Preference and performance of Diachasmimorpha kraussii (Fullaway) (Hymenoptera: Braconidae) on five commercial fruit species

Diachasmimorpha kraussii is a polyphagous endoparasitoid of dacine fruit flies. The fruit fly hosts of D. krausii, in turn, attack a wide range of fruits and vegetables. The role that fruits play in host selection behaviour of D. kraussii has not been previously investigated. This study examines fruit preference of D. kraussii through a laboratory choice-test trial and field fruit sampling. In the laboratory trial, oviposition preference and offspring performance measures (sex ratio, developmental time, body length, hind tibial length) of D. kraussii were investigated with respect to five fruit species [Psidium guajava L. (guava), Prunis persica L. (peach), Malus domestica Borkh. (apple), Pyrus communis L. (pear) and Citrus sinensis L. (orange)], and two fruit fly species (Bactrocera jarvisi and B. tryoni). Diachasmimorpha kraussii responded to infested fruit of all fruit types in both choice and no-choice tests, but showed stronger preference for guava and peach in the choice tests irrespective of the species of fly larvae within the fruit. The wasp did not respond to uninfested fruit. The offspring performance measures differed in a non-consistent fashion between the fruit types, but generally wasp offspring performed better in guava, peach and orange. The offspring sex ratio, except for one fruit/fly combination (B. jarvisi in apple), was always female biased. The combined results suggest that of the five fruits tested, guava and peach are the best fruit substrates for D. krausii. Field sampling indicated a non-random use of available, fruit fly infested fruit by D. kraussii. Fruit fly maggots within two fruit species, Plachonia careya and Terminalia catappa, had disproportionately higher levels of D. krausii parasitism than would be expected based on the proportion of different infested fruit species sampled, or levels of fruit fly infestation within those fruit.

LZW Based Distance Measures for Spoken Language Identification

We present a new approach to spoken language modeling for language identification (LID) using the Lempel-Ziv-Welch (LZW) algorithm. The LZW technique is applicable to any kind of tokenization of the speech signal. Because of the efficiency of LZW algorithm to obtain variable length symbol strings in the training data, the LZW codebook captures the essentials of a language effectively. We develop two new deterministic measures for LID based on the LZW algorithm namely: (i) Compression ratio score (LZW-CR) and (ii) weighted discriminant score (LZW-WDS). To assess these measures, we consider error-free tokenization of speech as well as artificially induced noise in the tokenization. It is shown that for a 6 language LID task of OGI-TS database with clean tokenization, the new model (LZW-WDS) performs slightly better than the conventional bigram model. For noisy tokenization, which is the more realistic case, LZW-WDS significantly outperforms the bigram technique

Prey preference of lingcod (Ophiodon elongatus), a top marine predator: implications for ecosystem-based fisheries management

Many highly exploited ecosystems are managed on the basis of single-species demographic information. This management approach can exacerbate tensions among stakeholders with competing interests who in turn rely on data with notoriously high variance. In this case study, an application of diet and dive survey data was used to describe the prey preference of lingcod (Ophiodon elongatus) in a predictive framework on nearshore reefs off Oregon. The lingcod is a large, fast-growing generalist predator of invertebrates and fishes. In response to concerns that lingcod may significantly reduce diminished populations of rockfishes (Sebastes spp.), the diets of 375 lingcod on nearshore reefs along the Oregon Coast were compared with estimates of relative prey availability from dive surveys. In contrast to the transient pelagic fishes that comprised 46% of lingcod diet by number, rockfishes comprised at most 4.7% of prey items. Rockfishes were the most abundant potential prey observed in dive surveys, yet they were the least preferred. Ecosystem-based fisheries management (EBFM) requires information about primary trophic relationships, as well as relative abundance and distribution data for multiple species. This study shows that, at a minimum, predation relative to prey availability must be considered before predator effects can be understood in a management context.

Swimming depth, ambient water temperature preference, and feeding frequency of young Pacific bluefin tuna (Thunnus orientalis) determined with archival tags

We investigated the migration and behavior of young Pacific Bluefin tuna (Thunnus orientalis) using archival tags. The archival tag measures environmental variables, records them in its memory, and estimates daily geographical locations based on measured light levels. Of 166 archival tags implanted in Pacific bluefin tuna that were released at the northeastern end of the East China Sea from 1995 to 1997, 30 tags were recovered, including one from a fish that migrated across the Pacific. This article describes swimming depth, ambient water temperature, and feeding frequency of young Pacific bluefin tuna based on retrieved data. Tag performance, effect of the tag on the fish, and horizontal movements of the species are described in another paper. Young Pacific bluefin tuna swim mainly in the mixed layer, usually near the sea surface, and swim in deeper water in daytime than at nighttime. They also exhibit a pattern of depth changes, corresponding to sunrise and sunset, apparently to avoid a specific low light level. The archival tags recorded temperature changes in viscera that appear to be caused by feeding, and those changes indicate that young Pacific bluefin tuna commonly feed at dawn and in the daytime, but rarely at dusk or at night. Water temperature restricts their distribution, as indicated by changes in their vertical distribution with the seasonal change in depth of the thermocline and by the fact that their horizontal distribution is in most cases confined to water in the temperature range of 14−20°C.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Copula-based Kernel Dependency Measures

The paper presents a new copula based method for measuring dependence between random variables. Our approach extends the Maximum Mean Discrepancy to the copula of the joint distribution. We prove that this approach has several advantageous properties. Similarly to Shannon mutual information, the proposed dependence measure is invariant to any strictly increasing transformation of the marginal variables. This is important in many applications, for example in feature selection. The estimator is consistent, robust to outliers, and uses rank statistics only. We derive upper bounds on the convergence rate and propose independence tests too. We illustrate the theoretical contributions through a series of experiments in feature selection and low-dimensional embedding of distributions.

