Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Resilience-Complexity Tradeoff of Network Coding in Dynamic P2P Networks

Most current-generation P2P content distribution protocols use line-granularity blocks to distribute content to all the peers in a decentralized fashion. Such protocols often suffer from a significant degree of imbalance in block distributions, such that certain blocks become rare or even unavailable, adversely affecting content availability. It has been pointed out that randomized network coding may improve block availability in P2P networks, as coded blocks are equally innovative and useful to peers. However, the computational complexity of network coding mandates that, in reality, network coding needs to be performed within segments, each containing a subset of blocks. In this paper, using both theoretical analysis and simulations, we quantitatively evaluate how segment-based network coding may improve resilience to peer dynamics and content availability. The objective of this paper is to explore the fundamental tradeoff between the resilience gain of network coding and its inherent coding complexity. We introduce a differential equations approach to quantify the resilience gain of network coding as a function of the number of blocks in a segment, as well as various other tunable parameters. We conclude that a small number of blocks in each segment is sufficient to realize the major benefits of network coding, with acceptable coding complexity.
Mechanistic features of CAG•CTG repeat contractions in cultured cells revealed by a novel genetic assay

Trinucleotide repeats (TNRs) undergo high frequency mutagenesis to cause at least 15 neurodegenerative diseases. To understand better the molecular mechanisms of TNR instability in cultured cells, a new genetic assay was created using a shuttle vector. The shuttle vector contains a promoter-TNR-reporter gene construct whose expression is dependent on TNR length. The vector harbors the SV40 ori and large T antigen gene, allowing portability between primate cell lines. The shuttle vector is propagated in cultured cells, then recovered and analyzed in yeast using selection for reporter gene expression. We show that (CAG•CTG)25−33 contracts at frequencies as high as 1% in 293T and 293 human cells and in COS-1 monkey cells, provided that the plasmid undergoes replication. Hairpin-forming capacity of the repeat sequence stimulated contractions. Evidence for a threshold was observed between 25 and 33 repeats in COS-1 cells, where contraction frequencies increased sharply (up 720%) over a narrow range of repeat lengths. Expression of the mismatch repair protein Mlh1 does not correlate with repeat instability, suggesting contractions are independent of mismatch repair in our system. Together, these findings recapitulate certain features of human genetics and therefore establish a novel cell culture system to help provide new mechanistic insights into CAG•CTG repeat instability.
Image seam carving using depth assisted saliency map

Retargeting algorithms are needed to transfer an image from a device to another with different size and resolution. The goal is to preserve the best visual quality for important objects of the original image. In order to reduce image size, pixels should be removed from less important parts of the image. Therefore, we need an energy function to select less important pixels in seam carving. Various energy functions have been proposed in previous works to minimize the distortion in salient objects. In this paper we combine three different importance maps to form a new energy map. We first use both gradient and depth maps to highlight the values in the saliency map, eventually generates the final energy map. Experimental results using the proposed energy map show better visual appearance in comparison to previous algorithms even at high resizing percentage. The visual artifacts that cause shape deformation in salient objects and deteriorates geometrical consistency of the scene are considerably reduced in our proposed algorithm.
Where are we in transcribing French broadcast news?

Given the high flexional properties of the French language, transcribing French broadcast news (BN) is more challenging than English BN. This is in part due to the largenumber of homophones in the inflected forms. This paper describes advances in automatic processing of broadcast news speech in French based on recent improvements to the LIMSI English system. The main differences between the English and French BN systems are: a 200k vocabulary to overcome the lower lexical coverage in French (including contextual pronunciations to model liaisons), a case sensitive language model, and the use of a POS based language model to lower the impact of homophonic gender and number disagreement. The resulting system was evaluated in the first French TECHNOLANGUE-ESTERASR benchmark test. This system achieved the lowest word error rate in this evaluation by a significant margin. We also report on a 1xRT version of this system.
Visualization and Classification of Documents: A New Probabilistic Model to Automated Text Classification

A novel two-dimensional representation of documents may be used both to visualize and classify textual documents and to build classification schemes that may be used to browse, explore, and retrieve resources from Digital Library Management System (DLMS)s. We propose a mathematical formalization of the two-dimensional approach where documents’ coordinates are defined as probabilities. An extension of the two-dimensional classification algorithm, named selective re-projection, is also proposed. Experiments showed that this approach confirmed to be an alternative to classical classification methods for text classification. In particular the low requirements of space and time and the intuitive representation of the two-dimensional plots make this approach a valuable support for analysis of textual collections.
Glioblastoma Formation from Cell Population Depleted of Prominin1-Expressing Cells

