Reliability of yellow bodies as indexes of egg laying activity in the primitively eusocial wasp Polistes dominula

Understanding the evolution of asymmetric access to reproduction requires reliable tools to measure individual reproductive share. In social insects, reproductive skew is usually evaluated by measuring the degree of ovarian development. However, this approach has been recently shown to reliably estimate only the physiological investment in reproduction, while it is rather inconsistent regarding the individual egg laying rate. Here, I assess the reliability of other physiological traits, the presence and size of yellow bodies, i.e. the remains of nurse cells deposited at the base of the ovarioles whenever an egg is laid. Their usefulness in indicating previous egg laying activity has been recognized since decades, but a formal assessment of their reliability has never been performed. By combining behavioural observations and physiological measurements in the social wasp Polistes dominula I determined whether yellow bodies presence and size reliably track previous reproductive activity. Despite the presence of yellow bodies is associated with egg laying, the classification of individuals to egg layer/non egg layer categories is not completely reliable, inducing in a relevant rate of false positive and false negatives. Moreover, size of yellow bodies is poorly correlated with egg laying and does not allow to properly infer the relative reproductive activity. Overall, yellow bodies do not precisely track small differences in egg laying and their use is thus recommended only when moderate to big differences are expected. Prudence is especially suggested in primitively eusocial species, where the short reproductive period and the distributed totipotency may result in small differences in individual reproduction

Insight on Hole-Hole Interaction and Magnetic Order from Dichroic Auger-Photoelectron Coincidence Spectra

The absence of sharp structures in the core-valence-valence Auger line shapes of partially filled bands has severely limited the use of electron spectroscopy in magnetic crystals and other correlated materials. Here by a novel interplay of experimental and theoretical techniques we achieve a combined understanding of the Photoelectron, Auger %$M_{23}M_{45}M_{45}$ and Auger-Photoelectron Coincidence Spectra (APECS) of CoO. This is a prototype antiferromagnetic material in which the recently discovered Dichroic Effect in Angle Resolved (DEAR) APECS reveals a complex pattern in the strongly correlated Auger line shape. A calculation of the \textit{unrelaxed} spectral features explains the pattern in detail, labeling the final states by the total spin. The present theoretical analysis shows that the dichroic effect arises from a spin-dependence of the angular distribution of the photoelectron-Auger electron pair detected in coincidence, and from the selective power of the dichroic technique in assigning different weights to the various spin components. Since the spin-dependence of the angular distribution exists in the antiferromagnetic state but vanishes at the N\'eel temperature, the DEAR-APECS technique detects the phase transition from its local effects, thus providing a unique tool to observe and understand magnetic correlations in such circumstances, where the usual methods (neutron diffraction, specific heat measurements) are not applicable.Comment: Accepted by: Physical Review Letter

Tracing outliers in the dataset of Drosophila suzukii records with the Isolation Forest method

The analysis of big data is a fundamental challenge for the current and future stream of data coming from many different sources. Geospatial data is one of the sources currently less investigated. A typical example of always increasing data set is that produced by the distribution data of invasive species on the concerned territories. The dataset of Drosophila suzuki invasion sites in Europe up to 2011 was used to test a possible method to pinpoint its outliers (anomalies). Our aim was to find a method of analysis that would be able to treat large amount of data in order to produce easily readable outputs to summarize and predict the status and, possibly, the future development of a biological invasion. To do that, we aimed to identify the so called anomalies of the dataset, identified with a Python script based on the machine learning algorithm “Isolation Forest”. We used also the K-Means clustering method to partition the dataset. In our test, based on a real dataset, the Silhouette method yielded a number of clusters of 10 as the best result. The clusters were drawn on the map with a Voronoi tessellation, showing that 8 clusters were centered on industrial harbours, while the last two were in the hinterland. This fact led us to guess that: (1) the main entrance mechanisms in Europe may be the wares import fluxes through ports, occurring apparently several times; (2) the spreading into the inland may be due to road transportation of wares; (3) the outliers (anomalies) found with the isolation forest method would identify individuals or populations that tend to detach from their original cluster and hence represent indications about the lines of further spreading of the invasion. This type of analysis aims hence to identify the future direction of an invasion, rather than the center of origin as in the case of geographic profiling. Isolation Forest provides therefore complimentary results with respect to PGP. The recent records of the invasive species, mainly localized close to the outliers position, are an indication that the isolation forest method can be considered predictive and proved to be a useful method to treat large datasets of geospatial data

Underactuated Attitude Control with Deep Reinforcement Learning

Autonomy is a key challenge for future space exploration endeavors. Deep Reinforcement Learning holds the promises for developing agents able to learn complex behaviors simply by interacting with their environment. This work investigates the use of Reinforcement Learning for satellite attitude control applied to two working conditions: the nominal case, in which all the actuators (a set of 3 reaction wheels) are working properly, and the underactuated case, where an actuator failure is simulated randomly along one of the axes. In particular, a control policy is implemented and evaluated to maneuver a small satellite from a random starting angle to a given pointing target. In the proposed approach, the control policies are implemented as Neural Networks trained with a custom version of the Proximal Policy Optimization algorithm, and they allow the designer to specify the desired control properties by simply shaping the reward function. The agents learn to effectively perform large-angle slew maneuvers with fast convergence and industry-standard pointing accuracy

THE LEAN SIX SIGMAAPPROACH FOR PROCESS IMPROVEMENT: A CASE STUDY IN A HIGH QUALITY TUSCANY WINERY

This paper describes the application of a Lean Six Sigma (LSS) project to a winemaking process in a high-quality, Italian winery. LSS is used to focus on the problem through a quantitative analysis of waste and quality performances. The LSS basic algorithm (called “DMAIC”) helps to detect and quantify critical aspects of the process for transferring liquid used in the cellar. The improvement solution is developed and applied through the modification of the cellar system and the process procedure. The results obtained with this solution are shown and discussed in this paper, so too the long term reliability of the improved process analyzed. The results obtained by this case study can help to understand the importance of the LSS method to drive the improvement of agricultural and agrofood productions also in terms of environmental impact which is strongly connected to waste reduction

Rethinking recognition: social context in adult life rather than early experience shapes recognition in a social wasp

Social recognition represents the foundation of social living. To what extent social recognition is hard-wired by early-life experience or flexible and influenced by social context of later life stages is a crucial question in animal behaviour studies. Social insects have represented classic models to investigate the subject, and the acknowledged idea is that relevant information to create the referent template for nest-mate recognition (NMR) is usually acquired during an early sensitive period in adult life. Experimental evidence, however, highlighted that other processes may also be at work in creating the template and that such a template may be updated during adult life according to social requirements. However, currently, we lack an ad hoc experiment testing the alternative hypotheses at the basis of NMR ontogeny in social insects. Thus, to investigate the mechanisms underlying the ontogeny of NMR in Polistes wasps, a model genus in recognition studies, and their different role in determining recognition abilities, we subjected Polistes dominula workers to different olfactory experiences in different phases of their life before inserting them into the social environment of a novel colony and testing them in recognition bioassays. Our results show that workers develop their NMR abilities based on their social context rather than through pre-imaginal and early learning or self-referencing. Our study demonstrates that the social context represents the major component shaping recognition abilities in a social wasp, therefore shedding new light on the ontogeny of recognition in paper wasps and prompting the reader to rethink about the traditional knowledge at the basis of the recognition in social insects. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests'

Opinion dynamics within a virtual small group: the stubbornness effect

The modeling of opinion dynamics in social systems has attracted a good deal of attention in the last decade. Even though based on intuition and observation, the mechanisms behind many of these models need solid empirical grounding. In this work, we investigate the relation among subjective variables (such as the personality), the dynamics of the affinity network dynamics, the communication patterns emerging throughout the social interactions and the opinions dynamics in a series of experiments with five small groups of ten people each. In order to ignite the discussion, the polemic topic of animal experimentation was proposed. The groups essentially polarized in two factions with a set of stubborn individuals (those not changing their opinions in time) playing the role of anchors. Our results suggest that the different layers present in the group dynamics (i.e., individual level, group dynamics and meso-communication) are deeply intermingled, specifically the stubbornness effect appears to be related to the dynamical features of the network topologies, and only in an undirected way to the personality of the participants.This work was funded by the European Commission under the FET-AWARENESS RECOGNITION (257756). AG and FB acknowledges partial financial support from the EU projects 288021 (EINS – Network of Excellence in Internet Science) and 611299 (FP7 Programme on Collective-Awareness Platforms SciCafe2.0).Peer Reviewe

A network of sex and competition: the promiscuous mating system of an invasive weevil.

Invasive alien pest insect species represent a major threat for agriculture and biodiversity. Because chemical treatments employed to contrast such pests elicit serious environmental and human health problems, a great effort is currently directed to develop long term and environmentally friendly biological control strategies. However, the successful application of some promising techniques, such as the Sterile Insect Technique (SIT), requires a deep knowledge of the pest basic biology. Here, we argue that understanding pest sexual biology using a social network approach can significantly improve the performance of control strategies. For example, SIT may benefit from understanding how individuals interact and how males accede to reproduction, in order to target the most reproductively active and polygamic males. In this paper we studied the socio-sexual networks of the Asian red palm weevil (RPW) Rhynchophorus ferrugineus, a worldwide invader which is causing heavy economic impacts on several palm species. We found that the RPW has a highly promiscuous mating system, characterized by forced interruptions of pair copulations by additional males. The social network is highly non-random nor regular: few males almost monopolize reproduction, behaving as key-players in the network of matings. Additionally, males have a stable pattern of sexual behaviour over time. We use RPW social network as a case study to direct the development of management techniques such as SIT strateg