LIAD-fs: A novel method for studies of ultrafast processes in gas phase neutral biomolecules

A new experimental technique for femtosecond (fs) pulse studies of gas phase biomolecules is reported. Using Laser-Induced Acoustic Desorption (LIAD) to produce a plume of neutral molecules, a time-delayed fs pulse is employed for ionisation/fragmentation, with subsequent products extracted and mass analysed electrostatically. By varying critical laser pulse parameters, this technique can be used to implement control over molecular fragmentation for a range of small biomolecules, with specific studies of amino acids demonstrated.

A biological survey method applied to seafloor massive sulphides (SMS) with contagiously distributed hydrothermal-vent fauna

Strategies for mitigation of seafloor massive sulphide (SMS) extraction in the deep sea include establishment of suitable reference sites that allow for studies of natural environmental variability and that can serve as sources of larvae for re-colonisation of extracted hydrothermal fields. In this study, we characterize deep-sea vent communities in Manus Basin (Bismarck Sea, Papua New Guinea) and use macrofaunal data sets from a proposed reference site (South Su) and a proposed mine site (Solwara 1) to test the hypothesis that there was no difference in macrofaunal community structure between the sites. We used dispersion weighting to adjust taxa-abundance matrices to down-weight the contribution of contagious distributions of numerically abundant taxa. Faunal assemblages of 3 habitat types defined by biogenic taxa (2 provannid snails, Alviniconcha spp. and Ifremeria nautilei; and a sessile barnacle, Eochionelasmus ohtai) were distinct from one another and from the vent peripheral assemblage, but were not differentiable from mound-to-mound within a site or between sites. Mussel and tubeworm populations at South Su but not at Solwara 1 enhance the taxonomic and habitat diversity of the proposed reference site. © Inter-Research 2012.

A method of measuring anterior chamber volume using the anterior segment optical coherence tomographer and specialized software.

PURPOSE: To describe and evaluate a new method for measuring anterior chamber volume (ACV). DESIGN: Observational case series. METHODS: The authors measured ACV using the anterior chamber (AC) optical coherence tomographer (OCT) and applied image-processing software developed by them. Repeatability was evaluated. The ACV was measured in patient groups with normal ACs, shallow ACs, and deep ACs. The volume difference before and after laser peripheral iridotomy (LPI) was analyzed for the shallow and deep groups. RESULTS: Coefficients of repeatability for intraoperator, interoperator, and interimage measurements were 0.406%, 0.958%, and 0.851%, respectively. The limits of agreement for intraoperator and interoperator measurement were -0.911 microl to 1.343 microl and -7.875 microl to -2.463 microl, respectively. There were significant ACV differences in normal, shallow, and deep AC eyes (P < .001) and before and after LPI in shallow AC (P < .001) and deep AC (P = .008) eyes. CONCLUSIONS: The ACV values obtained by this method were repeatable and in accord with clinical observation.

Parallel Time Series Analysis and Income Inequality: A New Approach to Comparative Case Studies

This case study deals with the role of time series analysis in sociology, and its relationship with the wider literature and methodology of comparative case study research. Time series analysis is now well-represented in top-ranked sociology journals, often in the form of ‘pooled time series’ research designs. These studies typically pool multiple countries together into a pooled time series cross-section panel, in order to provide a larger sample for more robust and comprehensive analysis. This approach is well suited to exploring trans-national phenomena, and for elaborating useful macro-level theories specific to social structures, national policies, and long-term historical processes. It is less suited however, to understanding how these global social processes work in different countries. As such, the complexities of individual countries - which often display very different or contradictory dynamics than those suggested in pooled studies – are subsumed. Meanwhile, a robust literature on comparative case-based methods exists in the social sciences, where researchers focus on differences between cases, and the complex ways in which they co-evolve or diverge over time. A good example of this is the inequality literature, where although panel studies suggest a general trend of rising inequality driven by the weakening power of labour, marketisation of welfare, and the rising power of capital, some countries have still managed to remain resilient. This case study takes a closer look at what can be learned by applying the insights of case-based comparative research to the method of time series analysis. Taking international income inequality as its point of departure, it argues that we have much to learn about the viability of different combinations of policy options by examining how they work in different countries over time. By taking representative cases from different welfare systems (liberal, social democratic, corporatist, or antipodean), we can better sharpen our theories of how policies can be more specifically engineered to offset rising inequality. This involves a fundamental realignment of the strategy of time series analysis, grounding it instead in a qualitative appreciation of the historical context of cases, as a basis for comparing effects between different countries.

Photoionization of Cl-like Argon using the Breit-Pauli R-matrix method

Here we present the photoionization cross sections for the ground and metastable states of Cl-like Argon by exploiting the fully relativistic Breit-Pauli R-matrix computer codes to determine these transitions of interest. We compare our work with previous theoretical and experimental results and present a detailed investigation into the model of Ar III, the resonant structure and identification process.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.