"If You Can't Beat them, Join them": A Usability Approach to Interdependent Privacy in Cloud Apps

Cloud storage services, like Dropbox and Google Drive, have growing ecosystems of 3rd party apps that are designed to work with users' cloud files. Such apps often request full access to users' files, including files shared with collaborators. Hence, whenever a user grants access to a new vendor, she is inflicting a privacy loss on herself and on her collaborators too. Based on analyzing a real dataset of 183 Google Drive users and 131 third party apps, we discover that collaborators inflict a privacy loss which is at least 39% higher than what users themselves cause. We take a step toward minimizing this loss by introducing the concept of History-based decisions. Simply put, users are informed at decision time about the vendors which have been previously granted access to their data. Thus, they can reduce their privacy loss by not installing apps from new vendors whenever possible. Next, we realize this concept by introducing a new privacy indicator, which can be integrated within the cloud apps' authorization interface. Via a web experiment with 141 participants recruited from CrowdFlower, we show that our privacy indicator can significantly increase the user's likelihood of choosing the app that minimizes her privacy loss. Finally, we explore the network effect of History-based decisions via a simulation on top of large collaboration networks. We demonstrate that adopting such a decision-making process is capable of reducing the growth of users' privacy loss by 70% in a Google Drive-based network and by 40% in an author collaboration network. This is despite the fact that we neither assume that users cooperate nor that they exhibit altruistic behavior. To our knowledge, our work is the first to provide quantifiable evidence of the privacy risk that collaborators pose in cloud apps. We are also the first to mitigate this problem via a usable privacy approach.Comment: Authors' extended version of the paper published at CODASPY 201

Strong electron correlations in the normal state of FeSe0.42Te0.58

We investigate the normal state of the '11' iron-based superconductor FeSe0.42Te0.58 by angle resolved photoemission. Our data reveal a highly renormalized quasiparticle dispersion characteristic of a strongly correlated metal. We find sheet dependent effective carrier masses between ~ 3 - 16 m_e corresponding to a mass enhancement over band structure values of m*/m_band ~ 6 - 20. This is nearly an order of magnitude higher than the renormalization reported previously for iron-arsenide superconductors of the '1111' and '122' families but fully consistent with the bulk specific heat.Comment: 5 pages, 4 figures, to appear in Phys. Rev. Let

Novel statistical approaches for non-normal censored immunological data: analysis of cytokine and gene expression data

Background: For several immune-mediated diseases, immunological analysis will become more complex in the future with datasets in which cytokine and gene expression data play a major role. These data have certain characteristics that require sophisticated statistical analysis such as strategies for non-normal distribution and censoring. Additionally, complex and multiple immunological relationships need to be adjusted for potential confounding and interaction effects. Objective: We aimed to introduce and apply different methods for statistical analysis of non-normal censored cytokine and gene expression data. Furthermore, we assessed the performance and accuracy of a novel regression approach in order to allow adjusting for covariates and potential confounding. Methods: For non-normally distributed censored data traditional means such as the Kaplan-Meier method or the generalized Wilcoxon test are described. In order to adjust for covariates the novel approach named Tobit regression on ranks was introduced. Its performance and accuracy for analysis of non-normal censored cytokine/gene expression data was evaluated by a simulation study and a statistical experiment applying permutation and bootstrapping. Results: If adjustment for covariates is not necessary traditional statistical methods are adequate for non-normal censored data. Comparable with these and appropriate if additional adjustment is required, Tobit regression on ranks is a valid method. Its power, type-I error rate and accuracy were comparable to the classical Tobit regression. Conclusion: Non-normally distributed censored immunological data require appropriate statistical methods. Tobit regression on ranks meets these requirements and can be used for adjustment for covariates and potential confounding in large and complex immunological datasets

Swarm Keeping Strategies for Spacecraft under J_2 and Atmospheric Drag Perturbations

