Growers’ risk perception and trust in control options for huanglongbing citrus-disease in Florida and California

Citrus huanglongbing disease is an acute bacterial disease that threatens the sustainability of citrus production across the world. In the USA, the Asian Citrus Psyllid (ACP) is responsible for spreading the disease. Successful suppression of HLB requires action against ACP at large spatial scales, i.e. growers must cooperate. In Florida and California, the regions in which citrus is grown have been split into management areas and growers are encouraged to coordinate spraying of insecticide across these (area-wide control). We surveyed growers from Florida and California to assess the consensus of opinions concerning issues that influence HLB management. Our results show that risk perception and trust in control options are central to the decision by growers on whether to join an area-wide control program. Growers’ perceptions on risk and control efficacy are influenced by information networks and observations about the state of the epidemic and psyllid populations. Researchers and extension agents were reported to have the largest influence on these perceptions. Differences in opinion between California and Florida growers as to the efficacy of treatments were largely a function of experience. A large proportion of growers identified failure of participation as a reason why participation in area-wide control might not occur

Using Functional Traits to Model Annual Plant Community Dynamics

Predicting the response of biological communities to changes in the environment or management is a fundamental pursuit of community ecology. Meeting this challenge requires the integration of multiple processes: habitat filtering, niche differentiation, biotic interactions, competitive exclusion, and stochastic demographic events. Most approaches to this long-standing problem focus either on the role of the environment, using trait-based filtering approaches, or on quantifying biotic interactions with process-based community dynamics models. We introduce a novel approach that uses functional traits to parametrise a process-based model. By combining the two approaches we make use of the extensive literature on traits and community filtering as a convenient means of reducing the parametrisation requirements of a complex population dynamics model whilst retaining the power to capture the processes underlying community assembly. Using arable weed communities as a case study, we demonstrate that this approach results in predictions that show realistic distributions of traits and that trait selection predicted by our simulations is consistent with in-field observations. We demonstrate that trait-based filtering approaches can be combined with process-based models to derive the emergent distribution of traits. While initially developed to predict the impact of crop management on functional shifts in weed communities, our approach has the potential to be applied to other annual plant communities if the generality of relationships between traits and model parameters can be confirmed

L'estime de soi globale et physique à l'adolescence

International audienceObjective. From a data collection conducted among junior high-school students, we propose to assess global and physical self-esteem. Indeed, profound physical changes, psychological and social affect this phase of development of the person and the object of this article is to clarify what are the potential impacts of these changes on self-esteem as a function of age and gender. Methods. 579 junior high-school students of the Midi Pyrenees region, aged 11 to 17 years (M = 13.34, SD = 1.20) have informed the Rosenberg self-esteem scale (1965) and the physical self-inventory (Ninot, Delignières and Fortes, 2000). Results. The reliability of both tools is confirmed from our study sample. The results allow to update significant differences in global and physical self-esteem according to the age and gender of the adolescents. Conclusion. The discussion focuses on the interpretation of gender differences in the assessment of global self-esteem and physical interpretation of the differences in the development of the person.Objectif de l'étude : À partir d'un recueil de données réalisé auprès d'élèves de collège, nous proposons d'évaluer l'estime de soi dans les domaines global et physique. En effet, de profondes modifications physiques, psychologiques et sociales affectent cette phase de développement de la personne et l'objet de cet article est de préciser quelles sont les répercussions possibles de ces transformations sur l'estime de soi en fonction de l'âge et du genre. Sujets : 579 collégien(ne)s de la région Midi Pyrénées, âgés de 11 à 17 ans (M = 13,34 ; ET = 1,20) ont renseigné l'échelle unidimensionnelle de Rosenberg (1965) et l'Inventaire de Soi Physique de Ninot, Delignières et Fortes (2000). Résultats. La fiabilité des deux outils utilisés est confirmée auprès de notre échantillon d'étude. Les résultats permettent de mettre à jour des différences significatives d'estime de soi globale et physique en fonction de l'âge et du genre des adolescent(e)s. Conclusion. La discussion s'oriente sur l'interprétation des différences de genre dans l'évaluation de l'estime de soi globale et physique et sur l'interprétation de différences au cours du développement de la personne

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound Images

Breast cancer is one of the leading causes of cancer death among women worldwide. The proposed approach comprises three steps as follows. Firstly, the image is preprocessed to remove speckle noise while preserving important features of the image. Three methods are investigated, i.e., Frost Filter, Detail Preserving Anisotropic Diffusion, and Probabilistic Patch-Based Filter. Secondly, Normalized Cut or Quick Shift is used to provide an initial segmentation map for breast lesions. Thirdly, a postprocessing step is proposed to select the correct region from a set of candidate regions. This approach is implemented on a dataset containing 20 B-mode ultrasound images, acquired from UDIAT Diagnostic Center of Sabadell, Spain. The overall system performance is determined against the ground truth images. The best system performance is achieved through the following combinations: Frost Filter with Quick Shift, Detail Preserving Anisotropic Diffusion with Normalized Cut and Probabilistic Patch-Based with Normalized Cut

Tail state limited photocurrent collection of thick photoactive layers in organic solar cells

We analyse organic solar cells with four different photoactive blends exhibiting differing dependencies of short-circuit current upon photoactive layer thickness. These blends and devices are analysed by transient optoelectronic techniques of carrier kinetics and densities, air photoemission spectroscopy of material energetics, Kelvin probe measurements of work function, Mott-Schottky analyses of apparent doping density and by device modelling. We conclude that, for the device series studied, the photocurrent loss with thick active layers is primarily associated with the accumulation of photo-generated charge carriers in intra-bandgap tail states. This charge accumulation screens the device internal electrical field, preventing efficient charge collection. Purification of one studied donor polymer is observed to reduce tail state distribution and density and increase the maximal photoactive thickness for efficient operation. Our work suggests that selecting organic photoactive layers with a narrow distribution of tail states is a key requirement for the fabrication of efficient, high photocurrent, thick organic solar cells

Influence of Surface Recombination on Charge-Carrier Kinetics in Organic Bulk Heterojunction Solar Cells with Nickel Oxide Interlayers

The choice of electrode for organic photovoltaics is known to be of importance to both device stability and performance, especially regarding the open-circuit voltage (VOC). Here we show that the work function of a nickel oxide anode, varied using an O2 plasma treatment, has a considerable influence on the open-circuit voltage VOC of an organic solar cell. We probe recombination in the devices using transient photovoltage and charge extraction to determine the lifetime as a function of charge-carrier concentration and compare the experimental results with numerical drift-diffusion simulations. This combination of experiment and simulations allows us to conclude that the variations in VOC are due to a change in surface recombination, localized at the NiO anode, although only a small change in carrier lifetime is observed