Injection Molding and Appearance of Cellulose-Reinforced Composites

Composite materials based on an ethylene-acrylic acid (EAA) copolymer and 20 wt% cellulose fibers were compounded by two runs in a twin-screw extruder. The composite material with cellulose fibers (CF) and a reference of unfilled EAA were injection molded into plaques using three different temperature profiles with end zone temperatures of 170\ub0C, 200\ub0C, and 230\ub0C. The injection molded samples were then characterized in terms of their mechanical properties, thermal properties, appearance (color and gloss), and surface topography. The higher processing temperatures resulted in a clear discoloration of the composites, but there was no deterioration in the mechanical performance. The addition of cellulose typically gave a tensile modulus three times higher than that of the unfilled EAA, but the strength and strain at rupture were reduced when fibers were added. The processing temperature had no significant influence on the mechanical properties of the composites. Gloss measurements revealed negligible differences between the samples molded at the different melt temperatures but the surface smoothness was somewhat higher when the melt temperature was increased. In general, addition of the cellulose to the EAA reduced the gloss level and the surface smoothness. POLYM. ENG. SCI., 2019. \ua9 2019 Society of Plastics Engineers

Role of cellulose oxidation in the yellowing of ancient paper

The yellowing of paper on aging causes major aesthetic damages of cultural heritage. It is due to cellulose oxidation, a complex process with many possible products still to be clarified. By comparing ultraviolet-visible reflectance spectra of ancient and artificially aged modern papers with ab initio time-dependent density functional theory calculations, we identify and estimate the abundance of oxidized functional groups acting as chromophores and responsible of paper yellowing. This knowledge can be used to set up strategies and selective chemical treatments preventing paper yellowing

Optical response of strongly absorbing inhomogeneous materials: Application to paper degradation

n/

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study

Introduction Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newborns with CDH to develop forecasting models in prenatal epoch, based on the integrated analysis of clinical data, to provide neonatal PH as the first outcome and, possibly: Favorable response to fetal endoscopic tracheal occlusion (FETO), need for Extracorporeal Membrane Oxygenation (ECMO), survival to ECMO, and death. Moreover, we plan to produce a (semi)automatic fetus lung segmentation system in Magnetic Resonance Imaging (MRI), which will be useful during project implementation but will also be an important tool itself to standardize lung volume measures for CDH fetuses. Methods and analytics Patients with isolated CDH from singleton pregnancies will be enrolled, whose prenatal checks were performed at the Fetal Surgery Unit of the Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (Milan, Italy) from the 30th week of gestation. A retrospective data collection of clinical and radiological variables from newborns' and mothers' clinical records will be performed for eligible patients born between 01/01/2012 and 31/12/2020. The native sequences from fetal magnetic resonance imaging (MRI) will be collected. Data from different sources will be integrated and analyzed using ML and DL, and forecasting algorithms will be developed for each outcome. Methods of data augmentation and dimensionality reduction (feature selection and extraction) will be employed to increase sample size and avoid overfitting. A software system for automatic fetal lung volume segmentation in MRI based on the DL 3D U-NET approach will also be developed. Ethics and dissemination This retrospective study received approval from the local ethics committee (Milan Area 2, Italy). The development of predictive models in CDH outcomes will provide a key contribution in disease prediction, early targeted interventions, and personalized management, with an overall improvement in care quality, resource allocation, healthcare, and family savings. Our findings will be validated in a future prospective multicenter cohort study

Quantum ESPRESSO: a modular and open-source software project for quantum simulations of materials

Quantum ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). Quantum ESPRESSO stands for "opEn Source Package for Research in Electronic Structure, Simulation, and Optimization". It is freely available to researchers around the world under the terms of the GNU General Public License. Quantum ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the original authors of novel electronic-structure algorithms and applied in the last twenty years by some of the leading materials modeling groups worldwide. Innovation and efficiency are still its main focus, with special attention paid to massively-parallel architectures, and a great effort being devoted to user friendliness. Quantum ESPRESSO is evolving towards a distribution of independent and inter-operable codes in the spirit of an open-source project, where researchers active in the field of electronic-structure calculations are encouraged to participate in the project by contributing their own codes or by implementing their own ideas into existing codes.Comment: 36 pages, 5 figures, resubmitted to J.Phys.: Condens. Matte

