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The Balkan Conditional in South Slavic

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Book Series: Slavistische Beitraege ISBN: 9783876908519 Year: Pages: 320 DOI: 10.3726/b12699 Language: German
Publisher: Peter Lang International Academic Publishing Group
Subject: Linguistics
Added to DOAB on : 2019-01-15 13:31:33
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This study examines the morphological and semantic development of the modal construction formed with either the imperfect of 'to want' (Croatian/Serbian) plus the infinitive, or with a modal particle from 'to want' (Macedonian) plus the imperfect of the main verb. The Balkan conditional is analyzed using material from diverse sources, including epic folk poetry, dialectal texts, and the standard literary language in the South Slavic languages, as well as in the Balkan non-Slavic languages of Greek, Albanian, Daco-Rumanian, Istro-Rumanian, and Arumanian. Specific syntactic and semantic contexts are analyzed, and the Balkan conditional is compared to other modal constructions in these languages. One of the characteristic analytic verbal forms shared by the languages of the Balkan league is the Balkan conditional or the so-called 'future-in-the-past'. In the majority of these languages, the Balkan conditional has the status of a grammatical category, whose invariant components are 'modality', specifically 'potentiality', and 'reference to past tense'. With such components, these expressions most frequently and naturally refer to actions which did not take place, i.e., the past, contrary-to-fact conditional.

Novel Approaches to the Analysis of Family Data in Genetic Epidemiology

Authors: --- --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199327 Year: Pages: 84 DOI: 10.3389/978-2-88919-932-7 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Genetics
Added to DOAB on : 2016-01-19 14:05:46
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Genome-wide association studies (GWAS) for complex disorders with large case-control populations have been performed on hundreds of traits in more than 1200 published studies (http://www.genome.gov/gwastudies/) but the variants detected by GWAS account for little of the heritability of these traits, leading to an increasing interest in using family based designs. While GWAS studies are designed to find common variants with low to moderate attributable risks, family based studies are expected to find rare variants with high attributable risk. Because family-based designs can better control both genetic and environmental background, this study design is robust to heterogeneity and population stratification. Moreover, in family-based analysis, the background genetic variation can be modeled to control the residual variance which could increase the power to identify disease associated rare variants. Analysis of families can also help us gain knowledge about disease transmission and inheritance patterns. Although a family-based design has the advantage of being robust to false positives, novel and powerful methods to analyze families in genetic epidemiology continue to be needed, especially for the interaction between genetic and environmental factors associated with disease. Moreover, with the rapid development of sequencing technology, advances in approaches to the design and analysis of sequencing data in families are also greatly needed. The 11 articles in this book all introduce new methodology and, using family data, substantial new findings are presented in the areas of infectious diseases, diabetes, eye traits, autism spectrum disorder and prostate cancer.

Unjust Conditions

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ISBN: 9780520296992 9780520969520 Year: Pages: 212 DOI: 10.1525/luminos.49 Language: English
Publisher: University of California Press
Subject: Gender Studies --- History --- Migration
Added to DOAB on : 2018-05-09 11:01:52
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Unjust Conditions follows the lives and labors of poor mothers in rural Peru, richly documenting the ordeals they face to participate in mainstream poverty alleviation programs. Championed by behavioral economists and the World Bank, conditional cash transfer (CCT) programs are praised as efficient mechanisms for changing poor people’s behavior. While rooted in good intentions and dripping with the rhetoric of social inclusion, CCT programs’ successes ring hollow, based solely on metrics for children’s attendance at school and health appointments. Looking beyond these statistics reveals a host of hidden costs for the mothers who meet the conditions. With a poignant voice and keen focus on ethnographic research, Tara Patricia Cookson turns the reader’s gaze to women’s care work in landscapes of grossly inadequate state investment, cleverly drawing out the tensions between social inclusion and conditionality.

Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation

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Book Series: Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory ISSN: 18673813 ISBN: 9783866449527 Year: Volume: 11 Pages: XIV, 210 p. DOI: 10.5445/KSP/1000031356 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:01:58
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This thesis is concerned with intention recognition for a humanoid robot and investigates how the challenges of uncertain and incomplete observations, a high degree of detail of the used models, and real-time inference may be addressed by modeling the human rationale as hybrid, dynamic Bayesian networks and performing inference with these models. The key focus lies on the automatic identification of the employed nonlinear stochastic dependencies and the situation-specific inference.

Lie and non-Lie Symmetries: Theory and Applications for Solving Nonlinear Models

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ISBN: 9783038425267 9783038425274 Year: Pages: XII, 414 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics
Added to DOAB on : 2017-10-25 13:19:05
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Since the end of the 19th century when the prominent Norwegian mathematician Sophus Lie created the theory of Lie algebras and Lie groups and developed the method of their applications for solving differential equations, his theory and method have continuously been the research focus of many well-known mathematicians and physicists. This book is devoted to recent development in Lie theory and its applications for solving physically and biologically motivated equations and models. The book contains the articles published in two Special Issue of the journal Symmetry, which are devoted to analysis and classification of Lie algebras, which are invariance algebras of real-word models; Lie and conditional symmetry classification problems of nonlinear PDEs; the application of symmetry-based methods for finding new exact solutions of nonlinear PDEs (especially reaction-diffusion equations) arising in applications; the application of the Lie method for solving nonlinear initial and boundary-value problems (especially those for modelling processes with diffusion, heat transfer, and chemotaxis).

