Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Temperature dependent structural properties of nanocrystalline SnS structures

This letter explores the structural behavior of nanocrystalline tin mono sulfide (SnS) structures with respect to temperature (100-600 K). These studies emphasize that the structural properties of SnS nanocrystalline structures depend on the surrounding temperature. The lattice parameters of SnS nanocrystals slightly varied like their microstructures with the increase of temperature. These changes strongly influence the optical properties of SnS nanostructures. On the other hand, the structures exhibited higher strain (similar to 0.44%) than that of microstructured (0.3%) and bulk (0.12%) counterparts. The observed results are discussed under the light of existing concepts and reported.

RecA Protein of Mycobacterium tuberculosis Possesses pH-Dependent Homologous DNA Pairing and Strand Exchange Activities: Implications for Allele Exchange in Mycobacteria

To gain insights into inefficient allele exchange in mycobacteria, we compared homologous pairing and strand exchange reactions promoted by RecA protein of Mycobacterium tuberculosis to those of Escherichia coli RecA protein. The extent of single-stranded binding protein (SSB)-stimulated formation of joint molecules by MtRecA was similar to that of EcRecA over a wide range of pH values. In contrast, strand exchange promoted by MtRecA was inhibited around neutral pH due to the formation of DNA networks. At higher pH, MtRecA was able to overcome this constraint and, consequently, displayed optimal strand exchange activity. Order of addition experiments suggested that SSB, when added after MtRecA, was vital for strand exchange. Significantly, with shorter duplex DNA, MtRecA promoted efficient strand exchange without network formation in a pH-independent fashion. Increase in the length of duplex DNA led to incomplete strand exchange with concomitant rise in the formation of intermediates and networks in a pH-dependent manner. Treatment of purified networks with S1 nuclease liberated linear duplex DNA and products, consistent with a model in which the networks are formed by the invasion of hybrid DNA by the displaced linear single-stranded DNA. Titration of strand exchange reactions with ATP or salt distinguished a condition under which the formation of networks was blocked, but strand exchange was not significantly affected. We discuss how these results relate to inefficient allele exchange in mycobacteria.

Position preference and diffusion path of an oxygen ion in apatite-type lanthanum silicate La9.33Si6O26: A density functional study

Using density functional theory, we investigated the position preference and diffusion mechanisms of interstitial oxygen ions in lanthanum silicate La9.33Si6O26, which is an apatite-structured oxide and a promising candidate electrolyte material for solid oxide fuel cells. The reported lanthanum vacancies were explicitly taken into account by theoretically determining their arrangement with a supercell model. The most stable structures and the formation energies of oxygen interstitials were determined for each charged state. It was found that the double-negatively charged state is stable over a wide range of the Fermi level, and that the excess oxygen ions form split interstitials with the original oxygen ions, while the neutral and the single-negatively charged states preferably form molecular oxygen. These species were found near the lanthanum vacancy site. The theoretically determined migration pathway along the c-axis essentially follows an interstitialcy mechanism. The obtained migration barrier is sensitive to the charge state, and is also affected by the lanthanum vacancy. The barrier height of the double-negatively charged state was calculated to be 0.58 eV for the model structure, which is consistent with the measured activation energy.

CAE-based prediction of projectile residual velocity for impact on single and multi-layered metallic armour plates

The present, paper deals with the CAE-based study Of impact of jacketed projectiles on single- and multi-layered metal armour plates using LS-DYNA. The validation of finite element modelling procedure is mainly based on the mesh convergence study using both shell and solid elements for representing single-layered mild steel target plates. It, is shown that the proper choice of mesh density and the strain rate-dependent material properties are essential for all accurate prediction of projectile residual velocity. The modelling requirements are initially arrived at by correlating against test residual velocities for single-layered mild steel plates of different depths at impact velocities in the ran.-c of approximately 800-870 m/s. The efficacy of correlation is adjudged, in terms of a 'correlation index', defined in the paper: for which values close to unity are desirable. The experience gained for single-layered plates is next; used in simulating projectile impacts on multi-layered mild steel target plates and once again a high degree of correlation with experimental residual velocities is observed. The study is repeated for single- and multi-layered aluminium target plates with a similar level of success in test residual velocity prediction. TO the authors' best knowledge, the present comprehensive study shows in particular for the first time that, with a. proper modelling approach, LS-DYNA can be used with a great degree of confidence in designing perforation-resistant single and multi-layered metallic armour plates.

Free-volume dependent pressure sensitivity of Zr-based bulk metallic glass

Instrumented indentation experiments on a Zr-based bulk metallic glass (BMG) in as-cast, shot-peened and structurally relaxed conditions were conducted to examine the dependence of plastic deformation on its structural state. Results show significant differences in hardness, H, with structural relaxation increasing it and shot peening markedly reducing it, and slightly changed morphology of shear bands around the indents. This is in contrast to uniaxial compressive yield strength, sigma(y), which remains invariant with the change in the structural state of the alloys investigated. The plastic constraint factor, C = H/sigma(y), of the relaxed BMG increases compared with that of the as-cast glass, indicating enhanced pressure sensitivity upon annealing. In contrast, C of the shot-peened layer was found to be similar to that observed in crystalline metals, indicating that severe plastic deformation could eliminate pressure sensitivity. Microscopic origins for this result, in terms of shear transformation zones and free volume, are discussed.

