Ion association in low-polarity solvents: comparisons between theory, simulation, and experiment

The association of ions in electrolyte solutions at very low concentration and low temperature is studied using computer simulations and quasi-chemical ion-pairing theory. The specific case of the restricted primitive model (charged hard spheres) is considered. Specialised simulation techniques are employed that lead to efficient sampling of the arrangements and distributions of clusters and free ions, even at conditions corresponding to nanomolar solutions of simple salts in solvents with dielectric constants in the range 5-10, as used in recent experimental work on charged-colloid sus- pensions. A direct comparison is effected between theory and simulation using a variety of clustering criteria and theoretical approximations. It is shown that conventional distance-based cluster criteria can give erroneous results. A reliable set of theoretical and simulation estimators for the degree of association is proposed. The ion-pairing theory is then compared to experimental results for salt solutions in low-polarity solvents. The agreement is excellent, and on this basis some calculations are made for the screening lengths which will figure in the treatment of colloid-colloid interactions in such solutions. The accord with available experimental results is complete

Quantum Mechanics and Quantum Information Theory

The principle aim of this dissertation is to investigate the philosophical application of quantum information theory to interpretational issues regarding the theory of quantum mechanics. Recently, quantum information theory has emerged as a potential source for such an interpretation. The main question with which this dissertation will be concerned is whether or not an information-theoretic interpretation can serve as a conceptually acceptable interpretation of quantum mechanics. It will be argued that some of the more obvious approaches - that quantum information theory shows us that ultimately the world is made of information, and quantum Bayesianism - fail as philosophical interpretations of quantum mechanics. However, the information-theoretic approach of Clifton, Bub, and Halvorson introduces Einstein's distinction between principle theories and constructive theories, arguing that quantum mechanics is best understood as an information-theoretic principle theory. While I argue that this particular approach fails, it does offer a viable new philosophical role for information theory. Specifically, an investigation of interpretationally successful principle theories such as Newtonian mechanics, special relativity, and general relativity, shows that the particular principles employed are necessary as constitutive elements of a framework which partially defines the basic explanatory concepts of space, time, and motion. Without such constitutive principles as preconditions for empirical meaning, scientific progress is hampered. It is argued that the philosophical issues in quantum mechanics stem from an analogous conceptual crisis. On the basis of this comparison, the best strategy for resolving these problems is to apply a similar sort of conceptual analysis to quantum mechanics so as to provide an appropriate set of constitutive principles clarifying the conceptual issues at stake. It is further argued that quantum information theory is ideally placed as a novel conceptual framework from which to conduct this analysis

Comparison of the Relative Nitrogen Fixing Ability of Five Legumes

Soil

Study of arc-jet propulsion devices Final report, 20 Nov. 1964 - 19 Dec. 1965

Energy transfer mechanisms in radiation, water, and regeneratively cooled, and MPD arc jet propulsion device

Using a gamified monitoring app to change adolescents' snack intake : the development of the REWARD app and evaluation design

Background: As the snacking pattern of European adolescents is of great concern, effective interventions are necessary. Till now health promotion efforts in children and adolescents have had only limited success in changing adolescents' eating patterns and anthropometrics. Therefore, the present study proposes an innovative approach to influence dietary behaviors in youth based on new insights on effective behavior change strategies and attractive intervention channels to engage adolescents. This article describes the rationale, the development, and evaluation design of the 'Snack Track School' app. The aim of the app is to improve the snacking patterns of Flemish 14- to 16-year olds. Methods: The development of the app was informed by the systematic, stepwise, iterative, and collaborative principles of the Intervention Mapping protocol. A four week mHealth intervention was developed based on the dual-system model with behavioral change strategies targeting both the reflective (i.e., active learning, advance organizers, mere exposure, goal-setting, monitoring, and feedback) and automatic processes (i.e., rewards and positive reinforcement). This intervention will be evaluated via a controlled pre-post design in Flemish schools among 1400 adolescents. Discussion: When this intervention including strategies focused on both the reflective and automatic pathway proves to be effective, it will offer a new scientifically-based vision, guidelines and practical tools for public health and health promotion (i.e., incorporation of learning theories in intervention programs)

