Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles

In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who think differently have not worked well. In this paper, we hypothesize, first, that previous approaches have not worked because they have been direct -- they have tried to explicitly connect people with those having opposing views on sensitive issues. Second, that neither recommendation or presentation of information by themselves are enough to encourage behavioral change. We propose a platform that mixes a recommender algorithm and a visualization-based user interface to explore recommendations. It recommends politically diverse profiles in terms of distance of latent topics, and displays those recommendations in a visual representation of each user's personal content. We performed an "in the wild" evaluation of this platform, and found that people explored more recommendations when using a biased algorithm instead of ours. In line with our hypothesis, we also found that the mixture of our recommender algorithm and our user interface, allowed politically interested users to exhibit an unbiased exploration of the recommended profiles. Finally, our results contribute insights in two aspects: first, which individual differences are important when designing platforms aimed at behavioral change; and second, which algorithms and user interfaces should be mixed to help users avoid cognitive mechanisms that lead to biased behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User Interfaces 201

Discovering Polarized Communities in Signed Networks

Signed networks contain edge annotations to indicate whether each interaction is friendly (positive edge) or antagonistic (negative edge). The model is simple but powerful and it can capture novel and interesting structural properties of real-world phenomena. The analysis of signed networks has many applications from modeling discussions in social media, to mining user reviews, and to recommending products in e-commerce sites. In this paper we consider the problem of discovering polarized communities in signed networks. In particular, we search for two communities (subsets of the network vertices) where within communities there are mostly positive edges while across communities there are mostly negative edges. We formulate this novel problem as a "discrete eigenvector" problem, which we show to be NP-hard. We then develop two intuitive spectral algorithms: one deterministic, and one randomized with quality guarantee $\sqrt{n}$ (where $n$ is the number of vertices in the graph), tight up to constant factors. We validate our algorithms against non-trivial baselines on real-world signed networks. Our experiments confirm that our algorithms produce higher quality solutions, are much faster and can scale to much larger networks than the baselines, and are able to detect ground-truth polarized communities

Host-interactor screens of Phytophthora infestans RXLR proteins reveal vesicle trafficking as a major effector-targeted process

Pathogens modulate plant cell structure and function by secreting effectors into host tissues. Effectors typically function by associating with host molecules and modulating their activities. This study aimed to identify the host processes targeted by the RXLR class of host-translocated effectors of the potato blight pathogen Phytophthora infestans. To this end, we performed an in planta protein-protein interaction screen by transiently expressing P. infestans RXLR effectors in Nicotiana benthamiana leaves followed by co-immunoprecipitation and liquid chromatography tandem mass spectrometry. This screen generated an effector-host protein interactome matrix of 59 P. infestans RXLR effectors x 586 N. benthamiana proteins. Classification of the host interactors into putative functional categories revealed over 35 biological processes possibly targeted by P. infestans. We further characterized the PexRD12/31 family of RXLR-WY effectors, which associate and co-localize with components of the vesicle trafficking machinery. One member of this family, PexRD31, increased the number of FYVE positive vesicles in N. benthamiana cells. FYVE positive vesicles also accumulated in leaf cells near P. infestans hyphae, indicating that the pathogen may enhance endosomal trafficking during infection. This interactome data set will serve as a useful resource for functional studies of P. infestans effectors and of effector-targeted host processes

Full wafer integration of NEMS on CMOS by nanostencil lithography

Wafer scale nanostencil lithography is used to define 200 nm scale mechanically resonating silicon cantilevers monolithically integrated into CMOS circuits. We demonstrate the simultaneous patterning of ~2000 nanodevices by post-processing standard CMOS wafers using one single metal evaporation, pattern transfer to silicon and subsequent etch of the sacrificial layer. Resonance frequencies around 1.5 MHz were measured in air and vacuum and tuned by applying dc voltages of 10V and 1V respectively.LMIS

Vascular Endothelial Growth Factor Mediates Intracrine Survival in Human Breast Carcinoma Cells through Internally Expressed VEGFR1/FLT1

Shalom Avraham and colleagues' study provides evidence of a survival system in breast cancer cells by which VEGF acts as an internal autocrine survival factor through its binding to VEGFR1

SARS-CoV-2 Catalonia contact tracing program : evaluation of key performance indicators

Background: Guidance on SARS-CoV-2 contact tracing indicators have been recently revised by international public health agencies. The aim of the study is to describe and analyse contact tracing indicators based on Catalonia's (Spain) real data and proposing to update them according to recommendations. Methods: Retrospective cohort analysis including Catalonia's contact tracing dataset from 20 May until 31 December 2020. Descriptive statistics are performed including sociodemographic stratification by age, and differences are assessed over the study period. Results: We analysed 923,072 contacts from 301,522 SARS-CoV-2 cases with identified contacts (67.1% contact tracing coverage). The average number of contacts per case was 4.6 (median 3, range 1-243). A total of 403,377 contacts accepted follow-up through three phone calls over a 14-day quarantine period (84.5% of contacts requiring follow-up). The percentage of new cases declared as contacts 14 days prior to diagnosis evolved from 33.9% in May to 57.9% in November. All indicators significantly improved towards the target over time (p < 0.05 for all four indicators). Conclusions: Catalonia's SARS-CoV-2 contact tracing indicators improved over time despite challenging context. The critical revision of the indicator's framework aims to provide essential information in control policies, new indicators proposed will improve system delay's follow-up. The study provides information on COVID-19 indicators framework experience from country's real data, allowing to improve monitoring tools in 2021-2022. With the SARS-CoV-2 pandemic being so harmful to health systems and globally, is important to analyse and share contact tracing data with the scientific community