Miracle-dz/UniFAR-FTUs huggingface dataset:
A Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming

In this paper, we focus on the application of the Peaceman-Rachford splitting method (PRSM) to a convex minimization model with linear constraints and a separable objective function. Compared to the Douglas-Rachford splitting method (DRSM), another splitting method from which the alternating direction method of multipliers originates, PRSM requires more restrictive assumptions to ensure its convergence, while it is always faster whenever it is convergent. We first illustrate that the reason for this difference is that the iterative sequence generated by DRSM is strictly contractive, while that generated by PRSM is only contractive with respect to the solution set of the model. With only the convexity assumption on the objective function of the model under consideration, the convergence of PRSM is not guaranteed. But for this case, we show that the first t iterations of PRSM still enable us to find an approximate solution with an accuracy of O(1/t). A worst-case O(1/t) convergence rate of PRSM in the ergodic sense is thus established under mild assumptions. After that, we suggest attaching an underdetermined relaxation factor with PRSM to guarantee the strict contraction of its iterative sequence and thus propose a strictly contractive PRSM. A worst-case O(1/t) convergence rate of this strictly contractive PRSM in a nonergodic sense is established. We show the numerical efficiency of the strictly contractive PRSM by some applications in statistical learning and image processing.
The duality of spatial death–birth and birth–death processes and limitations of the isothermal theorem

Evolutionary models on graphs, as an extension of the Moran process, have two major implementations: birth–death (BD) models (or the invasion process) and death–birth (DB) models (or voter models). The isothermal theorem states that the fixation probability of mutants in a large group of graph structures (known as isothermal graphs, which include regular graphs) coincides with that for the mixed population. This result has been proved by Lieberman et al. (2005 Nature 433, 312–316. (doi:10.1038/nature03204)) in the case of BD processes, where mutants differ from the wild-types by their birth rate (and not by their death rate). In this paper, we discuss to what extent the isothermal theorem can be formulated for DB processes, proving that it only holds for mutants that differ from the wild-type by their death rate (and not by their birth rate). For more general BD and DB processes with arbitrary birth and death rates of mutants, we show that the fixation probabilities of mutants are different from those obtained in the mass-action populations. We focus on spatial lattices and show that the difference between BD and DB processes on one- and two-dimensional lattices is non-small even for large population sizes. We support these results with a generating function approach that can be generalized to arbitrary graph structures. Finally, we discuss several biological applications of the results.
The Open University ’ s repository of research publications and other research outputs Sinh-arcsinh distributions

Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page. Sinh-arcsinh distributions: a broad family giving rise to powerful tests of normality and symmetry Summary. We introduce the 'sinh-arcsinh transformation' and thence, by applying it to random variables from some 'generating' distribution with no further parameters beyond location and scale (which we take for most of the paper to be the normal), a new family of 'sinh-arcsinh distributions'. This four parameter family has both symmetric and skewed members and allows for tailweights that are both heavier and lighter than those of the generating distribution. The 'central' place of the normal distribution in this family affords likelihood ratio tests of normality that appear to be superior to the state-of-the-art because of the range of alternatives against which they are very powerful. Likelihood ratio tests of symmetry are also available and very successful. Three-parameter symmetric and asymmetric subfamilies of the full family are of interest too. Heavy-tailed symmetric sinh-arcsinh distributions behave like Johnson S U distributions while light-tailed symmetric sinh-arcsinh distributions behave like Rieck and Nedelman's sinh-normal distributions , the sinh-arcsinh family allowing a seamless transition between the two, via the normal, controlled by a single parameter. The sinh-arcsinh family is very tractable and many properties are explored. Likelihood inference is pursued, including an attractive reparametrisation. A multivariate version is considered. Options and extensions are discussed.
Understanding Microblog Users for Social Recommendation Based on Social Networks Analysis

With the rapid growth of Internet and social networking websites, various services are provided in these platforms. For instance, Facebook focuses on social activities, Twitter and Plurk (which are called microblogs) are both focusing on the interaction of users through short messages. Millions of users enjoy services from these websites which are full of marketing possibilities. Understanding the users can assist companies to enhance the accuracy and efficiency of the target market. In this paper, a social recommendation system based on the data from microblogs is proposed. This social recommendation system is built according to the messages and social structure of target users. The similarity of the discovered features of users and products will then be calculated as the essence of the recommendation engine. A case study included in the paper presents how the recommendation system works based on real data from Plurk.
Characterizing Group-Level User Behavior in Major Online Social Networks

