Sentence context prevails over word association in aphasia patients with spared comprehension : evidence from N400 event-related potential

Behavioral and event-related potential (ERP) studies on aphasia patients showed that lexical information is not lost but rather its integration into the working context is hampered. Studies have been conducted on the processing of sentence-level information (meaningful versus meaningless) and of word-level information (related versus unrelated) in aphasia patients, but we are not aware of any study that assesses the relationship between the two. In healthy subjects the processing of a single word in a sentence context has been studied using the N400 ERP. It was shown that, even when there is only a weak expectation of a final word in a sentence, this expectation will dominate word relatedness. In order to study the effect of semantic relatedness between words in sentence processing in aphasia patients, we conducted a crossed design ERP study, crossing the factors of word relatedness and sentence congruity. We tested aphasia patients with mild to minimum comprehension deficit and healthy young and older (age-matched with our patients) controls on a semantic anomaly judgment task when simultaneously recording EEG. Our results show that our aphasia patient's N400 amplitudes in response to the sentences of our crossed-design study were similar to those of our age-matched healthy subjects. However, we detected an increase in the N400 ERP latency in those patients, indicating a delay in the integration of the new word into the working context. Additionally, we observed a positive correlation between comprehension level of those patients and N400 effect in response to meaningful sentences without word relatedness contrasted to meaningless sentences without word relatedness

Diversity of Listeria monocytogenes strains of clinical and food chain origins in Belgium between 1985 and 2014

Listeriosis is a rare but severe disease, mainly caused by Listeria monocytogenes. This study shows the results of the laboratory-based surveillance of Listeriosis in Belgium over the period 1985-2014. Besides the incidence and some demographic data we present also more detailed microbiological and molecular characteristics of human strains isolated since 2000. The strains from the latter period were compared to food and animal strains from the same period. Our study shows that different food matrices were commonly contaminated with L. monocytogenes presenting the same PFGE profile as in patient's isolates. Since 1985, we observed a significant decrease in incidence of the Materno-Neonatal cases (from 0.15 to 0.04 cases /100,000 inhabitants-year), which is probably to be attributed to active prevention campaigns targeting pregnant women. Despite the strengthening of different control measures by the food industry, the incidence of non-Materno-Neonatal listeriosis increased in Belgium (from 0.3 to 0.7 cases /100,000 inhabitants-year), probably due to the rise of highly susceptible patients in an aging population. This significant increase found in non-Materno-Neonatal cases (slope coefficient 7.42%/year, P< 0.0001) can be attributed to significant increase in incidence of isolates belonging to serovars 1/2a (n = 393, slope coefficient 6.62%/year, P< 0.0001). Although resistance to antimicrobials is rare among L. monocytogenes isolates, a trend to increasing MIC values is evident with chloramphenicol, amoxicillin, tetracycline and ciprofloxacin. We show that fluoroquinolone resistance is not linked to chromosomal mutations, but caused by a variety of efflux pumps. Our study also shows that huge majority of known underlying pathologies (426 out of 785 cases) were cancers (185/426, 43.1%) and haematological malignancies (75/185, 40.5%). Moreover the risk population is susceptible to low levels of contamination in food stressing the need of prevention campaigns specifically targeting these persons

Mobile phone indicators and their relation to the socioeconomic organisation of cities

Thanks to the use of geolocated big data in computational social science research, the spatial and temporal heterogeneity of human activities is increasingly being revealed. Paired with smaller and more traditional data, this opens new ways of understanding how people act and move, and how these movements crystallise into the structural patterns observed by censuses. In this article we explore the convergence between mobile phone data and more traditional socioeconomic data from the national census in French cities. We extract mobile phone indicators from six months worth of Call Detail Records (CDR) data, while census and administrative data are used to characterize the socioeconomic organisation of French cities. We address various definitions of cities and investigate how they impact the statistical relationships between mobile phone indicators, such as the number of calls or the entropy of visited cell towers, and measures of economic organisation based on census data, such as the level of deprivation, inequality and segregation. Our findings show that some mobile phone indicators relate significantly with different socioeconomic organisation of cities. However, we show that relations are sensitive to the way cities are defined and delineated. In several cases, changing the city delineation rule can change the significance and even the sign of the correlation. In general, cities delineated in a restricted way (central cores only) exhibit traces of human activity which are less related to their socioeconomic organisation than cities delineated as metropolitan areas and dispersed urban regions

Detecting Home Locations from CDR Data: Introducing Spatial Uncertainty to the State-of-the-Art

