Alfalfa Snout Beetle, \u3ci\u3eOtiorhynchus Ligustici\u3c/i\u3e L. (Coleoptera: Curculionidae): Methods for Egg Collection and Larval Rearing

The alfalfa snout beetle, Otiorhynchus ligustici L., is the most serious pest of alfalfa in northern New York State. Recent research efforts focused on the biological control of this insect require the availability of all life stages. With a 2-year lifecycle and a mandatory diapause, the artificial rearing of a laboratory culture appears to be a non-viable option at present, but methods described here can be used to obtain sufficient numbers of eggs and larvae over an extended period of time for research purposes. The crowding of adult beetles in egg production units (cups) had a significant, negative effect on egg production per beetle but the total egg production per cup was still higher with higher number of beetles per cup resulting in a significant saving of labor per egg produced. Larval survival rates in alfalfa-planted cans were surprisingly low given the protected conditions of the greenhouse. The larval survival rates were not significantly different among the dates for the second instar and later instars, suggesting that larval mortality occurs in the first instar in alfalfa-planted cans

A note on the fate of the Landau-Yang theorem in non-Abelian gauge theories

Using elementary considerations of Lorentz invariance, Bose symmetry and BRST invariance, we argue why the decay of a massive color-octet vector state into a pair of on-shell massless gluons is possible in a non-Abelian SU(N) Yang-Mills theory, we constrain the form of the amplitude of the process and offer a simple understanding of these results in terms of effective-action operators.Comment: 7 pages. v2: typos corrected, one reference adde

Multi-year Biological Control of Black Vine Weevil, Otiorhynchus sulcatus, with Persistent Entomopathogenic Nematodes

Abstract: The black vine weevil (BVW), Otiorhynchus sulcatus Fabricius (Coleoptera: Curculionidae), has a worldwide distribution and is a serious pest of many agricultural crops with a host plant species range of 140 plants. Common economic losses occur in small fruits, including strawberries, ornamental and nursery plants, caused primarily by the root feeding larvae resulting in reduced vigor and plant death. The susceptibility of BVW to entomopathogenic nematodes (EPNs) is well established with numerous authors publishing papers using a wide array of EPN species from commercial sources and very high application rates for use as a biopesticide. The concept of using native EPN strains that are climate adapted and retain the genetic traits of phased infectivity to persist across multiple years was successfully developed and tested on a related species, Otiorhynchus ligustici, alfalfa snout beetle. In this study, a single application of climate adapted persistent EPN strains resulted in a reduction of an economically damaging BVW population in strawberries to sub-economic levels. Subsequently, the BVW population remained undetectable for four years while the EPN populations remained moderately high

Management of Wireworms in Sweet Potatoes with Persistent NY Entomopathogenic Nematodes

Wireworms are the larval stages of click beetles (Coleoptera: Elateridae) and common polyphagous soil dwelling pests feeding on different plant parts including seeds, roots, stems, and tubers inhibiting plant growth eventually leading to plant death. With the ban of persistent synthetic insecticides such as lindane in 2009 due to negative effects on the environment, no effective control tactics (chemical or biological) are available for wireworms. Some entomopathogenic nematode species/strains have been reported to attack wireworms in the soil, causing death. Non-native EPN species have the advantage of being easily available commercial products for insect pest control. However, these strains do not persist and require annual application as a biopesticide. Native species provide an advantage because application is a single event with multi-year persistence and pest suppression. In the first harvest, the EPN combination of Steinernema feltiae x Heterorhabditis bacteriophora had significantly less wireworm feeding damage than the untreated check irrespective of whether the plants were located in the outside rows or the inside rows. The EPN combination of S. carpocapsae x S. feltiae were numerically different from the untreated checks, but the fewer wireworm feeding wounds were not statistically different from the untreated check. Inoculated EPNs were still present in 30% of the soil samples in all treated plots 1076 days after application/inoculation

Alfalfa Snout Beetle, \u3ci\u3eOtiorhynchus Ligustici\u3c/i\u3e L. (Coleoptera: Curculionidae): Methods for Egg Collection and Larval Rearing

The alfalfa snout beetle, Otiorhynchus ligustici L., is the most serious pest of alfalfa in northern New York State. Recent research efforts focused on the biological control of this insect require the availability of all life stages. With a 2-year lifecycle and a mandatory diapause, the artificial rearing of a laboratory culture appears to be a non-viable option at present, but methods described here can be used to obtain sufficient numbers of eggs and larvae over an extended period of time for research purposes. The crowding of adult beetles in egg production units (cups) had a significant, negative effect on egg production per beetle but the total egg production per cup was still higher with higher number of beetles per cup resulting in a significant saving of labor per egg produced. Larval survival rates in alfalfa-planted cans were surprisingly low given the protected conditions of the greenhouse. The larval survival rates were not significantly different among the dates for the second instar and later instars, suggesting that larval mortality occurs in the first instar in alfalfa-planted cans

Semi-supervised detection of structural damage using Variational Autoencoder and a One-Class Support Vector Machine

In recent years, Artificial Neural Networks (ANNs) have been introduced in Structural Health Monitoring (SHM) systems. A semi-supervised method with a data-driven approach allows the ANN training on data acquired from an undamaged structural condition to detect structural damages. In standard approaches, after the training stage, a decision rule is manually defined to detect anomalous data. However, this process could be made automatic using machine learning methods, whom performances are maximised using hyperparameter optimization techniques. The paper proposes a semi-supervised method with a data-driven approach to detect structural anomalies. The methodology consists of: (i) a Variational Autoencoder (VAE) to approximate undamaged data distribution and (ii) a One-Class Support Vector Machine (OC-SVM) to discriminate different health conditions using damage sensitive features extracted from VAE's signal reconstruction. The method is applied to a scale steel structure that was tested in nine damage's scenarios by IASC-ASCE Structural Health Monitoring Task Group