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Electrochemical SPM study of 2D phase and 3D phase formation of Zn at the ionic liquid / Au(111) interface [online]

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ISBN: 3937300090 Year: DOI: 10.5445/KSP/1132004 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Chemistry (General)
Added to DOAB on : 2019-07-30 20:01:58

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Zn electrodeposition in the under- (UPD) and overpotential (OPD) ranges by means of in-situ Scanning Tunneling Microscopy (STM) was examined, supported by in-situ cyclic voltammetry and chronoamperometrie. The underpotential deposition of Zn follows a layer-by-layer growth. For the first time the formation of three successive Zn monolayers has been observed in the UPD range. It has been shown, that the UPD of Zn is complicated due to surface alloying. The same growth mechanism extends from the UPD into OPD range until Al bulk deposition sets in. The UPD of Al at 100 mV vs. Zn/Zn(II) is marked by Moiré pattern formation. For the first time in this system the effective tunneling barrier f has been measured by STS. A first insight into the 2D phase formation of electrodeposited Zn at the electrolyte / electrode interface was obtained from STM images at various times and potentials. Before a coherent layer is formed wormlike structures are observed characteristic of spinodal decomposition. This implies a first order phase transition, which has been resolved here for the first time for 2D electrodeposition.

New Insights into Microbial Ecology through Subtle Nucleotide Variation

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199884 Year: Pages: 133 DOI: 10.3389/978-2-88919-988-4 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Microbiology
Added to DOAB on : 2016-01-19 14:05:46
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The 16S ribosomal RNA gene commonly serves as a molecular marker for investigating microbial community composition and structure. Vast amounts of 16S rRNA amplicon data generated from environmental samples thanks to the recent advances in sequencing technologies allowed microbial ecologists to explore microbial community dynamics over temporal and spatial scales deeper than ever before. However, widely used methods for the analysis of bacterial communities generally ignore subtle nucleotide variations among high-throughput sequencing reads and often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial datasets. Lack of proper partitioning of the sequencing data into relevant units often masks important ecological patterns. Our research topic contains articles that use oligotyping to demonstrate the importantance of high-resolution analyses of marker gene data, and providides further evidence why microbial ecologists should open the "black box" of OTUs identified through arbitrary sequence similarity thresholds.

Morphologically complex words in the mind/brain

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198030 Year: Pages: 230 DOI: 10.3389/978-2-88919-803-0 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-04-07 11:22:02
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The question of how morphologically complex words (assign-ment, listen-ed) are represented and processed in the brain has been one of the most hotly debated topics in the cognitive neuroscience of language. Do complex words engage cortical representations and processes equivalent to single lexical objects or are they processed as sequences of separate morpheme-like units? Research on morphological processing has suggested that adults make efficient use of both lexical (i.e., whole word) storage and retrieval, as well as combinatorial computation in processing morphologically complex words. Psycholinguistic studies have demonstrated that processing of complex words can be affected both by properties of the morphemes and the whole words, such as their frequency, transparency, and regularity. Furthermore, this research has been informative about the time-course of complex word recognition and production, and the role of morphological structure in these processes. At the neural level, left-hemisphere inferior frontal and superior temporal areas, and negative-going event-related potentials, have been consistently associated with morphological processing. While most previous research has been done on the recognition of morphologically complex words in adult native speakers, much less is known about neurocognitive processes involved in the on-line production of morphologically complex words, and even less on morphological processing in children and non-native speakers. Moreover, we have limited understanding of how linguistically distinct morphological processes, e.g. inflectional (listen-ed) versus derivational (assign-ment), are handled by the cortical language networks. This e-book gives an up-to-date overview of the questions currently addressed in the field of morphological processing. It highlights the significance of morphological information in language processing, both written and spoken, as assessed by a variety of methods and approaches. It also points to a number of unresolved issues, and provides future directions for research in this key area of cognitive neuroscience of language.

Keywords

morphology --- derivation --- inflection --- Compound --- L2 --- Dyslexia --- ERP --- MEG --- semantics --- decomposition

Information Decomposition of Target Effects from Multi-Source Interactions

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ISBN: 9783038970156 9783038970163 Year: Pages: 336 DOI: 10.3390/books978-3-03897-016-3 Language: englisch
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics --- Physics (General)
Added to DOAB on : 2018-09-04 13:22:10
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Using Shannon information theory to analyse the contributions from two source variables to a target, for example, we can measure the information held by one source about the target, the information held by the other source about the target, and the information held by those sources together about the target. Intuitively, however, there is strong desire to measure further notions of how this directed information interaction may be decomposed, e.g., how much information the two source variables hold redundantly about the target, how much each source variable holds uniquely, and how much information can only be discerned by synergistically examining the two sources together.The absence of measures for such decompositions into redundant, unique and synergistic information is arguably the most fundamental missing piece in classical information theory. Triggered by the formulation of the Partial Information Decomposition framework by Williams and Beer in 2010, the past few years have witnessed a concentration of work by the community in proposing, contrasting, and investigating new measures to capture these notions of information decomposition.This Special Issue seeks to bring together these efforts, to capture a snapshot of the current research, as well as to provide impetus for and focused scrutiny on newer work, present progress to the wider community and attract further research. Our contributions present: several new approaches for measures of such decompotions; commentary on properties, interpretations and limitations of such approaches; and applications to empirical data (in particular to neural data).

