Parasitism of \u3ci\u3ePlathypena Scabra\u3c/i\u3e (Lepidoptera: Noctuidae) by \u3ci\u3eSinophorus Teratis\u3c/i\u3e (Hymenoptera: Ichneumonidae)

(excerpt) A study was conducted at the Ecology Research Center, Miami University, Butler County, Ohio, during the summer of 1990 to examine the effects of strip intercropping sorghum and soybean on the occurrence of parasitoids and incidence of disease in larvae ofthe green cloverworm, Plathypena scabra (F.) (Lepidoptera: Noctuidae), a sporadic pest of soybeans. The details of the experimental design and results are reported elsewhere (Williams et al. 1995)

Alien Registration- Taylor, Charles E. (Lubec, Washington County)

https://digitalmaine.com/alien_docs/1886/thumbnail.jp

Increase of phenotypic variance in stressful environments

The hypothesis that genetic homeostasis breaks down to yield greater genetic variance in more stressful environments was examined. Environmental stress was measured by mean development time and by wing length, it being expected that more stress generally gives rise to longer development times and shorter wings. The correlations between mean values and genetic variance were predicted to be positive for development time and negative for wing length. The correlations were not always statistically significant, but were in the predicted direction in 7 out of 8 tests. Quite possibly this phenomenon contributes to observed increases of genetic variation in marginal environments and more rapid evolution during periods of special stres

Selecting International Modes of Entry and Expansion

Selecting a mode for entering or expanding in a foreign market is a crucial strategic decision for an international firm. This article identifies and compares the most influential factors that affect the international modes of entry and expansion decisions of US and Japanese firms. Using mail surveys, this is one of the first studies on this subject to collect data from top executives in both Japan and the USA. Findings reveal that the Japanese are particularly sensitive to external risk and other target market factors. For Americans, company factors, such as international experience, appear to be most important when selecting modes of entry. Joint ventures may be more appropriate for internationally‐experienced firms, than for inexperienced companies

Statistical analysis of particulate matter data in Doha, Qatar

Pollution in Doha is measured using passive, active and automatic sampling. In this paper we consider data automatically sampled in which various pollutants were continually collected and analysed every hour. At each station the sample is analysed on-line and in real time and the data is stored within the analyser, or a separate logger so it can be downloaded remotely by a modem. The accuracy produced enables pollution episodes to be analysed in detail and related to traffic flows, meteorology and other variables. Data has been collected hourly over more than 6 years at 3 different locations, with measurements available for various pollutants – for example, ozone, nitrogen oxides, sulphur dioxide, carbon monoxide, THC, methane and particulate matter (PM1.0, PM2.5 and PM10), as well as meteorological data such as humidity, temperature, and wind speed and direction. Despite much care in the data collection process, the resultant data has long stretches of missing values, when the equipment has malfunctioned – often as a result of more extreme conditions. Our analysis is twofold. Firstly, we consider ways to “clean” the data, by imputing missing values, including identified outliers. The second aspect specifically considers prediction of each particulate (PM1.0, PM2.5 and PM10) 24 hours ahead, using current (and previous) pollution and meteorological data. In this case, we use vector autoregressive models, compare with decision trees and propose variable selection criteria which explicitly adapt to missing data. Our results show that the regression tree models, with no variable transformations, perform the best, and that attempts to impute missing values are hampered by non-random missingness

Strain-Compensated InGaAsP Superlattices for Defect Reduction of InP Grown on Exact-Oriented (001) Patterned Si Substrates by Metal Organic Chemical Vapor Deposition.

We report on the use of InGaAsP strain-compensated superlattices (SC-SLs) as a technique to reduce the defect density of Indium Phosphide (InP) grown on silicon (InP-on-Si) by Metal Organic Chemical Vapor Deposition (MOCVD). Initially, a 2 μm thick gallium arsenide (GaAs) layer was grown with very high uniformity on exact oriented (001) 300 mm Si wafers; which had been patterned in 90 nm V-grooved trenches separated by silicon dioxide (SiO₂) stripes and oriented along the [110] direction. Undercut at the Si/SiO₂ interface was used to reduce the propagation of defects into the III-V layers. Following wafer dicing; 2.6 μm of indium phosphide (InP) was grown on such GaAs-on-Si templates. InGaAsP SC-SLs and thermal annealing were used to achieve a high-quality and smooth InP pseudo-substrate with a reduced defect density. Both the GaAs-on-Si and the subsequently grown InP layers were characterized using a variety of techniques including X-ray diffraction (XRD); atomic force microscopy (AFM); transmission electron microscopy (TEM); and electron channeling contrast imaging (ECCI); which indicate high-quality of the epitaxial films. The threading dislocation density and RMS surface roughness of the final InP layer were 5 × 10⁸/cm² and 1.2 nm; respectively and 7.8 × 10⁷/cm² and 10.8 nm for the GaAs-on-Si layer

Multi-criterial analysis of surface air temperature patterns in Arctic Canada

1 online resource (ix, 54 leaves) : ill. (some col.), map.Includes abstract.Includes bibliographical references (leaves 52-54).Interest in monitoring global climate has increased in recent years as the potential implications of climate change have come into the conscious of the public. Climate models and observations have shown that the polar regions are especially sensitive to climate change. This is especially concerning since the polar regions could experience several positive feedbacks as a result of increasing surface temperatures and/or change in their variability. The purpose of this study is to analyze surface air temperature data from nine weather stations in Arctic Canada to gain a better understanding of the status of the region’s climate. Nine stations spread across the Canadian Arctic region were chosen from a larger database of homogenized surface temperature time series extracted from the National Climate Data Archive. The nine stations were chosen based on their length (equal or greater than 50 years). A multi-scale analysis was conducted to explore whether surface temperature patterns in Arctic Canada appear to be changing from the point of view of overall trends and temporal variability in the region. Pattern change was analyzed using a height-height correlation analysis of time series of different lengths. Statistical patterns examined using these methods include mean, standard deviation, range, moments on n[superscript th], and the Hurst-exponent (for analyzing pattern persistence). The results indicate that there are spatial correlations in pattern persistence, and that the correlations change over time