First Generation Immigrant Adolescents’ Motives to Volunteer

One of the ways immigrant adolescents may try to pursue their dreams in the new place is by volunteering. Volunteerism is a socially important activity which altruistically helps the other and the local community. It is unclear whether volunteerism is an instrument for social inclusion, or it is the goal in itself. The motives of 1st generation immigrant adolescents to volunteer are still an enigma. Hence, this study aims to answer two different research questions; (1) what motivates them to volunteer? and (2) is there a difference between 1st generation immigrant adolescents and native adolescents in their motivation to volunteer? The analysis yields a higher motivated 1st generation immigrant adolescents compared to the native adolescents. First generation immigrant adolescents perceive volunteerism as an integrative action for their social participation. Volunteerism helps them to understand the new culture and it is an indication for their importance in the new community

Private Computations on Streaming Data

We present a framework for privacy-preserving streaming algorithms which combine the memory-efficiency of streaming algorithms with strong privacy guarantees. These algorithms enable some number of servers to compute aggregate statistics efficiently on large quantities of user data without learning the user\u27s inputs. While there exists limited prior work that fits within our model, our work is the first to formally define a general framework, interpret existing methods within this general framework, and develop new tools broadly applicable to this model. To highlight our model, we designed and implemented a new privacy-preserving streaming algorithm to compute heavy hitters, which are the most frequent elements in a data stream. We provide a performance comparison between our system and Poplar, the only other private statistics algorithm which supports heavy hitters. We benchmarked ours and Poplar\u27s systems and provided direct performance comparisons within the same hardware platform. Of note, Poplar requires linear space compared to our poly-logarithmic space, meaning our system is the first to compute heavy hitters within the privacy-preserving streaming model. A small memory footprint allows our algorithm (among other benefits) to run efficiently on a very large input sizes without running out of memory or crashing

Pediatric T- and NK-cell lymphomas: new biologic insights and treatment strategies

T- and natural killer (NK)-cell lymphomas are challenging childhood neoplasms. These cancers have varying presentations, vast molecular heterogeneity, and several are quite unusual in the West, creating diagnostic challenges. Over 20 distinct T- and NK-cell neoplasms are recognized by the 2008 World Health Organization classification, demonstrating the diversity and potential complexity of these cases. In pediatric populations, selection of optimal therapy poses an additional quandary, as most of these malignancies have not been studied in large randomized clinical trials. Despite their rarity, exciting molecular discoveries are yielding insights into these clinicopathologic entities, improving the accuracy of our diagnoses of these cancers, and expanding our ability to effectively treat them, including the use of new targeted therapies. Here, we summarize this fascinating group of lymphomas, with particular attention to the three most common subtypes: T-lymphoblastic lymphoma, anaplastic large cell lymphoma, and peripheral T-cell lymphoma-not otherwise specified. We highlight recent findings regarding their molecular etiologies, new biologic markers, and cutting-edge therapeutic strategies applied to this intriguing class of neoplasms

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk

Prio+: Private Aggregate Statistics via Boolean Shares

This paper introduces Prio+, a privacy-preserving system for the collection of aggregate statistics, with the same model and goals in mind as the original and highly influential Prio paper by Henry Corrigan-Gibbs and Dan Boneh (NSDI 2017). As in the original Prio, each client holds a private data value (e.g. number of visits to a particular website) and a small set of servers privately compute statistical functions over the set of client values (e.g. the average number of visits). To achieve security against faulty or malicious clients, unlike Prio, Prio+ clients use Boolean secret-sharing instead of zero-knowledge proofs to convince servers that their data is of the correct form and Prio+ servers execute a share conversion protocol as needed in order to properly compute over client data. This allows us to ensure that clients' data is properly formatted essentially for free, and the work shifts to novel share-conversion protocols between servers, where some care is needed to make it efficient. Our overall approach is simpler than Prio and our Prio+ strategy reduces the client's computational burden by at least two orders of magnitude (or more depending on the statistic) while keeping server costs comparable to Prio. Prio+ permits computation of exactly the same wide range of complex statistics as the original Prio protocol, including high-dimensional linear regression over private values held by clients. We report detailed benchmarks of our Prio+ implementation and compare these to both the original Go implementation of Prio and the Mozilla implementation of Prio. Our Prio+ software is open-source and released with the same license as Prio