Prominin1 (Prom1, also known as CD133 in human) has been widely used as a marker for cancer stem cells (CSCs), which self-renew and are tumorigenic, in malignant tumors including glioblastoma multiforme (GBM). However, there is other evidence showing that Prom1-negative cancer cells also form tumors in vivo. Thus it remains controversial whether Prom1 is a bona fide marker for CSCs. To verify if Prom1-expressing cells are essential for tumorigenesis, we established a mouse line, whose Prom1-expressing cells can be eliminated conditionally by a Cre-inducible DTA gene on the Prom1 locus together with a tamoxifen-inducible CreERTM, and generated glioma-initiating cells (GICs-LD) by overexpressing both the SV40 Large T antigen and an oncogenic H-RasL61 in neural stem cells of the mouse line. We show here that the tamoxifen-treated GICs-LD (GICs-DTA) form tumor-spheres in culture and transplantable GBM in vivo. Thus, our studies demonstrate that Prom1-expressing cells are dispensable for gliomagenesis in this mouse model.
Protection of Web User ’ s Privacy by Securing Browser from Web Privacy Attacks

The Internet and World Wide Web being an essential part of everyone’s life, the users have become more conscious about their privacy. The user’s web privacy unfortunately, is not focused much by the current browsers. This paper focuses on the attacks which compromises user’s anonymity, grab user’s private data. It highlights the privacy attacks such as history sniffing, web beacons, browser fingerprinting. We focus on the protection of user’s information which is transferred over the network to the web server without the users consent rather than stealing attempts which fools the user and trap them to install malicious software which perform the theft, using social engineering techniques. A generic algorithm has been proposed in this paper which will stop the attacker from violating privacy. We have proposed a secure way of interaction between browser objects through browser API’S and the JavaScript. We developed an add-on which implements the proposed solution.
Hamming Compressed Sensing

Compressed sensing (CS) and 1-bit CS cannot directly recover quantized signals and require time consuming recovery. In this paper, we introduce \textit{Hamming compressed sensing} (HCS) that directly recovers a k-bit quantized signal of dimensional $n$ from its 1-bit measurements via invoking $n$ times of Kullback-Leibler divergence based nearest neighbor search. Compared with CS and 1-bit CS, HCS allows the signal to be dense, takes considerably less (linear) recovery time and requires substantially less measurements ($\mathcal O(\log n)$). Moreover, HCS recovery can accelerate the subsequent 1-bit CS dequantizer. We study a quantized recovery error bound of HCS for general signals and "HCS+dequantizer" recovery error bound for sparse signals. Extensive numerical simulations verify the appealing accuracy, robustness, efficiency and consistency of HCS.
GMU: Genuine Multiversion Update-Serializable Partial Data Replication

In this article we introduce GMU, a genuine partial replication protocol for transactional systems, which exploits an innovative, highly scalable, distributed multiversioning scheme. Unlike existing multiversion-based solutions, GMU does not rely on any global logical clock, which may represent a contention point and a major impairment to system scalability. Also, GMU never aborts read-only transactions and spares them from undergoing distributed validation schemes. This makes GMU particularly efficient in presence of read-intensive workloads, as typical of a wide range of real-world applications. GMU guarantees the Extended Update Serializability (EUS) isolation level. This consistency criterion is particularly attractive as it is sufficiently strong to ensure correctness even for very demanding applications (such as TPC-C), but is also weak enough to allow efficient and scalable implementations, such as GMU. Further, unlike several relaxed consistency models proposed in literature, EUS shows simple and intuitive semantics, thus being an attractive consistency model for ordinary programmers. We integrated GMU in a popular open source in-memory transactional data grid, namely Infinispan. On the basis of a wide experimental study performed on heterogeneous platforms and using industry standard benchmarks (namely TPC-C and YCSB), we show that GMU achieves almost linear scalability and that it introduces reduced overhead, with respect to solutions ensuring non-serializable semantics, in a wide range of workloads.
Recruitment of older African Americans for survey research: a process evaluation of the community and church-based strategy in The Durham Elders Project.