Ventilation effectiveness measures based on heat removal: Part 2. Application to natural ventilation flows

The three effectiveness measures based on the ability of a flow to flush buoyancy from a ventilated space proposed by Coffey and Hunt [Ventilation effectiveness measures based on heat removal-part 1. Definitions. Building and Environment, in press, doi:10.1016/j.buildenv.2006.03.016.] are applied to assess and compare two fundamental natural ventilation flows. We focus on the limiting cases of passive displacement and passive mixing ventilation flows during transient conditions. These transient flows occur when, for example, heat is purged from a building at night. Whilst it is widely recognised that mixing flows are less efficient at purging heat than displacement flows, our results indicate that, when a particular zone of a room is considered, displacement ventilation can result in lower effectiveness than mixing ventilation. When a room is considered as a whole, displacement ventilation yields higher effectiveness than mixing ventilation and we quantify these differences in terms of the geometry of the space and opening area. The proposed theoretical predictions are compared with effectiveness deduced from measurements made during laboratory experiments and show good agreement. © 2006 Elsevier Ltd. All rights reserved.

Ventilation effectiveness measures based on heat removal: Part 1. Definitions

The effectiveness of ventilation flows is considered from the perspective of buoyancy (or heat) removal from a space. This perspective is distinct from the standard in which the effectiveness is based on the concentrations of a neutrally buoyant contaminant/passive tracer. Three new measures of effectiveness are proposed based on the ability of a flow to flush buoyancy from a ventilated space. These measures provide estimates of instantaneous and time-averaged effectiveness for the entire space, and local effectiveness at any height of interest. From a generalisation of the latter, a vertical profile of effectiveness is defined. These measures enable quantitative comparisons to be made between different flows and they are applicable when there is a difference in density (as is typical due to temperature differences) between the interior environment and the replacement air. Applications, therefore, include natural ventilation, hybrid ventilation and a range of forced ventilation flows. Finally, we demonstrate how the ventilation effectiveness of a room may be assessed from simple traces of temperature versus time. © 2006 Elsevier Ltd. All rights reserved.

New ventilation efficiency measures based on buoyancy removal

New measures for estimating the efficiency of transient ventilation flows are proposed. These measures are developed by considering how effectively a ventilation system removes buoyancy from a space. This approach is distinct from standard efficiency measures which are, in general, based on the removal of a neutrally-buoyant passive tracer. Our new measures, based on (active) buoyancy removal, allow both the instantaneous and time-averaged efficiency of the entire space, or of any region within it, to be determined. In addition, expressions for determining vertical profiles of efficiency are proposed. These new measures enable the effectiveness of different flows to be compared directly and are applicable providing density (temperature) differences exist between the interior environment and the replacement air. Thus, they may be used to contrast the effectiveness of a broad range of building ventilation flows including natural, hybrid and forced ventilation.

Development and usability testing of a Web-based decision aid for families of patients receiving prolonged mechanical ventilation.

BACKGROUND: Web-based decision aids are increasingly important in medical research and clinical care. However, few have been studied in an intensive care unit setting. The objectives of this study were to develop a Web-based decision aid for family members of patients receiving prolonged mechanical ventilation and to evaluate its usability and acceptability. METHODS: Using an iterative process involving 48 critical illness survivors, family surrogate decision makers, and intensivists, we developed a Web-based decision aid addressing goals of care preferences for surrogate decision makers of patients with prolonged mechanical ventilation that could be either administered by study staff or completed independently by family members (Development Phase). After piloting the decision aid among 13 surrogate decision makers and seven intensivists, we assessed the decision aid's usability in the Evaluation Phase among a cohort of 30 surrogate decision makers using the Systems Usability Scale (SUS). Acceptability was assessed using measures of satisfaction and preference for electronic Collaborative Decision Support (eCODES) versus the original printed decision aid. RESULTS: The final decision aid, termed 'electronic Collaborative Decision Support', provides a framework for shared decision making, elicits relevant values and preferences, incorporates clinical data to personalize prognostic estimates generated from the ProVent prediction model, generates a printable document summarizing the user's interaction with the decision aid, and can digitally archive each user session. Usability was excellent (mean SUS, 80 ± 10) overall, but lower among those 56 years and older (73 ± 7) versus those who were younger (84 ± 9); p = 0.03. A total of 93% of users reported a preference for electronic versus printed versions. CONCLUSIONS: The Web-based decision aid for ICU surrogate decision makers can facilitate highly individualized information sharing with excellent usability and acceptability. Decision aids that employ an electronic format such as eCODES represent a strategy that could enhance patient-clinician collaboration and decision making quality in intensive care.