A Large-Scale Comparison of Historical Text Normalization Systems

There is no consensus on the state-of-the-art approach to historical text normalization. Many techniques have been proposed, including rule-based methods, distance metrics, character-based statistical machine translation, and neural encoder--decoder models, but studies have used different datasets, different evaluation methods, and have come to different conclusions. This paper presents the largest study of historical text normalization done so far. We critically survey the existing literature and report experiments on eight languages, comparing systems spanning all categories of proposed normalization techniques, analysing the effect of training data quantity, and using different evaluation methods. The datasets and scripts are made publicly available.Comment: Accepted at NAACL 201

Transmuting CHY formulae

© The Author(s) 2019.The various formulations of scattering amplitudes presented in recent years have underlined a hidden unity among very different theories. The KLT and BCJ relations, together with the CHY formulation, connect the S-matrices of a wide range of theories: the transmutation operators, recently proposed by Cheung, Shen and Wen, provide an account for these similarities. In this note we use the transmutation operators to link the various CHY integrands at tree-level. Starting from gravity, we generate the integrands for YangMills, biadjoint scalar, Einstein-Maxwell, Yang-Mills scalar, Born-Infeld, Dirac-Born-Infeld, non-linear sigma model and special Galileon theories, as well as for their extensions. We also commence the study of the CHY-like formulae at loop level.Peer reviewe

Estuarine Nitrifiers: New Players, Patterns and Processes

Ever since the first descriptions of ammonia-oxidizing Bacteria by Winogradsky in the late 1800s, the metabolic capability of aerobic ammonia oxidation has been restricted to a phylogenetically narrow group of bacteria. However, the recent discovery of ammonia-oxidizing Archaea has forced microbiologists and ecologists to re-evaluate long-held paradigms and the role of niche partitioning between bacterial and archaeal ammonia oxidizers. Much of the current research has been conducted in open ocean or terrestrial systems, where community patterns of archaeal and bacterial ammonia oxidizers are highly congruent. Studies of archaeal and bacterial ammonia oxidizers in estuarine systems, however, present a very different picture, with highly variable patterns of archaeal and bacterial ammonia oxidizer abundances. Although salinity is often identified as an important factor regulating abundance, distribution, and diversity of both archaeal and bacterial ammonia oxidizers, the data suggest that the variability in the observed patterns is likely not due to a simple salinity effect. Here we review current knowledge of ammonia oxidizers in estuaries and propose that because of their steep physico-chemical gradients, estuaries may serve as important natural laboratories in which to investigate the relationships between archaeal and bacterial ammonia oxidizers

Few-Shot and Zero-Shot Learning for Historical Text Normalization

Historical text normalization often relies on small training datasets. Recent work has shown that multi-task learning can lead to significant improvements by exploiting synergies with related datasets, but there has been no systematic study of different multi-task learning architectures. This paper evaluates 63~multi-task learning configurations for sequence-to-sequence-based historical text normalization across ten datasets from eight languages, using autoencoding, grapheme-to-phoneme mapping, and lemmatization as auxiliary tasks. We observe consistent, significant improvements across languages when training data for the target task is limited, but minimal or no improvements when training data is abundant. We also show that zero-shot learning outperforms the simple, but relatively strong, identity baseline.Comment: Accepted at DeepLo-201

Perceived Market Risks and Strategic Risk Management of Food Manufactures: Empirical Results from the German Brewing Industry

The food industry is currently facing huge structural changes, such as growing concentration ratios and degrees of internationalization and as well as the reorganizations of food supply chains. Such developments do not only contribute to growing market risks but also require strategic reorientations on the part of food manufacturers. So far, risk management and strategic planning have been two fairly separated theoretical strands. In this paper we blend both schools of thought and analyze food manufacturers' perceived market risks and strategic risk management of food manufacturers. Empirical Our data stem from large-scale empirical research in the German brewing industry.Brewing industry, market risks, risk management, Agribusiness, Risk and Uncertainty,

