Polar Coding for Secret-Key Generation

Practical implementations of secret-key generation are often based on sequential strategies, which handle reliability and secrecy in two successive steps, called reconciliation and privacy amplification. In this paper, we propose an alternative approach based on polar codes that jointly deals with reliability and secrecy. Specifically, we propose secret-key capacity-achieving polar coding schemes for the following models: (i) the degraded binary memoryless source (DBMS) model with rate-unlimited public communication, (ii) the DBMS model with one-way rate-limited public communication, (iii) the 1-to-m broadcast model and (iv) the Markov tree model with uniform marginals. For models (i) and (ii) our coding schemes remain valid for non-degraded sources, although they may not achieve the secret-key capacity. For models (i), (ii) and (iii), our schemes rely on pre-shared secret seed of negligible rate; however, we provide special cases of these models for which no seed is required. Finally, we show an application of our results to secrecy and privacy for biometric systems. We thus provide the first examples of low-complexity secret-key capacity-achieving schemes that are able to handle vector quantization for model (ii), or multiterminal communication for models (iii) and (iv).Comment: 26 pages, 9 figures, accepted to IEEE Transactions on Information Theory; parts of the results were presented at the 2013 IEEE Information Theory Worksho

On the market value of information commodities. I. The nature of information and information commodities

This article lays the conceptual foundations for the study of the market value of information commodities. The terms “information” and “commodity” are given precise definitions in order to characterize “information commodity,” and thus to provide a sound basis for examining questions of pricing. Information is used by marketplace actors to make decisions or to control processes. Thus, we define information as the ability of a goal‐seeking system to decide or control. By “decide” we mean choosing one alternative among several that may be executed in pursuit of a well‐defined objective. “Control” means the ordering of actions. Two factors make it possible to turn something into a commodity: (1) appropriability, and (2) valuability. If something cannot be appropriated (i.e., owned), it cannot be traded; moreover, if it cannot be valued, there is no way to determine for what it might be exchanged. We define an information commodity as a commodity whose function it is to enable the user, a goal‐seeking system, to obtain information, i.e., to otain the ability to decide or control. Books, databases, computer programs, and advisory services are common examples of information commodities. Their market value derives from their capacity to furnish information

Local Algorithms for Block Models with Side Information

There has been a recent interest in understanding the power of local algorithms for optimization and inference problems on sparse graphs. Gamarnik and Sudan (2014) showed that local algorithms are weaker than global algorithms for finding large independent sets in sparse random regular graphs. Montanari (2015) showed that local algorithms are suboptimal for finding a community with high connectivity in the sparse Erd\H{o}s-R\'enyi random graphs. For the symmetric planted partition problem (also named community detection for the block models) on sparse graphs, a simple observation is that local algorithms cannot have non-trivial performance. In this work we consider the effect of side information on local algorithms for community detection under the binary symmetric stochastic block model. In the block model with side information each of the $n$ vertices is labeled $+$ or $-$ independently and uniformly at random; each pair of vertices is connected independently with probability $a/n$ if both of them have the same label or $b/n$ otherwise. The goal is to estimate the underlying vertex labeling given 1) the graph structure and 2) side information in the form of a vertex labeling positively correlated with the true one. Assuming that the ratio between in and out degree $a/b$ is $\Theta(1)$ and the average degree $(a+b) / 2 = n^{o(1)}$, we characterize three different regimes under which a local algorithm, namely, belief propagation run on the local neighborhoods, maximizes the expected fraction of vertices labeled correctly. Thus, in contrast to the case of symmetric block models without side information, we show that local algorithms can achieve optimal performance for the block model with side information.Comment: Due to the limitation "The abstract field cannot be longer than 1,920 characters", the abstract here is shorter than that in the PDF fil

Effect of β-glucan and black tea in a functional bread on short chain fatty acid production by the gut microbiota in a gut digestion/fermentation model