Elements of Causal Inference

Authors: --- ---
Book Series: Adaptive Computation and Machine Learning series ISBN: 9780262344296 9780262037310 Year: Pages: 288 Language: English
Publisher: The MIT Press
Subject: Computer Science
Added to DOAB on : 2019-01-17 11:41:31
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A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

Nonparametric Econometric Methods and Application

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ISBN: 9783038979647 / 9783038979654 Year: Pages: 224 DOI: 10.3390/books978-3-03897-965-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Mathematics
Added to DOAB on : 2019-06-26 08:44:06
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The present Special Issue collects a number of new contributions both at the theoretical level and in terms of applications in the areas of nonparametric and semiparametric econometric methods. In particular, this collection of papers that cover areas such as developments in local smoothing techniques, splines, series estimators, and wavelets will add to the existing rich literature on these subjects and enhance our ability to use data to test economic hypotheses in a variety of fields, such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth, to name a few.

Financial Econometrics

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ISBN: 9783039216260 / 9783039216277 Year: Pages: 136 DOI: 10.3390/books978-3-03921-627-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Economics
Added to DOAB on : 2019-12-09 11:49:15
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Financial econometrics has developed into a very fruitful and vibrant research area in the last two decades. The availability of good data promotes research in this area, specially aided by online data and high-frequency data. These two characteristics of financial data also create challenges for researchers that are different from classical macro-econometric and micro-econometric problems. This Special Issue is dedicated to research topics that are relevant for analyzing financial data. We have gathered six articles under this theme.

Quantum Probability and Randomness

Authors: ---
ISBN: 9783038977148 9783038977155 Year: Pages: 276 DOI: 10.3390/books978-3-03897-715-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2019-04-25 16:37:17
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The last few years have been characterized by a tremendous development of quantum information and probability and their applications, including quantum computing, quantum cryptography, and quantum random generators. In spite of the successful development of quantum technology, its foundational basis is still not concrete and contains a few sandy and shaky slices. Quantum random generators are one of the most promising outputs of the recent quantum information revolution. Therefore, it is very important to reconsider the foundational basis of this project, starting with the notion of irreducible quantum randomness. Quantum probabilities present a powerful tool to model uncertainty. Interpretations of quantum probability and foundational meaning of its basic tools, starting with the Born rule, are among the topics which will be covered by this issue. Recently, quantum probability has started to play an important role in a few areas of research outside quantum physics&mdash;in particular, quantum probabilistic treatment of problems of theory of decision making under uncertainty. Such studies are also among the topics of this issue.

Keywords

quantum logic --- groups --- partially defined algebras --- quasigroups --- viable cultures --- quantum information theory --- bit commitment --- protocol --- entropy --- entanglement --- orthogonality --- quantum computation --- Gram–Schmidt process --- quantum probability --- potentiality --- complementarity --- uncertainty relations --- Copenhagen interpretation --- indefiniteness --- indeterminism --- causation --- randomness --- quantum information --- quantum dynamics --- entanglement --- algebra --- causality --- geometry --- probability --- quantum information theory --- realism --- reality --- entropy --- correlations --- qubits --- probability representation --- Bayes’ formula --- quantum entanglement --- three-qubit random states --- entanglement classes --- entanglement polytope --- anisotropic invariants --- quantum random number --- vacuum state --- maximization of quantum conditional min-entropy --- quantum logics --- quantum probability --- holistic semantics --- epistemic operations --- Bell inequalities --- algorithmic complexity --- Borel normality --- Bayesian inference --- model selection --- random numbers --- quantum-like models --- operational approach --- information interpretation of quantum theory --- social laser --- social energy --- quantum information field --- social atom --- Bose–Einstein statistics --- bandwagon effect --- social thermodynamics --- resonator of social laser --- master equation for socio-information excitations --- quantum contextuality --- Kochen–Specker sets --- MMP hypergraphs --- Greechie diagrams --- quantum foundations --- probability --- irreducible randomness --- random number generators --- quantum technology --- entanglement --- quantum-like models for social stochasticity --- contextuality

Nucleic Acid Architectures for Therapeutics, Diagnostics, Devices and Materials

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ISBN: 9783039212590 / 9783039212606 Year: Pages: 186 DOI: 10.3390/books978-3-03921-260-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology
Added to DOAB on : 2019-12-09 11:49:15
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Nucleic acids (RNA and DNA) and their chemical analogs have been utilized as building materials due to their biocompatibility and programmability. RNA, which naturally possesses a wide range of different functions, is now being widely investigated for its role as a responsive biomaterial which dynamically reacts to changes in the surrounding environment. It is now evident that artificially designed self-assembling RNAs, that can form programmable nanoparticles and supra-assemblies, will play an increasingly important part in a diverse range of applications, such as macromolecular therapies, drug delivery systems, biosensing, tissue engineering, programmable scaffolds for material organization, logic gates, and soft actuators, to name but a few. The current exciting Special Issue comprises research highlights, short communications, research articles, and reviews that all bring together the leading scientists who are exploring a wide range of the fundamental properties of RNA and DNA nanoassemblies suitable for biomedical applications.

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