Isolation of microplastics in biota-rich seawater samples and marine organisms

Microplastic litter is a pervasive pollutant present in aquatic systems across the globe. A range of marine organisms have the capacity to ingest microplastics, resulting in adverse health effects. Developing methods to accurately quantify microplastics in productive marine waters, and those internalized by marine organisms, is of growing importance. Here we investigate the efficacy of using acid, alkaline and enzymatic digestion techniques in mineralizing biological material from marine surface trawls to reveal any microplastics present. Our optimized enzymatic protocol can digest >97% (by weight) of the material present in plankton-rich seawater samples without destroying any microplastic debris present. In applying the method to replicate marine samples from the western English Channel, we identified 0.27 microplastics m−3. The protocol was further used to extract microplastics ingested by marine zooplankton under laboratory conditions. Our findings illustrate that enzymatic digestion can aid the detection of microplastic debris within seawater samples and marine biota.

Mutual Solubilities of Water and Hydrophobic Ionic Liquids

The ionic nature of ionic liquids (ILs) results in a unique combination of intrinsic properties that produces increasing interest in the research of these fluids as environmentally friendly "neoteric" solvents. One of the main research fields is their exploitation as solvents for liquid-liquid extractions, but although ILs cannot vaporize leading to air pollution, they present non-negligible miscibility with water that may be the cause of some environmental aquatic risks. It is thus important to know the mutual solubilities between ILs and water before their industrial applications. In this work, the mutual solubilities of hydrophobic yet hygroscopic imidazolium-, pyridinium-, pyrrolidinium-, and piperidinium-based ILs in combination with the anions bis(trifluoromethylsulfonyl)imide, hexafluorophosphate, and tricyanomethane with water were measured between 288.15 and 318.15 K. The effect of the ILs structural combinations, as well as the influence of several factors, namely cation side alkyl chain length, the number of cation substitutions, the cation family, and the anion identity in these mutual solubilities are analyzed and discussed. The hydrophobicity of the anions increases in the order [C(CN)3] <[PF6] <[Tf2N] while the hydrophobicity of the cations increases from [Cnmim] <[Cnmpy] [Cnmpyr] <[Cnmpip] and with the alkyl chain length increase. From experimental measurements of the temperature dependence of ionic liquid solubilities in water, the thermodynamic molar functions of solution, such as Gibbs energy, enthalpy, and entropy at infinite dilution were determined, showing that the solubility of these ILs in water is entropically driven and that the anion solvation at the IL-rich phase controls their solubilities in water. The COSMO-RS, a predictive method based on unimolecular quantum chemistry calculations, was also evaluated for the description of the water-IL binary systems studied, where it showed to be capable of providing an acceptable qualitative agreement with the experimental data.

Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Assessment Method for a Power Analysis to Identify Differentially Expressed Pathways

Gene expression data can provide a very rich source of information for elucidating the biological function on the pathway level if the experimental design considers the needs of the statistical analysis methods. The purpose of this paper is to provide a comparative analysis of statistical methods for detecting the differentially expression of pathways (DEP). In contrast to many other studies conducted so far, we use three novel simulation types, producing a more realistic correlation structure than previous simulation methods. This includes also the generation of surrogate data from two large-scale microarray experiments from prostate cancer and ALL. As a result from our comprehensive analysis of 41,004 parameter configurations, we find that each method should only be applied if certain conditions of the data from a pathway are met. Further, we provide method-specific estimates for the optimal sample size for microarray experiments aiming to identify DEP in order to avoid an underpowered design. Our study highlights the sensitivity of the studied methods on the parameters of the system. © 2012 Tripahti and Emmert-Streib.

A multiconfigurational time-dependent Hartree-Fock method for excited electronic states. I. General formalism and application to open-shell states

The solution of the time-dependent Schrodinger equation for systems of interacting electrons is generally a prohibitive task, for which approximate methods are necessary. Popular approaches, such as the time-dependent Hartree-Fock (TDHF) approximation and time-dependent density functional theory (TDDFT), are essentially single-configurational schemes. TDHF is by construction incapable of fully accounting for the excited character of the electronic states involved in many physical processes of interest; TDDFT, although exact in principle, is limited by the currently available exchange-correlation functionals. On the other hand, multiconfigurational methods, such as the multiconfigurational time-dependent Hartree-Fock (MCTDHF) approach, provide an accurate description of the excited states and can be systematically improved. However, the computational cost becomes prohibitive as the number of degrees of freedom increases, and thus, at present, the MCTDHF method is only practical for few-electron systems. In this work, we propose an alternative approach which effectively establishes a compromise between efficiency and accuracy, by retaining the smallest possible number of configurations that catches the essential features of the electronic wavefunction. Based on a time-dependent variational principle, we derive the MCTDHF working equation for a multiconfigurational expansion with fixed coefficients and specialise to the case of general open-shell states, which are relevant for many physical processes of interest. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3600397]

Measurement-based Method for Wind Farm Power System Oscillation Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

Liouville-space R-matrix-Floquet description of atomic radiative processes involving autoionizing states in the presence of intense electromagnetic fields

A reduced-density-operator description is developed for coherent optical phenomena in many-electron atomic systems, utilizing a Liouville-space, multiple-mode Floquet–Fourier representation. The Liouville-space formulation provides a natural generalization of the ordinary Hilbert-space (Hamiltonian) R-matrix-Floquet method, which has been developed for multi-photon transitions and laser-assisted electron–atom collision processes. In these applications, the R-matrix-Floquet method has been demonstrated to be capable of providing an accurate representation of the complex, multi-level structure of many-electron atomic systems in bound, continuum, and autoionizing states. The ordinary Hilbert-space (Hamiltonian) formulation of the R-matrix-Floquet method has been implemented in highly developed computer programs, which can provide a non-perturbative treatment of the interaction of a classical, multiple-mode electromagnetic field with a quantum system. This quantum system may correspond to a many-electron, bound atomic system and a single continuum electron. However, including pseudo-states in the expansion of the many-electron atomic wave function can provide a representation of multiple continuum electrons. The 'dressed' many-electron atomic states thereby obtained can be used in a realistic non-perturbative evaluation of the transition probabilities for an extensive class of atomic collision and radiation processes in the presence of intense electromagnetic fields. In order to incorporate environmental relaxation and decoherence phenomena, we propose to utilize the ordinary Hilbert-space (Hamiltonian) R-matrix-Floquet method as a starting-point for a Liouville-space (reduced-density-operator) formulation. To illustrate how the Liouville-space R-matrix-Floquet formulation can be implemented for coherent atomic radiative processes, we discuss applications to electromagnetically induced transparency, as well as to related pump–probe optical phenomena, and also to the unified description of radiative and dielectronic recombination in electron–ion beam interactions and high-temperature plasmas.

Evaluation of the effect of wheat aleurone-rich foods on markers of antioxidant status, inflammation and endothelial function in apparently healthy men and women

Observational data show an inverse association between the consumption of whole-grain foods, and inflammation and related diseases. Although the underlying mechanisms are unclear, whole grains, and in particular the aleurone layer, contain a wide range of components with putative antioxidant and anti-inflammatory effects. We evaluated the effects of a diet high in wheat aleurone on plasma antioxidants status, markers of inflammation and endothelial function. In this parallel, participant-blinded intervention, seventy-nine healthy, older, overweight participants (45-65 years, BMI>25 kg/m²) incorporated either aleurone-rich cereal products (27 g aleurone/d), or control products balanced for fibre and macronutrients, into their habitual diets for 4 weeks. Fasting blood samples were taken at baseline and on day 29. Results showed that, compared to control, consumption of aleurone-rich products provided substantial amounts of micronutrients and phytochemicals which may function as antioxidants. Additionally, incorporating these products into a habitual diet resulted in significantly lower plasma concentrations of the inflammatory marker, C-reactive protein (P = 0·035), which is an independent risk factor for CVD. However, no changes were observed in other markers of inflammation, antioxidant status or endothelial function. These results provide a possible mechanism underlying the beneficial effects of longer-term whole-grain intake. However, it is unclear whether this effect is owing to a specific component, or a combination of components in wheat aleurone.

Photodissociation and chemistry of N2 in the circumstellar envelope of carbon-rich AGB stars

