Performance of pilot-scale microbial fuel cells treating wastewater with associated bioenergy production in the Caribbean context

Microbial fuel cell (MFC) technology represents a form of renewable energy that generates bioelectricity from what would otherwise be considered a waste stream. MFCs may be ideally suited to the small island developing state (SIDS) context, such as Trinidad and Tobago where seawater as the main electrolyte is readily available and economical renewable and sustainable electricity is also deemed a priority. Hence this project tested two identical laboratory-scaled MFC systems that were specifically designed and developed for the Caribbean regional context. They consisted of two separate chambers, an anaerobic anodic chamber inoculated with wastewater and an aerobic cathodic chamber separated by a proton exchange membrane. Domestic wastewater from two various wastewater treatment plants inflow (after screening) was placed into the anodic chamber, and seawater from the Atlantic Ocean and Gulf of Paria placed into the cathodic chambers respectively with the bacteria present in the wastewater attaching to the anode. Experimental results demonstrated that the bacterial degradation of the wastewaters as substrate induced an electron flow through the electrodes producing bioelectricity whilst simultaneously reducing the organic matter as biochemical oxygen demand and chemical oxygen demand by 30 to 75%. The average bioenergy output for both systems was 84 mW/m² and 96 mW/m² respectively. This study demonstrated the potential for simultaneous bioenergy production and wastewater treatment in the SIDS context

Bayesian optimization for materials design

We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian process regression, which allows predicting the performance of a new design based on previously tested designs. After providing a detailed introduction to Gaussian process regression, we introduce two Bayesian optimization methods: expected improvement, for design problems with noise-free evaluations; and the knowledge-gradient method, which generalizes expected improvement and may be used in design problems with noisy evaluations. Both methods are derived using a value-of-information analysis, and enjoy one-step Bayes-optimality

Transformation Pathways of Silica under High Pressure

Concurrent molecular dynamics simulations and ab initio calculations show that densification of silica under pressure follows a ubiquitous two-stage mechanism. First, anions form a close-packed sub-lattice, governed by the strong repulsion between them. Next, cations redistribute onto the interstices. In cristobalite silica, the first stage is manifest by the formation of a metastable phase, which was observed experimentally a decade ago, but never indexed due to ambiguous diffraction patterns. Our simulations conclusively reveal its structure and its role in the densification of silica.Comment: 14 pages, 4 figure

Serial optical coherence microscopy for label-free volumetric histopathology

The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories. However, slide-based microscopic pathology is not suitable for visualizing the large-scale tissue and native 3D organ structure due to its sampling limitation and shallow imaging depth. Here, we demonstrate serial optical coherence microscopy (SOCM) technique that offers label-free, high-throughput, and large-volume imaging of ex vivo mouse organs. A 3D histopathology of whole mouse brain and kidney including blood vessel structure is reconstructed by deep tissue optical imaging in serial sectioning techniques. Our results demonstrate that SOCM has unique advantages as it can visualize both native 3D structures and quantitative regional volume without introduction of any contrast agents

First observation of psi(2S)-->K_S K_L

The decay psi(2S)-->K_S K_L is observed for the first time using psi(2S) data collected with the Beijing Spectrometer (BESII) at the Beijing Electron Positron Collider (BEPC); the branching ratio is determined to be B(psi(2S)-->K_S K_L) = (5.24\pm 0.47 \pm 0.48)\times 10^{-5}. Compared with J/psi-->K_S K_L, the psi(2S) branching ratio is enhanced relative to the prediction of the perturbative QCD ``12%'' rule. The result, together with the branching ratios of psi(2S) decays to other pseudoscalar meson pairs (\pi^+\pi^- and K^+K^-), is used to investigate the relative phase between the three-gluon and the one-photon annihilation amplitudes of psi(2S) decays.Comment: 5 pages, 4 figures, 2 tables, submitted to Phys. Rev. Let

Biological measurement beyond the quantum limit

Quantum noise places a fundamental limit on the per photon sensitivity attainable in optical measurements. This limit is of particular importance in biological measurements, where the optical power must be constrained to avoid damage to the specimen. By using non-classically correlated light, we demonstrated that the quantum limit can be surpassed in biological measurements. Quantum enhanced microrheology was performed within yeast cells by tracking naturally occurring lipid granules with sensitivity 2.4 dB beyond the quantum noise limit. The viscoelastic properties of the cytoplasm could thereby be determined with a 64% improved measurement rate. This demonstration paves the way to apply quantum resources broadly in a biological context

Mental wellbeing amongst younger and older migrant workers in comparison to their urban counterparts in Guangzhou city, China: a cross-sectional study

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Beyond Gross-Pitaevskii Mean Field Theory

A large number of effects related to the phenomenon of Bose-Einstein Condensation (BEC) can be understood in terms of lowest order mean field theory, whereby the entire system is assumed to be condensed, with thermal and quantum fluctuations completely ignored. Such a treatment leads to the Gross-Pitaevskii Equation (GPE) used extensively throughout this book. Although this theory works remarkably well for a broad range of experimental parameters, a more complete treatment is required for understanding various experiments, including experiments with solitons and vortices. Such treatments should include the dynamical coupling of the condensate to the thermal cloud, the effect of dimensionality, the role of quantum fluctuations, and should also describe the critical regime, including the process of condensate formation. The aim of this Chapter is to give a brief but insightful overview of various recent theories, which extend beyond the GPE. To keep the discussion brief, only the main notions and conclusions will be presented. This Chapter generalizes the presentation of Chapter 1, by explicitly maintaining fluctuations around the condensate order parameter. While the theoretical arguments outlined here are generic, the emphasis is on approaches suitable for describing single weakly-interacting atomic Bose gases in harmonic traps. Interesting effects arising when condensates are trapped in double-well potentials and optical lattices, as well as the cases of spinor condensates, and atomic-molecular coupling, along with the modified or alternative theories needed to describe them, will not be covered here.Comment: Review Article (19 Pages) - To appear in 'Emergent Nonlinear Phenomena in Bose-Einstein Condensates: Theory and Experiment', Edited by P.G. Kevrekidis, D.J. Frantzeskakis and R. Carretero-Gonzalez (Springer Verlag

Determining the neurotransmitter concentration profile at active synapses

Establishing the temporal and concentration profiles of neurotransmitters during synaptic release is an essential step towards understanding the basic properties of inter-neuronal communication in the central nervous system. A variety of ingenious attempts has been made to gain insights into this process, but the general inaccessibility of central synapses, intrinsic limitations of the techniques used, and natural variety of different synaptic environments have hindered a comprehensive description of this fundamental phenomenon. Here, we describe a number of experimental and theoretical findings that has been instrumental for advancing our knowledge of various features of neurotransmitter release, as well as newly developed tools that could overcome some limits of traditional pharmacological approaches and bring new impetus to the description of the complex mechanisms of synaptic transmission

Measurement of the Branching Fraction of J/psi --> pi+ pi- pi0

Using 58 million J/psi and 14 million psi' decays obtained by the BESII experiment, the branching fraction of J/psi --> pi+ pi- pi0 is determined. The result is (2.10+/-0.12)X10^{-2}, which is significantly higher than previous measurements.Comment: 9 pages, 8 figures, RevTex