A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1

We present a Bayesian inference for a three-dimensional hydrodynamic model of Lake Geneva with stochastic weather forcing and high-frequency observational datasets. This is achieved by coupling a Bayesian inference package, SPUX, with a hydrodynamics package, MITgcm, into a single framework, SPUX-MITgcm. To mitigate uncertainty in the atmospheric forcing, we use a smoothed particle Markov chain Monte Carlo method, where the intermediate model state posteriors are resampled in accordance with their respective observational likelihoods. To improve the uncertainty quantification in the particle filter, we develop a bi-directional long short-term memory (BiLSTM) neural network to estimate lake skin temperature from a history of hydrodynamic bulk temperature predictions and atmospheric data. This study analyzes the benefit and costs of such a state-of-the-art computationally expensive calibration and assimilation method for lakes.</p

The read-across hypothesis and environmental risk assessment of pharmaceuticals

This article is made available through the Brunel Open Access Publishing Fund. Copyright © 2013 American Chemical Society.Pharmaceuticals in the environment have received increased attention over the past decade, as they are ubiquitous in rivers and waterways. Concentrations are in sub-ng to low μg/L, well below acute toxic levels, but there are uncertainties regarding the effects of chronic exposures and there is a need to prioritise which pharmaceuticals may be of concern. The read-across hypothesis stipulates that a drug will have an effect in non-target organisms only if the molecular targets such as receptors and enzymes have been conserved, resulting in a (specific) pharmacological effect only if plasma concentrations are similar to human therapeutic concentrations. If this holds true for different classes of pharmaceuticals, it should be possible to predict the potential environmental impact from information obtained during the drug development process. This paper critically reviews the evidence for read-across, and finds that few studies include plasma concentrations and mode of action based effects. Thus, despite a large number of apparently relevant papers and a general acceptance of the hypothesis, there is an absence of documented evidence. There is a need for large-scale studies to generate robust data for testing the read-across hypothesis and developing predictive models, the only feasible approach to protecting the environment.BBSRC Industrial Partnership Award BB/ I00646X/1 and BBSRC Industrial CASE Partnership Studentship BB/I53257X/1 with AstraZeneca Safety Health and Environment Research Programme

Protecting the environment from psychoactive drugs: Problems for regulators illustrated by the possible effects of tramadol on fish behaviour

© 2019 The Authors. There is concern that psychoactive drugs present in the aquatic environment could affect the behaviour of fish, and other organisms, adversely. There is considerable experimental support for this concern, although the literature is not consistent. To investigate why, fish were exposed to three concentrations of the synthetic opiate tramadol for 23–24 days, and their anxiolytic behaviour in a novel tank diving test was assessed both before and after exposure. The results were difficult to interpret. The positive control drug, the anti-depressant fluoxetine, produced the expected results: exposed fish explored the novel tank more, and swam more slowly while doing so. An initial statistical analysis of the results provided relatively weak support for the conclusion that both the low and high concentrations of tramadol affected fish behaviour, but no evidence that the intermediate concentration did. To gain further insight, UK and Japanese experts in ecotoxicology were asked for their independent opinions on the data for tramadol. These were highly valuable. For example, about half the experts replied that a low concentration of a chemical can cause effects that higher concentrations do not, although a similar number did not believe this was possible. Based both on the inconclusive effects of tramadol on the behaviour of the fish and the very varied opinions of experts on the correct interpretation of those inconclusive data, it is obvious that more research on the behavioural effects of tramadol, and probably all other psychoactive drugs, on aquatic organisms is required before any meaningful risk assessments can be conducted. The relevance of these findings may apply much more widely than just the environmental risk assessment of psychoactive drugs. They suggest that much more rigorous training of research scientists and regulators is probably required if consensus decisions are to be reached that adequately protect the environment from chemicals.Ecotoxicology Research Group, Brunel University London funded the fish experiments. We would also like to thank Dr. Matt Winter, University of Exeter, for his support with the behavioural analysis. This study was also supported by the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) to a project on Joint Usage/Research Centre – Leading Academia in Marine and Environment Pollution Research (LaMer), and Japan Society for the Promotion of Science (JSPS) Grants-in-Aid (KAKENHI) for JSPS Fellows (JP26·2800), Scientific Research (A) (JP25257403), Scientific Research (A) (JP16H01784), and Young Scientists (JP18K18206)

Quantitative cross-species extrapolation between humans and fish: The case of the anti-depressant fluoxetine

