Broadly speaking: vocabulary in semantic dementia shifts towards general, semantically diverse words

One of the cardinal features of semantic dementia (SD) is a steady reduction in expressive vocabulary. We investigated the nature of this breakdown by assessing the psycholinguistic characteristics of words produced spontaneously by SD patients during an autobiographical memory interview. Speech was analysed with respect to frequency and imageability, and a recently-developed measure called semantic diversity. This measure quantifies the degree to which a word can be used in a broad range of different linguistic contexts. We used this measure in a formal exploration of the tendency for SD patients to replace specific terms with more vague and general words, on the assumption that more specific words are used in a more constrained set of contexts. Relative to healthy controls, patients were less likely to produce low-frequency, high-imageability words, and more likely to produce highly frequent, abstract words. These changes in the lexical-semantic landscape were related to semantic diversity: the highly frequent and abstract words most prevalent in the patients' speech were also the most semantically diverse. In fact, when the speech samples of healthy controls were artificially engineered such that low semantic diversity words (e.g., garage, spanner) were replaced with broader terms (e.g., place, thing), the characteristics of their speech production came to closely resemble that of SD patients. A similar simulation in which low-frequency words were replaced was less successful in replicating the patient data. These findings indicate systematic biases in the deterioration of lexical-semantic space in SD. As conceptual knowledge degrades, speech increasingly consists of general terms that can be applied in a broad range of linguistic contexts and convey less specific information.

Macroeconomic forecasting with mixed-frequency data: forecasting output growth in the United States

Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way to exploit monthly data compared with alternative methods.

Improved MATLAB GUIs for learning frequency response methods

The author developed two GUIs for asymptotic Bode plots and identification from such plots aimed at improving the learning of frequency response methods: these were presented at UKACC Control 2012. Student feedback and reflection by the author suggested various improvements to these GUIs, which have now been implemented. This paper reviews the earlier work, describes the improvements, and includes positive feedback from the students on the GUIs and how they have helped their understanding of the methods.

Late Quaternary highstands at Lake Chilwa, Malawi: frequency, timing and possible forcing mechanisms in the last 44ka

The extensive shoreline deposits of Lake Chilwa, southern Malawi, a shallow water body today covering 600 km2 of a basin of 7500 km2, are investigated for their record of late Quaternary highstands. OSL dating, applied to 36 samples from five sediment cores from the northern and western marginal sand ridges, reveal a highstand record spanning 44 ka. Using two different grouping methods, highstand phases are identified at 43.7–33.3 ka, 26.2–21.0 ka and 17.9–12.0 ka (total error method) or 38.4–35.5 ka, 24.3–22.3 ka, 16.2–15.1 ka and 13.5–12.7 ka (Finite Mixture Model age components) with two further discrete events recorded at 11.01 ± 0.76 ka and 8.52 ± 0.56 ka. Highstands are comparable to the timing of wet phases from other basins in East and southern Africa, demonstrating wet conditions in the region before the LGM, which was dry, and a wet Lateglacial, which commenced earlier in the southern compared to northern hemisphere in East Africa. We find no evidence that wet phases are insolation driven, but analysis of the dataset and GCM modelling experiments suggest that Heinrich events may be associated with enhanced monsoon activity in East Africa in both timing and as a possible causal mechanism.

On the F-word: a corpus-based analysis of the media representation of Feminism in British and German press discourse,1990-2009

Research in social psychology has shown that public attitudes towards feminism are mostly based on stereotypical views linking feminism with leftist politics and lesbian orientation. It is claimed that such attitudes are due to the negative and sexualised media construction of feminism. Studies concerned with the media representation of feminism seem to confirm this tendency. While most of this research provides significant insights into the representation of feminism, the findings are often based on a small sample of texts. Also, most of the research was conducted in an Anglo-American setting. This study attempts to address some of the shortcomings of previous work by examining the discourse of feminism in a large corpus of German and British newspaper data. It does so by employing the tools of Corpus Linguistics. By investigating the collocation profiles of the search term feminism, we provide evidence of salient discourse patterns surrounding feminism in two different cultural contexts.

Drivers of in-group and out-of-group electronic word-of-mouth (eWOM)

Purpose – The purpose of this study is to address a recent call for additional research on electronic word-of-mouth (eWOM). In response to this call, this study draws on the social network paradigm and the uses and gratification theory (UGT) to propose and empirically test a conceptual framework of key drivers of two types of eWOM, namely in-group and out-of-group. Design/methodology/approach – The proposed model, which examines the impact of usage motivations on eWOM in-group and eWOM out-of-group, is tested in a sample of 302 internet users in Portugal. Findings – Results from the survey show that the different drivers (i.e. mood-enhancement, escapism, experiential learning and social interaction) vary in terms of their impact on the two different types of eWOM. Surprisingly, while results show a positive relationship between experiential learning and eWOM out-of-group, no relationship is found between experiential learning and eWOM in-group. Research limitations/implications – This is the first study investigating the drivers of both eWOM in-group and eWOM out-of-group. Additional research in this area will contribute to the development of a general theory of eWOM. Practical implications – By understanding the drivers of different eWOM types, this study provides guidance to marketing managers on how to allocate resources more efficiently in order to achieve the company's strategic objectives. Originality/value – No published study has investigated the determinants of these two types of eWOM. This is the first study offering empirical considerations of how the various drivers differentially impact eWOM in-group and eWOM out-of-group.

