How (not) to Choose Peers in Studying Groups

This paper analyzes social group formation when agents are subject to peer effects within groups increasing human capital and instantaneous utility. When agents are heterogeneous on two dimensions, ability and social skills, and monetary payments are not feasible the model predicts segregation at the top and at the bottom of the attribute space and bunching for heterogeneous intermediate types. Groups may be heterogeneous in taste types and more heterogeneous types are more likely to participate. The equilibrium allocation does not induce cost-efficient human capital accumulation. Introducing ability tracking may produce beneficial results despite decreasing differences in human capital production.Education, Peer-effects, Matching, Group Formation

Automated user documentation generation based on the Eclipse application model

An application's user documentation, also referred to as the user manual, is one of the core elements required in application distribution. While there exist many tools to aid an application's developer in creating and maintaining documentation on and for the code itself, there are no tools that complement code development with user documentation for modern graphical applications. Approaches like literate programming are not applicable to this scenario, as not a library, but a full application is to be documented to an end-user. Documentation generation on applications up to now was only partially feasible due to the gap between the code and its semantics. The new generation of Eclipse rich client platform developed applications is based on an application model, closing a broad semantic gap between code and visible interface. We use this application model to provide a semantic description for the contained elements. Combined with the internal relationships of the application model, these semantic descriptions are aggregated to well-structured user documentations that comply to the ISO/IEC 26514. This paper delivers a report on the Ecrit research project, where the potentials and limitations of user documentation generation based on the Eclipse application model were investigated.Comment: 9 pages, 9 figure

Calorimetric study of water's two glass transitions in the presence of LiCl

A DSC study of dilute glassy LiCl aqueous solutions in the water-dominated regime provides direct evidence of a glass-to-liquid transition in expanded high density amorphous (eHDA)-type solutions. Similarly, low density amorphous ice (LDA) exhibits a glass transition prior to crystallization to ice Ic. Both glass transition temperatures are independent of the salt concentration, whereas the magnitude of the heat capacity increase differs. By contrast to pure water, the glass transition endpoint for LDA can be accessed in LiCl aqueous solutions above 0.01 mole fraction. Furthermore, we also reveal the endpoint for HDA's glass transition, solving the question on the width of both glass transitions. This suggests that both equilibrated HDL and LDL can be accessed in dilute LiCl solutions, supporting the liquid-liquid transition scenario to understand water's anomalies.Fil: Ruiz, Guadalupe N.. Universidad de Innsbruck; Austria. Universidad Politécnica de Catalunya; EspañaFil: Amann Winkel, Katrin. AlbaNova University Center; Suecia. Universidad de Innsbruck; AustriaFil: Bove, Livia E.. Université Pierre et Marie Curie; FranciaFil: Corti, Horacio Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica; Argentina. Universidad de Buenos Aires; ArgentinaFil: Loerting, Thomas. Universidad de Innsbruck; Austri

The Rise of Certificate Transparency and Its Implications on the Internet Ecosystem

In this paper, we analyze the evolution of Certificate Transparency (CT) over time and explore the implications of exposing certificate DNS names from the perspective of security and privacy. We find that certificates in CT logs have seen exponential growth. Website support for CT has also constantly increased, with now 33% of established connections supporting CT. With the increasing deployment of CT, there are also concerns of information leakage due to all certificates being visible in CT logs. To understand this threat, we introduce a CT honeypot and show that data from CT logs is being used to identify targets for scanning campaigns only minutes after certificate issuance. We present and evaluate a methodology to learn and validate new subdomains from the vast number of domains extracted from CT logged certificates.Comment: To be published at ACM IMC 201

Equine recurrent uveitis - A spontaneous horse model of uveitis

Equine recurrent uveitis (ERU) is an autoimmune disease that occurs with a high prevalence (10%) in horses. ERU represents the only reliable spontaneous model for human autoimmune uveitis. We already identified and characterized novel autoantigens (malate dehydrogenase, recoverin, CRALBP) by analyzing the autoantibody-binding pattern of horses affected by spontaneous recurrent uveitis (ERU) to the retinal proteome. CRALBP also seems to be relevant to human autoimmune uveitis. Proteomic screening of vitreous and retinal samples from ERU diseased cases in comparison to healthy controls has led to the identification of a series of differentially regulated proteins, which are functionally linked to the immune system and the maintenance of the blood-retinal barrier. Copyright (c) 2008 S. Karger AG, Basel

Infrastructure and its role in Brazil's development process

AbstractThis article considers the relationship between growth and infrastructure spending in the Brazilian context and the nature and causes of infrastructural underinvestment. The paper begins by considering the relationship between infrastructural investment and economic growth on both a national and regional basis. Next, focusing on the critical urban transportation sector, the paper gauges the infrastructural shortfall facing Brazil and the policies designed to overcome it. Given the obvious importance of infrastructure, why has investment not been higher? In the final section we argue that a central reason for this lies in regulatory design and implementation

Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does "trustworthy AI" mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic