John Terrane: A Study of a First World War Revisionist

Of all the British military historians who started writing about the First World War during the boom of the sixties, perhaps no one has had greater influence or generated more controversy than John Alfred Terraine. As G.F. Elliot wrote in a 1965 review, John Terraine is one of the younger generation of British military analysts who are now proving, with brilliance and vigour, the value of the long view in putting World War I in proper perspective. It is this idea of perspective, trying to bring balance to the historical arguments concerning the British contribution to the First World War, that drove John Terraine in all his work. Terraine\u27s nine books on the British Expeditionary Force challenged the comfortable mainstream theories and assumptions, defended the generals, and debunked the myths. His opinions gave him both notoreity and influence

Investigating effects of emoji on neutral narrative text: evidence from eye movements and perceived emotional valence

Digital images of faces such as emoji in virtual communication have become increasingly popular, but current research findings are inconsistent regarding their emotional effects on perceptions of text. Similarly, emoji effects on reading behaviours are largely unknown and require further examination. The present study (N = 41) investigated how the position and emotional valence of emoji in neutral narrative sentences influenced eye movements during reading and perceptions of sentence valence. Participants read neutral narrative sentences containing smiling or frowning emoji in sentence-initial or sentence-final positions and rated the perceived emotional valence of the sentence. Results from linear mixed-effects models demonstrated significantly longer fixations on sentence-final emoji and longer sentence reading times when emoji were in sentence-final positions. These findings are comparable to sentence ‘wrap-up’ effects witnessed in the processing of lexical units during sentence reading, providing new evidence towards the way readers integrate emoji into contextual processing. However, no impact of emoji valence or position on first-pass target word processing or sentence-valence ratings were found. This would refute previous suggestions that digital faces influence text valence, raising questions about reader preference for emoji or sentence sentiment, the influence of sentence formatting, and delivery/display mechanism on these effects

Biases in Multi-Year Management Financial Forecasts: Evidence From Private Venture-Backed U.S. Companies

This paper studies the properties and determinants of managers’ multi-year financial forecasts. Using one- to five-year-ahead forecasts reported by private venture-backed firms, we ask whether, by how much, and why biases in managers’ forecasts of revenues, expenses and profits depend on the forecasting horizon and the verifiability of assets. We find that profitability forecasts contain a strategic component, in that [1] one-year-ahead revenue (expense) forecasts are slightly and asymmetrically pessimistic (optimistic), while five-year-ahead forecasts are hugely and asymmetrically optimistic (pessimistic); and [2] biases in revenue and expense forecasts are larger, the harder to verify or more intangible-intensive are firms’ assets

Market-to-Revenue Multiples in Public and Private Capital Markets

The behavior and determinants of market-to-revenue ratios in public and private capital markets is examined. Three samples are analysed: (1) all publicly traded stocks listed at some time on the New York Stock Exchange/American Stock Exchange/National Association of Securities Dealers Automated Quotation System in the 1980—2004 period; (2) sample of over 300 so-called ‘internet companies’ in the 1996—2004 period; and (3) over 5500 privately held venture capital-backed companies in the 1992—2004 period. Both company size and the most recent revenue growth rate are found to explain significant variation across companies in their market-to-revenue multiples — smaller companies and companies with higher recent revenue growth rates have higher multiples. We also document how the capital market appears to use a broad-based information set when setting market-to-revenue multiples for companies with negative revenue growth rates — transitory revenue growth components appear to be identified (in a probabilistic sense) by the capital market. Contrary to much anecdotal comment, we present evidence that the capital market behaved directionally along the lines predicted by capital market theory in the pricing of internet stocks in the 1996—2004 period

Exploring the measurement of markedness and its relationship with other linguistic variables

Antonym pair members can be differentiated by each word's markedness-that distinction attributable to the presence or absence of features at morphological or semantic levels. Morphologically marked words incorporate their unmarked counterpart with additional morphs (e.g., "unlucky" vs. "lucky"); properties used to determine semantically marked words (e.g., "short" vs. "long") are less clearly defined. Despite extensive theoretical scrutiny, the lexical properties of markedness have received scant empirical study. The current paper employs an antonym sequencing approach to measure markedness: establishing markedness probabilities for individual words and evaluating their relationship with other lexical properties (e.g., length, frequency, valence). Regression analyses reveal that markedness probability is, as predicted, related to affixation and also strongly related to valence. Our results support the suggestion that antonym sequence is reflected in discourse, and further analysis demonstrates that markedness probabilities, derived from the antonym sequencing task, reflect the ordering of antonyms within natural language. In line with the Pollyanna Hypothesis, we argue that markedness is closely related to valence; language users demonstrate a tendency to present words evaluated positively ahead of those evaluated negatively if given the choice. Future research should consider the relationship of markedness and valence, and the influence of contextual information in determining which member of an antonym pair is marked or unmarked within discourse

