A Profile-Based Method for Authorship Verification

Abstract. Authorship verification is one of the most challenging tasks in stylebased text categorization. Given a set of documents, all by the same author, and another document of unknown authorship the question is whether or not the latter is also by that author. Recently, in the framework of the PAN-2013 evaluation lab, a competition in authorship verification was organized and the vast majority of submitted approaches, including the best performing models, followed the instance-based paradigm where each text sample by one author is treated separately. In this paper, we show that the profile-based paradigm (where all samples by one author are treated cumulatively) can be very effective surpassing the performance of PAN-2013 winners without using any information from external sources. The proposed approach is fully-trainable and we demonstrate an appropriate tuning of parameter settings for PAN-2013 corpora achieving accurate answers especially when the cost of false negatives is high.

Design Principles for Two-Dimensional Molecular Aggregates Using Kasha's Model: Tunable Photophysics in Near and Short-Wave Infrared

Technologies which utilize near-infrared (700 – 1000 nm) and short-wave infrared (1000 – 2000 nm) electromagnetic radiation have applications in deep-tissue imaging, telecommunications and satellite telemetry due to low scattering and decreased background signal in this spectral region. It is therefore necessary to develop materials that absorb light efficiently beyond 1000 nm. Transition dipole moment coupling (e.g. J-aggregation) allows for redshifted excitonic states and provides a pathway to highly absorptive electronic states in the infrared. We present aggregates of two cyanine dyes whose absorption peaks redshift dramatically upon aggregation in water from ~800 nm to 1000 nm and 1050 nm respectively with sheet-like morphologies and high molar absorptivities (e ~ 105 M-1cm-1). We use Frenkel exciton theory to extend Kasha’s model for J and H aggregation and describe the excitonic states of 2-dimensional aggregates whose slip is controlled by steric hindrance in the assembled structure. A consequence of the increased dimensionality is the phenomenon of an intermediate “I-aggregate”, one which redshifts yet displays spectral signatures of band-edge dark states akin to an H-aggregate. We distinguish between H-, I- and J-aggregates by showing the relative position of the bright (absorptive) state within the density of states using temperature dependent spectroscopy. I-aggregates hold potential for applications as charge injection moieties for semiconductors and donors for energy transfer in NIR and SWIR. Our results can be used to better design chromophores with predictable and tunable aggregation with new photophysical properties

Computer program developed for flowsheet calculations and process data reduction

Computer program PACER-65, is used for flowsheet calculations and easily adapted to process data reduction. Each unit, vessel, meter, and processing operation in the overall flowsheet is represented by a separate subroutine, which the program calls in the order required to complete an overall flowsheet calculation

Effects of Fungicide Euparen Multi (Tolylfluanid) on Development of Preimplantation Embryos in Mouse

The effect of the fungicide Euparen Multi (containing 50% tolylfluanid) on the development of mouse preimplantation embryos was evaluated. Euparen Multi was daily administered per os to female mice (ICR strain) at four different doses of 118, 294, 588 and 1177 mg/kg b.m., beginning on day 1 of pregnancy. Embryos obtained on day 4 of pregnancy were stained by morphological triple staining (Hoechst 33342, propidium iodide, Calcein AM), and the number of nuclei, blastocyst formation, distribution of embryos according to the nucleus number and cell death incidence were determined. Embryos in the experimental groups (except for the lowest dose 118 mg/kg b.m.) showed a highly significant dose-dependent reduction in total cell numbers corresponding to the lower proportion of blastocysts. The occurrence of cell death was significantly increased in all experimental groups, indicating that Euparen Multi is able to cause cell death at relatively low doses. Our data demonstrate that Euparen Multi could induce significant alterations in the preimplantation embryo development

Asynchronous and Parallel Distributed Pose Graph Optimization

We present Asynchronous Stochastic Parallel Pose Graph Optimization (ASAPP), the first asynchronous algorithm for distributed pose graph optimization (PGO) in multi-robot simultaneous localization and mapping. By enabling robots to optimize their local trajectory estimates without synchronization, ASAPP offers resiliency against communication delays and alleviates the need to wait for stragglers in the network. Furthermore, ASAPP can be applied on the rank-restricted relaxations of PGO, a crucial class of non-convex Riemannian optimization problems that underlies recent breakthroughs on globally optimal PGO. Under bounded delay, we establish the global first-order convergence of ASAPP using a sufficiently small stepsize. The derived stepsize depends on the worst-case delay and inherent problem sparsity, and furthermore matches known result for synchronous algorithms when there is no delay. Numerical evaluations on simulated and real-world datasets demonstrate favorable performance compared to state-of-the-art synchronous approach, and show ASAPP's resilience against a wide range of delays in practice.Comment: full paper with appendice

Algorithmic statistics: forty years later

Algorithmic statistics has two different (and almost orthogonal) motivations. From the philosophical point of view, it tries to formalize how the statistics works and why some statistical models are better than others. After this notion of a "good model" is introduced, a natural question arises: it is possible that for some piece of data there is no good model? If yes, how often these bad ("non-stochastic") data appear "in real life"? Another, more technical motivation comes from algorithmic information theory. In this theory a notion of complexity of a finite object (=amount of information in this object) is introduced; it assigns to every object some number, called its algorithmic complexity (or Kolmogorov complexity). Algorithmic statistic provides a more fine-grained classification: for each finite object some curve is defined that characterizes its behavior. It turns out that several different definitions give (approximately) the same curve. In this survey we try to provide an exposition of the main results in the field (including full proofs for the most important ones), as well as some historical comments. We assume that the reader is familiar with the main notions of algorithmic information (Kolmogorov complexity) theory.Comment: Missing proofs adde