A Mathematical Framework for Protein Structure Comparison

Comparison of protein structures is important for revealing the evolutionary relationship among proteins, predicting protein functions and predicting protein structures. Many methods have been developed in the past to align two or multiple protein structures. Despite the importance of this problem, rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison. One notable issue in this field is that with many different distances used to measure the similarity between protein structures, none of them are proper distances when protein structures of different sequences are compared. Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous. In this work, we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves. Using an elastic Riemannian metric on spaces of curves, geodesic distance, a proper distance on spaces of curves, can be computed for any two protein structures. In this framework, protein structures can be treated as random variables on the shape manifold, and means and covariance can be computed for populations of protein structures. Furthermore, these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing. The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification. With curves representing protein structures, the matching is performed using elastic shape analysis of curves, which can effectively model conformational changes and insertions/deletions. We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set

Astrophysically Triggered Searches for Gravitational Waves: Status and Prospects

In gravitational-wave detection, special emphasis is put onto searches that focus on cosmic events detected by other types of astrophysical observatories. The astrophysical triggers, e.g. from gamma-ray and X-ray satellites, optical telescopes and neutrino observatories, provide a trigger time for analyzing gravitational wave data coincident with the event. In certain cases the expected frequency range, source energetics, directional and progenitor information is also available. Beyond allowing the recognition of gravitational waveforms with amplitudes closer to the noise floor of the detector, these triggered searches should also lead to rich science results even before the onset of Advanced LIGO. In this paper we provide a broad review of LIGO's astrophysically triggered searches and the sources they target

Swift follow-up observations of candidate gravitational-wave transient events

We present the first multi-wavelength follow-up observations of two candidate gravitational-wave (GW) transient events recorded by LIGO and Virgo in their 2009-2010 science run. The events were selected with low latency by the network of GW detectors and their candidate sky locations were observed by the Swift observatory. Image transient detection was used to analyze the collected electromagnetic data, which were found to be consistent with background. Off-line analysis of the GW data alone has also established that the selected GW events show no evidence of an astrophysical origin; one of them is consistent with background and the other one was a test, part of a "blind injection challenge". With this work we demonstrate the feasibility of rapid follow-ups of GW transients and establish the sensitivity improvement joint electromagnetic and GW observations could bring. This is a first step toward an electromagnetic follow-up program in the regime of routine detections with the advanced GW instruments expected within this decade. In that regime multi-wavelength observations will play a significant role in completing the astrophysical identification of GW sources. We present the methods and results from this first combined analysis and discuss its implications in terms of sensitivity for the present and future instruments.Comment: Submitted for publication 2012 May 25, accepted 2012 October 25, published 2012 November 21, in ApJS, 203, 28 ( http://stacks.iop.org/0067-0049/203/28 ); 14 pages, 3 figures, 6 tables; LIGO-P1100038; Science summary at http://www.ligo.org/science/Publication-S6LVSwift/index.php ; Public access area to figures, tables at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p110003

Search for Gravitational Waves from Low Mass Compact Binary Coalescence in LIGO's Sixth Science Run and Virgo's Science Runs 2 and 3

We report on a search for gravitational waves from coalescing compact binaries using LIGO and Virgo observations between July 7, 2009 and October 20, 2010. We searched for signals from binaries with total mass between 2 and 25 solar masses; this includes binary neutron stars, binary black holes, and binaries consisting of a black hole and neutron star. The detectors were sensitive to systems up to 40 Mpc distant for binary neutron stars, and further for higher mass systems. No gravitational-wave signals were detected. We report upper limits on the rate of compact binary coalescence as a function of total mass, including the results from previous LIGO and Virgo observations. The cumulative 90%-confidence rate upper limits of the binary coalescence of binary neutron star, neutron star- black hole and binary black hole systems are 1.3 x 10^{-4}, 3.1 x 10^{-5} and 6.4 x 10^{-6} Mpc^{-3}yr^{-1}, respectively. These upper limits are up to a factor 1.4 lower than previously derived limits. We also report on results from a blind injection challenge.Comment: 11 pages, 5 figures. For a repository of data used in the publication, go to: . Also see the announcement for this paper on ligo.org at: <http://www.ligo.org/science/Publication-S6CBCLowMass/index.php

Search for gravitational waves associated with the InterPlanetary Network short gamma ray bursts

We outline the scientific motivation behind a search for gravitational waves associated with short gamma ray bursts detected by the InterPlanetary Network (IPN) during LIGO's fifth science run and Virgo's first science run. The IPN localisation of short gamma ray bursts is limited to extended error boxes of different shapes and sizes and a search on these error boxes poses a series of challenges for data analysis. We will discuss these challenges and outline the methods to optimise the search over these error boxes.Comment: Methods paper; Proceedings for Eduardo Amaldi 9 Conference on Gravitational Waves, July 2011, Cardiff, U