Morphological decomposition in Broca's aphasia

Background: Few studies have investigated how individuals diagnosed with post-stroke Broca’s aphasia decompose words into their constituent morphemes in real-time processing. Previous research has focused on morphologically complex words in non-time-constrained settings or in syntactic frames, but not in the lexicon. Aims: We examined real-time processing of morphologically complex words in a group of five Greek-speaking individuals with Broca’s aphasia to determine: (1) whether their morphological decomposition mechanisms are sensitive to lexical (orthography and frequency) vs. morphological (stem-suffix combinatory features) factors during visual word recognition, (2) whether these mechanisms are different in inflected vs. derived forms during lexical access, and (3) whether there is a preferred unit of lexical access (syllables vs. morphemes) for inflected vs. derived forms. Methods & Procedures: The study included two real-time experiments. The first was a semantic judgment task necessitating participants’ categorical judgments for high- and low-frequency inflected real words and pseudohomophones of the real words created by either an orthographic error at the stem or a homophonous (but incorrect) inflectional suffix. The second experiment was a letter-priming task at the syllabic or morphemic boundary of morphologically transparent inflected and derived words whose stems and suffixes were matched for length, lemma and surface frequency. Outcomes & Results: The majority of the individuals with Broca’s aphasia were sensitive to lexical frequency and stem orthography, while ignoring the morphological combinatory information encoded in the inflectional suffix that control participants were sensitive to. The letter-priming task, on the other hand, showed that individuals with aphasia—in contrast to controls—showed preferences with regard to the unit of lexical access, i.e., they were overall faster on syllabically than morphemically parsed words and their morphological decomposition mechanisms for inflected and derived forms were modulated by the unit of lexical access. Conclusions: Our results show that in morphological processing, Greek-speaking persons with aphasia rely mainly on stem access and thus are only sensitive to orthographic violations of the stem morphemes, but not to illegal morphological combinations of stems and suffixes. This possibly indicates an intact orthographic lexicon but deficient morphological decomposition mechanisms, possibly stemming from an underspecification of inflectional suffixes in the participants’ grammar. Syllabic information, however, appears to facilitate lexical access and elicits repair mechanisms that compensate for deviant morphological parsing procedures.

Evaluating interval forecasts of high-frequency financial data

A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing interval forecast evaluation techniques, such as the Markov chain approach of Christoffersen (1998), are shown to be inappropriate in the presence of periodic heteroscedasticity. Instead, we consider a regression-based test, and a modified version of Christoffersen's Markov chain test for independence, and analyse their properties when the financial time series exhibit periodic volatility. These approaches lead to different conclusions when interval forecasts of FTSE100 index futures returns generated by various GARCH(1,1) and periodic GARCH(1,1) models are evaluated.

The water quality of the River Enborne, UK: observations from high-frequency Monitoring in a rural, lowland river system

This paper reports the results of a 2-year study of water quality in the River Enborne, a rural river in lowland England. Concentrations of nitrogen and phosphorus species and other chemical determinands were monitored both at high-frequency (hourly), using automated in situ instrumentation, and by manual weekly sampling and laboratory analysis. The catchment land use is largely agricultural, with a population density of 123 persons km−2. The river water is largely derived from calcareous groundwater, and there are high nitrogen and phosphorus concentrations. Agricultural fertiliser is the dominant source of annual loads of both nitrogen and phosphorus. However, the data show that sewage effluent discharges have a disproportionate effect on the river nitrogen and phosphorus dynamics. At least 38% of the catchment population use septic tank systems, but the effects are hard to quantify as only 6% are officially registered, and the characteristics of the others are unknown. Only 4% of the phosphorus input and 9% of the nitrogen input is exported from the catchment by the river, highlighting the importance of catchment process understanding in predicting nutrient concentrations. High-frequency monitoring will be a key to developing this vital process understanding.

Testing the Revised Hierarchical Model: evidence from word associations

The main purpose of the work described in this paper is to examine the extent to which the L2 developmental changes predicted by Kroll and Stewart's (1994) Revised Hierarchical Model (RHM) can be understood by word association response behaviour. The RHM attempts to account for the relative “strength of the links between words and concepts in each of the bilingual's languages” (Kroll, Van Hell, Tokowicz & Green, 2010, p. 373). It proposes that bilinguals with higher L2 proficiency tend to rely less on mediation, while less proficient L2 learners tend to rely on mediation and access L2 words by translating from L1 equivalents. In this paper, I present findings from a simple word association task. More proficient learners provided a greater proportion of collocational links, suggesting that they mediate less when compared to less proficient learners. The results provide tentative support for Kroll and Stewart's model

A word of caution on calculating market-based minimum capital risk requirements

This paper demonstrates that the use of GARCH-type models for the calculation of minimum capital risk requirements (MCRRs) may lead to the production of inaccurate and therefore inefficient capital requirements. We show that this inaccuracy stems from the fact that GARCH models typically overstate the degree of persistence in return volatility. A simple modification to the model is found to improve the accuracy of MCRR estimates in both back- and out-of-sample tests. Given that internal risk management models are currently in widespread usage in some parts of the world (most notably the USA), and will soon be permitted for EC banks and investment firms, we believe that our paper should serve as a valuable caution to risk management practitioners who are using, or intend to use this popular class of models.

Linear and non-linear (non-)forecastability of high-frequency exchange rates

This paper forecasts Daily Sterling exchange rate returns using various naive, linear and non-linear univariate time-series models. The accuracy of the forecasts is evaluated using mean squared error and sign prediction criteria. These show only a very modest improvement over forecasts generated by a random walk model. The Pesaran–Timmerman test and a comparison with forecasts generated artificially shows that even the best models have no evidence of market timing ability.