Critical test for Altshuler-Aronov theory: Evolution of the density of states singularity in double perovskite Sr2FeMoO6 with controlled disorder

With high-resolution photoemission spectroscopy measurements, the density of states (DOS) near the Fermi level (E-F) of double perovskite Sr2FeMoO6 having different degrees of Fe/Mo antisite disorder has been investigated with varying temperature. The DOS near E-F showed a systematic depletion with increasing degree of disorder, and recovered with increasing temperature. Altshuler-Aronov (AA) theory of disordered metals well explains the dependences of the experimental results. Scaling analysis of the spectra provides experimental indication for the functional form of the AA DOS singularity.

Correction of Ocular Artifacts in EEG Recordings using Empirical Mode Decomposition

EEG recordings are often contaminated with ocular artifacts such as eye blinks and eye movements. These artifacts may obscure underlying brain activity in the electroencephalogram (EEG) data and make the analysis of the data difficult. In this paper, we explore the use of empirical mode decomposition (EMD) based filtering technique to correct the eye blinks and eye movementartifacts in single channel EEG data. In this method, the single channel EEG data containing ocular artifact is segmented such that the artifact in each of the segment is considered as some type of slowly varying trend in the dataand the EMD is used to remove the trend. The filtering is done using partial reconstruction from components of the decomposition. The method is completely data dependent and hence adaptive and nonlinear. Experimental results are provided to check the applicability of the method on real EEG data and the results are quantified using power spectral density (PSD) as a measure. The method has given fairlygood results and does not make use of any preknowledge of artifacts or the EEG data used.

Investigation of inter-ion interactions in N,N,N',N'-tetramethylethylenediammonium dithiocyanate via experimental and theoretical charge density studies

The crystal structure of the N,N,N',N'-tetramethylethylenediammonium dithiocyanate salt has been examined by experimental charge density studies from high-resolution X-ray diffraction data. The corresponding results are compared with multipole refinements, using theoretical structure factors obtained from a periodic density functional theory calculation at the B3LYP level with a 6-31G** basis set. The salt crystallizes in space group P (1) over bar and contains only a single ion pair with an inversion center in the cation. The salt has thus one unique classical N+-H center dot center dot center dot(NCS)(-) hydrogen bond but also has six other weaker interactions: four C-H center dot center dot center dot S, one C-H center dot center dot center dot N, and one C-H center dot center dot center dot C-pi. The nature of all these interactions has been examined topologically using Bader's quantum theory of "atoms in molecules" and all eight of the Koch-Popelier criteria. The experimental and theoretical approaches agree well and both show that the inter-ion interactions, even in this simplest of systems, play an integrated and complex role in the packing of the ions in the crystal. Electrostatic potential maps are derived from experimental charge densities. This is the first time such a system has been examined in detail by these methods.

Low power pipelined TCAM employing mismatch dependent power allocation technique

This paper presents design of a Low power 256x72 bit TCAM in 0.13um CMOS technology. In contrast to conventional Match line (ML) sensing scheme in which equal power is consumed irrespective of match or mismatch, the ML scheme employed in this design allocates less power to match decisions involving a large number of mismatched bits. Typically, the probability of mismatch is high so this scheme results in significant CAM power reduction. We propose to use this technique along with pipelining of search operation in which the MLs are broken into several segments. Since most words fail to match in first segment, the search operation for subsequent segments is discontinued, resulting in further reduction in power consumption. The above architecture provides 70% power reduction while performing search in 3ns.

Discrete parameter simulation optimization algorithms with applications to admission control with dependent service times

We propose certain discrete parameter variants of well known simulation optimization algorithms. Two of these algorithms are based on the smoothed functional (SF) technique while two others are based on the simultaneous perturbation stochastic approximation (SPSA) method. They differ from each other in the way perturbations are obtained and also the manner in which projections and parameter updates are performed. All our algorithms use two simulations and two-timescale stochastic approximation. As an application setting, we consider the important problem of admission control of packets in communication networks under dependent service times. We consider a discrete time slotted queueing model of the system and consider two different scenarios - one where the service times have a dependence on the system state and the other where they depend on the number of arrivals in a time slot. Under our settings, the simulated objective function appears ill-behaved with multiple local minima and a unique global minimum characterized by a sharp dip in the objective function in a small region of the parameter space. We compare the performance of our algorithms on these settings and observe that the two SF algorithms show the best results overall. In fact, in many cases studied, SF algorithms converge to the global minimum.