Transgenerational Effects of Stress Exposure on Offspring Phenotypes in Apomictic Dandelion

Heritable epigenetic modulation of gene expression is a candidate mechanism to explain parental environmental effects on offspring phenotypes, but current evidence for environment-induced epigenetic changes that persist in offspring generations is scarce. In apomictic dandelions, exposure to various stresses was previously shown to heritably alter DNA methylation patterns. In this study we explore whether these induced changes are accompanied by heritable effects on offspring phenotypes. We observed effects of parental jasmonic acid treatment on offspring specific leaf area and on offspring interaction with a generalist herbivore; and of parental nutrient stress on offspring root-shoot biomass ratio, tissue P-content and leaf morphology. Some of the effects appeared to enhance offspring ability to cope with the same stresses that their parents experienced. Effects differed between apomictic genotypes and were not always consistently observed between different experiments, especially in the case of parental nutrient stress. While this context-dependency of the effects remains to be further clarified, the total set of results provides evidence for the existence of transgenerational effects in apomictic dandelions. Zebularine treatment affected the within-generation response to nutrient stress, pointing at a role of DNA methylation in phenotypic plasticity to nutrient environments. This study shows that stress exposure in apomictic dandelions can cause transgenerational phenotypic effects, in addition to previously demonstrated transgenerational DNA methylation effects

Customer emotions in service failure and recovery encounters

Emotions play a significant role in the workplace, and considerable attention has been given to the study of employee emotions. Customers also play a central function in organizations, but much less is known about customer emotions. This chapter reviews the growing literature on customer emotions in employee–customer interfaces with a focus on service failure and recovery encounters, where emotions are heightened. It highlights emerging themes and key findings, addresses the measurement, modeling, and management of customer emotions, and identifies future research streams. Attention is given to emotional contagion, relationships between affective and cognitive processes, customer anger, customer rage, and individual differences

Time Series Modelling and Prediction using Fuzzy Trend Information

This paper presents a novel approach to modelling time series datasets using fuzzy trend information. A time series is described using natural linguistic terms such as rising more steeply and falling less steeply. These natural shape descriptors enable us to produce a glass box model of the series. The linguistic shape descriptors are represented in our system by a new feature called the trend fuzzy set. All trend fuzzy sets are derived from a window on the time series and as such describe the shape of the series within that window. Each window can have membership in any number of different trend fuzzy sets. Prediction using these trend fuzzy sets is performed using the Fril evidential logic rule. Examples of series prediction are shown using sine wave and sunspot time series data. 1 Introduction The aim of this research is to describe a time series with a set of rules which use natural linguistic terms such as rising, falling, rising more steeply, crest etc. Using these natural term..

Recurrent Fuzzy Rules for Belief Updating

In this paper we present a simple belief updating system using recurrent fuzzy rules which improves class prediction in ordered datasets. The recurrent fuzzy rule builds up belief in a class for each point in a sample-ordered or time-ordered dataset. Belief in each class is represented by a fuzzy set predicted class defined on the class universe. Belief in a class increases as positive cases are presented and decreases with negative cases. We show how the importance and characteristics of belief updating are determined through the generation of reference previous class fuzzy sets and evidential logic rule weights using mass assignment and semantic discrimination analysis. Performance of the recurrent belief updating rule is compared to the non-recurrent rule in application to facial feature detection and the classification of particles in gaseous streams. 1 Introduction Fuzzy rules which include a simple belief and memory term can perform markedly better at classification than fuzzy ..

Detection of antifungal compounds in Arabidopsis thaliana and brassica oleracea by thin layer chromatography .

Thin Layer Chromatography (TLC) was applied to detect antifungal compounds both in Arabidopsis thaliana and Brassica oleracea after elicited by various biotic and abiotic elicitors.From TLC bioassays the only strong zone of inhibition detected after challenged by Pseudomonas syringae pv.maculicola was from Arabidopsis tissue and later confirmed by spectrophotometry as camalexin but no corresponding phytoalexin was found in broccoli leaf

Object-Oriented Modelling with Words

Object-oriented modelling with words seeks to extend the new field of modelling with words, itself derived form computing with words, with features of object-oriented knowledge representation and programming. We show that object-oriented modelling with words has two key benefits; firstly the uncertain class hierarchy provides a natural knowledge representation framework for real-world problems, and secondly the object-oriented paradigm enforces a strict software engineering design and implementation process. In this paper we present a new approach to object-oriented modelling with words based on a new theory of inheritance where object memberships and property applicabilities are uncertain. We present the uncertain object-oriented logic programming language Fril++ as a tool for object-oriented modelling with words. We present an example application of object-oriented modelling with words; an extendible object-oriented data browser and machine learning environment

Effect of video game playing and a glucose preload on subjective appetite, subjective emotions, and food intake in overweight and obese boys.

Video game playing (VGP) is associated with overweight/obesity (OW/OB). VGP and caloric preloads in the pre-meal environment influence short-term food intake (FI) in healthy weight children. Therefore, the purpose of the present study was to examine the effect of pre-meal VGP and a glucose preload on subjective emotions, subjective appetite, and FI in boys with OW/OB. On four separate mornings, boys with OW/OB (n = 22; mean±SD: age = 11.9±1.6 years; BMI percentile = 94.3±3.9) participated in four test conditions. Two hours after a standardized breakfast, boys consumed equally sweetened preloads (250 mL) of sucralose (0 kcal) or glucose (200 kcal), with or without 30 min of subsequent VGP. FI from an ad libitum pizza meal was measured immediately after all test conditions. Subjective appetite was measured at 0 (baseline), 15, and 30 min. Subjective emotions (aggression, anger, excitement, disappointment, happiness, upset, and frustration) were measured at 0 and 30 min. VGP did not affect FI, but the glucose preload decreased FI compared with the sucralose control (∆ = -103±48 kcal, pThe accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author