The synthesis and analysis of lignin-bound Hibbert ketone structures in technical lignins

This work was supported by EPSRC Ph.D. studentships (EP/1518175 (DMB), EP/1517938 (AN)), the Industrial Biotechnology Innovation Centre (Ph.D. studentship to DMB), CRITICAT Centre for Doctoral Training (Ph.D. studentship to IP; EP/L016419/1), EPSRC grants EP/J018139/1 and EP/K00445X/1 (SOJO) and an EPSRC Doctoral Prize Fellowship (CSL).Understanding the structure of technical lignins resulting from acid-catalysed treatment of lignocellulosic biomass is important for their future applications. Here we report an investigation into the fate of lignin under acidic aqueous organosolv conditions. In particular we examine in detail the formation and reactivity of non-native Hibbert ketone structures found in isolated organosolv lignins from both Douglas fir and beech woods. Through the use of model compounds combined with HSQC, HMBC and HSQC-TOCSY NMR experiments we demonstrate that, depending on the lignin source, both S and G lignin-bound Hibbert ketone units can be present. We also show that these units can serve as a source of novel mono-aromatic compounds following an additional lignin depolymerisation reaction.PostprintPeer reviewe

Spinning dust emission: the effect of rotation around a non-principal axis

We investigate the rotational emission from dust grains that rotate around non- principal axes. We argue that in many phases of the interstellar medium, the smallest grains, which dominate spinning dust emission, are likely to have their nutation state (orientation of principal axes relative to the angular momentum vector) randomized during each thermal spike. We recompute the excitation and damping rates associated with rotational emission from the grain permanent dipole, grain-plasma interactions, infrared photon emission, and collisions. The resulting spinning dust spectra gener- ally show a shift toward higher emissivities and peak frequencies relative to previous calculations.Comment: Version accepted for publication in MNRAS. The derivation of the emission spectrum was clarified. The companion code, SPDUST.2, can be downloaded from http://www.tapir.caltech.edu/~yacine/spdust/spdust.htm

Excess Dietary Sugar Alters Colonocyte Metabolism and Impairs the Proliferative Response to Damage

Background & Aims The colonic epithelium requires continuous renewal by crypt resident intestinal stem cells (ISCs) and transit-amplifying (TA) cells to maintain barrier integrity, especially after inflammatory damage. The diet of high-income countries contains increasing amounts of sugar, such as sucrose. ISCs and TA cells are sensitive to dietary metabolites, but whether excess sugar affects their function directly is unknown. Methods Here, we used a combination of 3-dimensional colonoids and a mouse model of colon damage/repair (dextran sodium sulfate colitis) to show the direct effect of sugar on the transcriptional, metabolic, and regenerative functions of crypt ISCs and TA cells. Results We show that high-sugar conditions directly limit murine and human colonoid development, which is associated with a reduction in the expression of proliferative genes, adenosine triphosphate levels, and the accumulation of pyruvate. Treatment of colonoids with dichloroacetate, which forces pyruvate into the tricarboxylic acid cycle, restored their growth. In concert, dextran sodium sulfate treatment of mice fed a high-sugar diet led to massive irreparable damage that was independent of the colonic microbiota and its metabolites. Analyses on crypt cells from high-sucrose–fed mice showed a reduction in the expression of ISC genes, impeded proliferative potential, and increased glycolytic potential without a commensurate increase in aerobic respiration. Conclusions Taken together, our results indicate that short-term, excess dietary sucrose can directly modulate intestinal crypt cell metabolism and inhibit ISC/TA cell regenerative proliferation. This knowledge may inform diets that better support the treatment of acute intestinal injury

Global and Regional Trends of Atmospheric Sulfur

The profound changes in global SO[subscript 2] emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and europe. europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and east Asia. the uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a decrease, while in India a steady increase over the whole period has been observed and modelled. the agreement between a bottom-up approach, which uses emissions and process-based chemical transport models, with independent observations gives an improved confidence in the understanding of the atmospheric sulfur budget

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases