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Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)
No full textRecently, increasing works have been proposed to drive evolutionary algorithms using machine-learning models. Usually, the performance of such model-based evolutionary algorithms is highly dependent on the training qualities of the adopted models. Since it usually requires a certain amount of data (i.e., the candidate solutions generated by the algorithms) for model training, the performance deteriorates rapidly with the increase of the problem scales due to the curse of dimensionality. To address this issue, we propose a multiobjective evolutionary algorithm driven by the generative adversarial networks (GANs). At each generation of the proposed algorithm, the parent solutions are first classified into real and fake samples to train the GANs; then the offspring solutions are sampled by the trained GANs. Thanks to the powerful generative ability of the GANs, our proposed algorithm is capable of generating promising offspring solutions in high-dimensional decision space with limited training data. The proposed algorithm is tested on ten benchmark problems with up to 200 decision variables. The experimental results on these test problems demonstrate the effectiveness of the proposed algorithm
Benchmarking the PreSPEC@GSI experiment for Coulex-multipolarimetry on the π(<i>p</i><sub>3/2</sub>) → π(<i>p</i><sub>1/2</sub>) spin-flip transition in <sup>85</sup>Br
No full textA first performance test of the Coulomb excitation multipolarimetry (Coulex-multipolarimetry) method is presented. It is based on a 85Br π(p3/2) → π(p1/2) spin-flip experiment performed as part of the PreSPEC-AGATA campaign at the GSI Helmholtzzentrum für Schwerionenforschung (GSI). Via determination of background levels around the expected 85Br excitations as well as measured 197Au excitations, an upper limit for the M1 transition strength of the 1/2⁻₁ → 3/2⁻g.s. transition in 85Br and a lower beam time limit for upcoming experimental campaigns utilizing Coulex-multipolarimetry have been inferred. The impact of the use of AGATA in its anticipated 1π configuration on these estimates is deduced via Geant4 simulations
User experiences with a type 2 diabetes coaching app: a qualitative study
No full textBackground: Diabetes self-management apps have the potential to improve self-management by people with type 2 diabetes. Although efficacy trials provide evidence of health benefits, premature disengagement from apps is common. Therefore, it is important to understand factors that influence engagement in real-world settings.
Objective: To explore users’ real-world experiences with the ‘My Diabetes Coach’ self-management app.
Methods: We conducted telephone-based interviews with participants who had accessed the ‘My Diabetes Coach’ self-management app via their own smartphone for up to 12 months. Interviews focused on the users’ characteristics, the context within which the app was used, barriers and facilitators of app use, and on the design, content and delivery of support within the app.
Results: Nineteen interviewees were aged 60 (SD=14) years. Eight (42%) were women. Eight (42%) participants had type 2 diabetes for less than five years, eight (42%) for five-ten years and three (16%) for more than ten years. Two themes were constructed from interview data: 1) the moderating effect of diabetes self-management styles on needs, preferences and expectations and 2) factors influencing users’ engagement with the app: one size does not fit all.
Conclusions: User characteristics, context of use and features of the app interact and influence engagement. Promoting engagement is vital if diabetes self-management apps are to become a useful complement to clinical care in supporting optimal self-management
Ultra-Sensitive Strain Gauges Enabled by Graphene-Stabilized Silicone Emulsions
No full textHere, we present an approach to incorporate graphene nanosheets into a silicone rubber matrix via
solid stabilization of oil-in-water emulsions. These emulsions can be cured into discrete, graphenecoated
silicone balls or continuous, elastomeric films by controlling the degree of coalescence. We
characterize the electromechanical properties of the resulting composites as a function of
interdiffusion time and graphene loading level. With conductivities approaching 1 S m-1, elongation
to break up to 160% and a gauge factor of ~20 in the low-strain linear regime, we can accurately
measure small strains such as pulse. At higher strains, the electromechanical response exhibits a
robust exponential dependence, allowing accurate readout for higher strain movements such as
chest motion and joint bending. The exponential gauge factor is found to be ~20, independent of
loading level and valid up to 80% strain; this consistent performance is due to the emulsiontemplated
microstructure of the composites. The robust behavior may facilitate high-strain sensing
in the non-linear regime using nanocomposites, where relative resistance change values in excess of
107 enable highly accurate bodily motion monitoring
Morphology-dependent electrochemical performance of MnO₂ nanostructures on graphene towards efficient capacitive deionization
No full textCapacitive deionization (CDI) is an emerging desalination technology that still needs further development to enhance its performance for practical implementation. Herein, we present a hybrid CDI approach, which integrates the electrical double-layer (EDL) with the sodium-ion battery concept to improve the separation of sodium and chloride ions from saline water. The hybrid CDI cell is achieved by using hydrothermally-grown and uniformly dispersed prawn-like α-MnO₂/graphene (α-MnO₂/G) nanocomposite as anode material, and graphene at the cathode. In this paper, the effect of MnO₂ morphology on the electrode electrochemical performance and its effect on capacitive deionization performance have been fully investigated. In this configuration, the Na⁺ ions are inserted by the electrochemical reaction at the α-MnO₂/G electrode, whereas Cl⁻ ions are captured by the graphene-based electrode. The morphological dependent electrochemical properties of the obtained nanocomposites were studied deeply through CV and EIS analysis. The established hybrid CID cell provides an electrical capacitance as high as 375 F g⁻¹ at 10 mV s⁻¹, cation-selectivity, good electrical stability and low internal resistance. The hybrid CDI device also shows a stable and reversible salt insertion/de-insertion capacity up to 29.5 mg g⁻¹ at 1.2 V. These results demonstrate the suitability of prawn-like α-MnO₂/G nanocomposite to produce high-performance hybrid CDI cells
Dynamic coupling between fluid motion and rectilinear vessel motion in a system of connected vessels
No full textIn this thesis we investigate the dynamics of coupled liquid sloshing systems, which consist
of a one-dimensional array of vessels, partially filled with fluid, being connected together
by nonlinear springs. The fluid motion induces a hydrodynamic force on the side walls of
the vessel, which induces the vessel to move. The vessel movement is also controlled via a
restoring force of the attached springs, which in turn causes the fluid to alter its motion.
The simplest coupled liquid sloshing system consists of one vessel connected to a side wall via
a spring. We review this example and investigate the techniques documented in the literature
to study the linear problem of such a system. Then we extend this linear theory to multivessel systems, in particular focussing on the 2-vessel system which introduces the notion of
modes being in-phase or out-of-phase with each other. In the general N-vessel system we
also identify the existence in parameter space of internal resonances, where different modes
oscillates at the same frequency. Such a resonance provides a mechanism for energy exchange
between modes in the nonlinear system.
The nonlinear dynamics of the coupled liquid sloshing system are studied by employing a
symplectic integration scheme based on a variational principle, to the shallow-water form of
the governing equations. We present results for the shallow-water scheme in the linear, weakly
nonlinear and fully nonlinear regimes. The shallow-water numerical scheme has trouble
dealing with breaking waves, so we perform a feasibility study where we attempt to use a
similar approach for a non-shallow fluid system. The governing equations are derived and
results presented in the linear amplitude regime for the 1-vessel system.
Finally, we develop variational principles for the coupled liquid sloshing system in the Eulerian
framework based on the principle of constrained variations to derive the governing fluid
equations and free-surface boundary conditions, from a natural Lagrangian functional. We
use this constrained variational approach to derive the fully rotational 2D Euler equations
and its stream function formulation
Investigation of powder flowability at low stresses by DEM modelling
No full textBall indentation is a technique capable of assessing powder flowability down to very low consolidation stresses (≤1 kPa). With this method, powder flowability is determined by measuring the hardness of a powder bed, which allows the unconfined yield strength to be inferred via the constraint factor. The latter is well established for continuum materials, whereas for particulate systems its dependency on stress level and powder properties is not well defined. This work investigates these factors by simulating the ball indentation method using DEM. The constraint factor is shown to be independent of pre-consolidation stress. Constraint factor generally increases with interface energy for relatively cohesion-less powders, though not for cohesive powders. An increase in plastic yield stress leads to a decrease in the constraint factor. Increasing the coefficient of interparticle static friction reduces the constraint factor, while increasing the coefficient of inter-particle rolling friction significantly increases the constraint factor
Four-year assessment of ambient particulate matter and trace gases in the Delhi-NCR region of India
No full textA key challenge in controlling Delhi’s air quality is a lack of clear understanding of the impacts of emissions from the surrounding National Capital Region (NCR). Our objectives are to understand the limitations of publicly available data, its utility to determine pollution sources across Delhi-NCR and establish seasonal profiles of chemically active trace gases. We obtained the spatiotemporal characteristics of daily-averaged particulate matter (PM10 and PM2.5) and trace gases (NOX,O3,SO2, and CO) within a network of 12 air quality monitoring stations located over 2000 km2 across Delhi-NCR from January 2014 to December 2017. The highest concentrations of pollutants, except O3, were found at Anand Vihar compared with lowest at Panchkula. A high homogeneity in PM2.5 was observed among Delhi sites as opposed to a high spatial divergence between Delhi and NCR sites. The bivariate polar plots and k-means clustering showed that PM2.5 and PM10 concentrations are dominated by local sources for all monitoring sites across Delhi-NCR. A consequence of the dominance of local source contributions to measured concentrations, except to one site remote from Delhi, is that it is not possible to evaluate the influence of regional pollution transport upon PM concentrations measured at sites within Delhi and the NCR from concentration measurements alone
A cohesive fracture model for discrete element method based on polyhedral blocks
No full textFailure processes are common in geomaterials under external loads. In this study, a cohesive fracture model (CFM) and its implementation in a graphical processing unit (GPU)-based discrete element method (DEM) solver is presented within the context of simulating the failure of rock and other geomaterials. The CFM and its GPU implementation advances the simulation of the processes of meso-fracture initiation, propagation, and interaction. The CFM discretizes a domain into a series of pre-defined rigid polyhedral blocks. These blocks are bonded along the contact faces by a cohesive criterion with normal and shear strengths. This poses a computational challenge as few DEM codes can simulate polyhedrons, and amongst those the limited number of particles and required computational run-time make it intractable to do simulations of more than a few thousand polyhedral elements. This makes it computationally infeasible to combine CFM with such DEM models for practical applications. However, the GPU based code Blaze-DEM does allow for simulations of tens of millions of polyhedrons within practical runtimes. In this study we implement the CFM in Blaze-DEM and show the efficiency and usefulness of the model using GPU compute. Two typical examples, including a block sliding along a slope and the fracture process of an arch structure, are used to verify the provided CFM. This is followed by the simulation of Brazilian tests and uniaxial tests of limestone using the CFM that are validated against laboratory experiments. These tests demonstrate that the provided CFM can simulate not only the fracture process well, but also mechanical behaviors at the meso and macro scale of the geomaterials. Furthermore, based on the failure mechanisms of the Brazilian test and uniaxial test, an inversion method is proposed to obtain the mechanical parameters in CFM
International spillovers of US monetary and fiscal policies on small open economies
No full textThis thesis focuses on the spillover effects of US monetary and fiscal policies on some of its main trading partners. The first chapter examines the cross-border macroeconomic effects of US monetary policy shocks on Canada and Mexico. To do this, we depart from the standard two-country VAR models routinely used in the literature by adopting a proxy VAR approach. In particular, we employ the first-stage model averaging method to construct an optimal instrument for US monetary policy shocks. The main finding of this chapter is that US monetary policy shocks have a significant impact on Canada’s macroeconomic variables, but not so for those of Mexico. The second chapter provides a theoretical model of the spillover effects of monetary policies based on various competing price regimes. It investigates the impact of the US monetary policy on its two neighbours, Canada and Mexico, under two different pricing regimes: Producer Currency Pricing (PCP); and Dominant Currency Pricing (DCP). We use a New Keynesian DSGE model to explain the transmission channels of monetary policy under various pricing systems. We find that in a Likelihood race, the model with DCP outperforms the model with PCP. Furthermore, by analysing the variance decomposition of business cycle fluctuations, the dominant role of foreign monetary shock in overall fluctuations is observed. The third chapter focuses on the second wing of the domestic policy which is fiscal policy. Since the recent financial crisis of 2007/08, the spillover effects of fiscal policies have become increasingly important in the wake of the zero interest rate lower bound. Using SVARs with external instruments and data on macroeconomics variables from the UK and Canada, we find that shocks to the US fiscal policy cause the trade balance in the UK to increase, while they cause the Canadian dollar to appreciate against the US dollar
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