Creative Coding for Humor Design: A Preliminary Exploration

Both humor and art aims are creative and complex processes, and both aim to induce an emotional effect (mirth in the former case, aesthetic pleasure in the latter one). In recent years a number of programming languages and computational environment for creative coding have been diffused and have attracted a growing community of artists and enthusiasts. This contribution is a small collection of observations emerged during an explorative study of these environments, performed during the last months. It is aimed to search new ideas and methodological directions for the future development of research in computational humor generation.Non peer reviewe

Screening for type 1 diabetes-, thyroid-, gastric-, and adrenal-specific humoral autoimmunity in 529 children and adolescents with celiac disease at diagnosis identifies as positive one in every nine patients

No abstract availabl

Corpus-Based Generation of Content and Form in Poetry

We employ a corpus-based approach to generate content and form in poetry. The main idea is to use two different corpora, on one hand, to provide semantic content for new poems, and on the other hand, to generate a specific grammatical and poetic structure. The approach uses text mining methods, morphological analysis, and morphological synthesis to produce poetry in Finnish. We present some promising results obtained via the combination of these methods and preliminary evaluation results of poetry generated by the system.Peer reviewe

Lexical Creativity from Word Associations

A fluent ability to associate tasks, concepts, ideas, knowledge and experiences in a relevant way is often considered an important factor of creativity, especially in problem solving. We are interested in providing computational support for discovering such creative associations. In this paper we design minimally supervised methods that can perform well in the remote associates test (RAT), a well-known psychometric measure of creativity. We show that with a large corpus of text and some relatively simple principles, this can be achieved. We then develop methods for a more general word association model that could be used in lexical creativity support systems, and which also could be a small step towards lexical creativity in computers.Peer reviewe

Decomposition and Distribution of Humorous Effect in Interactive Systems

Non peer reviewe

Population balances in case of crossing characteristic curves: Application to T-cells immune response

The progression of a cell population where each individual is characterized by the value of an internal variable varying with time (e.g. size, weight, and protein concentration) is typically modeled by a Population Balance Equation, a first order linear hyperbolic partial differential equation. The characteristics described by internal variables usually vary monotonically with the passage of time. A particular difficulty appears when the characteristic curves exhibit different slopes from each other and therefore cross each other at certain times. In particular such crossing phenomenon occurs during T-cells immune response when the concentrations of protein expressions depend upon each other and also when some global protein (e.g. Interleukin signals) is also involved which is shared by all T-cells. At these crossing points, the linear advection equation is not possible by using the classical way of hyperbolic conservation laws. Therefore, a new Transport Method is introduced in this article which allowed us to find the population density function for such processes. The newly developed Transport method (TM) is shown to work in the case of crossing and to provide a smooth solution at the crossing points in contrast to the classical PDF techniques.Comment: 18 pages, 10 figure

Variability of CD3 membrane expression and T cell activation capacity

αβT cells have a wide distribution of their CD3 membrane density. The aim of this paper was to evaluate the significance of the CD3 differential expression on T cell subsets. Analysis was performed on healthy donors and renal transplant patients by flowcytometry The results obtained are : 1-CD3 expression was widely distributed (CV =38.3±3.1 to (43±2.3%). 2-The CD4, CD8,CD45 and forward scatter were similarly distributed. 3-The diversity of CD3 expression was direcly related to the clonotypes: γ9, non γ9 from γδT cells and Vβ clonotype from αβT cells (e.g.: Vβ3FITC 7980±1628 Vβ8PE: Vβ20-FITC 11768±1510). 4-Using a computer simulation, we could confirm differential kinetics of T cell activation according to the initial parameters. Finally, in vitro activation was significantly higher on Vβ8 and Vβ9 (high CD3) compared to Vβ2 and Vβ3 (low CD3, P=0.040 to 0.0003). In conclusion: T cells have highly heterogeneous CD3 expression, possibly predetermined and with clear functional significance

Deterministic mechanical model of T-killer cell polarization reproduces the wandering of aim between simultaneously engaged targets

T-killer cells of the immune system eliminate virus-infected and tumorous cells through direct cell-cell interactions. Reorientation of the killing apparatus inside the T cell to the T-cell interface with the target cell ensures specificity of the immune response. The killing apparatus can also oscillate next to the cell-cell interface. When two target cells are engaged by the T cell simultaneously, the killing apparatus can oscillate between the two interface areas. This oscillation is one of the most striking examples of cell movements that give the microscopist an unmechanistic impression of the cell's fidgety indecision. We have constructed a three-dimensional, numerical biomechanical model of the molecular-motor-driven microtubule cytoskeleton that positions the killing apparatus. The model demonstrates that the cortical pulling mechanism is indeed capable of orienting the killing apparatus into the functional position under a range of conditions. The model also predicts experimentally testable limitations of this commonly hypothesized mechanism of T-cell polarization. After the reorientation, the numerical solution exhibits complex, multidirectional, multiperiodic, and sustained oscillations in the absence of any external guidance or stochasticity. These computational results demonstrate that the strikingly animate wandering of aim in T-killer cells has a purely mechanical and deterministic explanation. © 2009 Kim, Maly

The macroscopic effects of microscopic heterogeneity

Over the past decade, advances in super-resolution microscopy and particle-based modeling have driven an intense interest in investigating spatial heterogeneity at the level of single molecules in cells. Remarkably, it is becoming clear that spatiotemporal correlations between just a few molecules can have profound effects on the signaling behavior of the entire cell. While such correlations are often explicitly imposed by molecular structures such as rafts, clusters, or scaffolds, they also arise intrinsically, due strictly to the small numbers of molecules involved, the finite speed of diffusion, and the effects of macromolecular crowding. In this chapter we review examples of both explicitly imposed and intrinsic correlations, focusing on the mechanisms by which microscopic heterogeneity is amplified to macroscopic effect.Comment: 20 pages, 5 figures. To appear in Advances in Chemical Physic

SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods

In the last few years thousands of scientific papers have investigated sentiment analysis, several startups that measure opinions on real data have emerged and a number of innovative products related to this theme have been developed. There are multiple methods for measuring sentiments, including lexical-based and supervised machine learning methods. Despite the vast interest on the theme and wide popularity of some methods, it is unclear which one is better for identifying the polarity (i.e., positive or negative) of a message. Accordingly, there is a strong need to conduct a thorough apple-to-apple comparison of sentiment analysis methods, \textit{as they are used in practice}, across multiple datasets originated from different data sources. Such a comparison is key for understanding the potential limitations, advantages, and disadvantages of popular methods. This article aims at filling this gap by presenting a benchmark comparison of twenty-four popular sentiment analysis methods (which we call the state-of-the-practice methods). Our evaluation is based on a benchmark of eighteen labeled datasets, covering messages posted on social networks, movie and product reviews, as well as opinions and comments in news articles. Our results highlight the extent to which the prediction performance of these methods varies considerably across datasets. Aiming at boosting the development of this research area, we open the methods' codes and datasets used in this article, deploying them in a benchmark system, which provides an open API for accessing and comparing sentence-level sentiment analysis methods