Delineating extravagance

DR Congo: investigational research against Ebola virus

In this paper we apply speech recognition for automatic transcript generation for spoken document retrieval. The transcripts are used to compute an index for an archive of historical speeches and to provide the index, speech, and transcripts available for query based retrieval and browsing. In addition to acoustic variability, the task is challenging, because it covers a broad spectrum of different speaking styles and use of language. Language modeling is important for speech recognition to determine the prior probabilities of the compared word and sentence candidates in decoding. Various large text corpora are available in electronic format for language model training, but the open question is what and how should we include to improve the audio transcripts of this task. In this work we compare large overall language models to focused ones trained on selected subsets of the data, and to combinations between both. With respect to the potential index terms, improvements were obtained for transcripts that did not fit well to the scope of the large overall language model.

This book explores a paradox. In a society in which justice is uncertain and contested, how can we talk meaningfully about miscarriage of justice? The book examines the structural conditions that inevitably produce high-profile miscarriages of justice. The thesis of the book is that there is a tension between the rhetoric of justice as understood outside of law, particularly in the media, and legal practice. Despite evidence that miscarriages of justice must be a normal and expected consequence of imperfect arrangements for investigations, prosecutions, and trials, they are ordinarily understood as exceptional and unacceptable events. Periodically, however, miscarriages are seen not as exceptional, but widespread and normal. At such moments, the legitimacy of the criminal justice process is called into question in the media. These moments are constructed in the media as a crisis of public confidence in criminal justice. With the mass media's vivid interest in crime and punishment and their relentless reconstruction of relevant facts, the courts fact-finding monopoly is fundamentally contested. While this happens in all phases of a criminal process, the contest becomes particularly dramatic when after a criminal conviction the mass media continue their investigation and discover, according to their criteria of truth, a miscarriage of justice. But there is no set of common criteria that would allow for the design of rational procedures to end the contest. There is no forum, no procedure, and no set of criteria that would make possible a common search for truth.

The present study investigates the functions that language learners attribute to the first language (L1) within a teaching context that maximizes the target language (TL). Beginners of French in an Australian university (N = 52) completed a questionnaire consisting of 21 closed questions on their views on L1/TL use and two open questions on the advantages/disadvantages of using the L1 in teaching and learning a language. Results confirm previous studies indicating that students attribute a function to L1 to impart knowledge about the TL medium. The particularities of the context may help explain other findings of the study. First, a majority of students showed a preference for the use of L1 to perform classroom management. Second, for respondents, L1 and TL have an impact on anxiety and motivation. While L1 use may alleviate classroom anxiety, it may also be a demotivating factor. This article calls for further research to examine the impact of the teaching context on students' views of L1/TL distribution.

Initial vs. non-initial placement of agent constructions in spoken clauses: A corpus-based study of language production under time pressure

First linguistic studies have paid attention to the influence of the current corona pandemic on language use in the German media coverage. They have revealed, amongst other things, that compounds beginning with corona are very productive and frequent. Against this background, the questions arise how frequent these compounds de facto are, what their morphological and graphematic characteristics look like, which second constituents can be observed, which semantic relations between the constituents exist and what their referents are. However, not only people being able to read texts in standard language need information concerning the pandemic; individuals lacking this capacity also need to know which rules apply to public life and social interaction. Therefore, information on the corona pandemic is also available in German Easy Language. But translators are faced with several dilemmas regarding the translation of compounds into Easy Language. It is thus an open question whether compounds beginning with corona, recently observed in the media coverage in standard language, also occur in the media coverage in Easy Language and, if present, what their characteristics are in comparison to the relevant compounds in standard language. An additional question is how the referents of compounds beginning with corona in standard language are designated in Easy Language in those cases where no comparable compound beginning with corona is used for this purpose. The present study uses a corpus linguistic approach to address these questions.

Though current researches of online collaboration often study the social relationship from an objective view, individuals’ subjective attitudes on their interrelationships are more important for collaboration. Inspired by sociolinguistic theories, the latest work indicates that individuals’ different attitudes on interrelationships can be measured by interactive language. However, it is still an open problem that what kind of factors influences our different attitudes on interrelationships. In this work, we investigate how individuals’ position i.e., the topological factors in social network influence the differences in our bidirectional attitudes on interrelationships. Measuring the attitudes with interactive language on Enron email dataset, we analyze the correlation between attitudes and the topological factors of email network. The results indicate that individuals’ differences in attitudes on interrelationships are related to some typical topological factors. These results inspire us to measure individuals’ attitude in online collaboration with their topological factors in social network.