PURPOSE The disproportionately high burden of morbidity and mortality among older African Americans is due, in part, to a lack of understanding of the factors contributing to these outcomes. In order to more fully understand the factors that contribute to African American morbidity and mortality, researchers must identify strategies for increasing the inclusion of older African Americans in research on social and health phenomena. DESIGN AND METHODS This article is a process evaluation describing the successes and challenges associated with recruitment of older African Americans into research. It considers an effort to nurture collaboration between university and community institutions to both facilitate research endeavors and offer meaningful and culturally-appropriate contributions to the community. RESULTS The primary challenges discovered in this observational process evaluation of a church-based recruitment strategy include the effective coordination of a community research advisory board, ensuring participant autonomy, and reducing concerns of exploitation among potential participants. IMPLICATIONS A strategy of coordinating a community research advisory board to incorporate the views of community members and to drive a church-based recruitment procedure provides a starting point for tapping into an immensely important segment of society historically ignored by the research community.
Strong and consistent natural selection associated with armour reduction in sticklebacks

Measuring the strength of natural selection is tremendously important in evolutionary biology, but remains a challenging task. In this work, we analyse the characteristics of selection for a morphological change (lateral‐plate reduction) in the threespine stickleback Gasterosteus aculeatus. Adaptation to freshwater, leading with the reduction or loss of the bony lateral armour, has occurred in parallel on numerous occasions in this species. Completely‐plated and low‐plated sticklebacks were introduced into a pond, and the phenotypic changes were tracked for 20 years. Fish from the last generation were genotyped for the Ectodysplasin‐A (Eda) locus, the major gene involved in armour development. We found a strong fitness advantage for the freshwater‐type fish (on average, 20% fitness advantage for the freshwater morph, and 92% for the freshwater genotype). The trend is best explained by assuming that this fitness advantage is maximum at the beginning of the invasion and decreases with time. Such fitness differences provide a quantifiable example of rapid selection‐driven phenotypic evolution associated with environmental change in a natural population.
Computational Semiotics : A New Aproach for the Study of Intelligent System Part II : Theory and Application

The aim of this paper is to introduce the theoretical foundations of an approach for intelligent systems development. Derived from semiotics, a classic discipline in human sciences, the theory developed provides a mathematical framework for the concept of knowledge and for knowledge processing. As a result, a new perspective to study and to develop intelligent systems emerges. In part I, we focused on the essentials of such a theory. It included the background needed from semiotics, describing the relationship between semiotics, intelligent systems and cognition. A taxonomy of the elementary types of knowledge was proposed, followed by another classification considered by the point of view of its application in a cognitive system. In addition, a mathematical definition of objects and object networks, were proposed. Here, in part II, we proceed introducing the issues concerning knowledge modeling and system development. The elementary types of knowledge are modelled using the concepts of objects and object networks. Based on the idea of applied knowledge, a general architecture for an intelligent system is suggested. An example concerning control of an autonomous vehicle is addressed to illustrate the use of computational semiotics in developing intelligent systems, and to show how intelligent systems can be implemented. Finally, the conclusions and further work are addressed.
Alamouti Multiuser MIMO OSUC Detection and Antenna Selection

The existing uplink multi-user detection algorithm based on maximizing signal-to-noise-plus-interference-ratio (SINR) doesn't take full advantage of the system diversity benefit. A new order successive user cancellation (OSUC) detection algorithm is presented in this paper. However, OSUC suffers from error propagation especially with few receive antennas (RF chains). antenna selection (AS) technology is introduced into OSUC detection for the low hardware cost. Simulations show OSUC detection algorithm outperforms the existing detection algorithm. For OSUC detection with receive AS, it achieves almost all the diversity benefit of a full complexity system utilizing all receive antennas when the number of selected antennas is not under 2(P - 1) +1.
On the Computation of Intrinsic Volumes

Many methods are known to compute the intrinsic volumes of a set given in a digital image. However, most of these methods have the disadvantage that they are not multigrid convergent. This means that the computed values do not converge to the true values for increasing resolution of the digital image. One exception is the volume which can easily be estimated by counting pixels and the Euler characteristic for which Kiderlen [14] presented a multigrid convergent estimator for polyconvex sets with some regularity assumptions. We propose two methods for the computation of all d + 1 intrinsic volumes which are multigrid convergent forUPR-sets under mild regularity assumptions. TheUPR-class contains sets which can be represented as a nite union of compact sets with positive reach and include polyconvex sets. We provide numerical results and compare this approach with other methods known in the literature. 2010 Mathematics Subject Classication: Primary 65D18; Secondary 68U05, 52A38
Using random forest to find Nuclear Export Signals (NESs) in proteins of Arabidopsis thaliana

