Skip to main content
Bicocca Open Archive Research Data

Datasets within this collection

Filter Results
1970 2024
415 results
  • IN2SIGHT_DES_UNIMIB_In vivo label-free tissue histology on chicken embryo_part2
    This is the second part of the dataset contains the data used for the publication Conci, L. Sironi, E. Jacchetti, D. Panzeri, D. Inverso, R. Martinez-Vazquez, R. Osellame, M. Collini, G. Cerullo, G. Chirico, and M.T. Raimondi, “In vivo label-free tissue histology through a microstructured imaging window. ,” APL Bioeng. accepted november 2023. The detailed description of the contents can be found in the file "Dataset_chickenEmbyo.docx", readable with Word or equivalent. In brief, the whole dataset contains 6 folders, each with a set of data taken either on histological sections, stained with H&E, or in vivo in chicken Embryos with fluorescence optical microscopy, either confocal or two-photon excitation. Two folders are in the part 1 of this data set. The remaining 4 folders can be found here.
    • Dataset
  • IN2SIGHT_DES_POLIMI_WP2_PhysicalData_20220425
    This dataset contains a set of data related to the characterization of the 2-photon polymerized microstructures for the IN2SIGHT project. Mostly, they are supplementary data for publications.
    • Dataset
  • In2Sight_WP2.Microfabrication
    Data related to the design of the microoptics for in2sight, D2.1
    • Dataset
  • IN2SIGHT_MAN_UNIMIB_WP{1,5,7}_Management_Plans_20220223
    This folder contains documents related to the regulatory plan (folder: Regulatory plan, D.5.1), to the Risk managament plan (folder: Risk Management, D1.1) and to the data management plan (folder: data management plan, D7.1). Update from Version 3 is the addition of the Annex 1 to the DMP that contains the indications for the data storage of digital pathology data.
    • Dataset
  • MCNNTUNES: Tuning Shower Monte Carlo generators with machine learning
    The parameters tuning of event generators is a research topic characterized by complex choices: the generator response to parameter variations is difficult to obtain on a theoretical basis, and numerical methods are hardly tractable due to the long computational times required by generators. Event generator tuning has been tackled by parametrization-based techniques, with the most successful one being a polynomial parametrization. In this work, an implementation of tuning procedures based on artificial neural networks is proposed. The implementation was tested with closure testing and experimental measurements from the ATLAS experiment at the Large Hadron Collider.
    • Dataset
  • Vbfnlo: A parton level Monte Carlo for processes with electroweak bosons
    This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract Vbfnlo is a fully flexible parton level Monte Carlo program for the simulation of vector boson fusion, double and triple vector boson production in hadronic collisions at next-to-leading order in the strong coupling constant. Vbfnlo includes Higgs and vector boson decays with full spin correlations and all off-shell effects. In addition, Vbfnlo implements CP-even and CP-odd Higgs boson via gluon fusion, associated with two jets, at the leading-order one-loop level with the full top- a... Title of program: VBFNLO Catalogue Id: AEDO_v1_0 Nature of problem To resolve the large scale dependence inherent in leading order calculations and to quantify the cross section error induced by uncertainties in the determination of parton distribution functions, it is necessary to include NLO corrections. Moreover, whenever stringent cuts are required on decay products and/or identified jets the question arises whether the scale dependence and a k-factor, defined as the ratio of NLO to LO cross section, determined for the inclusive production cross sections ar ... Versions of this program held in the CPC repository in Mendeley Data AEDO_v1_0; VBFNLO; 10.1016/j.cpc.2009.03.006
    • Dataset
  • Search for W$\gamma$ resonances in proton-proton collisions at $\sqrt{s} =$ 13 TeV using hadronic decays of Lorentz-boosted W bosons
    A search for $W\gamma$ resonances in the mass range between 0.7 and 6.0 TeV is presented. The $W$ boson is reconstructed via its hadronic decays, with the final-state products forming a single large-radius jet, owing to a high Lorentz boost of the $W$ boson. The search is based on proton-proton collision data at $\sqrt{s} = 13 ~\text{TeV}$, corresponding to an integrated luminosity of 137 $\text{fb}^{-1}$, collected with the CMS detector at the LHC in 2016--2018. The $W\gamma$ mass spectrum is parameterized with a smoothly falling background function and examined for the presence of resonance-like signals. No significant excess above the predicted background is observed. Model-specific upper limits at 95% confidence level on the product of the cross section and branching fraction to the $W\gamma$ channel are set. Limits for narrow resonances and for resonances with an intrinsic width equal to 5% of their mass, for spin-0 and spin-1 hypotheses, range between 0.17 fb at 6.0 TeV and 55 fb at 0.7 TeV. These are the most restrictive limits to date on the existence of such resonances. In specific narrow-resonance benchmark models, heavy scalar (vector) triplet resonances with masses between 0.75 (1.15) and 1.40 (1.36) TeV are excluded for a range of model parameters. Model-independent limits on the product of the cross section, signal acceptance, and branching fraction to the $W\gamma$ channel are set for minimum $W\gamma$ mass thresholds between 1.5 and 8.0 TeV.
    • Collection
  • Dataset from: Multi-messenger observations of binary neutron star mergers in the O4 run
    The binary neutron stars population data from the paper "Multi-messenger observations of binary neutron star mergers in the O4 run" ( Details of how to use the data, as well as the scripts to reproduce the figures of the main text of the paper are given in the accompanying Github repository If you use this data, please cite the above manuscript.
    • Dataset
  • ViolaDeRenzis/twoprecessingspins: Data release
    No description provided.
    • Software/Code
  • The Einstein Toolkit
    The Einstein Toolkit is a community-driven software platform of core computational tools to advance and support research in relativistic astrophysics and gravitational physics. The Einstein Toolkit has been supported by NSF 2004157/2004044/2004311/2004879/2003893/1550551/1550461/1550436/1550514, Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
    • Software/Code