β-Glucan and black tea are fermented by the colonic microbiota producing short chain fatty acids (SCFA) and phenolic acids (PA). We hypothesized that the addition of β-glucan, a dietary fiber, and tea polyphenols to a food matrix like bread will also affect starch digestion in the upper gut and thus further influence colonic fermentation and SCFA production. This study investigated SCFA and PA production from locally developed breads: white bread (WB), black tea bread (BT), β-glucan bread (βG), β-glucan plus black tea bread (βGBT). Each bread was incubated in an in vitro system mimicking human digestion and colonic fermentation. Digestion with α-amylase significantly (p = 0.0001) increased total polyphenol and polyphenolic metabolites from BT bread compared with WB, βG, and βGBT. Total polyphenols in βGBT remained higher (p = 0.016; 1.3-fold) after digestion with pepsin and pancreatin compared with WB. Fermentations containing βG and βGBT produced similar propionate concentrations ranging from 17.5 to 18.6 mmol/L and total SCFA from 46.0 to 48.9 mmol/L compared with control WB (14.0 and 37.4 mmol/L, respectively). This study suggests that combination of black tea with β-glucan in this functional bread did not impact on SCFA production. A higher dose of black tea and β-glucan or in combination with other fibers may be needed to increase SCFA production

Generation of Boundary Manikin Anthropometry

The purpose of this study was to develop 3D digital boundary manikins that are representative of the anthropometry of a unique population. These digital manikins can be used by designers to verify and validate that the components of the spacesuit design satisfy the requirements specified in the Human Systems Integration Requirements (HSIR) document. Currently, the HSIR requires the suit to accommodate the 1st percentile American female to the 99th percentile American male. The manikin anthropometry was derived using two methods: Principal Component Analysis (PCA) and Whole Body Posture Based Analysis (WBPBA). PCA is a statistical method for reducing a multidimensional data set by using eigenvectors and eigenvalues. The goal is to create a reduced data set that encapsulates the majority of the variation in the population. WBPBA is a multivariate analytical approach that was developed by the Anthropometry and Biomechanics Facility (ABF) to identify the extremes of the population for a given body posture. WBPBA is a simulation-based method that finds extremes in a population based on anthropometry and posture whereas PCA is based solely on anthropometry. Both methods yield a list of subjects and their anthropometry from the target population; PCA resulted in 20 female and 22 male subjects anthropometry and WBPBA resulted in 7 subjects' anthropometry representing the extreme subjects in the target population. The subjects anthropometry is then used to 'morph' a baseline digital scan of a person with the same body type to create a 3D digital model that can be used as a tool for designers, the details of which will be discussed in subsequent papers

Pediatric ADHD symptom burden relates to distinct neural activity across executive function domains

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent childhood disorder marked by inattention and/or hyperactivity symptoms. ADHD may also relate to impaired executive function (EF), but is often studied in a single EF task per sample. The current study addresses the question of unique vs. overlapping relations in brain activity across multiple EF tasks and ADHD symptom burden. Three in-scanner tasks drawn from distinct EF domains (cognitive flexibility, working memory, and inhibition) were collected from children with and without an ADHD diagnosis (N = 63). Whole-brain activity and 11 regions of interest were correlated with parent reports of inattention and hyperactivity symptoms. Across the three EF domains, brain activity related to ADHD symptom burden, but the direction and location of these associations differed across tasks. Overall, activity in sensory and default mode network regions related to ADHD, and these relations did not consistently overlap across EF domains. We observed both distinct and overlapping patterns for inattention and hyperactivity symptoms. By studying multiple EF tasks in the same sample, we identified a heterogenous neural profile related to attention symptom burden in children. Our results inform ADHD characterization and treatment and explain some of the variable brain results related to EF and ADHD reported in the literature

Premature Cell Senescence and T Cell Receptor‐Independent Activation of CD8+ T Cells in Juvenile Idiopathic Arthritis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99044/1/art38015.pd

