Controlled motion of electrically neutral microparticles by pulsed direct current

A controlled motion of electrically neutral microparticles in a conductive liquid at high temperatures has not yet been realized under the uniform direct electric current field. We propose a simple method, which employs pulsed direct current to a conductive liquid metal containing low-conductivity objects at high temperature. The electric current enables the low-conductivity particles to pass from the centre towards the various surfaces of the high-conductivity liquid metal. Most interestingly, the directionality of microparticles can be controlled and their speed can be easily regulated by adjusting pulsed current density. We find that the movement may arise from the configuration of electrical domains which generates a driving force which exceeds the force of gravity and viscous friction. All of these features are of potential benefit in separating the particles of nearly equal density but distinctly different electrical conductivities, and also offer considerable promise for the precise and selective positioning of micro-objects or the controlled motion of minute quantities of surrounding fluids

Knowledge discovery for friction stir welding via data driven approaches: Part 2 – multiobjective modelling using fuzzy rule based systems

In this final part of this extensive study, a new systematic data-driven fuzzy modelling approach has been developed, taking into account both the modelling accuracy and its interpretability (transparency) as attributes. For the first time, a data-driven modelling framework has been proposed designed and implemented in order to model the intricate FSW behaviours relating to AA5083 aluminium alloy, consisting of the grain size, mechanical properties, as well as internal process properties. As a result, ‘Pareto-optimal’ predictive models have been successfully elicited which, through validations on real data for the aluminium alloy AA5083, have been shown to be accurate, transparent and generic despite the conservative number of data points used for model training and testing. Compared with analytically based methods, the proposed data-driven modelling approach provides a more effective way to construct prediction models for FSW when there is an apparent lack of fundamental process knowledge

PIV characterisation of flocculation dynamics and floc structure in water treatment

Particle flocculation with chemical flocculant addition is an essential step in water treatment. The performance of flocculation and the property of the flocs formed affect the overall results of the treatment process. In addition to particulate impurities, the presence of organic matter in water, such as natural organic materials (NOM), also influence the effectiveness of chemical flocculation. In this paper, the PIV system was employed to investigate the flocculation dynamics for different flocculants in different model waters. With the PIV and image analysis, the change in particle size distribution could be well recorded. Using the sequence of flocculation, shear breakage and re-flocculation on a jar-test device together with the PIV system, the rate of floc formation, the strength of the flocs, the recovery of broken flocs, and the morphological and structural features of the flocs were characterized. The results indicated that the adsorption of HA on the particle will stabilized the particles, hence hindered the flocculation process. Sweep flocculation using a higher chemical coagulant dosage was an effective means of process enhancement for the removal of particulates and associated organic matter. The dynamics of A-B-R process was characterized by particle size distribution (PSD) measurement with PIV setup. The particle strength and reversibility capability were examined. Strength index showed the HA flocs have comparable strength, while recovery index indicated a less recovery capability with the increasing of HA concentration after exposure to a higher shear, especially for ferric HA flocs. It appears that the bonds holding HA flocs together are not purely physical bonds given the limited regrowth seen. Finally, evolution of floc structure during A-B-R process was analysed by investigated the fractal dimension Db. The results were generally consistent with previous PSD measurements. It suggested that the structure of flocs in breakage became more compact with little permeability. An increase in floc compaction provides a further explanation for the limited regrowth for most of flocs. According to the performances of alum and ferric, it can be noticed that HA flocs have different properties dependent on which chemical coagulant is used. Alum produced larger HA flocs which endured a higher recovery capability after exploring higher shear, hence, compared to ferric, it could be preferred to using in the practical enhanced coagulation unit.postprin

Electric-field-induced alignment of electrically neutral disk-like particles: modelling and calculation

This work reveals a torque from electric field to electrically neutral flakes that are suspended in a higher electrical conductive matrix. The torque tends to rotate the particles toward an orientation with its long axis parallel to the electric current flow. The alignment enables the anisotropic properties of tiny particles to integrate together and generate desirable macroscale anisotropic properties. The torque was obtained from thermodynamic calculation of electric current free energy at various microstructure configurations. It is significant even when the electrical potential gradient becomes as low as 100 v/m. The changes of electrical, electroplastic and thermal properties during particles alignment were discussed

Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset

Microarray gene expression data has been used in genome-wide association studies to allow researchers to study gene regulation as well as other complex phenotypes including disease risks and drug response. To reach scientifically sound conclusions from these studies, however, it is necessary to get reliable summarization of gene expression intensities. Among various factors that could affect expression profiling using a microarray platform, single nucleotide polymorphisms (SNPs) in target mRNA may lead to reduced signal intensity measurements and result in spurious results. The recently released 1000 Genomes Project dataset provides an opportunity to evaluate the distribution of both known and novel SNPs in the International HapMap Project lymphoblastoid cell lines (LCLs). We mapped the 1000 Genomes Project genotypic data to the Affymetrix GeneChip Human Exon 1.0ST array (exon array), which had been used in our previous studies and for which gene expression data had been made publicly available. We also evaluated the potential impact of these SNPs on the differentially spliced probesets we had identified previously. Though the 1000 Genomes Project data allowed a comprehensive survey of the SNPs in this particular array, the same approach can certainly be applied to other microarray platforms. Furthermore, we present a detailed catalogue of SNP-containing probesets (exon-level) and transcript clusters (gene-level), which can be considered in evaluating findings using the exon array as well as benefit the design of follow-up experiments and data re-analysis

Continuous-action reinforcement learning for memory allocation in virtualized servers

In a virtualized computing server (node) with multiple Virtual Machines (VMs), it is necessary to dynamically allocate memory among the VMs. In many cases, this is done only considering the memory demand of each VM without having a node-wide view. There are many solutions for the dynamic memory allocation problem, some of which use machine learning in some form. This paper introduces CAVMem (Continuous-Action Algorithm for Virtualized Memory Management), a proof-of-concept mechanism for a decentralized dynamic memory allocation solution in virtualized nodes that applies a continuous-action reinforcement learning (RL) algorithm called Deep Deterministic Policy Gradient (DDPG). CAVMem with DDPG is compared with other RL algorithms such as Q-Learning (QL) and Deep Q-Learning (DQL) in an environment that models a virtualized node. In order to obtain linear scaling and be able to dynamically add and remove VMs, CAVMem has one agent per VM connected via a lightweight coordination mechanism. The agents learn how much memory to bid for or return, in a given state, so that each VM obtains a fair level of performance subject to the available memory resources. Our results show that CAVMem with DDPG performs better than QL and a static allocation case, but it is competitive with DQL. However, CAVMem incurs significant less training overheads than DQL, making the continuous-action approach a more cost-effective solution.This research is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 754337 (EuroEXA) and the European Union’s 7th Framework Programme under grant agreement number 610456 (Euroserver). It also received funding from the Spanish Ministry of Science and Technology (project TIN2015-65316-P), Generalitat de Catalunya (contract 2014-SGR-1272), and the Severo Ochoa Programme (SEV-2015-0493) of the Spanish Government.Peer ReviewedPostprint (author's final draft

Electric current-driven migration of electrically neutral particles in liquids

We design and experimentally demonstrate a migration of electrically neutral particles in liquids driven by electric current according to the discrepancies of their electrical conductivities. A force from electric current to electrically neutral particles has been identified to drive the particles toward the lateral surface from the centre of suspension via three distinguishable zones, namely, pushing, trapping, and expelling zones. The driving force can overtake gravity in practical cases. The property of the force is found neither similar to that of the force in electromagnetophoresis nor similar to that of the electromigration force in terms of direction and magnitude. An expression for the force at the pushing zone has been developed based on the numerical calculation of the thermodynamics of suspension fluids. The excellent agreement between numerical calculations and experimental data demonstrates that our calculation provides fundamental and predictive insight into particles separation from the liquids. Therefore, it is possible to use the force in many engineering applications such as separation of particles according to the differences of their electrical conductivities

Cardiac magnetic resonance T1 and extracellular volume mapping with motion correction and co-registration based on fast elastic image registration

OBJECTIVE: Our aim was to investigate the technical feasibility of a novel motion compensation method for cardiac magntic resonance (MR) T1 and extracellular volume fraction (ECV) mapping. MATERIALS AND METHODS: Native and post-contrast T1 maps were obtained using modified look-locker inversion recovery (MOLLI) pulse sequences with acquisition scheme defined in seconds. A nonrigid, nonparametric, fast elastic registration method was applied to generate motion-corrected T1 maps and subsequently ECV maps. Qualitative rating was performed based on T1 fitting-error maps and overlay images. Local deformation vector fields were produced for quantitative assessment. Intra- and inter-observer reproducibility were compared with and without motion compensation. RESULTS: Eighty-two T1 and 39 ECV maps were obtained in 21 patients with diverse myocardial diseases. Approximately 60% demonstrated clear quality improvement after motion correction for T1 mapping, particularly for the poor-rating cases (23% before vs 2% after). Approximately 67% showed further improvement with co-registration in ECV mapping. Although T1 and ECV values were not clinically significantly different before and after motion compensation, there was improved intra- and inter-observer reproducibility after motion compensation. CONCLUSIONS: Automated motion correction and co-registration improved the qualitative assessment and reproducibility of cardiac MR T1 and ECV measurements, allowing for more reliable ECV mapping