An X-ray absorption spectroscopic study at the mercury LIII edge on phenylmercury(II) oxygen species

The X-ray absorption spectra of the reference and model compounds HgCl2, PhHgCl, PhHgOAc and [(PhHg)2OH][BF4].H2O have been analysed in both the XANES and EXAFS regions, and the technique was extended to determine the structures of (PhHg)2O, PhHgOH, and the basic salts PhHgOH.PhHgNO3 and PhHgOH.(PhHg)2SO4, which were previously structurally uncharacterised. Results indicate that (PhHg)2O is a molecular species with Hg-O-Hg 135°, while PhHgOH contains the [(PhHg)2OH]+ cation and is better formulated as [(PhHg)2OH]OH. The same cation is also featured in the two basic salts. Electrospray mass spectral studies of PhHgOH in aqueous solutions show that [PhHgOH2]+, [(PhHg)2OH]+ and [(PhHg)3O]+ co-exist in solution in a pH-dependent equilibrium

A 'symbiosis effect' perspective to understand reverse logistics and household recycling waste systems

Paper presented at 19th ISL, 2014, Ho Chi Minh The essence of the problem with waste is that it is by definition something that is not wanted. We argue here that achieving a sustainable solution requires consideration of both regulatory responsibilities and social norms (Deutz and Frostick, 2009). Landfill costs levy a high financial impact on municipalities due to the environmental directives that compel them to collect and recycle household waste. More efficient and effective systems are therefore crucial for municipalities from both a financial and environmental perspective. Thus, householders and municipalities “symbiotically” working together in a natural system could enhance sustainable living (Fennell and Weaver, 2005; Ehrenreich, 2002). This paper reports on the first two stages of a PhD research study project conducted within the two municipalities in the North of England. This research investigates the relationship between the sustainability and effectiveness of household recycling systems and household recycling behavior, reveals how factors associated with household recycling systems affect household recycling behaviour, and how household recycling behaviour affect the provision of household recycling systems by the local authorities. The main objective is to reveal and explain the interaction and symbiosis. In fact, this study has found that a ‘symbiosis effect’ perspective appears to be a robust framework to bring together effective household waste recycling systems and sustainable development considerations to enhance both sustainability and the economy. Further, the study provides empirical evidence examining both situational and personal factors of households and their interactions, which were previously not well-understood. This study has incorporated behavioural aspects in the reverse logistics process that should help improve the municipalities’ planning processes. Also, municipalities may be more adaptive to the changing behaviour of their constituents and more willing to change their waste and recycling strategies to more sustainable methods. The paper is structured as follows. The literature reviews from multiple lenses of multiple disciplines and research design that accessible for interdisciplinary study and the current findings with discussion as well as conclusion that explain and encapsulate symbiosis effect perspective in understanding reverse logistics and household waste recycling system (HRWS)

Molecular Simulation of Flow-Enhanced Nucleation in n-Eicosane Melts Under Steady Shear and Uniaxial Extension

Non-equilibrium molecular dynamics is used to study crystal nucleation of n-eicosane under planar shear and, for the first time, uniaxial extension. A method of analysis based on the mean first-passage time is applied to the simulation results in order to determine the effect of the applied flow field type and strain rate on the steady-state nucleation rate and a characteristic growth rate, as well as the effects on kinetic parameters associated with nucleation: the free energy barrier, critical nucleus size, and monomer attachment pre-factor. The onset of flow-enhanced nucleation (FEN) occurs at a smaller critical strain rate in extension as compared to shear. For strain rates larger than the critical rate, a rapid increase in the nucleation rate is accompanied by decreases in the free energy barrier and critical nucleus size, as well as an increase in chain extension. These observations accord with a mechanism in which FEN is caused by an increase in the driving force for crystallization due to flow-induced entropy reduction. At high applied strain rates, the free energy barrier, critical nucleus size, and degree of stretching saturate, while the monomer attachment pre-factor and degree of orientational order increase steadily. This trend is indicative of a significant diffusive contribution to the nucleation rate under intense flows that is correlated with the degree of global orientational order in a nucleating system. Both flow fields give similar results for all kinetic quantities with respect to the reduced strain rate, which we define as the ratio of the applied strain rate to the critical rate. The characteristic growth rate increases with increasing strain rate, and shows a correspondence with the nucleation rate that does not depend on the type of flow field applied. Additionally, a structural analysis of the crystalline clusters indicates that the flow field suppresses the compaction and crystalline ordering of clusters, leading to the formation of large articulated clusters under strong flow fields, and compact well-ordered clusters under weak flow fields