This paper presents several new open-loop guidance methods for spacecraft swarms composed of hundreds to thousands of agents with each spacecraft having modest capabilities. These methods have three main goals: preventing relative drift of the swarm, preventing collisions within the swarm, and minimizing the propellant used throughout the mission. The development of these methods progresses by eliminating drift using the Hill-Clohessy-Wiltshire equations, removing drift due to nonlinearity, and minimizing the J_2 drift. In order to verify these guidance methods, a new dynamic model for the relative motion of spacecraft is developed. These dynamics include the two main disturbances for spacecraft in Low Earth Orbit (LEO), J_2 and atmospheric drag. Using this dynamic model, numerical simulations are provided at each step to show the effectiveness of each method and to see where improvements can be made. The main result is a set of initial conditions for each spacecraft in the swarm which provides the trajectories for hundreds of collision-free orbits in the presence of J_2. Finally, a multi-burn strategy is developed in order to provide hundreds of collision-free orbits under the influence of atmospheric drag. This last method works by enforcing the initial conditions multiple times throughout the mission thereby providing collision-free trajectories for the duration of the mission

Antiferromagnetic interlayer exchange coupling across an amorphous metallic spacer layer

By means of magneto-optical Kerr effect we observe for the first time antiferromagnetic coupling between ferromagnetic layers across an amorphous metallic spacer layer. Biquadratic coupling occurs at the transition from a ferromagnetically to an antiferromagnetically coupled region. Scanning tunneling microscopy images of all involved layers are used to extract thickness fluctuations and to verify the amorphous state of the spacer. The observed antiferromagnetic coupling behavior is explained by RKKY interaction taking into account the amorphous structure of the spacer material.Comment: Typset using RevTex, 4 pages with 4 figures (.eps

Optimizing integrated steelworks process off-gas distribution through Economic Hybrid Model Predictive Control and Echo State Networks

Steel production in integrated steelworks involves the simultaneous production of various byproducts, including process off-gases that are usually exploited for generating electricity in the internal power plant, heat and steam. Their discontinuous production is managed through complex network, gasholders and torches, which must be managed with stringent operational constraints. In this paper we present a supervision and control system designed to optimize the economic management of the distribution of process off-gases that also allows minimizing the environmental impact. The system implements a digital twin based mainly on machine learning techniques, including Echo State Networks, and a hierarchical optimization system, which first level is based on an economic model predictive approach and the second level is based on the economic hybrid model predictive control. This system allows to effectively maximize the use of off-gases while minimizing the environmental impact of their use up to 97%

Microparticles from patients with metabolic syndrome induce vascular hypo-reactivity via Fas/Fas-ligand pathway in mice

Peer reviewedPublisher PD

Bonding of gold nanoclusters to oxygen vacancies on rutile TiO2(110)

Through an interplay between scanning tunneling microscopy (STM) and density functional theory (DFT) calculations, we show that bridging oxygen vacancies are the active nucleation sites for Au clusters on the rutile TiO2(110) surface. We find that a direct correlation exists between a decrease in density of vacancies and the amount of Au deposited. From the DFT calculations we find that the oxygen vacancy is indeed the strongest Au binding site. We show both experimentally and theoretically that a single oxygen vacancy can bind 3 Au atoms on average. In view of the presented results, a new growth model for the TiO2(110) system involving vacancy-cluster complex diffusion is presented

Cloning and characterization of a trypsin-encoding cDNA of the human body louse Pediculus humanus

Abstract From a cDNA library of the whole insect, a trypsin gene of Pediculus humanus has been cloned and sequenced. The 908 bp clone has an open reading frame of 759 bp, which encodes a pre-proenzyme with 253 amino acid residues. A sixteen-residue N-terminal signal peptide is followed by a twelve-residue activation peptide with putative cleavage sites at Gly16 and Tyr28. The deduced amino acid sequence has several features typical of trypsin proteases and an overall identity of 35 -43% with the trypsins of several haematophagous Diptera. The 1.0 kb genomic trypsin gene contains three introns of 102, 79 and 80 nucleotides following the codons for Gly16, Gln74 and Ala155, respectively. Only a single gene seems to be present. In Northern blot analysis, unfed first instar larvae have an identical or slightly lower level of trypsin mRNA than fed adult lice, and in adults 2-24 h after the bloodmeal this gene shows a constitutive expression. After in vitro transcription and translation, the activation peptide is cleaved by chymotrypsin, a so far unreported phenomenon in trypsin activation