of the beamline fromthehighpressureSF6 of the high voltage (1MV) transmission line, through which the power, gas and coolingwater are supplied to the beam source. Also themagnetic field reduction system is not described

Discrete time crystals in the absence of manifest symmetries or disorder in open quantum systems

We establish a link between metastability and a discrete time-crystalline phase in a periodically driven open quantum system. The mechanism we highlight requires neither the system to display any microscopic symmetry nor the presence of disorder, but relies instead on the emergence of a metastable regime. We investigate this in detail in an open quantum spin system, which is a canonical model for the exploration of collective phenomena in strongly interacting dissipative Rydberg gases. Here, a semiclassical approach reveals the emergence of a robust discrete time-crystalline phase in the thermodynamic limit in which metastability, dissipation, and interparticle interactions play a crucial role. We perform numerical simulations in order to investigate the dependence on the range of interactions, from all to all to short ranged, and the scaling with system size of the lifetime of the time crystal