CSI : A nonparametric Bayesian approach to network inference from multiple perturbed time series gene expression data

How an organism responds to the environmental challenges it faces is heavily influenced by its gene regulatory networks (GRNs). Whilst most methods for inferring GRNs from time series mRNA expression data are only able to cope with single time series (or single perturbations with biological replicates), it is becoming increasingly common for several time series to be generated under different experimental conditions. The CSI algorithm (Klemm, 2008) represents one approach to inferring GRNs from multiple time series data, which has previously been shown to perform well on a variety of datasets (Penfold and Wild, 2011). Another challenge in network inference is the identification of condition specific GRNs i.e., identifying how a GRN is rewired under different conditions or different individuals. The Hierarchical Causal Structure Identification (HCSI) algorithm (Penfold et al., 2012) is one approach that allows inference of condition specific networks (Hickman et al., 2013), that has been shown to be more accurate at reconstructing known networks than inference on the individual datasets alone. Here we describe a MATLAB implementation of CSI/HCSI that includes fast approximate solutions to CSI as well as Markov Chain Monte Carlo implementations of both CSI and HCSI, together with a user-friendly GUI, with the intention of making the analysis of networks from multiple perturbed time series datasets more accessible to the wider community.1 The GUI itself guides the user through each stage of the analysis, from loading in the data, to parameter selection and visualisation of networks, and can be launched by typing >> csi into the MATLAB command line. For each step of the analysis, links to documentation and tutorials are available within the GUI, which includes documentation on visualisation and interacting with output file

Analysis of nucleation using mean first-passage time data from molecular dynamics simulation

We introduce a method for the analysis of nucleation using mean first-passage time (MFPT) statistics obtained by molecular dynamics simulation. The method is based on the Becker-Döring model for the dynamics of a nucleation-mediated phase change and rigorously accounts for the system size dependence of first-passage statistics. It is thus suitable for the analysis of systems in which the separation between time scales for nucleation and growth is small, due to either a small free energy barrier or a large system size. The method is made computationally practical by an approximation of the first-passage time distribution based on its cumulant expansion. Using this approximation, the MFPT of the model can be fit to data from molecular dynamics simulation in order to estimate valuable kinetic parameters, including the free energy barrier, critical nucleus size, and monomer attachment pre-factor, as well as the steady-state rates of nucleation and growth. The method is demonstrated using a case study on nucleation of n-eicosane crystals from the melt. For this system, we found that the observed distribution of first-passage times do not follow an exponential distribution at short times, rendering it incompatible with the assumptions made by some other methods. Using our method, the observed distribution of first-passage times was accurately described, and reasonable estimates for the kinetic parameters and steady-state rates of nucleation and growth were obtained

Fluctuations in the muskellunge ( Esox masquinongy Mitchill) population of Chautauqua Lake, New York

Population and exploitation estimates were made from angler recaptures of Chautauqua Lake muskellunge, Esox masquinongy Mitchill. Fish were tagged during Conservation Department studies in 1941–1946, 1961–1965 and 1976–1978. Population estimates of adult fish ranged from one to seven fish per hectare and angler exploitation rates of tagged fish fluctuated from 3.8% to 14.1%. Relative catch indicators suggest a major decline in the lake's muskellunge population during the last decade. Overexploitation, habitat alteration and interspecific competition with recently introduced fish species were cited as probable causes of the decline.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42642/1/10641_2004_Article_BF00002785.pd

Discretized Wiener-Khinchin theorem for Fourier-Laplace transformation: application to molecular simulations

The Wiener-Khinchin theorem for the Fourier-Laplace transformation (WKT-FLT) provides a robust method to calculate numerically single-side Fourier transforms of arbitrary autocorrelation functions from molecular simulations. However, the existing WKT-FLT equation produces two artifacts in the output of the frequency-domain relaxation function. In addition, these artifacts are more apparent in the frequency-domain response function converted from the relaxation function. We find the sources of these artifacts that are associated with the discretization of the WKT-FLT equation. Taking these sources into account, we derive the new discretized WKT-FLT equations designated for both the frequency-domain relaxation and response functions with the artifacts removed. The use of the discretized WKT-FLT equations is illustrated by a flow chart of an on-the-fly algorithm. We also give application examples of the discretized WKT-FLT equations for computing dynamic structure factor and wave-vector-dependent dynamic susceptibility from molecular simulations