Econometrics and Income Inequality

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ISBN: 9783038973669 9783038973676 Year: Pages: 322 DOI: 10.3390/books978-3-03897-367-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Social Sciences --- Business and Management
Added to DOAB on : 2018-11-26 12:04:46
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This Special Issue is devoted to the econometric analysis of income inequality and income distributions. Given the recent surge of inequality research, this Special Issue seeks to combine both theoretical and applied contributions which advance the econometric analysis of income inequality and income distributions. Possible topics include, but are not limited to, statistical inference for inequality measurement, inequality measurement with complex survey data, parametric or nonparametric modeling of income distributions, statistical decomposition methodology, methods to investigate the determinants of distributional change, causal inference in inequality measurement, and applications of such methods to substantive research questions in different fields of economics.

Economic Inequality in Latin America

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Book Series: Goettinger Studien zur Entwicklungsoekonomik / Goettingen Studies in Development Economics ISBN: 9783631639764 Year: Pages: 172 Language: English
Publisher: Peter Lang International Academic Publishing Group
Subject: Economics --- Political Science --- Sociology
Added to DOAB on : 2019-01-15 13:32:58
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Inequality in Latin America is very large and there is a great desire for greater social justice, inclusion and equal opportunities. In order to contribute to the understanding of such developments, this volume addresses the problem of economic inequality in Paraguay, Honduras and Chile. The studies show from different angles how an adverse family background has permanent negative effects on employment, wages and labour mobility, particularly in the presence of structural economic changes. In general, this book is a contribution to understand why inequality is highly persistent in Latin America, a place where low levels of income, poverty and vulnerability are likely to be passed on to the next generation.

Poverty, Income Growth and Inequality in Paraguay During the 1990s

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Book Series: Goettinger Studien zur Entwicklungsoekonomik / Goettingen Studies in Development Economics ISBN: 9783631572016 Year: Pages: 140 Language: English
Publisher: Peter Lang International Academic Publishing Group
Subject: Economics --- Political Science
Added to DOAB on : 2019-01-15 13:32:27
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The Paraguayan economy did not suffer debt crises in the eighties and had significant growth rates in the second half on the seventies, but poverty remained a problem. Understanding the performance and spatial distribution of poverty and inequality over a period of more than ten years can shed new light on structural causes behind what seems to be a low growth – high poverty – high inequality trap in Paraguay. How did poverty and inequality change during the 1990s. Did inequality reduce income growth? What were the growth determinants and what are the main forces driving inequality changes? These are the questions being answered in this book.

China in Transition

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Book Series: Hohenheimer volkswirtschaftliche Schriften ISBN: 9783631633281 Year: Pages: 236 Language: English
Publisher: Peter Lang International Academic Publishing Group
Subject: Economics
Added to DOAB on : 2019-01-15 13:32:59
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In China, inequality in social welfare is of rising political concern. This case study analyzes the determinants of well-being of rural households in Hebei using a secondary panel data set (1986 to 2006). One key question is how well-being was affected by institutional changes in times of societal transition. Based on population grouping, the author analyzes poverty and income development. The study reveals impacts of new possibilities to provide labor outside the own farm on the allocation of households’ labor time and the stability of full- and part-time farming over time. The assessments ground on agricultural household models, microeconomic concepts of labor allocation, and welfare theories. Different methodologies, e.g. inequality decomposition or hazard analysis, are applied.

Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting

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ISBN: 9783038972860 9783038972877 Year: Pages: 250 DOI: 10.3390/books978-3-03897-287-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2018-10-19 11:45:03
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More accurate and precise energy demand forecasts are required when energy decisions are made in a competitive environment. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated. Examples include seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. These forecasting models have resulted in an over-reliance on the use of informal judgment and higher expenses when lacking the ability to determine data characteristics and patterns. The hybridization of optimization methods and superior evolutionary algorithms can provide important improvements via good parameter determinations in the optimization process, which is of great assistance to actions taken by energy decision-makers.This book aimed to attract researchers with an interest in the research areas described above. Specifically, it sought contributions to the development of any hybrid optimization methods (e.g., quadratic programming techniques, chaotic mapping, fuzzy inference theory, quantum computing, etc.) with advanced algorithms (e.g., genetic algorithms, ant colony optimization, particle swarm optimization algorithm, etc.) that have superior capabilities over the traditional optimization approaches to overcome some embedded drawbacks, and the application of these advanced hybrid approaches to significantly improve forecasting accuracy.

Kernel Methods and Hybrid Evolutionary Algorithms in Energy Forecasting

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ISBN: 9783038972921 9783038972938 Year: Pages: 186 DOI: 10.3390/books978-3-03897-293-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science --- General and Civil Engineering
Added to DOAB on : 2018-10-22 10:01:53
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The development of kernel methods and hybrid evolutionary algorithms (HEAs) to support experts in energy forecasting is of great importance to improving the accuracy of the actions derived from an energy decision maker, and it is crucial that they are theoretically sound. In addition, more accurate or more precise energy demand forecasts are required when decisions are made in a competitive environment. Therefore, this is of special relevance in the Big Data era. These forecasts are usually based on a complex function combination. These models have resulted in over-reliance on the use of informal judgment and higher expense if lacking the ability to catch the data patterns. The novel applications of kernel methods and hybrid evolutionary algorithms can provide more satisfactory parameters in forecasting models. We aimed to attract researchers with an interest in the research areas described above. Specifically, we were interested in contributions towards the development of HEAs with kernel methods or with other novel methods (e.g., chaotic mapping mechanism, fuzzy theory, and quantum computing mechanism), which, with superior capabilities over the traditional optimization approaches, aim to overcome some embedded drawbacks and then apply these new HEAs to be hybridized with original forecasting models to significantly improve forecasting accuracy.

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