Based on two syntactically annotated corpora, and within the theoretical tradition of dependency grammar, the current study investigates the quantitative differences and similarities between written and spoken French. Our findings support the assumption that spoken and written French are two realizations of one language that do not differ in the syntactic categories, but in the frequency of these categories, and also in their organization in sentence. The subjects in spoken French are mostly pronouns, whereas in written French the subjects are mostly nouns and pronouns. Spoken and written French share many syntactic relations, but with different frequencies. For instance, dislocations are more diverse and frequent in spoken French. Spoken French and written French differ in the word order of vocative nominal phrases. Finally, written French is slightly more difficult to process than spoken French.

The impact of greenhouse gas (GHG) reduction on the efficiency of Alberta’s dairy industry is assessed through a technical efficiency analysis over the period 1996–2016, with and without emissions included as a “bad” output. Environmentally adjusted technical efficiency and technical efficiency estimates are highly correlated; thus, reducing GHG emissions may not result in decreased efficiency. Increased milk per cow, a southern Alberta location, and increased use of forage are associated with greater environmentally adjusted technical efficiency. The opportunity cost of foregone milk revenue associated with reduced emissions is Can$308.29 per metric ton of GHG. The results imply possible policy strategies to reduce emissions.

In the literature, there have been several methods and definitions for working out whether two theories are “equivalent” (essentially the same) or not. In this article, we do something subtler. We provide a means to measure distances (and explore connections) between formal theories. We introduce two natural notions for such distances. The first one is that of axiomatic distance, but we argue that it might be of limited interest. The more interesting and widely applicable notion is that of conceptual distance which measures the minimum number of concepts that distinguish two theories. For instance, we use conceptual distance to show that relativistic and classical kinematics are distinguished by one concept only.

Why are some voters less likely to align with their group when group-based voting is both the norm and advantageous? I argue that the answer to this question can be found in the extent to which individuals are apparently consistent with the prototypical individual in their group. I develop a concept of racial distance, which improves upon the in-group out-group focus of the race and ethnic politics literature. Empirically, I investigate this relationship in South Africa using an original panel survey, which brackets the 2014 national elections. I find that those who are not readily identified as members of their group are less likely to vote with their group and more likely to change their vote due to an election campaign. Analyzing data from the South Africa 2016 the US 2012 elections suggests that this relationship holds for racial majorities but only minorities with a relatively weak sense of solidarity.

We show that several machine learning estimators, including square-root least absolute shrinkage and selection and regularized logistic regression, can be represented as solutions to distributionally robust optimization problems. The associated uncertainty regions are based on suitably defined Wasserstein distances. Hence, our representations allow us to view regularization as a result of introducing an artificial adversary that perturbs the empirical distribution to account for out-of-sample effects in loss estimation. In addition, we introduce RWPI (robust Wasserstein profile inference), a novel inference methodology which extends the use of methods inspired by empirical likelihood to the setting of optimal transport costs (of which Wasserstein distances are a particular case). We use RWPI to show how to optimally select the size of uncertainty regions, and as a consequence we are able to choose regularization parameters for these machine learning estimators without the use of cross validation. Numerical experiments are also given to validate our theoretical findings.

The Low Countries' Early Iron Age is marked by the emergence of lavish burials known as chieftains’ graves or princely burials. These extraordinary elite burials of the Hallstatt C/D period contain weaponry, bronze vessels as well as decorated wagons and horse-gear imported from the Hallstatt culture of Central Europe, where the same objects are found in the famous Fürstengräber. While the connection between these regions has long been recognized, the nature of this contact remains poorly understood. Here we present the preliminary results of an on-going re-examination of elite funerary practices in both regions and the likely direct long-distance interactions reflected in them. Similarities and differences in the treatment of objects and the dead in funerary rituals indicate that, to a certain extent at least, these geographically separated social groups were integrated in a specific elite burial practice, indicating frequent contact across hundreds of kilometres.

Grain boundaries (GBs) play an important role in material behavior, so considerable effort has gone into determining their structure and properties. Studies of GBs have revealed a correlation between the GB energy and expansion of the planes normal to the GB, or the so-called normal volume expansion. In this investigation, the volume expansion at several GBs was experimentally determined using extended energy-loss fine structure (EXELFS) analysis in a scanning/transmission electron microscope, allowing changes in the nearest-neighbor (n.n.) distances to be determined with nanometer spatial resolution. EXELFS performed on three-model GBs showed that the average n.n. distances at the GBs increased with increasing GB energy. Additionally, the total volume expansion at the GBs, calculated using complementary plasmon energy profiles, showed excellent agreement with volume expansions measured using other experimental techniques. Hence, this study demonstrates that EXELFS is a useful technique to measure the normal volume expansion at GBs. When combined with the results from complementary studies on the same GBs using valence electron energy-loss spectroscopy, this work further shows that the GB energy increases in relation to both the decrease in electron density at the GB and an accompanying increase in specific volume expansion at the GB.

Can children tell how different a speaker's accent is from their own? In Experiment 1 (N = 84), four- and five-year-olds heard speakers with different accents and indicated where they thought each speaker lived relative to a reference point on a map that represented their current location. Five-year-olds generally placed speakers with stronger accents (as judged by adults) at more distant locations than speakers with weaker accents. In contrast, four-year-olds did not show differences in where they placed speakers with different accents. In Experiment 2 (N = 56), the same sentences were low-pass filtered so that only prosodic information remained. This time, children judged which of five possible aliens had produced each utterance, given a reference speaker. Children of both ages showed differences in which alien they chose based on accent, and generally rated speakers with foreign accents as more different from their native accent than speakers with regional accents. Together, the findings show that preschoolers perceive accent distance, that children may be sensitive to the distinction between foreign and regional accents, and that preschoolers likely use prosody to differentiate among accents.

The classical Monge–Kantorovich (MK) problem as originally posed is concerned with how best to move a pile of soil or rubble to an excavation or fill with the least amount of work relative to some cost function. When the cost is given by the square of the Euclidean distance, one can define a metric on densities called the Wasserstein distance. In this note, we formulate a natural matrix counterpart of the MK problem for positive-definite density matrices. We prove a number of results about this metric including showing that it can be formulated as a convex optimisation problem, strong duality, an analogue of the Poincaré–Wirtinger inequality and a Lax–Hopf–Oleinik–type result.

Social media play an important role in emergency management. The location of citizens and distance from a disaster influence the social media usage patterns. Using the Tianjin Port Explosion, we apply the correlation analysis and regression analysis to explore the relationship between online engagement and location. Citizens’ online engagement is estimated by social media. Three dimensions of the psychological distance – spatial, temporal, and social distances – are applied to measure the effects of location and distance. Online engagement is negatively correlated to such 3 kinds of the distance, which indicates that citizens may pay less attention to a disaster that happens at a far away location and at an area of less interaction or at a relatively long period of time. Furthermore, a linear model is proposed to measure the psychological distance. The quantification relationship between online engagement and psychological distance is discussed. The result enhances our understanding of social media usage patterns related to location and distance. The study gives a new insight on situation awareness, decision-making during disasters.

In this paper we address the problem of coverage path planning (CPP) for multiple cooperating mobile robots. We use a ‘partition and cover’ approach using Voronoi partition to achieve natural passive cooperation between robots to avoid task duplicity. We combine two generalizations of Voronoi partition, namely geodesic-distance-based Voronoi partition and Manhattan-distance-based Voronoi partition, to address contiguity of partition in the presence of obstacles and to avoid partition-boundary-induced coverage gap. The region is divided into 2D×2D grids, where D is the size of the robot footprint. Individual robots can use any of the single-robot CPP algorithms. We show that with the proposed Geodesic-Manhattan Voronoi-partition-based coverage (GM-VPC), a complete and non-overlapping coverage can be achieved at grid level provided that the underlying single-robot CPP algorithm has similar property.We demonstrated using two representative single-robot coverage strategies, namely Boustrophedon-decomposition-based coverage and Spanning Tree coverage, first based on so-called exact cellular decomposition and second based on approximate cellular decomposition, that the proposed partitioning scheme completely eliminates coverage gaps and coverage overlaps. Simulation experiments using Matlab and V-rep robot simulator and experiments with Fire Bird V mobile robot are carried out to validate the proposed coverage strategy.