Privacy-Preserving Methods for Sharing Financial Risk Exposures

Unlike other industries in which intellectual property is patentable, the financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. We develop methods for sharing and aggregating such risk exposures that protect the privacy of all parties involved and without the need for a trusted third party. Our approach employs secure multi-party computation techniques from cryptography in which multiple parties are able to compute joint functions without revealing their individual inputs. In our framework, individual financial institutions evaluate a protocol on their proprietary data which cannot be inverted, leading to secure computations of real-valued statistics such a concentration indexes, pairwise correlations, and other single- and multi-point statistics. The proposed protocols are computationally tractable on realistic sample sizes. Potential financial applications include: the construction of privacy-preserving real-time indexes of bank capital and leverage ratios; the monitoring of delegated portfolio investments; financial audits; and the publication of new indexes of proprietary trading strategies

Identification of and Molecular Basis for SIRT6 Loss-of-Function Point Mutations in Cancer

SummaryChromatin factors have emerged as the most frequently dysregulated family of proteins in cancer. We have previously identified the histone deacetylase SIRT6 as a key tumor suppressor, yet whether point mutations are selected for in cancer remains unclear. In this manuscript, we characterized naturally occurring patient-derived SIRT6 mutations. Strikingly, all the mutations significantly affected either stability or catalytic activity of SIRT6, indicating that these mutations were selected for in these tumors. Further, the mutant proteins failed to rescue sirt6 knockout (SIRT6 KO) cells, as measured by the levels of histone acetylation at glycolytic genes and their inability to rescue the tumorigenic potential of these cells. Notably, the main activity affected in the mutants was histone deacetylation rather than demyristoylation, pointing to the former as the main tumor-suppressive function for SIRT6. Our results identified cancer-associated point mutations in SIRT6, cementing its function as a tumor suppressor in human cancer

T Cell Receptor-Independent, CD31/IL-17A-Driven Inflammatory Axis Shapes Synovitis in Juvenile Idiopathic Arthritis

T cells are considered autoimmune effectors in juvenile idiopathic arthritis (JIA), but the antigenic cause of arthritis remains elusive. Since T cells comprise a significant proportion of joint-infiltrating cells, we examined whether the environment in the joint could be shaped through the inflammatory activation by T cells that is independent of conventional TCR signaling. We focused on the analysis of synovial fluid (SF) collected from children with oligoarticular and rheumatoid factor-negative polyarticular JIA. Cytokine profiling of SF showed dominance of five molecules including IL-17A. Cytometric analysis of the same SF samples showed enrichment of αβT cells that lacked both CD4 and CD8 co-receptors [herein called double negative (DN) T cells] and also lacked the CD28 costimulatory receptor. However, these synovial αβT cells expressed high levels of CD31, an adhesion molecule that is normally employed by granulocytes when they transit to sites of injury. In receptor crosslinking assays, ligation of CD31 alone on synovial CD28nullCD31+ DN αβT cells effectively and sufficiently induced phosphorylation of signaling substrates and increased intracytoplasmic stores of cytokines including IL-17A. CD31 ligation was also sufficient to induce RORγT expression and trans-activation of the IL-17A promoter. In addition to T cells, SF contained fibrocyte-like cells (FLC) expressing IL-17 receptor A (IL-17RA) and CD38, a known ligand for CD31. Stimulation of FLC with IL-17A led to CD38 upregulation, and to production of cytokines and tissue-destructive molecules. Addition of an oxidoreductase analog to the bioassays suppressed the CD31-driven IL-17A production by T cells. It also suppressed the downstream IL-17A-mediated production of effectors by FLC. The levels of suppression of FLC effector activities by the oxidoreductase analog were comparable to those seen with corticosteroid and/or biologic inhibitors to IL-6 and TNFα. Collectively, our data suggest that activation of a CD31-driven, αβTCR-independent, IL-17A-mediated T cell-FLC inflammatory circuit drives and/or perpetuates synovitis. With the notable finding that the oxidoreductase mimic suppresses the effector activities of synovial CD31+CD28null αβT cells and IL-17RA+CD38+ FLC, this small molecule could be used to probe further the intricacies of this inflammatory circuit. Such bioactivities of this small molecule also provide rationale for new translational avenue(s) to potentially modulate JIA synovitis