Efficacy of diamide, neonicotinoid, pyrethroid, and phenyl pyrazole insecticide seed treatments for controlling the sugar beet wireworm, Limonius californicus (Coleoptera: Elateridae), in spring wheat

Four classes of insecticide applied on seed were evaluated for managing high populations of the sugar beet wireworm, Limonius californicus (Coleoptera: Elateridae), in spring wheat in southern Alberta, Canada. Three separate field trials were conducted, and assessments made for stand protection, yield, and wireworm survival. Imidacloprid and thiamethoxam applied at 10–30 g AI and cyantraniliprole applied at 10–40 g AI provided initial stand protection, but did not protect seedlings until harvest and did not decrease wireworm populations. λ-cyhalothrin applied at 30 g AI provided stand protection that persisted until harvest, but yields were considerably lower than observed in fipronil treatments and there was little (23%) decrease in populations relative to controls. Fipronil applied at 0.6, 1.0, and 5.0 g AI, either singly or in blend with thiamethoxam at 10 g AI, provided stand protection until harvest and significantly reduced numbers of wireworms larger than 10 mm (range: 74–96%). Very low numbers of small (<11 mm) wireworms were observed in all trials. These results are compared to data from laboratory and field studies for this and other wireworm species. The relation between crop stand protection and wireworm mortality, the potential of insecticide blends, and the importance of seed type, wireworm species, and activity periods for managing wireworms with seed treatments are discussed

A first step toward uncovering the truth about weight tuning in deformable image registration

Deformable image registration is currently predominantly solved by optimizing a weighted linear combination of objectives. Successfully tuning the weights associated with these objectives is not trivial, leading to trial-and-error approaches. Such an approach assumes an intuitive interplay between weights, optimization objectives, and target registration errors. However, it is not known whether this always holds for existing registration methods. To investigate the interplay between weights, optimization objectives, and registration errors, we employ multi-objective optimization. Here, objectives of interest are optimized simultaneously, causing a set of multiple optimal solutions to exist, called the optimal Pareto front. Our medical application is in breast cancer and includes the challenging prone-supine registration problem. In total, we studied the interplay in three different ways. First, we ran many random linear combinations of objectives using the well-known registration software elastix. Second, since the optimization algorithms used in registration are typically of a local-search nature, final solutions may not always form a Pareto front. We therefore employed a multi-objective evolutionary algorithm that finds weights that correspond to registration outcomes that do form a Pareto front. Third, we examined how the interplay differs if a true multi-objective (i.e., weight-free) image registration method is used. Results indicate that a trial-and-error weight-adaptation approach can be successful for the easy prone to prone breast image registration case, due to the absence of many local optima. With increasing problem difficulty the use of more advanced approaches can be of value in finding and selecting the optimal registration outcomes

On the usefulness of gradient information in multi-objective deformable image registration using a B-spline-based dual-dynamic transformation model: comparison of three optimization algorithms

The use of gradient information is well-known to be highly useful in single-objective optimization-based image registration methods. However, its usefulness has not yet been investigated for deformable image registration from a multi-objective optimization perspective. To this end, within a previously introduced multi-objective optimization framework, we use a smooth B-spline-based dual-dynamic transformation model that allows us to derive gradient information analytically, while still being able to account for large deformations. Within the multi-objective framework, we previously employed a powerful evolutionary algorithm (EA) that computes and advances multiple outcomes at once, resulting in a set of solutions (a so-called Pareto front) that represents efficient trade-offs between the objectives. With the addition of the B-spline-based transformation model, we studied the usefulness of gradient information in multiobjective deformable image registration using three different optimization algorithms: the (gradient-less) EA, a gradientonly algorithm, and a hybridization of these two. We evaluated the algorithms to register highly deformed images: 2D MRI slices of the breast in prone and supine positions. Results demonstrate that gradient-based multi-objective optimization significantly speeds up optimization in the initial stages of optimization. However, allowing sufficient computational resources, better results could still be obtained with the EA. Ultimately, the hybrid EA found the best overall approximation of the optimal Pareto front, further indicating that adding gradient-based optimization for multiobjective optimization-based deformable image registration can indeed be beneficial

Diversifying Multi-Objective Gradient Techniques and their Role in Hybrid Multi-Objective Evolutionary Algorithms for Deformable Medical Image Registration