This paper presents a new computational strategy for predicting Nuclear Export Signals (NESs) in proteins of the model plant Arabidopsis thaliana based on a random forest classifier. NESs are amino acid sequences that enable a protein to interact with a nuclear receptor and in this way to be exported from the nucleus to the
Elsevier Editorial System(tm) for Schizophrenia Research Manuscript Draft

extrinsic connectivity within the magnetic mismatch negativity brain network in schizophrenia: a preliminary study. Abnormal intrinsic and extrinsic connectivity within the magnetic mismatch negativity brain network in schizophrenia: a preliminary study. Online is checked for eligibility for copyright before being made available in the live archive. URLs from City Research Online may be freely distributed and linked to from other web pages. Enquiries If you have any enquiries about any aspect of City Research Online, or if you wish to make contact with the author(s) of this paper, please email the team at publications@city.ac. uk. Title: Abnormal intrinsic and extrinsic connectivity within the magnetic mismatch negativity brain network in schizophrenia: a preliminary study Abstract: Altered neuroplasticity is increasingly invoked as a mechanism underpinning dysconnectivity in schizophrenia. We used Dynamic Causal Modelling to compare connectivity during the magnetic auditory Mismatch Negativity (MMN), an index of error prediction, between schizophrenia patients and controls. Patients showed reduced intrinsic connectivity within the primary auditory cortex suggestive of impaired local neuronal adaptation and disrupted forward and backward extrinsic connectivity throughout the MMN network indicative of reduced higher order input in disambiguating activity in lower network nodes. Our study provides the first empirical description of the dysplastic changes underpinning dysconnectivity between primary sensory and higher order cortical areas in schizophrenia. Title: Abnormal intrinsic and extrinsic connectivity within the magnetic mismatch negativity brain network in schizophrenia: a preliminary study. Abstract Altered neuroplasticity is increasingly invoked as a mechanism underpinning dysconnectivity in schizophrenia. We used Dynamic Causal Modelling to compare connectivity during the magnetic auditory Mismatch Negativity (MMN), an index of error prediction, between schizophrenia patients and controls. Patients showed reduced intrinsic connectivity within the primary auditory cortex suggestive of impaired local neuronal adaptation and disrupted forward and backward extrinsic connectivity throughout the MMN network indicative of reduced higher order input in disambiguating activity in lower network nodes. Our study provides the first empirical description of the dysplastic changes underpinning dysconnectivity between primary sensory and higher order cortical areas in schizophrenia.
Barriers to Technology Adoption and Development

We propose a theory of economic development in which technology adoption and barriers to such adoptions are the focus. The size of these barriers differs across countries and time. The larger these barriers, the greater the investment a firm must make to adopt a more advanced technology. The model is calibrated to the U.S. balanced growth observations and the postwar Japanese development miracle. For this calibrated structure we find that the disparity in technology adoption barriers needed to account for the huge observed income disparity across countries is not implausibly large.
A COST-EFFECTIVE ILU PRECONDITIONER FOR WEATHER SIMULATION

To date, the most efficient solver used in the weather sciences for the resolution of linear system in numerical weather prediction is the generalized minimal residual method called GMRES. However, difficulties still appear in matrix resolution when the GMRES iterative method is used without an appropriate preconditioner. For improving the computation speed in numerically solving weather equations, we investigate the use of Incomplete LU(ILU) factorization preconditioner. This is a fast algorithm for solving large scale linear equations. Some strategies for choosing the level of fill and threshold are described in this paper. As an example, we use the GMRES iterative algorithm to solve the finite difference equations of shallow equations and analyze the results that are obtained in preconditioned and un-preconditioned, respectively. It is shown that the computation speed is greatly improved by using ILU factorization preconditioner for the linear system. In addition, this preconditioning algorithm is simple and parallelizable. Therefore, the algorithm is potential in the applications of weather e-
Integrating Information from Multiple Methods into the Analysis of Perceived Risk of Crime: The Role of Geo-Referenced Field Data and Mobile Methods

This paper demonstrates the use of mixed methods discovery techniques to explore public perceptions of community safety and risk, using computational techniques that combine and integrate layers of information to reveal connections between community and place. Perceived vulnerability to crime is conceptualised using an etic/emic framework. The etic “outsider” viewpoint imposes its categorisation of vulnerability not only on areas (“crime hot spots” or “deprived neighbourhoods”) but also on socially constructed groupings of individuals (the “sick” or the “poor”) based on particular qualities considered relevant by the analyst. The range of qualities is often both narrow and shallow. The alternative, emic, “insider” perspective explores vulnerability based on the meanings held by the individuals informed by their lived experience. Using recorded crime data and Census-derived area classifications, we categorise an area in Southern England from an etic viewpoint. Mobile interviews with local residents and police community support officers and researcher-led environmental audits provide qualitative emic data. GIS software provides spatial context to analytically link both quantitative and qualitative data. We demonstrate how this approach reveals hidden sources of community resilience and produces findings that explicate low level social disorder and vandalism as turns in a “dialogue” of resistance against urbanisation and property development.