The AMIGA project. I. Optical characterization of the CIG catalog

The AMIGA project (Analysis of the Interstellar Medium of Isolated Galaxies) is compiling a multiwavelength database of isolated galaxies that includes optical (B and Halpha), infrared (FIR and NIR) and radio (continuum plus HI and CO lines) properties. It involves a refinement of the pioneering Catalog of Isolated Galaxies. This paper is the first in a series and begins with analysis of the global properties of the nearly redshift-complete CIG with emphasis on the Optical Luminosity Function (OLF) which we compare with other recent estimates of the OLF for a variety of environments. The CIG redshift distribution for n= 956 galaxies re-enforces the evidence for a bimodal structure seen earlier in smaller samples. The peaks at redshift near 1500 and 6000km/s correspond respectively to galaxies in the local supercluster and those in more distant large-scale components (particularly Perseus-Pisces). The two peaks in the redshift distribution are superimposed on 50% or more of the sample that is distributed in a much more homogeneous way. The CIG probably represents the most homogeneous local field example that has ever been compiled. Our derivation of the CIG OLF is consistent with other studies of the OLF for lower density environments. This comparison via the Schechter parameter formalization shows that: 1) M* increases with galaxy surface density on the sky and 2) alpha shows a weaker tendency to do the same. The CIG represents the largest and most complete foundation for studies of isolated galaxies and is likely as close as we can come to a field sample. (Tables 1, 2 and 3 are available in electronic form at http://www.iaa.es/AMIGA.html).Comment: In press in A&

Enhanced hydrogen production from thermochemical processes

To alleviate the pressing problem of greenhouse gas emissions, the development and deployment of sustainable energy technologies is necessary. One potentially viable approach for replacing fossil fuels is the development of a H2 economy. Not only can H2 be used to produce heat and electricity, it is also utilised in ammonia synthesis and hydrocracking. H2 is traditionally generated from thermochemical processes such as steam reforming of hydrocarbons and the water-gas-shift (WGS) reaction. However, these processes suffer from low H2 yields owing to their reversible nature. Removing H2 with membranes and/or extracting CO2 with solid sorbents in situ can overcome these issues by shifting the component equilibrium towards enhanced H2 production via Le Chatelier's principle. This can potentially result in reduced energy consumption, smaller reactor sizes and, therefore, lower capital costs. In light of this, a significant amount of work has been conducted over the past few decades to refine these processes through the development of novel materials and complex models. Here, we critically review the most recent developments in these studies, identify possible research gaps, and offer recommendations for future research

Development and Validation of a Symptom-Based Activity Index for Adults With Eosinophilic Esophagitis

Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE), to provide endpoints for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patients’ assessments of disease severity. We also evaluated relationships between patients’ assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Using GPS to model slip rate of the San Andreas Fault and other faults within a transect across the plate boundary passing through San Gorgonio Pass

Using Global Positioning System (GPS) observations along with a model of elastic motion, the slip rates for the San Andreas Fault (SAF), San Jacinto fault (SJF), and many other faults on the Pacific-North America plate boundary were determined in the vicinity of San Gorgonio Pass. After testing 414,722 slip rate combinations, the slip rate for the San Andreas Fault was determined to be between 4 and 16 mm/yr., with the best fitting slip rate being 8 mm/yr. The slip rate of the San Jacinto fault was determined to be between 6 and 18 mm/yr. with the best fitting slip rate being 18 mm/ yr. Other faults passing through the San Gorgonio Pass transect had slip rates ranging from 0 mm/yr. to 6 mm/yr

Machine Learning and Modeling Methods for Protein Engineering

Computation has been an integral part of structural biology, ever since the first protein macromolecular structure was solved via Fourier Synthesis on the EDSAC Mark I electronic computer in 1958 (Kendrew et al., 1958). Throughout my time at Caltech, I have endeavored to develop new methods to apply machine learning and molecular modeling to the study of biological macromolecules. These efforts have taken two distinct tracks, but are unified by a focus on studying proteins on a structural level. Through the application of molecular dynamics and modeling, I have studied insulin from several angles, including the incorporation of non-canonical amino acids, and how these modifications might be responsible for the modification of critical properties such as hexamer dissociation and fibrillation formation. Additionally, I have probed how insulin behaves at the interface of water and silica, a property which is critical for the effective dissemination and administration of this therapeutic molecule. I have helped to develop a novel computationally guided workflow for integrating drug conjugates into antibody CDRs. This technique yields molecules which exhibit synergistic binding and an enhanced ability for selective binding. The second major thrust of my research has focused on applying machine learning to protein engineering problems, particularly developing tools for working with structural data, and for making efficient re-use of data which has already been laboriously collected by other groups. The basic data parsing and processing tools which were created and refined over the course of my time at Caltech has enabled many other projects, both of my own and of collaborators. Studies into the use of generative networks for protein-protein docking have been conducted which lend useful insights for network architecture, the inclusion of intermediate learning objectives, and overcoming sparsity. The technique introduced in our ICLR 2021 paper demonstrates a regularization method which enables data from past protein engineering campaigns to be leveraged to learn policies which optimally select molecules to synthesize in unrelated engineering efforts, to potentially save a significant amount of time and money for future projects. Reference Kendrew, J. C.; Bodo, G.; Dintzis, H. M.; Parrish, R. G.; Wyckoff, H.; Phillips, D. C. A. "Three-Dimensional Model of the Myoglobin Molecule Obtained by X-Ray Analysis". Nature 1958, 181 (4610), 662–666.</p

Introduction to Anthropology

560 hal.;23 c

Guidance for effective discipline

When advising families about discipline strategies, pediatricians should use a comprehensive approach that includes consideration of the parent-child relationship, reinforcement of desired behaviors, and consequences for negative behaviors. Corporal punishment is of limited effectiveness and has potentially deterious side effects