Gradient methods and their value in single-objective, real-valued optimization are well-established. As such, they play a key role in tackling real-world, hard optimization problems such as deformable image registration (DIR). A key question is to which extent gradient techniques can also play a role in a multi-objective approach to DIR. We therefore aim to exploit gradient information within an evolutionary-algorithm-based multi-objective optimization framework for DIR. Although an analytical description of the multi-objective gradient (the set of all Pareto-optimal improving directions) is available, it is nontrivial how to best choose the most appropriate direction per solution because these directions are not necessarily uniformly distributed in objective space. To address this, we employ a Monte-Carlo method to obtain a discrete, spatially-uniformly distributed approximation of the set of Pareto-optimal improving directions. We then apply a diversification technique in which each solution is associated with a unique direction from this set based on its multi- as well as single-objective rank. To assess its utility, we compare a state-of-the-art multi-objective evolutionary algorithm with three different hybrid versions thereof on several benchmark problems and two medical DIR problems. Results show that the diversification strategy successfully leads to unbiased improvement, helping an adaptive hybrid scheme solve all problems, but the evolutionary algorithm remains the most powerful optimization method, providing the best balance between proximity and diversity

On the difference between type E and A OH/IR stars

The observed SEDs of a sample of 60 OH/IR stars are fitted using a radiative transfer model of a dusty envelope. Among the whole sample, 21 stars have reliable phase-lag distances while the others have less accurate distances. L*-P,Mlr-P and Mlr-L* relations have been plotted for these stars. It is found that type E (with emission feature at 10um and type A (with absorption feature at 10um) OH/IR stars have different L*-P and Mlr-L* relations while both of them follow a single Mlr-P relation. The type E stars are proven to be located in the area without large scale dense interstellar medium while the type A stars are located probably in dense interstellar medium. It is argued here that this may indicate the two types of OH/IR stars have different chemical composition or zero age main sequence mass and so evolve in different ways. This conclusion has reinforced the argument by Chen et al.(2001) who reached a similar conclusion from the galactic distribution of about 1000 OH/IR stars with the IRAS low-resolution spectra (LRS).Comment: 6 pages, 9 figures, 2 table

The influence of BRAF and KRAS mutation status on the association between aspirin use and survival after colon cancer diagnosis

Background: Use of aspirin after diagnosis of colon cancer has been associated with improved survival. Identification of cancer subtypes that respond to aspirin treatment may help develop personalized treatment regimens. The aim of this study was to investigate the influence of BRAF and KRAS mutation status on the association between aspirin use and overall survival after colon cancer diagnosis. Methods: A random selection of 599 patients with colon cancer were analyzed, selected from the Eindhoven Cancer Registry, and BRAF and KRAS mutation status was determined. Data on aspirin use (80 mg) were obtained from the PHARMO Database Network. Parametric survival models with exponential (Poisson) distribution were used. Results: Aspirin use after colon cancer diagnosis was associated with improved overall survival in wild-type BRAF tumors, adjusted rate ratio (RR) of 0.60 (95% CI 0.44-0.83). In contrast, aspirin use in BRAF mutated tumors was not associated with an improved survival (RR 1.11, 95% CI 0.57-2.16). P-value for interaction was non-significant. KRAS mutational status did not differentiate in the association between aspirin use and survival. Conclusion: Low-dose aspirin use after colon cancer diagnosis was associated with improved survival in BRAF wild-type tumors only. However, the large confidence interval of the rate ratio for the use of aspirin in patients with BRAF mutation does not rule out a possible benefit. These results preclude BRAF and KRAS mutation status to be used as a marker for individualized treatment with aspirin, if aspirin becomes regular adjuvant treatment for colon cancer patients in the future

Assessment of flatness and symmetry of megavoltage x-ray beam with an electronic portal imaging device (EPID)

Copyright © 2002 ACPSEM. All rights reserved. The document attached has been archived with permission from the publisher.The input/output characteristics of the Wellhofer BIS 710 electronic portal imaging device (EPID) have been investigated to establish its efficacy for periodic quality assurance (QA) applications. Calibration curves have been determined for the energy fluence incident on the detector versus the pixel values. The effect of the charge coupled device (CCD) camera sampling time and beam parameters (such as beam field size, dose rate, photon energy) on the calibration have been investigated for a region of interest (ROI) around the central beam axis. The results demonstrate that the pixel output is a linear function of the incident exposure, as expected for a video-based electronic portal imaging system. The field size effects of the BIS 710 are similar to that of an ion chamber for smaller field sizes up to 10 x 10 cm2. However, for larger field sizes the pixel value increases more rapidly. Furthermore, the system is slightly sensitive to dose rate and is also energy dependent. The BIS 710 has been used in the current study to develop a QA procedure for measurements of flatness and symmetry of a linac x-ray beam. As a two-dimensional image of the radiation field is obtained from a single exposure of the BIS 710, a technique has been developed to calculate flatness and symmetry from a defined radiation area. The flatness and symmetry values obtained are different from those calculated conventionally from major axes only (inplane, crossplane). This demonstrates that the technique can pick up the "cold" and "hot" spots in the analysed area, providing thus more information about the radiation beam. When calibrated against the water tank measurements, the BIS 710 can be used as a secondary device to monitor the x-ray beam flatness and symmetry.G. Liu, T. van Doorn and E. Beza