New Program Abstractions for Privacy

Static program analysis, once seen primarily as a tool for optimising programs, is now increasingly important as a means to provide quality guarantees about programs. One measure of quality is the extent to which programs respect the privacy of user data. Differential privacy is a rigorous quantified definition of privacy which guarantees a bound on the loss of privacy due to the release of statistical queries. Among the benefits enjoyed by the definition of differential privacy are compositionality properties that allow differentially private analyses to be built from pieces and combined in various ways. This has led to the development of frameworks for the construction of differentially private program analyses which are private-by-construction. Past frameworks assume that the sensitive data is collected centrally, and processed by a trusted curator. However, the main examples of differential privacy applied in practice - for example in the use of differential privacy in Google Chrome’s collection of browsing statistics, or Apple’s training of predictive messaging in iOS 10 -use a purely local mechanism applied at the data source, thus avoiding the collection of sensitive data altogether. While this is a benefit of the local approach, with systems like Apple’s, users are required to completely trust that the analysis running on their system has the claimed privacy properties. In this position paper we outline some key challenges in developing static analyses for analysing differential privacy, and propose novel abstractions for describing the behaviour of probabilistic programs not previously used in static analyses

Evaluation of the surface strength of glass plates shaped by hot slumping process

The Hot Slumping Technology is under development by several research groups in the world for the realization of grazing-incidence segmented mirrors for X-ray astronomy, based on thin glass plates shaped over a mould at temperatures above the transformation point. The performed thermal cycle and related operations might have effects on the strength characteristics of the glass, with consequences on the structural design of the elemental optical modules and consecutively on the entire X-ray optic for large astronomical missions like IXO and ATHENA. The mechanical strength of glass plates after they underwent the slumping process was tested through destructive double-ring tests in the context of a study performed by the Astronomical Observatory of Brera with the collaboration of Stazione Sperimentale del Vetro and BCV Progetti. The entire study has been realized on more than 200 D263 Schott borosilicate glass specimens of dimension 100 mm x 100 mm and thickness 0.4 mm, either flat or bent at a Radius of Curvature of 1000 mm through the particular pressure assisted hot slumping process developed by INAF-OAB. The collected experimental data have been compared to non-linear FEM analyses and treated with Weibull statistic to assess the current IXO glass X-ray telescope design, in terms of survival probability, when subject to static and acoustic loads characteristic of the launch phase. The paper describes the activities performed and presents the obtained results.Comment: Accepted for publication in Optical Enginnering (Jun 26, 2014

Nowcasting gentrification using Airbnb data

There is a rumbling debate over the impact of gentrification: presumed gentrifiers have been the target of protests and attacks in some cities, while they have been welcome as generators of new jobs and taxes in others. Census data fails to measure neighborhood change in real-time since it is usually updated every ten years. This work shows that Airbnb data can be used to quantify and track neighborhood changes. Specifically, we consider both structured data (e.g., number of listings, number of reviews, listing information) and unstructured data (e.g., user-generated reviews processed with natural language processing and machine learning algorithms) for three major cities, New York City (US), Los Angeles (US), and Greater London (UK). We find that Airbnb data (especially its unstructured part) appears to nowcast neighborhood gentrification, measured as changes in housing affordability and demographics. Overall, our results suggest that user-generated data from online platforms can be used to create socioeconomic indices to complement traditional measures that are less granular, not in real-time, and more costly to obtain

Who benefits from the "sharing" economy of Airbnb?

Sharing economy platforms have become extremely popular in the last few years, and they have changed the way in which we commute, travel, and borrow among many other activities. Despite their popularity among consumers, such companies are poorly regulated. For example, Airbnb, one of the most successful examples of sharing economy platform, is often criticized by regulators and policy makers. While, in theory, municipalities should regulate the emergence of Airbnb through evidence-based policy making, in practice, they engage in a false dichotomy: some municipalities allow the business without imposing any regulation, while others ban it altogether. That is because there is no evidence upon which to draft policies. Here we propose to gather evidence from the Web. After crawling Airbnb data for the entire city of London, we find out where and when Airbnb listings are offered and, by matching such listing information with census and hotel data, we determine the socio-economic conditions of the areas that actually benefit from the hospitality platform. The reality is more nuanced than one would expect, and it has changed over the years. Airbnb demand and offering have changed over time, and traditional regulations have not been able to respond to those changes. That is why, finally, we rely on our data analysis to envision regulations that are responsive to real-time demands, contributing to the emerging idea of “algorithmic regulation”

Designing All Graphdiyne Materials as Graphene Derivatives: Topologically Driven Modulation of Electronic Properties

Designing new 2D systems with tunable properties is an important subject for science and technology. Starting from graphene, we developed an algorithm to systematically generate 2D carbon crystals belonging to the family of graphdiynes (GDYs) and having different structures and sp/sp(2) carbon ratios. We analyze how structural and topological effects can tune the relative stability and the electronic behavior, to propose a rationale for the development of new systems with tailored properties. A total of 26 structures have been generated, including the already known polymorphs such as alpha-, beta-, and gamma-GDY. Periodic density functional theory calculations have been employed to optimize the 2D crystal structures and to compute the total energy, the band structure, and the density of states. Relative energies with respect to graphene have been found to increase when the values of the carbon sp/sp(2) ratio increase, following however different trends based on the peculiar topologies present in the crystals. These topologies also influence the band structure, giving rise to semiconductors with a finite band gap, zero-gap semiconductors displaying Dirac cones, or metallic systems. The different trends allow identifying some topological effects as possible guidelines in the design of new 2D carbon materials beyond graphene

The different story of π bonds

We revisit “classical” issues in multiply bonded systems between main groups elements, namely the structural distortions that may occur at the multiple bonds and that lead, e.g., to trans-bent and bond-length alternated structures. The focus is on the role that orbital hybridization and electron correlation play in this context, here analyzed with the help of simple models for σ-and π-bonds, numerically exact solutions of Hubbard Hamiltonians and first principles (density functional theory) investigations of an extended set of systems

Toward Engineering Chiral Rodlike Metal-Organic Frameworks with Rare Topologies

The establishment of novel design strategies to target chiral rodlike MOFs, elusively faced until now, is one of the most straightforward manners to widen the scope of MOFs. Here we describe our last advances on the application of the metalloligand design strategy toward the development of efficient routes to obtain chiral rodlike MOFs. To this end, we have used as precursor an enantiopure homochiral hexanuclear wheel (1), derived from the amino acid d-valine, which, after a supramolecular reorganization into a one-dimensional homochiral chain-with the same configuration as 1-led to the formation of a homochiral rodlike MOF (2) exhibiting rare etd topology

Autoluminescent Metal-Organic Frameworks (MOFs): Self-Photoemission of a Highly Stable Thorium MOF

A novel thorium(IV) metal-organic framework (MOF), Th(2,6-naphtalenedicarboxylate)2, has been synthesized via solvothermal reaction of thorium nitrate and 2,6-naphtalendicarboxilyc acid. This compound shows a new structural arrangement with an interesting topology and an excellent thermal resistance, as the framework is stable in air up to 450 \ub0C. Most notably, this MOF, combining the radioactivity of its metal center and the scintillation property of the ligand, has been proven capable of spontaneous photon emission