Testing the Underlying Chemical Principles of the Biotic Ligand Model (BLM) to Marine Copper Systems: Measuring Copper Speciation Using Fluorescence Quenching

Speciation of copper in marine systems strongly influences the ability of copper to cause toxicity. Natural organic matter (NOM) contains many binding sites which provides a protective effect on copper toxicity. The purpose of this study was to characterize copper binding with NOM using fluorescence quenching techniques. Fluorescence quenching of NOM with copper was performed on nine sea water samples. The resulting stability con- stants and binding capacities were consistent with literature values of marine NOM, show- ing strong binding with log K values from 7.64 to 10.2 and binding capacities ranging from 15 to 3110 nmole mg C −1 . Free copper concentrations estimated at total dissolved copper concentrations corresponding to previously published rotifer effect concentrations, in the same nine samples, were statistically the same as the range of free copper calculated for the effect concentration in NOM-free artificial seawater. These data confirms the applicability of fluorescence spectroscopy techniques for NOM and copper speciation characterization in sea water and demonstrates that such measured speciation is consistent with the chemical principles underlying the Biotic Ligand Model (BLM) approach for bioavailability-based metals risk assessment

Determination of Copper Speciation, Bioavailability and Toxicity in Saltwater Environments

The speciation of copper plays a strong role in determining bioavailability and toxicity upon copper exposure in marine environments. Specifically, natural organic matter (NOM) can complex with copper, influencing speciation and decreasing bioavailability. The aim of this research was to determine accurate copper speciation values using literature and new techniques and applying the techniques that reflect the most accurate speciation values to investigate the influence of NOM quantity and quality on copper speciation and toxicity. The results from this study will have implications on the development of a marine Biotic Ligand Model (BLM). Free copper was measured using a flow-through ion selective electrode (ISE) system. A published external calibration Cu ISE method showed a wide variability in measured free copper values and so method improvements were investigated. This resulted in the development of an internal calibration flow-through ISE method. This new method showed an increase in sample reproducibility and agreed well with modeled free copper values for well defined systems. This method was then applied to measure free copper at the LC50 for toxicity assays performed for nine sample locations using the rotifer, Brachionus plicatilis. NOM was characterized for each site through dissolved organic carbon (DOC) concentrations, fluorescence excitation-emission matrices (FEEM) and fluorescence quenching, combined with spectral resolution techniques to quantify humic-, fulvic-, tryptophan- and tyrosine-like fractions. The toxicity results showed two trends with DOC. In the first case, DOC was protective against copper toxicity (r2 = 0.72, p-value = 0.016), however a plateau in protective effect was observed above DOC concentrations above approximately 2 mg C L-1. This suggests salt- induced colloid formation could be occurring resulting in a decrease of binding sites available to complex free copper. The second relationship between LC50 and DOC can be described by the equation LC50 (µg L-1) = 25.15DOC0.47 (r2 = 0.61, p-value = 0.008) including two outlier sites in statistical analysis or LC50 (µg L-1) = 22.86DOC0.45 (r2 = 0.71, p-value = 0.009) excluding the outlier sites. Humic- and fulvic-like fractions showed a linear correlation with toxicity however tryptophan and tyrosine showed no correlation. Overall, only fulvic-like fractions were significant. Free copper at the LC50 for each site remained constant (average pCu = 10.14), within the Biotic Ligand Model (BLM) prediction factor of two, while the LC50 values ranged from 333 to 980 nM. This suggests that differences in water chemistries alter the total amount of copper that needs to be added to a system to reach a critical free copper concentration required to cause toxicity. This was supported by fluorescence quenching data that was used to determine binding capacities and stability constants for the different fluorescent fractions within DOC. Binding capacities at multiple fluorophores ranged from 4 to 1614 nmole mg C-1. The sum of the binding capacities were linearly correlated with LC50 (r2 = 0.67, p-value = 0.008) which supports the observed toxicity data that more total copper was required to reach the same free copper. Binding sites ranged from one to three ligands per sample. Binding was relatively strong for all sites, with logK values ranging from 9.33 to 11.22. In addition, free copper was calculated using this data and the results agreed with the ISE data within ± 0.3 pCu. This supports the theory that a critical free copper concentration is required to cause toxicity. As well these results confirm the applicability of fluorescence quenching techniques in marine water

SIMPEL: Circuit model for photonic spike processing laser neurons

We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber---a simulation model for photonic excitable lasers (SIMPEL). We show that by mapping the laser neuron rate equations into a circuit model, SPICE analysis can be used as an efficient and accurate engine for numerical calculations, capable of generalization to a variety of different laser neuron types found in literature. The development of this model parallels the Hodgkin--Huxley model of neuron biophysics, a circuit framework which brought efficiency, modularity, and generalizability to the study of neural dynamics. We employ the model to study various signal-processing effects such as excitability with excitatory and inhibitory pulses, binary all-or-nothing response, and bistable dynamics.Comment: 16 pages, 7 figure

Dynamical laser spike processing

Novel materials and devices in photonics have the potential to revolutionize optical information processing, beyond conventional binary-logic approaches. Laser systems offer a rich repertoire of useful dynamical behaviors, including the excitable dynamics also found in the time-resolved "spiking" of neurons. Spiking reconciles the expressiveness and efficiency of analog processing with the robustness and scalability of digital processing. We demonstrate that graphene-coupled laser systems offer a unified low-level spike optical processing paradigm that goes well beyond previously studied laser dynamics. We show that this platform can simultaneously exhibit logic-level restoration, cascadability and input-output isolation---fundamental challenges in optical information processing. We also implement low-level spike-processing tasks that are critical for higher level processing: temporal pattern detection and stable recurrent memory. We study these properties in the context of a fiber laser system, but the addition of graphene leads to a number of advantages which stem from its unique properties, including high absorption and fast carrier relaxation. These could lead to significant speed and efficiency improvements in unconventional laser processing devices, and ongoing research on graphene microfabrication promises compatibility with integrated laser platforms.Comment: 13 pages, 7 figure

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

Mapping disease data: A usability test of an internet based system of disease status disclosure

Disease maps are important tools in the management of disease. By communicating risk, disease maps can help raise awareness of disease and encourage farmers and veterinarians to employ best practice to eliminate the spread of disease. However, despite the importance of disease maps in communicating risk and the existence of various online disease maps, there are few studies that explicitly examine their usability. Where disease maps are complicated to use, it seems that they are unlikely to be used effectively. The paper outlines an attempt to create an open access, online, searchable map of incidents of bovine tuberculosis in England and Wales, and analyzes its usability among veterinarians. The paper describes the process of creating the map before describing the results of a series of usability trials. Results show the map to score highly on different measures of usability. However, the trials also revealed a number of social and technical limitations and challenges facing the use of online disease maps, including reputational dangers, role confusion, data accuracy, and data representation. The paper considers the challenges facing disease maps and their potential role in designing new methodologies to evaluate the effectiveness of disease prevention initiatives