In this paper, we conduct a detailed measurement study to characterize and compare the “group-level”behavior of users in Facebook, Twitter and Google+. We focus on Popular, Cross (with account in three OSNs) and Random group of users in each OSN since they offer complementary views. We capture user behavior with the following metrics: user connectivity, user activity and user reactions. Our grouplevel methodology enables us to capture major trends in the behavior of small but important groups of users, and to conduct interand intra-OSN comparison of user behavior. Furthermore, we conduct temporal analysis on different aspects of user behavior for all groups over a two-year period. Our analysis leads to a set of useful insights including: (i) The more likely reaction by Facebook and Google+ users is to express their opinion whereas TW users tend to relay a received post to other users and thus facilitate its propagation. Despite the culture of reshare among Twitter users, a post by a Popular Facebook user receives more Reshares than a post by a Popular Twitter user. (ii) Added features in an OSN can significantly boost the rate of action and reaction among its users.
Tourist's Re-visit Intention from Perspective of Value Perception, Destination Image and Satisfaction

This paper aims to identify the relationship between value perception, destination image and satisfaction in order to achieve tourists re-visit intention. Data was collected from the respondents via survey questionnaires developed from related literature. The data collected was then analyzed using structural equation modeling via Smart PLS. Research has found that value perception has a positive, significant impact on satisfaction and satisfaction also has a positive significant impact on re-visit intention. On the other hand, there is no impact between destination images and satisfaction. The implications of these findings are further elaborated.
High-Density Genetic Mapping with Interspecific Hybrids of Two Sea Urchins, Strongylocentrotus nudus and S. intermedius, by RAD Sequencing

Sea urchins have long been used as research model organisms for developmental biology and evolutionary studies. Some of them are also important aquaculture species in East Asia. In this work, we report the construction of RAD-tag based high-density genetic maps by genotyping F1 interspecific hybrids derived from a crossing between a female sea urchin Strongylocentrotus nudus and a male Strongylocentrotus intermedius. With polymorphisms present in these two wild individuals, we constructed a female meiotic map containing 3,080 markers for S. nudus, and a male meiotic map for S. intermedius which contains 1,577 markers. Using the linkage maps, we were able to anchor a total of 1,591 scaffolds (495.9 Mb) accounting for 60.8% of the genome assembly of Strongylocentrotus purpuratus. A genome-wide scan resulted in the identification of one putative QTL for body size which spanned from 25.3 cM to 30.3 cM. This study showed the efficiency of RAD-Seq based high-density genetic map construction using F1 progenies for species with no prior genomic information. The genetic maps are essential for QTL mapping and are useful as framework to order and orientate contiguous scaffolds from sea urchin genome assembly. The integration of the genetic map with genome assembly would provide an unprecedented opportunity to conduct QTL analysis, comparative genomics, and population genetics studies.
Retention time characterization and optimization of logic-compatible embedded DRAM cells

Logic-compatible 2T and 3T embedded DRAMs (eDRAM) have recently gained their popularity in embedded applications because of their high density and good voltage margin. The most important design requirements in eDRAM cells are cell area, data retention time and read speed. In this paper, we present an in-depth analysis on the data retention time of various logic-compatible eDRAM cells, followed by the effects of several design factors on the retention time. A systematic methodology is proposed for enhancing the retention time of the eDRAM cells. Simulation results using a standard 65nm CMOS technology show that the optimization process improves the data retention time more than 3×. Finally, the number of read operations per retention period is estimated to show the effectiveness of each eDRAM cell. Analysis demonstrates that although the 2T eDRAM cell has a shorter retention time than the conventional 3T cell, it has better effectiveness due to the faster read operation.
Doubly Stochastic Primal-Dual Coordinate Method for Empirical Risk Minimization and Bilinear Saddle-Point Problem

We proposed a doubly stochastic primal-dual coordinate (DSPDC) optimization algorithm for empirical risk minimization, which can be formulated as a bilinear saddle-point problem. In each iteration, our method randomly samples a block of coordinates of the primal and dual solutions to update. The convergence of our method is established in both the distance from the current iterate to the optimal solution and the primal-dual objective gap. We show that the proposed method has a lower overall complexity than existing coordinate methods when either the data matrix has a factorized structure or the proximal mapping on each block is computationally expensive, e.g., involves an eigenvalue decomposition. Furthermore, we give a theoretical lower bound on the iteration complexity of a general family of primal-dual (block) coordinate methods for bilinear saddle-point problems, which also includes DSPDC.
Robust Equilibrated Residual Error Estimator for Diffusion Problems: Conforming Elements

