Feeding Records of Aphids (Hemiptera: Aphididae) From Wisconsin

Basic to our understanding of any animal and its habitat requirements is knowing what it eats. Reported here are observations of feeding by 27 species of aphids encountered in Wisconsin over 1992-2002

Feeding Records of Aphids (Hemiptera: Aphididae) From Wisconsin

Basic to our understanding of any animal and its habitat requirements is knowing what it eats. Reported here are observations of feeding by 27 species of aphids encountered in Wisconsin over 1992-2002

Stabilisation of beta and gamma oscillation frequency in the mammalian olfactory bulb

International audienceThe dynamics of the mammalian olfactory bulb (OB) is characterized by local field potential (LFP) oscillations either slow, in the theta range (2-10Hz, tightly linked to the respiratory rhythm), or fast, in the beta (15-30Hz) or gamma (40-90Hz) range. These fast oscillations are known to be modulated by odorant features and animal experience or state, but both their mechanisms and implication in coding are still not well understood. In this study, we used a double canulation protocol to impose artificial breathing rhythms to anesthetized rats while recording the LFP in the OB. We observed that despite the changes in the input air flow parameters (frequency or flow rate), the main characteristics of fast oscillations (duration, frequency or amplitude) were merely constant. We thus made the hypothesis that fast beta and gamma oscillations dynamics are entirely determined by the OB network properties and that external stimulation was only able put the network in a state which permits the generation of one or the other oscillations (they are never present simultaneously)

Spatial Distribution of Aphis glycines (Hemiptera: Aphididae): A Summary of the Suction Trap Network

The soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is an economically important pest of soybean, Glycine max (L.) Merrill, in the United States. Phenological information ofA. glycines is limited; specifically, little is known about factors guiding migrating aphids and potential impacts of long distance flights on local population dynamics. Increasing our understanding of A. glycines population dynamics may improve predictions of A. glycines outbreaks and improve management efforts. In 2005 a suction trap network was established in seven Midwest states to monitor the occurrence of alates. By 2006, this network expanded to 10 states and consisted of 42 traps. The goal of the STN was to monitor movement of A. glycines from their overwintering hostRhamnus spp. to soybean in spring, movement among soybean fields during summer, and emigration from soybean to Rhamnus in fall. The objective of this study was to infer movement patterns ofA. glycines on a regional scale based on trap captures, and determine the suitability of certain statistical methods for future analyses. Overall, alates were not commonly collected in suction traps until June. The most alates were collected during a 3-wk period in the summer (late July to mid-August), followed by the fall, with a peak capture period during the last 2 wk of September. Alate captures were positively correlated with latitude, a pattern consistent with the distribution of Rhamnus in the United States, suggesting that more southern regions are infested by immigrants from the north

Assessing the Effects of Responsible Leadership and Ethical Conflict on Behavioral Intention

[[abstract]]This study develops a research model that elaborates how responsible leadership and ethical conflict influence employees from the perspectives of role theory and attachment theory. Its empirical results reveal that turnover intention indirectly relates to ethical conflict and responsible leadership via the mediating mechanisms of organizational identification and organizational uncertainty. At the same time, helping intention indirectly relates to ethical conflict and responsible leadership only through organizational identification. Finally, the managerial implications for international business and research limitations based on the empirical results are discussed.[[notice]]補正完

Gender Equality and Corporate Social Responsibility in the Middle East

This chapter focuses on corporate social responsibility (CSR) in relation to gender equality in the Arab Middle East. It examines the relationship between CSR and gender in the workplace whilst exploring the link between CSR and human resource management (HRM) policies and practices. The chapter first presents some seminal work on gender equality and diversity management, looking at the business case for gender equality within the CSR and HRM contexts, before engaging with relevant work on gender equality in the Arab Middle East. It concludes by offering recommendations on advancing the equality agenda at the macro- and meso-levels, within a framework which recognises the centrality of agency of women, as well as the potential of positive changes through corporations being seen as ‘agents of change’. The chapter advocates for organisational and governmental policies to promote gender equality in the Arab Middle East

A neo-institutional perspective on ethical decision-making

Drawing on neo-institutional theory, this study aims to discern the poorly understood ethical challenges confronted by senior executives in Indian multinational corporations and identify the strategies that they utilize to overcome them. We conducted in-depth interviews with 40 senior executives in Indian multinational corporations to illustrate these challenges and strategies. By embedding our research in contextually relevant characteristics that embody the Indian environment, we identify several institutional- and managerial-level challenges faced by executives. The institutional-level challenges are interpreted as regulative, normative and cognitive shortcomings. We recommend a concerted effort at the institutional and managerial levels by identifying relevant strategies for ethical decision-making. Moreover, we proffer a multi-level model of ethical decision-making and discuss our theoretical contributions and practical implications

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP).1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604102 (Human Brain Project) and from the European Unions Horizon 2020 Research and Innovation Programme under Grant Agreement No. 720270 (HBP SGA1)

Adaptive Robotic Control Driven by a Versatile Spiking Cerebellar Network

The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.European Union (Human Brain Project) REALNET FP7-ICT270434 CEREBNET FP7-ITN238686 HBP-60410