Hard constraints for grammatical function labelling

For languages with (semi-) free word order (such as German), labelling grammatical functions on top of phrase-structural constituent analyses is crucial for making them interpretable. Unfortunately, most statistical classifiers consider only local information for function labelling and fail to capture important restrictions on the distribution of core argument functions such as subject, object etc., namely that there is at most one subject (etc.) per clause. We augment a statistical classifier with an integer linear program imposing hard linguistic constraints on the solution space output by the classifier, capturing global distributional restrictions. We show that this improves labelling quality, in particular for argument grammatical functions, in an intrinsic evaluation, and, importantly, grammar coverage for treebankbased (Lexical-Functional) grammar acquisition and parsing, in an extrinsic evaluation

Agricultural Education Through News

If a visitor came into your office and offered to influence a thousand people in your behalf, with no cost or obligation to you, would you take him up on it? Your job is education. Your problem is reaching the great number of people in your county with the wealth of information you have at hand. Of course you would jump at the chance. That man is your local newspaperman. Extension education is primarily a proposition of personal contacts through schools, meetings, field tours and farm visits. Yet not everyone is enrolled in your crop improvement association or home demonstration dub. They don\u27t all turn out for field tours or meetings. The office mailing list doesn\u27t reach everyone in the county and there is a reasonable limitation on the number of mailings that may be made. Some people in the county have never set foot inside your office there is always that group that is hard to contact. So take your newspaperman up on his offer of help. The offer may not be made explicitly. You may not even be aware that it exists. But every progressive newspaperman is looking for good, live, local stories for his paper

Oligodendroglia heterogeneity in the human central nervous system

It is the centenary of the discovery of oligodendrocytes and we are increasingly aware of their importance in the functioning of the brain in development, adult learning, normal ageing and in disease across the life course, even in those diseases classically thought of as neuronal. This has sparked more interest in oligodendroglia for potential therapeutics for many neurodegenerative/neurodevelopmental diseases due to their more tractable nature as a renewable cell in the central nervous system. However, oligodendroglia are not all the same. Even from the first description, differences in morphology were described between the cells. With advancing techniques to describe these differences in human tissue, the complexity of oligodendroglia is being discovered, indicating apparent functional differences which may be of critical importance in determining vulnerability and response to disease, and targeting of potential therapeutics. It is timely to review the progress we have made in discovering and understanding oligodendroglial heterogeneity in health and neuropathology

Modeling the interface between morphology and syntax in data-driven dependency parsing

When people formulate sentences in a language, they follow a set of rules specific to that language that defines how words must be put together in order to express the intended meaning. These rules are called the grammar of the language. Languages have essentially two ways of encoding grammatical information: word order or word form. English uses primarily word order to encode different meanings, but many other languages change the form of the words themselves to express their grammatical function in the sentence. These languages are commonly subsumed under the term morphologically rich languages. Parsing is the automatic process for predicting the grammatical structure of a sentence. Since grammatical structure guides the way we understand sentences, parsing is a key component in computer programs that try to automatically understand what people say and write. This dissertation is about parsing and specifically about parsing languages with a rich morphology, which encode grammatical information in the form of words. Today’s parsing models for automatic parsing were developed for English and achieve good results on this language. However, when applied to other languages, a significant drop in performance is usually observed. The standard model for parsing is a pipeline model that separates the parsing process into different steps, in particular it separates the morphological analysis, i.e. the analysis of word forms, from the actual parsing step. This dissertation argues that this separation is one of the reasons for the performance drop of standard parsers when applied to other languages than English. An analysis is presented that exposes the connection between the morphological system of a language and the errors of a standard parsing model. In a second series of experiments, we show that knowledge about the syntactic structure of sentence can support the prediction of morphological information. We then argue for an alternative approach that models morphological analysis and syntactic analysis jointly instead of separating them. We support this argumentation with empirical evidence by implementing two parsers that model the relationship between morphology and syntax in two different but complementary ways

Overview of the SPMRL 2013 shared task: cross-framework evaluation of parsing morphologically rich languages

This paper reports on the first shared task on statistical parsing of morphologically rich languages (MRLs). The task features data sets from nine languages, each available both in constituency and dependency annotation. We report on the preparation of the data sets, on the proposed parsing scenarios, and on the evaluation metrics for parsing MRLs given different representation types. We present and analyze parsing results obtained by the task participants, and then provide an analysis and comparison of the parsers across languages and frameworks, reported for gold input as well as more realistic parsing scenarios

Characterisation of telomere length dynamics in dairy cattle and association with productive lifespan

