Spatial and temporal patterns of carabid activity-density in cereals do not explain levels of predation on weed seeds

Seed predation is an important component of seed mortality of weeds in agro-ecosystems, but the agronomic use and management of this natural weed suppression is hampered by a lack of insight in the underlying ecological processes. In this paper, we investigate whether and how spatial and temporal variation in activity-density of granivorous ground beetles (Coleoptera: Carabidae) results in a corresponding pattern of seed predation. Activity-density of carabids was measured by using pitfall traps in two organic winter wheat fields from March to July 2004. Predation of seeds (Capsella bursa-pastoris, Lamium amplexicaule, Poa annua and Stellaria media) was assessed using seed cards at the same sites and times. As measured by pitfall traps, carabids were the dominant group of insects that had access to the seed cards. In the field, predation of the four different species of seed was in the order: C. bursa-pastoris>P. annua>S. media>L. amplexicaule; and this order of preference was confirmed in the laboratory using the dominant species of carabid. On average, seed predation was higher in the field interior compared to the edge, whereas catches of carabids were highest near the edge. Weeks with elevated seed predation did not concur with high activity-density of carabids. Thus, patterns of spatial and temporal variation in seed predation were not matched by similar patterns in the abundance of granivorous carabid beetles. The lack of correspondence is ascribed to effects of confounding factors, such as weather, the background density of seeds, the composition of the carabid community, and the phenology and physiological state of the beetles. Our results show that differences in seed loss among weed species may be predicted from laboratory trials on preference. However, predator activity-density, as measured in pitfall traps, is an insufficient predictor of seed predation over time and space within a fiel

System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization

A complex system for control of swarms of micro aerial vehicles (MAV), in literature also called as unmanned aerial vehicles (UAV) or unmanned aerial systems (UAS), stabilized via an onboard visual relative localization is described in this paper. The main purpose of this work is to verify the possibility of self-stabilization of multi-MAV groups without an external global positioning system. This approach enables the deployment of MAV swarms outside laboratory conditions, and it may be considered an enabling technique for utilizing fleets of MAVs in real-world scenarios. The proposed visual-based stabilization approach has been designed for numerous different multi-UAV robotic applications (leader-follower UAV formation stabilization, UAV swarm stabilization and deployment in surveillance scenarios, cooperative UAV sensory measurement) in this paper. Deployment of the system in real-world scenarios truthfully verifies its operational constraints, given by limited onboard sensing suites and processing capabilities. The performance of the presented approach (MAV control, motion planning, MAV stabilization, and trajectory planning) in multi-MAV applications has been validated by experimental results in indoor as well as in challenging outdoor environments (e.g., in windy conditions and in a former pit mine)

Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups

A fault-tolerant method for stabilization and navigation of 3D heterogeneous formations is proposed in this paper. The presented Model Predictive Control (MPC) based approach enables to deploy compact formations of closely cooperating autonomous aerial and ground robots in surveillance scenarios without the necessity of a precise external localization. Instead, the proposed method relies on a top-view visual relative localization provided by the micro aerial vehicles flying above the ground robots and on a simple yet stable visual based navigation using images from an onboard monocular camera. The MPC based schema together with a fault detection and recovery mechanism provide a robust solution applicable in complex environments with static and dynamic obstacles. The core of the proposed leader-follower based formation driving method consists in a representation of the entire 3D formation as a convex hull projected along a desired path that has to be followed by the group. Such an approach provides non-collision solution and respects requirements of the direct visibility between the team members. The uninterrupted visibility is crucial for the employed top-view localization and therefore for the stabilization of the group. The proposed formation driving method and the fault recovery mechanisms are verified by simulations and hardware experiments presented in the paper

Biopolymer-based membranes associated with osteogenic growth peptide for guided bone regeneration

Barrier membranes for guided bone regeneration (GBR) mainly promote mechanical maintenance of bone defect space and induce osteopromotion. Additionally, biopolymer-based membranes may provide greater bioactivity and biocompatibility due to their similarity to extracellular matrix (ECM).In this study, biopolymers-based membranes from bacterial cellulose (BC) and collagen (COL) associated with osteogenic growth peptide (OGP(10–14)) were evaluated to determine in vitro osteoinductive potential in early osteogenesis; moreover, histological study was performed to evaluate the BC–COL OGP(10–14) membranes on bone healing after GBR in noncritical defects in rat femur. The results showed that the BC–COL and BC–COL OGP(10–14) membranes promoted cell proliferation and alkaline phosphatase activity in osteoblastic cell cultures. However, ECMmineralization was similar between cultures grown on BC OGP(10–14) and BC–COL OGP(10–14) membranes. In vivo results showed that all the membranes tested, including the peptide-free BC membrane, promoted better bone regeneration than control group. Furthermore, the BC–COL OGP(10–14) membranes induced higher radiographic density in the repaired bone than the other groups at 1, 4 and 16 weeks. Histomorpho-metric analyses revealed that the BC–COL OGP(10–14) induced higher percentage of bone tissue in the repaired area at 2 and 4 weeks than others membranes. In general, these biopolymer-based membranes might be potential candidates for bone regeneration applications

Bioaccumulation and Toxicity of Organic Chemicals in Terrestrial Invertebrates

Terrestrial invertebrates are key components in ecosystems, with crucial roles in soil structure, functioning, and ecosystem services. The present chapter covers how terrestrial invertebrates are impacted by organic chemicals, focusing on up-to-date information regarding bioavailability, exposure routes and general concepts on bioaccumulation, toxicity, and existing models. Terrestrial invertebrates are exposed to organic chemicals through different routes, which are dependent on both the organismal traits and nature of exposure, including chemical properties and media characteristics. Bioaccumulation and toxicity data for several groups of organic chemicals are presented and discussed, attempting to cover plant protection products (herbicides, insecticides, fungicides, and molluscicides), veterinary and human pharmaceuticals, polycyclic aromatic compounds, polychlorinated biphenyls, flame retardants, and personal care products. Chemical mixtures are also discussed bearing in mind that chemicals appear simultaneously in the environment. The biomagnification of organic chemicals is considered in light of the consumption of terrestrial invertebrates as novel feed and food sources. This chapter highlights how science has contributed with data from the last 5 years, providing evidence on bioavailability, bioaccumulation, and toxicity derived from exposure to organic chemicals, including insights into the main challenges and shortcomings to extrapolate results to real exposure scenarios

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong