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Hydrothermal ecosystems are of high conservation and scientific value, but they are sensitive to external perturbations that result from development. This study examines the composition of vegetation at four plots at the Wairakei-Tauhara geothermal field, New Zealand, using the Scott height-frequency method, ground temperatures at 0.1- and 1-m depth, soil pH, and photographic surveys. It highlights the response of plant communities, in particular that of Kunzea ericoides var. microflora, in terms of composition, structure, and biomass index values, measures changes in ground temperature, as well as provides baseline data against which to compare future changes. It was found that optimal growing conditions for K. ericoides var. microflora are at temperatures above background conditions with a slightly acidic pH. Plots with cooler, less acidic conditions support more diverse plant communities, which also promote the establishment of invasive species. This suggests that the largest threats to thermotolerant vegetation in New Zealand, including K. ericoides var. microflora, are further decreases in ground temperature because the establishment of invasive species may result in thermolerant vegetation being out-competed in hydrothermal ecosystems. Recognising and understanding the ecological diversity and dynamics of hydrothermal ecosystems, as well as acknowledging the competing interests between development and conservation, is key to the management and protection of these areas. [ABSTRACT FROM AUTHOR]

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices, which are then suitably combined to estimate the constant for the entire lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and that may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios, enabling us to implement a practical and efficient nonsimulation-based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The online supplementary materials include our C++ source code for computing the approximate normalizing constant and simulation studies. [ABSTRACT FROM AUTHOR]

Abstract: A time series method for the determination of combustion chamber resonant frequencies is outlined. This technique employs the use of Markov-chain Monte Carlo (MCMC) to infer parameters in a chosen model of the data. The development of the model is included and the resonant frequency is characterised as a function of time. Potential applications for cycle-by-cycle analysis are discussed and the bulk temperature of the gas and the trapped mass in the combustion chamber are evaluated as a function of time from resonant frequency information. [Copyright &y& Elsevier]

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Presented is an experiment which can be used in a first-year chemistry class to introduce the synthesis and analysis of compounds. Described are the experimental procedures, sample data, analysis, and discussion. (CW)

In this work, we detail a novel application of inverse design and advanced manufacturing to rapidly develop and experimentally validate modifications to a shaped charge jet analog. The shaped charge jet analog comprises a copper liner, a high explosive (HE), and a silicone buffer. We apply a genetic algorithm to determine an optimal buffer design that can be placed between the liner and the HE that results in the largest possible change in jet velocity. The use of a genetic algorithm allows for discoveries of unintuitive, complex, yet optimal buffer designs. Experiments using the optimal design verified the effectiveness of the buffer and validated the machine learning approach to hydrodynamic design optimization. [ABSTRACT FROM AUTHOR]

This bibliography consists of 605 journal articles selected from 12 journals. The articles are arranged under 33 subject headings, with headings arranged alphabetically, and authors listed alphabetically under each heading. For ease of use, articles are numbered consecutively 1-605. [ABSTRACT FROM PUBLISHER]