Non-continuous location traces inferred from Call Detail Records (CDR) at population scale are increasingly becoming available for research and show great potential for automated detection of meaningful places. Yet, a majority of Home Detection Algorithms (HDAs) suffer from “blind” deployment of criteria to define homes and from limited possibilities for validation. In this paper, we investigate the performance and capabilities of five popular criteria for home detection based on a very large mobile phone dataset from France (~18 million users, 6 months). Furthermore, we construct a data-driven framework to assess the spatial uncertainty related to the application of HDAs. Our findings appropriate spatial uncertainty in HDA and, in extension, for detection of meaningful places. We show how spatial uncertainties on the individuals’ level can be assessed in absence of ground truth annotation, how they relate to traditional, high-level validation practices and how they can be used to improve results for, e.g., nation-wide population estimation

Specializing Interpreters using Offline Partial Deduction

We present the latest version of the Logen partial evaluation system for logic programs. In particular we present new binding-types, and show how they can be used to effectively specialise a wide variety of interpreters.We show how to achieve Jones-optimality in a systematic way for several interpreters. Finally, we present and specialise a non-trivial interpreter for a small functional programming language. Experimental results are also presented, highlighting that the Logen system can be a good basis for generating compilers for high-level languages

Too Afraid to Learn: Attitudes towards Statistics as a Barrier to Learning Statistics and to Acquiring Quantitative Skills

Quantitative skills are important for studying and understanding social reality. Political science students, however, experience difficulties in acquiring and retaining such skills. Fear of statistics has often been listed among the major causes for this problem. This study aims at understanding the underlying factors for this anxiety and proposes a potential remedy. More specifically, we advocate the integration of quantitative material into non-methodological courses. After assessing the influence of dispositional, course-related and person-related factors on the attitudes towards statistics among political science students, we provide insights into the relation between these attitudes on the one hand and the learning and retention of statistics skills on the other. Our results indicate that a curriculum-wide approach to normalise the use of quantitative methods can not only foster interest in statistics but also foster retention of the acquired skills

Physical Conditions in Barnard\u27s Loop, Components of the Orion-Eridanus Bubble, and Implications for the Warm Ionized Medium Component of the Interstellar Medium

We have supplemented existing spectra of Barnard\u27s Loop with high accuracy spectrophotometry of one new position. Cloudy photoionization models were calculated for a variety of ionization parameters and stellar temperatures and compared with the observations. After testing the procedure with recent observations of M43, we establish that Barnard\u27s Loop is photoionized by four candidate ionizing stars, but agreement between the models and observations is only possible if Barnard\u27s Loop is enhanced in heavy elements by about a factor of 1.4. Barnard\u27s Loop is very similar in properties to the brightest components of the Orion-Eridanus Bubble and the warm ionized medium (WIM). We are able to establish models that bound the range populated in low-ionization color-color diagrams (I([S II])/I(Hα) versus I([N II])/I(Hα)) using only a limited range of ionization parameters and stellar temperatures. Previously established variations in the relative abundance of heavy elements render uncertain the most common method of determining electron temperatures for components of the Orion-Eridanus Bubble and the WIM based only on the I([N II])/I(Hα) ratio, although we confirm that the lowest surface brightness components of the WIM are on average of higher electron temperature. The electron temperatures for a few high surface brightness WIM components determined by direct methods are comparable to those of classical bright H II regions. In contrast, the low surface brightness H II regions studied by the Wisconsin Hα Mapper are of lower temperatures than the classical bright H II regions

Closer to the total? Long-distance travel of French mobile phone users

Analyzing long-distance travel demand has become increasingly relevant because the share of traffic induced by journeys related to remote activities which are not part of daily life is growing. In today’s mobile world, such journeys are responsible for almost 50 percent of all traffic. Traditionally, surveys have been used to gather data needed to analyze travel demand. Due to the high response burden and memory issues, respondents are known to underreport their number of long-distance journeys. The question of the actual number of long-distance journeys therefore remains unanswered without additional data sources. This paper is the first to quantify the underreporting of long-distance tour frequencies in travel diaries. We took a sample of mobile phone billing data covering five months and compared the observed long-distance travel with the results of a national travel survey covering the same period and the same country. The comparison shows that most of the estimates of the number of missing tours by researchers have thus been too low. Our work suggests that the actual number of longdistance journeys is twice as high as that reported in surveys. Two different causes of underreporting were identified. Firstly, soft refusers travelled long distances but reported no long-distance tours. Secondly, respondents underestimated their number of long-distance tours. Consequently, there is a need to use alternative data sources in order to gain better estimates of long-distance travel demand