Search

Although the intrinsic mechanisms that control whether stem cells divide symmetrically or asymmetrically underlie tissue growth and homeostasis, they remain poorly defined. We report that the RNAbinding protein fragile X mental retardation protein (FMRP) limits the symmetric division, and resulting expansion, of the stem cell population during adaptive intestinal growth in Drosophila. The elevated insulin sensitivity that FMRP-deficient progenitor cells display contributes to their accelerated expansion, which is suppressed by the depletion of insulinsignaling components. This FMRP activity is mediated solely via a second conserved RNA-binding protein, LIN-28, known to boost insulin signaling in stem cells. Via LIN-28, FMRP controls progenitor cell behavior by post-transcriptionally repressing the level of insulin receptor (InR). This study identifies the stem cell-based mechanismby which FMRP controls tissue adaptation, and it raises the possibility that defective adaptive growth underlies the accelerated growth, gastrointestinal, and other symptoms that affect fragile X syndrome patients. [ABSTRACT FROM AUTHOR]

Today’s mobile devices have changed the way we interact with technology. Internet, cloud access, online banking, instant messaging, and file exchange through the cloud are just a handful of the myriad of smartphone services that we make use of every day. At the same time, the very enablers of these services–mobile internet providers and cloud platforms that host them–pose several threats to the anonymity of our communications. In this paper, we consider the problem of providing end-to-end anonymous communications and file exchange under the cooperative privacy threat of involved parties including network operators and cloud providers, which actively tamper with the communication. We propose a solution for delay-tolerant applications (similar to Whatsapp or Email) and prove the security properties of the protocol under this strong attack model. Finally, we present an experimental analysis of the efficiency of our protocol in terms of performance overhead. [ABSTRACT FROM AUTHOR]

Concept drift is the problem that the statistical properties of the data generating process change over time. Recently, the Time Decaying Adaptive Prediction (TDAP) algorithm 1 1 Scalable Time-Decaying Adaptive Prediction Algorithm. (Tan et al., 2016). was proposed to address the problem of concept drift. TDAP was designed to account for the effect of drifting concepts by discounting the contribution of previous learning examples using an exponentially decaying factor. The drawback of TDAP is that the rate of its decaying factor is required to be manually tuned. To address this drawback, we propose a new adaptive online algorithm, called Follow-the-Regularized-Leader with Adaptive Decaying Proximal (FTRL-ADP). There are two novelties in our approach. First, we derive a rule to automatically update the decaying rate, based on a rigorous theoretical analysis. Second, we use a concept drift detector to identify major drifts and reset the update rule accordingly. Comparative experiments with 14 datasets and 6 other online algorithms show that FTRL-ADP is most advantageous in noisy environments with real drifts. [ABSTRACT FROM AUTHOR]