Bounds on gravitational wave backgrounds from large distance clock comparisons

Our spacetime is filled with gravitational wave backgrounds that constitute a fluctuating environment created by astrophysical and cosmological sources. Bounds on these backgrounds are obtained from cosmological and astrophysical data but also by analysis of ranging and Doppler signals from distant spacecraft. We propose here a new way to set bounds on those backgrounds by performing clock comparisons between a ground clock and a remote spacecraft equipped with an ultra-stable clock, rather than only ranging to an onboard transponder. This technique can then be optimized as a function of the signal to be measured and the dominant noise sources, leading to significant improvements on present bounds in a promising frequency range where different theoretical models are competing. We illustrate our approach using the SAGAS project which aims to fly an ultra stable optical clock in the outer solar system.Comment: 10 pages, 8 figures, minor amendment

Determining the origin of seafood products on the Belgian market: challenges to traceability and database management

In countries where the majority of the seafood is imported, information about seafood origin is important in particular from a food safety perspective. In the case of Belgium, no database is available describing the origin of commercial seafood products. This investigation to determine the origin revealed three important problems. First, information needed to stem from different non-related databases; second, import countries did not define fishing grounds or product sites; third, seafood may have transited many areas and no information was available on this. Since European traceability regulations have been established for seafood, some limited extra efforts with respect to data collection and management can lead to (inter)national databases making seafood traceability information more practically useful, for example towards public health policy making

Methods for removal of unwanted signals from gravity time-series : comparison using linear techniques complemented with analysis of system dynamics

We thanks the participants of the 35th General Assembly of the European Seismological Commission for comments on preliminary results. The authors are grateful to all IGETS contributors, particularly to the station operators and to ISDC/GFZ-Potsdam for providing the original gravity data used in this study. We also thank the developers of ATLANTIDA3.1 and UTide. Part of this work was performed using the ICSMB High Performance Computing Cluster, University of Aberdeen. We also thanks M. Thiel and A. Moura for reviewing a preliminary version and making comments on the methods section and M.A. Ara´ujo for comments on Lyapunov exponents. Funding: A. Valencio is supported by CNPq, Brazil [206246/2014-5]; and received a travel grant from the School of Natural and Computing Sciences, University of Aberdeen [PO2073498], for a presentation including preliminary results.Peer reviewedPostprintPublisher PD

Synthetic data of simulated microcalcification clusters to train and explain deep learning detection models in contrast-enhanced mammography

Deep learning (DL) models can be trained on contrast-enhanced mammography (CEM) images to detect and classify lesions in the breast. As they often put more emphasis on the masses enhanced in the recombined image, they can fail in recognizing microcalcification clusters since these are hardly enhanced and are mainly visible in the (processed) lowenergy image. Therefore, we developed a method to create synthetic data with simulated microcalcification clusters to be used for data augmentation and explainability studies when training DL models. At first 3-dimensional voxel models of simulated microcalcification clusters based on descriptors of the shape and structure were constructed. In a set of 500 simulated microcalcification clusters the range of the size and of the number of microcalcifications per cluster followed the distribution of real clusters. The insertion of these clusters in real images of non-delineated CEM cases was evaluated by radiologists. The realism score was acceptable for single view applications. Radiologists could more easily categorize synthetic clusters into benign versus malignant than real clusters. In a second phase of the work, the role of synthetic data for training and/or explaining DL models was explored. A Mask R-CNN model was trained with synthetic CEM images containing microcalcification clusters. After a training run of 100 epochs the model was found to overfit on a training set of 192 images. In an evaluation with multiple test sets, it was found that this high level of sensitivity was due to the model being capable of recognizing the image rather than the cluster. Synthetic data could be applied for more tests, such as the impact of particular features in both background and lesion models