Ghera: A Repository of Android App Vulnerability Benchmarks

Security of mobile apps affects the security of their users. This has fueled the development of techniques to automatically detect vulnerabilities in mobile apps and help developers secure their apps; specifically, in the context of Android platform due to openness and ubiquitousness of the platform. Despite a slew of research efforts in this space, there is no comprehensive repository of up-to-date and lean benchmarks that contain most of the known Android app vulnerabilities and, consequently, can be used to rigorously evaluate both existing and new vulnerability detection techniques and help developers learn about Android app vulnerabilities. In this paper, we describe Ghera, an open source repository of benchmarks that capture 25 known vulnerabilities in Android apps (as pairs of exploited/benign and exploiting/malicious apps). We also present desirable characteristics of vulnerability benchmarks and repositories that we uncovered while creating Ghera.Comment: 10 pages. Accepted at PROMISE'1

Not too far to help: residential mobility, global identity, and donations to distant beneficiaries

Extant research shows that consumers are more likely to donate to close than distant others, making donations to geographically distant beneficiaries a challenge. This article introduces residential mobility as a novel variable that can lead to increased donations toward distant beneficiaries. This article proposes that residential mobility (vs. stability) leads consumers to have a stronger global identity, whereby they see themselves as world citizens. This global identity results in higher donations to distant beneficiaries. A multi-method approach provides evidence for this prediction. An analysis of a national panel dataset demonstrates that high residential mobility is correlated with donations to distant beneficiaries. Lab experiments, including one with real monetary donations, replicate these effects using both actual moving experience and a residential mobility mindset

Rituals Enhance Consumption

Four experiments tested the novel hypothesis that ritualistic behavior potentiates and enhances the enjoyment of ensuing consumption—an effect found for chocolates, lemonade, and even carrots. Experiment 1 showed that ritual behaviors compared to a no-ritual condition, made chocolate more flavorful, valuable, and deserving of behavioral savoring. Experiment 2 demonstrated that random gestures do not boost consumption like ritualistic gestures do. It further showed that a delay between a ritual and the opportunity to consume heightens enjoyment, which attests to the idea that ritual behavior stimulates goal-directed action (to consume). Experiment 3 found that performing rituals oneself enhanced consumption more than merely watching someone else perform the same ritual, suggesting that personal involvement is crucial for the benefits of rituals to emerge. Last, Experiment 4 provided direct evidence of the underlying process: Rituals enhance consumption enjoyment due to the greater involvement they prompt in the experience

Fabrication and magnetic properties of Sm2Co17 and Sm2Co17/Fe7Co3 magnetic nanowires via AAO templates

AbstractThe Sm2Co17 single-phase and Sm2Co17/Fe7Co3 double-phase nanowire arrays with smaller diameter (around 50nm) have been fabricated into the anodic aluminum oxide (AAO) templates by direct-current electrodeposition. The crystal structure and micrograph of these nanowire arrays were characterized by X-ray diffraction, field-emission scanning electron microscopy and transmission electron microscopy (TEM). It is found that the as-deposited Sm2Co17 nanowires have the amorphous microstructure. The magnetic hysteresis loops obtained by vibrating sample magnetometer (VSM) show that the easily magnetized direction of the Sm2Co17 single-phase and Sm2Co17/Fe7Co3 double-phase nanowire arrays is parallel to the nanowire arrays and the exchange coupling interaction in nanocomposite Sm2Co17/Fe7Co3 is discussed. The study of the Sm2Co17 single-phase and Sm2Co17/Fe7Co3 double-phase nanowires with small diameter may open up new opportunities for the design and control of nanostructures such as the fabrication of magnetic recording devices

Vertex Aided Building Polygonization from Satellite Imagery Applying Deep Learning

Building extraction is an important task in many fields. The use of convolutional neural networks has been proven to be of great success in building extraction from satellite images. This paper presents a deep learning based vertex aided building polygonization method, which takes RGB satellite images as input and outputs building polygons. Unlike other methods which rely on vertex extraction followed by polygonization, our method requires neither pre-defined number of vertices nor thresholding to obtain extracted vertices. The proposed method has the advantage of simplicity in sense of model complexity, and achieved good performance with average precision of 48.1% and intersection over union of 84.1%

Economic and operational appraisal of an allogeneic CAR T-cell bioprocess

Allogeneic CAR T-cell therapies face a variety of challenges from a processing point of view. Pressures to deliver cell therapies at affordable prices demand the development of efficient and cost-effective manufacturing strategies and process technologies for the manufacture of such products. Consideration must be paid to both financial and operational aspects of bioprocess designs from the early stages of product development. This work presents the application of a decisional tool to a case study which describes the manufacture of an allogeneic CAR T-cell therapy. The tool, developed at University College London, is able to quantitatively evaluate bioprocess designs from both a financial and an operational perspective. In this instance the tool has been used to carry out mass balances and equipment sizing calculations in order to compute resource utilisation and cost of goods (COG) for a range of bioprocess designs. Scenario analyses have been used to pinpoint future process improvements that result in feasible manufacturing COG. Furthermore, multi-attribute decision making (MADM) has been employed in order to allow the appraisal of optimal bioprocess designs from both a financial and an operational perspective. The tool outputs provide COG breakdowns for bioprocess designs at a range of annual demands and dose sizes. MADM has been used to provide quantitative output values to key financial and operational performance metrics. Further to this, key process bottlenecks and economic drivers have been identified; these provide a basis for the focus of future process improvements. This work presents a computational technique that can be used to drive effective decision making early on in the development of allogeneic CAR T-cell therapy bioprocesses