The envelopes of AGB stars are irradiated externally by ultraviolet photons; hence, the chemistry is sensitive to the photodissociation of N$_2$ and CO, which are major reservoirs of nitrogen and carbon, respectively. The photodissociation of N$_2$ has recently been quantified by laboratory and theoretical studies. Improvements have also been made for CO photodissociation. For the first time, we use accurate N$_2$ and CO photodissociation rates and shielding functions in a model of the circumstellar envelope of the carbon-rich AGB star, IRC +10216. We use a state-of-the-art chemical model of an AGB envelope, the latest CO and N$_2$ photodissociation data, and a new method for implementing molecular shielding functions in full spherical geometry with isotropic incident radiation. We compare computed column densities and radial distributions of molecules with observations. The transition of N$_2$ $\to$ N (also, CO $\to$ C $\to$ C$^+$) is shifted towards the outer envelope relative to previous models. This leads to different column densities and radial distributions of N-bearing species, especially those species whose formation/destruction processes largely depend on the availability of atomic or molecular nitrogen, for example, C$_n$N ($n$=1, 3, 5), C$_n$N$^-$ ($n$=1, 3, 5), HC$_n$N ($n$=1, 3, 5, 7, 9), H$_2$CN and CH$_2$CN. The chemistry of many species is directly or indirectly affected by the photodissociation of N$_2$ and CO, especially in the outer shell of AGB stars where photodissociation is important. Thus, it is important to include N$_2$ and CO shielding in astrochemical models of AGB envelopes and other irradiated environments. In general, while differences remain between our model of IRC +10216 and the observed molecular column densities, better agreement is found between the calculated and observed radii of peak abundance.

Towards more flexible Architecture Description Languages for industrial applications

Architecture Description Languages (ADLs) have emerged in recent years as a tool for providing high-level descriptions of software systems in terms of their architectural elements and the relationships among them. Most of the current ADLs exhibit limitations which prevent their widespread use in industrial applications. In this paper, we discuss these limitations and introduce ALI, an ADL that has been developed to address such limitations. The ALI language provides a rich and flexible syntax for describing component interfaces, architectural patterns, and meta-information. Multiple graphical architectural views can then be derived from ALI's textual notation.

Energy-Aware Rate and Description Allocation Optimized Video Streaming for Mobile D2D Communications

The proliferation problem of video streaming applications and mobile devices has prompted wireless network operators to put more efforts into improving quality of experience (QoE) while saving resources that are needed for high transmission rate and large size of video streaming. To deal with this problem, we propose an energy-aware rate and description allocation optimization method for video streaming in cellular network assisted device-to-device (D2D) communications. In particular, we allocate the optimal bit rate to each layer of video segments and packetize the segments into multiple descriptions with embedded forward error correction (FEC) for realtime streaming without retransmission. Simultaneously, the optimal number of descriptions is allocated to each D2D helper for transmission. The two allocation processes are done according to the access rate of segments, channel state information (CSI) of D2D requester, and remaining energy of helpers, to gain the highest optimization performance. Simulation results demonstrate that our proposed method (named OPT) significantly enhances the performance of video streaming in terms of high QoE and energy saving.

Applications of the generalized Langevin equation: Towards a realistic description of the baths

The generalized Langevin equation (GLE) method, as developed previously [L. Stella et al., Phys. Rev. B 89, 134303 (2014)], is used to calculate the dissipative dynamics of systems described at the atomic level. The GLE scheme goes beyond the commonly used bilinear coupling between the central system and the bath, and permits us to have a realistic description of both the dissipative central system and its surrounding bath. We show how to obtain the vibrational properties of a realistic bath and how to convey such properties into an extended Langevin dynamics by the use of the mapping of the bath vibrational properties onto a set of auxiliary variables. Our calculations for a model of a Lennard-Jones solid show that our GLE scheme provides a stable dynamics, with the dissipative/relaxation processes properly described. The total kinetic energy of the central system always thermalizes toward the expected bath temperature, with appropriate fluctuation around the mean value. More importantly, we obtain a velocity distribution for the individual atoms in the central system which follows the expected canonical distribution at the corresponding temperature. This confirms that both our GLE scheme and our mapping procedure onto an extended Langevin dynamics provide the correct thermostat. We also examined the velocity autocorrelation functions and compare our results with more conventional Langevin dynamics.

Comparison Method for Differentiation of IEC 61850 based Substation Configuration Files

The increased construction and reconstruction of smart substations has exposed a problem with version management of substation configuration description language (SCL) files due to frequent changes. This paper proposes a comparative approach for differentiation of smart substation SCL configuration files. A comparison model for SCL configuration files is built in this method, which is based on the SCL structure and abstract model defined by IEC 61850. The proposed approach adopts the algorithms of depth-first traversal, sorting, and cross comparison in order to rapidly identify differences of changed SCL configuration files. This approach can also be utilized to detect malicious tampering or illegal manipulation tailoring for SCL files. SCL comparison software is developed using the Qt platform to validate the feasibility and effectiveness of the proposed approach.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.