Increased mantle convection during the mid-Cretaceous: A comparative study of mantle potential temperature

Mantle convection patterns of the past are not well known, yet an understanding of changing mantle convection characteristics is fundamental to understanding the evolution of plate tectonics. There are very few ways to examine mantle characteristics of the past. Changes in spreading rate and volcanic activity with time have been used to draw conclusions about historic changes in mantle activity. Mantle temperature has been found to be related to crustal thickness. With this relationship, crustal thicknesses may now yield new conclusions about historic changes in mantle characteristics. We have inferred changes in mantle convection patterns throughout the last 180 m.y. by examining variations in assumed crustal thickness within the Pacific basin. Crustal thicknesses were calculated from residual depth anomalies by assuming that residual depth anomalies are the result of isostatic compensation of variations in crustal thickness. Crustal thickness is determined at the time of crustal formation and is dependent upon the temperature of the mantle source material. Intraplate hot spot volcanism effects on crustal thickness were not ignored. Examination of variations in crustal thickness of crust of different ages can reveal information about changing temperatures of the mantle at the ridge through time. We have learned that mantle temperatures at the ridge during the mid-Cretaceous were more variable than those temperatures at the ridge after the mid-Cretaceous. Furthermore, we have inferred from the data that mantle temperatures at hot spots were higher during the mid-Cretaceous than those at hot spots existing after the mid-Cretaceous. We suggest that mantle convection at the ridge was more rapid during the mid-Cretaceous causing a higher variability of temperatures at the ridge. We also note that this period of increased mantle convection is concurrent with the increased mantle temperatures at hot spots within the Pacific basin

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Optimal Hermite Collocation Applied to a One-Dimensional Convection-Diffusion Equation Using an Adaptive Hybrid Optimization Algorithm

Purpose – The Hermite collocation method of discretization can be used to determine highly accurate solutions to the steady-state one-dimensional convection-diffusion equation (which can be used to model the transport of contaminants dissolved in groundwater). This accuracy is dependent upon sufficient refinement of the finite-element mesh as well as applying upstream or downstream weighting to the convective term through the determination of collocation locations which meet specified constraints. Owing to an increase in computational intensity of the application of the method of collocation associated with increases in the mesh refinement, minimal mesh refinement is sought. Very often this optimization problem is the one where the feasible region is not connected and as such requires a specialized optimization search technique. This paper aims to focus on this method. Design/methodology/approach – An original hybrid method that utilizes a specialized adaptive genetic algorithm followed by a hill-climbing approach is used to search for the optimal mesh refinement for a number of models differentiated by their velocity fields. The adaptive genetic algorithm is used to determine a mesh refinement that is close to a locally optimal mesh refinement. Following the adaptive genetic algorithm, a hill-climbing approach is used to determine a local optimal feasible mesh refinement. Findings – In all cases the optimal mesh refinements determined with this hybrid method are equally optimal to, or a significant improvement over, mesh refinements determined through direct search methods. Research limitations – Further extensions of this work could include the application of the mesh refinement technique presented in this paper to non-steady-state problems with time-dependent coefficients with multi-dimensional velocity fields. Originality/value – The present work applies an original hybrid optimization technique to obtain highly accurate solutions using the method of Hermite collocation with minimal mesh refinement

Least-Cost Groundwater Remediation Using Uncertain Hydrogeological Information

The design of groundwater remediation pump-and-treat well networks under aquifer parameter measurement uncertainty can be addressed using an optimal-design strategy based upon the concept of robust optimization. The robust-optimization approach allows for the admission of design alternatives that do not satisfy all design constraints. However in the selection process the algorithm penalizes such selections based upon the number of constraints violated. The result is a design which balances the importance of reliability with overall project cost. The robust-optimization method has been applied to the problem of groundwater plume containment and risk-based groundwater remediation design. Designs dedicated to groundwater-plume containment assure that the contaminant plume will not extend beyond a prespecified perimeter. Inwardly directed groundwater velocity must be achieved along this perimeter. The outer-approximation optimization technique in combination with a groundwater flow model ( PTC) is used to solve this optimal-design problem

Efficient groundwater remediation system designs with flow and concentration constraints subject to uncertainty

Δημοσίευση σε επιστημονικό περιοδικόSummarization: A nested optimization problem that utilizes a multiscenario approach based upon a method known as robust optimization is employed to determine a groundwater remediation design that considers the uncertainty in the hydraulic conductivity in the flow and transport model. This optimization approach reduces a complicated multiscenario approach to a simple deterministic method for optimization. The parameter values associated with the final deterministic model represent not the true physical model, but rather a model that results in a conservatively designed remediation system that accounts for the uncertainty in the hydraulic conductivity. Both flow constraints and concentration constraints are considered in this approach, and as such the optimization problem is nonlinear in both its objective function and its constraints. A search method that combines simulated annealing and a downhill simplex algorithm is used to determine the solution to this optimization problem.Presented on: Journal of Water Resources Planning and Managemen