Telomeres form protective caps at the ends of linear chromosomes. They consist of repetitive DNA nucleotides and associated proteins of the shelterin complex. In vitro telomeres become shorter during cell division and when a critical shortness is reached they trigger a DNA damage response that leads to replicative senescence or apoptosis. Telomere shortening is a recognised hallmark of cellular ageing and seems to be also associated with organismal ageing. Telomere length (TL) and the rate of shortening vary across individuals and several studies have found that short telomeres and fast telomere depletion are associated with poor survival and early onset of age related diseases. However, longitudinal studies are needed to better understand the relationship of TL and TL dynamics with longevity measures. Relevant studies on livestock species are largely missing from the literature. In the dairy industry, farmers are forced to cull a considerable percentage of their heifers and cows at a young age due to fertility problems or diseases. As a consequence many replacement heifers have to be reared to maintain a specific herd size. This results in increased costs, consumption of resources, and damage to the environment. Breeding for an improved productive lifespan is difficult because longevity measures are recorded at the end of life and are known to have a low heritability. Therefore, the expected genetic improvement is generally slow, but could be considerably accelerated if an early life heritable biomarker was identified that is predictive of productive lifespan and could be used for animal selection. The question is if TL could be used as such a biomarker. The objectives of this thesis were to 1) develop robust methods to measure average relative leukocyte TL (RLTL) in cattle, 2) examine RLTL dynamics with age at a population as well as at an individual level, 3) estimate genetic parameters and 4) assess the association of RLTL and RLTL dynamics with productive lifespan. A quantitative polymerase chain reaction (qPCR) based assay developed for human studies was adapted to cattle and delivered robust results (repeatability > 80%, coefficient of variation=0.05). Different DNA extraction methods were tested for their effect on RLTL measurements and it was demonstrated that fast silica based DNA extraction methods are suitable for telomere projects which can improve the sample throughput and enable large-scale projects. Subsequently, RLTL in 1328 whole blood samples of 308 Holstein Friesian dairy cows and additionally in 284 whole blood samples of 38 female calves was measured. Repeatability and random regression models were used for the statistical analysis of telomere data. RLTL decreased considerably within the first year of life, but remained relatively stable afterwards at population level. Animals varied significantly in their amount and direction of telomere change. The genetic correlation between consecutive measurements in the same individual weakened with increasing sample interval from r=1 to r=0.69 which indicates that TL in the beginning of life might be under a different genetic control than TL later in life. For the first time in a livestock species we calculated heritability estimates for RLTL which were high (0.32-0.38) and remained constant over life. Long telomeres at birth were not predictive of better productive lifespan. However, animals with long RLTL at the ages of one and five years had a survival advantage. Also, animals that showed less average RLTL attrition over their lives remained in production for longer. TL dynamics differed among individuals and a considerable subset of individuals demonstrated telomere lengthening between consecutive measurements. On average, telomeres tend to shorten early in life and then remain relatively constant. While TL is a heritable trait throughout lifetime, telomere change is not heritable. Short TL at specific ages and telomere attrition over life were associated with poorer productive lifespan

User experience driven CPU frequency scaling on mobile devices towards better energy efficiency

With the development of modern smartphones, mobile devices have become ubiquitous in our daily lives. With high processing capabilities and a vast number of applications, users now need them for both business and personal tasks. Unfortunately, battery technology did not scale with the same speed as computational power. Hence, modern smartphone batteries often last for less than a day before they need to be recharged. One of the most power hungry components is the central processing unit (CPU). Multiple techniques are applied to reduce CPU energy consumption. Among them is dynamic voltage and frequency scaling (DVFS). This technique reduces energy consumption by dynamically changing CPU supply voltage depending on the currently running workload. Reducing voltage, however, also makes it necessary to reduce the clock frequency, which can have a significant impact on task performance. Current DVFS algorithms deliver a good user experience, however, as experiments conducted later in this thesis will show, they do not deliver an optimal energy efficiency for an interactive mobile workload. This thesis presents methods and tools to determine where energy can be saved during mobile workload execution when using DVFS. Furthermore, an improved DVFS technique is developed that achieves a higher energy efficiency than the current standard. One important question when developing a DVFS technique is: How much can you slow down a task to save energy before the negative effect on performance becomes intolerable? The ultimate goal when optimising a mobile system is to provide a high quality of experience (QOE) to the end user. In that context, task slowdowns become intolerable when they have a perceptible effect on QOE. Experiments conducted in this thesis answer this question by identifying workload periods in which performance changes are directly perceptible by the end user and periods where they are imperceptible, namely interaction lags and interaction idle periods. Interaction lags are the time it takes the system to process a user interaction and display a corresponding response. Idle periods are the periods between interactions where the user perceives the system as idle and ready for the next input. By knowing where those periods are and how they are affected by frequency changes, a more energy efficient DVFS governor can be developed. This thesis begins by introducing a methodology that measures the duration of interaction lags as perceived by the user. It uses them as an indicator to benchmark the quality of experience for a workload execution. A representative benchmark workload is generated comprising 190 minutes of interactions collected from real users. In conjunction with this QOE benchmark, a DVFS Oracle study is conducted. It is able to find a frequency profile for an interactive mobile workload which has the maximum energy savings achievable without a perceptible performance impact on the user. The developed Oracle performance profile achieves a QOE which is indistinguishable from always running on the fastest frequency while needing 45% less energy. Furthermore, this Oracle is used as a baseline to evaluate how well current mobile frequency governors are performing. It shows that none of these governors perform particularly well and up to 32% energy savings are possible. Equipped with a benchmark and an optimisation baseline, a user perception aware DVFS technique is developed in the second part of this thesis. Initially, a runtime heuristic is introduced which is able to detect interaction lags as the user would perceive them. Using this heuristic, a reinforcement learning driven governor is developed which is able to learn good frequency settings for interaction lag and idle periods based on sample observations. It consumes up to 22% less energy than current standard governors on mobile devices, and maintains a low impact on QOE

Overview of the SPMRL 2013 Shared Task: A Cross-Framework Evaluation of Parsing Morphologically Rich Languages

International audienceThis paper reports on the first shared task on statistical parsing of morphologically rich lan- guages (MRLs). The task features data sets from nine languages, each available both in constituency and dependency annotation. We report on the preparation of the data sets, on the proposed parsing scenarios, and on the eval- uation metrics for parsing MRLs given dif- ferent representation types. We present and analyze parsing results obtained by the task participants, and then provide an analysis and comparison of the parsers across languages and frameworks, reported for gold input as well as more realistic parsing scenarios