Economically optimal timing for crop disease control under uncertainty: an options approach

Severe large-scale disease and pest infestations in agricultural regions can cause significant economic damage. Understanding if and when disease control measures should be taken in the presence of risk and uncertainty is a key issue. We develop a framework to examine the economically optimal timing of treatment. The decision to treat should only be undertaken when the benefits exceed the costs by a certain amount and not if they are merely equal to or greater than the costs as standard net-present-value (NPV) analysis suggests. This criterion leads to a reduction in fungicide use. We investigate the effect of the model for disease progress on the value required for immediate treatment by comparing two standard models for disease increase (exponential and logistic growth). Analyses show that the threshold value of benefits required for immediate release of treatment varies significantly with the relative duration of the agricultural season, the intrinsic rate of increase of the disease and the level of uncertainty in disease progression. In comparing the performance of the delay strategy introduced here with the conventional NPV approach, we show how the degree of uncertainty affects the benefits of delaying control.     

Recovering Occlusion Boundaries from an Image

Occlusion reasoning is a fundamental problem in computer vision. In this paper, we propose an algorithm to recover the occlusion boundaries and depth ordering of free-standing structures in the scene. Rather than viewing the problem as one of pure image processing, our approach employs cues from an estimated surface layout and applies Gestalt grouping principles using a conditional random field (CRF) model. We propose a hierarchical segmentation process, based on agglomerative merging, that re-estimates boundary strength as the segmentation progresses. Our experiments on the Geometric Context dataset validate our choices for features, our iterative refinement of classifiers, and our CRF model. In experiments on the Berkeley Segmentation Dataset, PASCAL VOC 2008, and LabelMe, we also show that the trained algorithm generalizes to other datasets and can be used as an object boundary predictor with figure/ground labels.     

Further Exploration of Controlled and Automatic Memory Processes in Early Alzheimer's Disease.

The authors' aim in this study was to explore automatic and controlled processes in Alzheimer's disease (AD) by using a variant of the word-stem completion task that applies the process-dissociation procedure. Several methodological precautions were taken in order to limit problems observed in previous studies (e.g., poor task sensitivity, ceiling and/or floor effects, no control over comprehension of instructions). Our results (a) confirmed the marked deterioration in controlled processes and (b) showed that when psychometric constraints were limited, automatic memory processes were preserved in AD. These data are in line with those from more global studies in suggesting that AD is characterized by an early deterioration in controlled processes and an initial preservation of automatic processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Background estimation under rapid gain change in thermal imagery

We consider detection of moving ground vehicles in airborne sequences recorded by a thermal sensor with automatic gain control, using an approach that integrates dense optic flow over time to maintain a model of background appearance and a foreground occlusion layer mask. However, the automatic gain control of the thermal sensor introduces rapid changes in intensity that makes this difficult. In this paper we show that an intensity-clipped affine model of sensor gain is sufficient to describe the behavior of our thermal sensor. We develop a method for gain estimation and compensation that uses sparse flow of corner features to compute the affine background scene motion that brings pairs of frames into alignment prior to estimating change in pixel brightness. Dense optic flow and background appearance modeling is then performed on these motion-compensated and brightness-compensated frames. Experimental results demonstrate that the resulting algorithm can segment ground vehicles from thermal airborne video while building a mosaic of the background layer, despite the presence of rapid gain changes.     

Mindful Attention Awareness Scale (MAAS): Psychometric properties of the French translation and exploration of its relations with emotion regulation strategies.

Over the past few years, several questionnaires have been developed to measure mindfulness. The Mindful Attention Awareness Scale (MAAS) was created to specifically capture attention and awareness in daily life (Brown & Ryan, 2003). In this article, we present a French adaptation of the MAAS. In the 1st study, we explored the psychometric properties of this adaptation. In the 2nd study, we investigated its relation to cognitive emotion regulation and depressive symptomatology using path analysis. As in the original version of the MAAS, the French adaptation has a strong 1-factor structure. Moreover, there was a negative relationship between the MAAS and the severity of depressive symptoms, both directly and indirectly. The indirect pathway was mediated by the nonadaptive cognitive emotion regulation strategy of self-blame and the adaptive cognitive emotion regulation strategy of positive reappraisal. In conclusion, this questionnaire represents a valid mindfulness measure for French-speaking clinicians and researchers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Metabolic Characterization of Caviar Specimens by 1H NMR Spectroscopy: Towards Caviar Authenticity and Integrity

Food Analytical Methods - The specific metabolic profile of aqueous extracts of caviar samples (n = 91) originating from producers in the Aquitaine region in France was determined using...     

Oxydation electrochimique de la N,N-dimethyl-mesidine (DMM) dans l'acetonitrile en presence de trimethoxy-1, 3, 5 benzene (TMB). Role du produit d'addition du cation iminium de la DMM sur le TMB

The electrochemical oxidation of DMM in acetonitrile (0.1 M LiClO₄) in the presence of TMB gives initially the unstable N-méthyl, N-(2,4,6-trimethoxybenzyl)-mesidine (III), resulting from the addition of TMB to the iminium cation (II) of DMM. However, (III) is itself oxidisable at a lower potential than DMM. Therefore, as soon as it is formed (III) is oxidized into two isomeric cations (IV) and (V). The fate of these cations depends on the circumstances. They may undergo hydrolysis, and, in the presence of diethylphosphonate they may react with the latter to give the products (XIII) and (XV).Moreover, the amine (III) is cleaved in acid medium to N-methyl-mesidine and a benzylic cation. The benzylic cation reacts with TMB to give not only (IX) but also a derivative of (IX), namely (X), having three methoxylated aromatic rings.As has been shown earlier [1], the oxidation of DMM also gives the dimer (VI) and its corresponding iminium cation, which is also capable of reacting with TMB.     

Evaluation of Surfactant Enhanced Water Mist Performance

Water-mist technology provides efficient fire suppression for compartments while minimizing water usage. Even with the many advantages of water mist systems, there is still room for improvement. Water mist systems have demonstrated effectiveness at suppressing flammable liquids (Class B) fires in compartments. However, an especially challenging fire suppression scenario for water mist systems is the small Class B fire. This scenario is often realized after a large fire has been reduced in size or ‘controlled’ by water mist. The small fire scenario is challenging because a small fire may not be able to generate enough vaporized water to displace sufficient oxygen for complete extinction. It should also be noted that even if the Class B fire is extinguished with a water mist system, re-ignition from the hot surrounding surfaces may occur at any time. In the present work, an additive is introduced into the water supply and its effect on the water mist suppression performance is studied. This Forafac^TM additive is a specific formulation, which includes fluorinated surfactants for creating a robust fire suppression foam. The enhanced suppressant exiting the mist nozzle is dispersed in the form of small droplets (not as a continuous foam) similar to a pure water mist spray. However, these droplets create a foam blanket on the surface of the fire, which acts to isolate the fuel from the air. With this formulation, the efficiency of the water mist system is improved even on small fires and most importantly the re-ignition of class B fires is prevented.