This article has been made available through the Brunel Open Access Publishing Fund.Fish are an important model for the pharmacological and toxicological characterization of human pharmaceuticals in drug discovery, drug safety assessment and environmental toxicology. However, do fish respond to pharmaceuticals as humans do? To address this question, we provide a novel quantitative cross-species extrapolation approach (qCSE) based on the hypothesis that similar plasma concentrations of pharmaceuticals cause comparable target-mediated effects in both humans and fish at similar level of biological organization (Read-Across Hypothesis). To validate this hypothesis, the behavioural effects of the anti-depressant drug fluoxetine on the fish model fathead minnow (Pimephales promelas) were used as test case. Fish were exposed for 28 days to a range of measured water concentrations of fluoxetine (0.1, 1.0, 8.0, 16, 32, 64 μg/L) to produce plasma concentrations below, equal and above the range of Human Therapeutic Plasma Concentrations (HTPCs). Fluoxetine and its metabolite, norfluoxetine, were quantified in the plasma of individual fish and linked to behavioural anxiety-related endpoints. The minimum drug plasma concentrations that elicited anxiolytic responses in fish were above the upper value of the HTPC range, whereas no effects were observed at plasma concentrations below the HTPCs. In vivo metabolism of fluoxetine in humans and fish was similar, and displayed bi-phasic concentration-dependent kinetics driven by the auto-inhibitory dynamics and saturation of the enzymes that convert fluoxetine into norfluoxetine. The sensitivity of fish to fluoxetine was not so dissimilar from that of patients affected by general anxiety disorders. These results represent the first direct evidence of measured internal dose response effect of a pharmaceutical in fish, hence validating the Read-Across hypothesis applied to fluoxetine. Overall, this study demonstrates that the qCSE approach, anchored to internal drug concentrations, is a powerful tool to guide the assessment of the sensitivity of fish to pharmaceuticals, and strengthens the translational power of the cross-species extrapolation

An Assessment of the Exporting Literature: Using Theory and Data to Identify Future Research Directions

Exporting research is an established facet of the field of international marketing. That stated, the radical increase in recent export activity necessitates a sustained research effort devoted to the topic. In this article, the authors provide a qualitative review of the core theoretical exporting areas and evaluate the exporting domain quantitatively over six decades (1958–2016). For the quantitative analysis, they use multidimensional scaling and apply established bibliometric principles to offer an understanding of the field and to provide suggestions for future exporting research. For the evaluations, the authors used data from 830 articles with 52,191 citations from 35 journals. Using cocitation analysis as the basis to evaluate the data, they propose a series of intellectual structure implications on exporting that relate to internationalization process stages, dynamic capabilities, knowledge scarcity, social networks, export marketing strategy, absorptive capacity and learning, and nonlinear performance relationships involving marketing channel relationships

Widening gap : development in the 1970's

Meeting: Columbia Conference on International Economic Development, 15-21 Feb. 1970, Williamsburg, Va., USMeeting: Colombia Conference on International Development, 15-21 Feb. 1970, New York, N.Y., USProceedings of a conference on the economic development of developing countries. Discusses the Pearson Report

Record of natural and anthropogenic changes in reef environments (Barbados West Indies) using laser ablation ICP-MS and sclerochronology on coral cores

Coral growth rate can be affected by environmental parameters such as seawater temperature, depth, and light intensity. The natural reef environment is also disturbed by human influences such as anthropogenic pollutants, which in Barbados are released close to the reefs. Here we describe a relatively new method of assessing the history of pollution and explain how these effects have influenced the coral communities off the west coast of Barbados. We evaluate the relative impact of both anthropogenic pollutants and natural stresses. Sclerochronology documents framework and skeletal growth rate and records pollution history (recorded as reduced growth) for a suite of sampled Montastraea annularis coral cores. X-radiography shows annual growth band patterns of the corals extending back over several decades and indicates significantly lower growth rate in polluted sites. Results using laser-ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) on the whole sample (aragonite, organic matter, trapped particulate matter, etc.), have shown contrasting concentrations of the trace elements (Cu, Sn, Zn, and Pb) between corals at different locations and within a single coral. Deepwater corals 7 km apart, record different levels of Pb and Sn, suggesting that a current transported the metal pollution in the water. In addition, the 1995 hurricanes are associated with anomalous values for Sn and Cu from most sites. These are believed to result from dispersion of nearshore polluted water. We compared the concentrations of trace elements in the coral growth of particular years to those in the relevant contemporaneous seawater. Mean values for the concentration factor in the coral, relative to the water, ranged from 10 for Cu and Ni to 2.4 and 0.7 for Cd and Zn, respectively. Although the uncertainties are large (60-80%), the coral record enabled us to demonstrate the possibility of calculating a history of seawater pollution for these elements from the 1940s to 1997. Our values were much higher than those obtained from analysis of carefully cleaned coral aragonite; they demonstrate the incorporation of more contamination including that from particulate material as well as dissolved metals

Versioned-PROV:A PROV extension to support mutable data entities

The PROV data model assumes that entities are immutable and all changes to an entity e are represented by the creation of a new entity e’. This is reasonable for many provenance applications but may produce verbose results once we move towards fine-grained provenance due to the possibility of multiple binds (i.e., variables, elements of data structures) referring to the same mutable data objects (e.g., lists or dictionaries in Python). Changing a data object that is referenced by multiple immutable entities requires duplicating those immutable entities to keep consistency. This imposes an overhead on the provenance storage and makes it hard to represent data-changing operations and their effect on the provenance graph. In this paper, we propose a PROV extension to represent mutable data structures. We do this by adding reference derivations and checkpoints. We evaluate our approach by comparing it to plain PROV and PROV-Dictionary. Results indicate a reduction in the storage overhead for assignments and changes in data structures from O(N) and Ώ(R × N), respectively, to O(1) in both cases when compared to plain PROV (N is the number of members in the data structure and R is the number of references to the data structure).</p