Mortality affects adaptive allocation to growth and reproduction: field evidence from a guild of body snatchers

<p>Abstract</p> <p>Background</p> <p>The probability of being killed by external factors (extrinsic mortality) should influence how individuals allocate limited resources to the competing processes of growth and reproduction. Increased extrinsic mortality should select for decreased allocation to growth and for increased reproductive effort. This study presents perhaps the first clear cross-species test of this hypothesis, capitalizing on the unique properties offered by a diverse guild of parasitic castrators (body snatchers). I quantify growth, reproductive effort, and expected extrinsic mortality for several species that, despite being different species, use the same species' phenotype for growth and survival. These are eight trematode parasitic castrators—the individuals of which infect and take over the bodies of the same host species—and their uninfected host, the California horn snail.</p> <p>Results</p> <p>As predicted, across species, growth decreased with increased extrinsic mortality, while reproductive effort increased with increased extrinsic mortality. The trematode parasitic castrator species (operating stolen host bodies) that were more likely to be killed by dominant species allocated less to growth and relatively more to current reproduction than did species with greater life expectancies. Both genders of uninfected snails fit into the patterns observed for the parasitic castrator species, allocating as much to growth and to current reproduction as expected given their probability of reproductive death (castration by trematode parasites). Additionally, species differences appeared to represent species-specific adaptations, not general plastic responses to local mortality risk.</p> <p>Conclusions</p> <p>Broadly, this research illustrates that parasitic castrator guilds can allow unique comparative tests discerning the forces promoting adaptive evolution. The specific findings of this study support the hypothesis that extrinsic mortality influences species differences in growth and reproduction.</p

Kenneth Gergen’s concept of multi-being : an application to the nurse–patient relationship

The nurse-patient relationship is of great significance for both nurses and patients. The purpose of this article is to gain an understanding of how the individual is constituted through a focus on the execution of the patient's and nurse's role in the joint relationship. The article represents a social-constructionist consideration using Kenneth Gergen's concept of multi-being. Gergen's notions of the self as a multi-being focuses on the individual's relational character through former relationships and social interactions. Gergen's concept is applied onto nurses and patients as individuals to gain an understanding of the broader institutional and social context of each role and their interactions within the nurse-patient relationship. The article focuses on the nurse-patient relationship in general with regard to specific challenges in the home care setting. Various demands and experiences from a myriad of past relationships merge as potential actions for nurses and patients during the forming of a relationship. Nurses as multi-beings see themselves confronted with guidelines and legal conditions, their own as well as the patients' expectations and the actual possible forming of a relationship in the light of daily nursing care. Patients as multi-beings experience an extended social environment that comprises the nurse-patient relationship while simultaneously having to cope with illness and increasing care dependency within their own homes. Discrepancies can be observed in the relationship with regard to the inherent human qualities, the demands of forming a relationship, and the actual relationship arising due to framework conditions

The role of the gender in formation of empathy in personality

У статті представлено огляд наукових підходів до визначення поняття емпатії. Проведено аналіз гендерних особливостей емпатії особистості. Визначено загальний рівень емпатії на основі проведеного експериментального дослідження, канали емпатії та її об’єкти в залежності від статі. Досліджено співвідношення емпатійних каналів та об’єктів емпатії особистості.The article presents an overview of scientific approaches to The notion of empathy. Analysis of gender peculiarities of personality empathy is performed. The overall level of empathy on the basis of conducted experimental Studies, channels of empathy and its objects depending on gender. Investigated Ratio of empathic channels and personality empathy objects

Categorising the World into Local Climate Zones -- Towards Quantifying Labelling Uncertainty for Machine Learning Models

Image classification is often prone to labelling uncertainty. To generate suitable training data, images are labelled according to evaluations of human experts. This can result in ambiguities, which will affect subsequent models. In this work, we aim to model the labelling uncertainty in the context of remote sensing and the classification of satellite images. We construct a multinomial mixture model given the evaluations of multiple experts. This is based on the assumption that there is no ambiguity of the image class, but apparently in the experts' opinion about it. The model parameters can be estimated by a stochastic Expectation Maximization algorithm. Analysing the estimates gives insights into sources of label uncertainty. Here, we focus on the general class ambiguity, the heterogeneity of experts, and the origin city of the images. The results are relevant for all machine learning applications where image classification is pursued and labelling is subject to humans

Towards Label Embedding -- Measuring classification difficulty

Uncertainty quantification in machine learning is a timely and vast field of research. In supervised learning, uncertainty can already occur in the very first stage of the training process, the labelling step. In particular, this is the case when not every instance can be unambiguously classified. The problem occurs for classifying instances, where classes may overlap or instances can not be clearly categorised. In other words, there is inevitable ambiguity in the annotation step and not necessarily a 'ground truth'. We look exemplary at the classification of satellite images. Each image is annotated independently by multiple labellers and classified into local climate zones (LCZs). For each instance we have multiple votes, leading to a distribution of labels rather than a single value. The main idea of this work is that we do not assume a ground truth label but embed the votes into a K-dimensional space, with K as the number of possible categories. The embedding is derived from the voting distribution in a Bayesian setup, modelled via a Dirichlet-Multinomial model. We estimate the model and posteriors using a stochastic Expectation Maximisation algorithm with Markov Chain Monte Carlo steps. While we focus on the particular example of LCZ classification, the methods developed in this paper readily extend to other situations where multiple annotators independently label texts or images. We also apply our approach to two other benchmark datasets for image classification to demonstrate this. Besides the embeddings themselves, we can investigate the resulting correlation matrices, which can be seen as generalised confusion matrices and reflect the semantic similarities of the original classes very well for all three exemplary datasets. The insights gained are valuable and can serve as general label embedding if a single ground truth per observation cannot be guaranteed

Maritrema orensense and Maritrema bonaerense (Digenea: Microphallidae): Descriptions, Life Cycles, and Comparative Morphometric Analyses

Fil: Alda, Pilar. Centro de Estudios en Parasitología y Vectores (CEPAVE). Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; ArgentinaFil: Bonel, Nicolás. Laboratorio de Zoología de Invertebrados I. Departamento de Biología, Bioquímica y Farmacia. Universidad Nacional del Sur. Buenos Aires; ArgentinaFil: Hechinger, Ryan F.. Marine Science Institute and Department of Ecology, Evolution, and Marine Biology. University of California. Santa Barbara. California; USAFil: Martorelli, Sergio Roberto. Centro de Estudios en Parasitología y Vectores (CEPAVE). Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; Argentin