Search results for "NEUROSCIENCE"

Honeybees prefer novel insect-pollinated flower shapes over bird-pollinated flower shapes

2019

AbstractPlant–pollinator interactions have a fundamental influence on flower evolution. Flower color signals are frequently tuned to the visual capabilities of important pollinators such as either bees or birds, but far less is known about whether flower shape influences the choices of pollinators. We tested European honeybee Apis mellifera preferences using novel achromatic (gray-scale) images of 12 insect-pollinated and 12 bird-pollinated native Australian flowers in Germany; thus, avoiding influences of color, odor, or prior experience. Independent bees were tested with a number of parameterized images specifically designed to assess preferences for size, shape, brightness, or the number…

Communal nesting in the garden dormouse (Eliomys quercinus)

2017

Communal nesting has been described in many rodents including some dormouse species. In this study, we report the existence of this reproductive strategy in the garden dormouse Eliomys quercinus. Data was recorded by checking natural nests and nest-boxes from 2003 to 2013 in SE Spain. Pups and adults dormice found in nests were captured and marked. Overall, 198 nests were found: 161 (81.31%) were singular nests and 37 (18.69%) were communal nests. Communal nests were composed by different combinations of one up to three females together with one up to three different size litters. The number of communal nests varied from year to year in accordance with the number of singular nests and no se…

Exploratory behaviour is not related to associative learning ability in the carabid beetle Nebria brevicollis.

2020

Abstract Recently, it has been hypothesised that as learning performance and animal personality vary along a common axis of fast and slow types, natural selection may act on both in parallel leading to a correlation between learning and personality traits. We examined the relationship between risk-taking, exploratory behaviour and associative learning ability in carabid beetle Nebria brevicollis females by quantifying the number of trials individuals required to reach criterion during an associative learning task (‘learning performance’). The associative learning task required the females to associate odour and direction with refugia from light and heat in a T-maze. Further, we assessed lea…

From habitat use to social behavior: natural history of a voiceless poison frog, Dendrobates tinctorius

2019

AbstractDescriptive studies of natural history have always been a source of knowledge on which experimental work and scientific progress rely. Poison frogs are a well-studied group of small Neotropical frogs with diverse parental behaviors, distinct calls, and bright colors that warn predators about their toxicity; and a showcase of advances in fundamental biology through natural history observations. The dyeing poison frog, Dendrobates tinctorius, is emblematic of the Guianas region, widespread in the pet-trade, and increasingly popular in research. This species shows several unusual behaviors, such as the lack of advertisement calls and the aggregation around tree-fall gaps, which remain …

2018

<b><i>Background:</i></b> A major and complex challenge when trying to support individuals with dementia is meeting the needs of those who experience changes in behaviour and mood. <b><i>Aim:</i></b> To explore how a sensor measuring electrodermal activity (EDA) impacts assistant nurses’ structured assessments of problematic behaviours amongst people with dementia and their choices of care interventions. <b><i>Methods:</i></b> Fourteen individuals with dementia wore a sensor that measured EDA. The information from the sensor was presented to assistant nurses during structured assessments of problematic behaviours. The e…

UJI RobInLab's approach to the Amazon Robotics Challenge 2017

2017

This paper describes the approach taken by the team from the Robotic Intelligence Laboratory at Jaume I University to the Amazon Robotics Challenge 2017. The goal of the challenge is to automate pick and place operations in unstructured environments, specifically the shelves in an Amazon warehouse. RobInLab's approach is based on a Baxter Research robot and a customized storage system. The system's modular architecture, based on ROS, allows communication between two computers, two Arduinos and the Baxter. It integrates 9 hardware components along with 10 different algorithms to accomplish the pick and stow tasks. We describe the main components and pipelines of the system, along with some e…

Extreme minimal learning machine: Ridge regression with distance-based basis

2019

The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…

2D/3D Object Recognition and Categorization Approaches for Robotic Grasping

2017

International audience; Object categorization and manipulation are critical tasks for a robot to operate in the household environment. In this paper, we propose new methods for visual recognition and categorization. We describe 2D object database and 3D point clouds with 2D/3D local descriptors which we quantify with the k-means clustering algorithm for obtaining the Bag of Words (BOW). Moreover, we develop a new global descriptor called VFH-Color that combines the original version of Viewpoint Feature Histogram (VFH) descriptor with the color quantization histogram, thus adding the appearance information that improves the recognition rate. The acquired 2D and 3D features are used for train…

Simulation Goals and Metrics Identification

2016

Agent-Based Modeling and Simulation (ABMS) is a very useful means for producing high quality models during simulation studies. When ABMS is part of a methodological ap- proach it becomes important to have a method for identifying the objectives of the simulation study in a disciplined fashion. In this work we propose a set of guidelines for properly capturing and representing the goals of the simulations and the metrics, allowing and evaluating the achievement of a simulation objective. We take inspiration from the goal-question-metric approach and with the aid of a specific problem formalization we are able to derive the right questions for relating simulation goals and metrics.

Fault detection for nonlinear networked systems based on quantization and dropout compensation: An interval type-2 fuzzy-model method

2016

Abstract This paper investigates the problem of filter-based fault detection for a class of nonlinear networked systems subject to parameter uncertainties in the framework of the interval type-2 (IT2) T–S fuzzy model-based approach. The Bernoulli random distribution process and logarithm quantizer are used to describe the measurement loss and signals quantization, respectively. In the framework of the IT2 T–S fuzzy model, the parameter uncertainty is handled by the membership functions with lower and upper bounds. A novel IT2 fault detection filter is designed to guarantee the residual system to be stochastically stable and satisfy the predefined H ∞ performance. It should be mentioned that…