Serial Correlations in Single-Subject fMRI with Sub-Second TR

When performing statistical analysis of single-subject fMRI data, serial correlations need to be taken into account to allow for valid inference. Otherwise, the variability in the parameter estimates might be under-estimated resulting in increased false-positive rates. Serial correlations in fMRI data are commonly characterized in terms of a first-order autoregressive (AR) process and then removed via pre-whitening. The required noise model for the pre-whitening depends on a number of parameters, particularly the repetition time (TR). Here we investigate how the sub-second temporal resolution provided by simultaneous multislice (SMS) imaging changes the noise structure in fMRI time series. We fit a higher-order AR model and then estimate the optimal AR model order for a sequence with a TR of less than 600 ms providing whole brain coverage. We show that physiological noise modelling successfully reduces the required AR model order, but remaining serial correlations necessitate an advanced noise model. We conclude that commonly used noise models, such as the AR(1) model, are inadequate for modelling serial correlations in fMRI using sub-second TRs. Rather, physiological noise modelling in combination with advanced pre-whitening schemes enable valid inference in single-subject analysis using fast fMRI sequences

Technical Note: Weight approximation of coccoliths using a circular polarizer and interference colour derived retardation estimates – (The CPR Method)

A circular polarizer is used for the first time to image coccoliths without the extinction pattern of crossed polarized light at maximum interference colour. The combination of a circular polarizer with retardation measurements based on grey values derived from theoretical calculations allows for the first time accurate calculations of the weight of single coccoliths thinner than 1.37 μm. The weight estimates of 364 Holocene coccoliths using this new method are in good agreement with published volumetric estimates. A robust calibration method based on the measurement of a calibration target of known retardation enables the comparison of data between different imaging systems. Therefore, the new method overcomes the shortcomings of the error prone empirical calibration procedure of a previously reported method based on birefringence of calcite. Furthermore, it greatly simplifies the identification of coccolithophore species on the light microscope as well as the calculation of the area and thus weight of a coccolith

DENSITY FUNCTIONAL THEORY STUDY OF THE THERMODYNAMICS OF CATALYTIC REMEDIATION OF NITRATE IN WATER

Over 1 billion people worldwide lack access to safe drinking water and 5,000 people die each day due to drinking contaminated water. With the development of new industries, new substances and chemicals are entering the waters every day, and the current water treatment processes are unable to remove them entirely. For example, agriculture is the world\u27s heaviest consumer of water, and nitrates and nitrites from fertilizers are washed away with the water to rivers and streams. These chemicals can cause problems to humans and to the environment. To humans, they can cause methemoglobinemia, also known as \u27blue baby syndrome\u27. To the environment, they can cause eutrophication, a phenomenon greatly reduced the dissolved oxygen content of the water harming the aquatic animals. Catalytic remediation of water is a promising strategy to meet the ecological, social and economic demands of the future, but the high-cost of developing new catalysts for wastewater treatment applications often limits their adoption in new wastewater treatment processes. In this work, we investigate nitrate and nitrite reduction over spherically shaped gold-based catalysts. Starting with Au13 we can modify composition by replacing just one or two atoms with other metals, forming Au12X and Au11XY clusters. Here, X/Y = Fe, Pd, In, and Cu, which were chosen because they cover a large range of groups in the periodic table, are relatively inexpensive, and are non-toxic. All of the tested catalysts tested show favorable behavior for nitrate reduction but not for nitrite reduction. We find that X,Y = Fe, Pd show the best results for nitrite dissociation because of the exothermic behavior towards both reactions. We also compute ammonia and water dissociation energies on the catalyst surfaces to determine if the catalysts will dissociate these species. This work provides the essential framework for modeling pollutant remediation in water. The methods described in this thesis were used to screen a range of catalysts compositions and identify small group of catalysts that performs the desired reactions selectively over water and organic matter