This paper analyzes an equilibrated residual a posteriori error estimator for the diffusion problem. The estimator, which is a modification of those in [D. Braess and J. Schoberl, Math. Comput. , 77 (2008), pp. 651-672; R. Verfurth, SIAM J. Numer. Anal. , 47 (2009), pp. 3180-3194], is based on the Prager-Synge identity and on a local recovery of an equilibrated flux. Numerical results for an interface test problem show that the modification is necessary for the robustness of the estimator. When the distribution of diffusion coefficients is local quasi-monotone, it is shown theoretically that the estimator is robust with respect to the size of jumps.
Hypermethylation of the GATA Genes in Lung Cancer

Purpose: In lung cancer, DNA hypermethylation is known to be a common event. Experimental Design: Gene expression and methylation status of GATA-4, GATA-5, and GATA-6 were analyzed with cell lines and primary human lung cancers. Methylation profiles of primary lung cancers were analyzed and correlated with clinical as well as histopathological data. Results: Complete methylation was detected by methylation-specific PCR for both GATA-4 and GATA-5 in four cell lines (H358, DMS-53, A549, and H1299), all of which had no expression by reverse transcription-PCR analysis. Demethylation with 5-aza-2′deoxycytidine restored expression in each case. GATA-6 was ubiquitously expressed in all of the six cell lines. GATA-4 bisulfite sequencing revealed complete methylation of the GATA-4 promoter in H358 cells, correlating well with its lack of expression at the mRNA level. Only a few CpG sites showed methylation by bisulfite sequencing within the GATA-4 promoter in a cell line that expressed the gene. In 63 cases of primary lung cancers, GATA-4 and GATA-5 promoter methylation was detected in (42 of 63) 67% and (26 of 63) 41%, respectively. GATA-6 remained unmethylated both in cell lines and primary tumors. Six autopsy specimens of normal lung tissue showed no aberrant promoter hypermethylation for the GATA genes. Correlation of concomitant GATA-4 and GATA-5 methylation with clinicopathological parameters only found a statistically significant increase in methylation frequency with increasing patient age (P < 0.001). Conclusions: These epigenetic changes in the GATA genes in lung cancer are tumor-specific, relate to the loss of GATA gene expression, and occur increasingly in the elderly.
The Semantic Content of the General Classifier in Mandarin

A basic question in the study of nominal classifier systems concerns the relative roles of lexical semantics and grammatical rules. In this paper we address this issue by studying whether the Mandarin general classifier ge can be selected by a lexicon-independent default rule. Evidence comes first from a corpus analysis, which found no semantically coherent set of privileged lexical exemplars for ge. This finding was confirmed in an experiment in which native speakers of Taiwan Mandarin were given classifiers and asked to list as many appropriate nouns as they could; the type/token ratio for ge was significantly lower than that for most other classifiers tested, again suggesting that ge has no privileged exemplars. A second experiment was conducted to determine if the choice of ge can be forced by the presence of specific lexical semantic features. The experiment showed that it cannot; no significant difference in rate of ge use was found between nonce words given specific semantic features and nonce words given no meaning at all. Together the evidence implies that ge does not have semantic content, and therefore is selected by grammatical rule independent of the lexicon.
A New Algorithm Based On Sequential Pattern Mining For Person Identification In Ubiquitous Environments

This paper presents an approach to person identification in ubiquitous environments. Our approach uses the sequential pattern mining principle to extract frequent patterns in data collected from the different sensors disseminated in the ubiquitous environment. In contrast with existing, intrusive, person identification algorithms that have been proposed in the literature, where the data is basically composed of audiovisual or image files recorded during experiments, our approach is fully non-intrusive and is based on event sequences collected from heterogeneous sensors. Our approach is divided into three main phases: (1) frequent pattern mining, (2) assignment of weights to extracted patterns, and (3) classification. Experiments using data collected in the Domus and Testbed smart homes demonstrate that our approach accurately identifies persons and improves classification results, outperforming two of the approaches reported in the literature.
Understanding the Mechanisms Linking College Education with Longevity

We go beyond estimating the effect of college education on longevity by uncovering the mechanisms behind this effect while controlling for latent skills and unobserved heterogeneity. We decompose the effect with respect to a large set of potential mechanisms, including health behaviors, lifestyles, earnings, and work conditions. On the basis of data from the Wisconsin Longitudinal Survey, we show that the effect of education on longevity is well explained by observed mechanisms. Furthermore, we find that for women, the positive effect of education on longevity has been historically masked by the negative effect of education on marriage. We discuss implications for longevity and health inequality.
Spectrum allocation for multi-operator device-to-device communication

In order to harvest the business potential of deviceto-device (D2D) communication, direct communication between devices subscribed to different mobile operators should be supported. This would also support meeting requirements resulting from D2D relevant scenarios, like vehicle-to-vehicle communication. In this paper, we propose to allocate the multi-operator D2D communication over dedicated cellular spectral resources contributed from both operators. Ideally, the operators should negotiate about the amount of spectrum to contribute, without revealing proprietary information to each other and/or to other parties. One possible way to do that is to use the sequence of operators' best responses, i.e., the operators make offers about the amount of spectrum to contribute using a sequential updating procedure until reaching consensus. Besides spectrum allocation, we need a mode selection scheme for the multi-operator D2D users. We use a stochastic geometry framework to capture the impact of mode selection on the distribution of D2D users and assess the performance of the best response iteration algorithm. With the performance metrics considered in the paper, we show that the best response iteration has a unique Nash equilibrium that can be reached from any initial strategy. In general, asymmetric operators would contribute unequal amounts of spectrum for multi-operator D2D communication. Provided that the multi-operator D2D density is not negligible, we show that both operators may experience significant performance gains as compared to the scheme without spectrum sharing.
An improved optimization method for iSAM2

There is an issue called maximum likelihood estimation in SLAM that corresponds to a nonlinear least-square problem. It is expected to earn an accurate solution for large-scale environments with high speed of convergence. Although all the applied optimization methods might be accepted in terms of accuracy and speed of convergence for small datasets, their solutions for large-scale datasets are often far from the ground truth. In this paper, a double Dogleg trust region method is proposed and adjusted with iSAM2 to level up performance and accuracy of the algorithm especially in large-scale datasets. Since the trust region methods are sensitive to their own parameters, Gould parameters are chosen to obtain better performance. Simulations are done on some large-scale datasets and the results indicate that the proposed method is more efficient compared to the conventional iSAM2 algorithm.
Broadcast yourself on YouTube: really?

One essential reason for people to publish on the web is to express themselves freely. YouTube facilitates this self-expression by allowing users to upload video content they generated. This paper investigates to what extent the videos on YouTube are self-generated content, instead of amalgamated content that was mainly professionally authored in the first place. Results show that most of the popular content on YouTube was professionally generated, even though a random sample shows that there is plenty of user-generated content available -- it just does not make the cut. As a result we propose that YouTube is more of a social filter, allowing anyone to share content they find interesting rather than a way for aspiring creative people to show their creative abilities to the world. The outcome is a set of requirements which describe better means for YouTube to support better authoring and presentation of video, where the core research direction is focused on the self-representation of humans in the realm of their creative possibilities on one side as well as the stimulation of new insights on existing material to stimulate new creative impulses.
Automatic inference of specifications using matching logic

Formal specifications can be used for various software engineering activities ranging from finding errors to documenting software and automatic test-case generation. Automatically discovering specifications for heap-manipulating programs is a challenging task. In this paper, we propose a technique for automatically inferring formal specifications from C code which is based on the symbolic execution and automated reasoning tandem "Matching Logic/K framework". We implemented our technique for a fragment of C called KernelC, in the automated tool KingSpec, which generates axioms that describe the precise input/output behavior of C routines that handle pointer-based structures, i.e., result values and state change. These specifications can be written either in Matching Logic itself, which is useful for further automated analysis within the K formal environment, or in sugared axiomatic form, which favors better human inspection. Since we rely on rewriting logic K semantics specification of programming languages, our approach can be easily extended to any language for which %that a formal semantics in K is given.
Automatic Landmark Extraction using Self-Organising Maps 1

A large number of registration techniques rely on manually s e ected landmark points. A system based on neural principles has been developed to automatically ex tract landmark types and positional information from magnetic resonance images. A single self-organising m ap is used to develop the features (landmark types) so that the final landmarks represent statistically signific ant contour sections. The combination of landmark types and positional information form the landmark set, whi ch can then be used for automated registration. The paper discusses the landmark extraction system as well as th e steps necessary for subsequent image registration.
From Knowledge Flows to the Triple Helix

The ‘triple helix’ model of university–industry–government interaction is explained and distinguished from the ‘knowledge flows' model. The ‘second academic revolution’ in the USA and the internal transformation of the university are then described and the paper cites MIT as an example of how bilateral relations with industry have led to the rise of entrepreneurial science. Finally the article describes the organizational changes being made at universities to accommodate academia ‘s new role.
Advances in FEFLO

This paper summarizes the major improvements and developments that have taken place during the last year for FEFLO, a general-purpose CFD code based on adaptive, unstructured grids. All aspects of a comprehensive CFD capability: gridding, solvers, mesh movement techniques and diagnostics saw important advances, and are treated.