Once severely rejected, first language (L1) use is no more considered to be inherently detrimental in foreign language pedagogy. Recent research within sociocultural framework has come up with numerous facilitative roles for L1 use (Anton and DiCamilla, 1999; Swain and Lapkin, 2000; Storch and Wigglesworth, 2003). Also, studies from humanistic perspectives that deal with the teachers’ and learners’ attitudes about L1 use report generally positive attitudes from both groups (Duff and Polio, 1990; Macaro, 2001). However, contrary to this bulk of theoretical and empirical support, there seems to have been an evident animosity towards L1 use in the Iranian private English language institutes. The present research was therefore designed to delve deeper into the apparent discrepancy between theory and practice in this regard by identifying some contextual constraints on the teachers’ language choice. After preliminary exploratory interviews and a small-scale pilot study to make sure of the reliability and validity of the instruments, two separate sets of questionnaires for young learners’ parents (243 participants) and teachers (31 participants) were designed and administered. The results of the analyses showed that both parents and teachers held significantly negative attitudes towards L1 use. The findings also indicated that parents reflect their negative attitudes to the institutes so as to hamper L1 use by talking directly to the teachers, threatening to change institutes in the case of dissatisfaction, and influencing the institute principals’ policies about L1 use.

The development and use of Domain Specific Languages emerged as a way to cope with complex problems using concepts closer to the problem domain. By leveraging the principles proposed by Model-Driven Development (MDD), like the separation of concerns and the use of model transformations, this approach became popular and caused the emergence of a variety of languages, known as Domain Specific Modeling Languages (DSMLs). Moreover, the use of DSMLs with graphical notations abstracts even more the problem domain, either by using extensions of UML or directly using metamodeling languages. The definition and use of DSMLs is only possible through specific tools, known as languages workbenches. This paper discusses the analysis and comparison of three of these tools (namely Papyrus, Enterprise Architect and Sirius) that were used to create the XIS-Mobile language, a non-trivial DSML defined as a UML profile for modeling mobile applications in a platform-independent way. These tools were evaluated considering a set of key criteria (namely learnability, usability, graphical completeness, validation support, transformation support, evolvability and interoperability) which show their suitability to develop non-trivial languages.

All language use is a multimodal endeavor. Language processing must deal with both auditory and visual signals and integrate them with millisecond precision. This chapter presents evidence for the inherently multimodal nature of language use, outlines the implications for the study of L2 processing, and provides a survey of the main methods used to probe multimodal processing in production and comprehension. The chapter describes some key issues in the study of L2 production and comprehension, and outlines pros and cons with the methods chosen. It closes with a discussion of open questions, challenges, and future research topics.

4 - Evaluation of Network Estimation

Chlorophyll fluorescence (ChlF) information offers a deep insight into the plant physiological status by reason of the close relationship it has with the photosynthetic activity. The unmanned aerial systems (UAS)-based assessment of solar induced ChlF (SIF) using non-imaging spectrometers and radiance-based retrieval methods, has the potential to provide spatio-temporal photosynthetic performance information at field scale. The objective of this manuscript is to report the main advances in the development of UAS-based methods for SIF retrieval with non-imaging spectrometers through the latest scientific contributions, some of which are being developed within the frame of the Training on Remote Sensing for Ecosystem Modelling (TRuStEE) program. Investigations from the Universities of Edinburgh (School of Geosciences) and Tasmania (School of Technology, Environments and Design) are first presented, both sharing the principle of the spectroradiometer optical path bifurcation throughout, the so called ‘Piccolo-Doppio’ and ‘AirSIF’ systems, respectively. Furthermore, JB Hyperspectral Devices’ ongoing investigations towards the closest possible characterization of the atmospheric interference suffered by orbital platforms are outlined. The latest approach focuses on the observation of one single ground point across a multiple-kilometer atmosphere vertical column using the high altitude UAS named as AirFloX, mounted on a specifically designed and manufactured fixed wing platform: ‘FloXPlane’. We present technical details and preliminary results obtained from each instrument, a summary of their main characteristics, and finally the remaining challenges and open research questions are addressed. On the basis of the presented findings, the consensus is that SIF can be retrieved from low altitude spectroscopy. However, the UAS-based methods for SIF retrieval still present uncertainties associated with the current sensor characteristics and the spatio-temporal mismatching between aerial and ground measurements, which complicate robust validations. Complementary studies regarding the standardization of calibration methods and the characterization of spectroradiometers and data processing workflows are also required. Moreover, other open research questions such as those related to the implementation of atmospheric correction, bidirectional reflectance distribution function (BRDF) correction, and accurate surface elevation models remain to be addressed.

Aim: The aims of the present study were (i) to identify the format of resources that nutrition professionals use to educate consumers about reading nutrition information panels; (ii) to identify the most common nutrient criteria; and (iii) to assess the suitability of the nutrient criteria by assessing them against foods commonly eaten in Australia, from products in NUTTAB 2006.Methods: An online 13‐question survey, asking about resources and nutrient criteria used, was distributed by email by the Dietitians Association of Australia. A total of 240 surveys were completed. The most common nutrient criteria were identified and tested against common foods in the NUTTAB 2006 database to make an assessment on suitability.Results: The most common resource format was diet sheet, and the most common criterion for each nutrient was: energy <600 kJ/snack food, total fat <10 g/100 g, saturated fat <3 g/100 g, sugar <10 g/100 g, fibre >3 g/serve and sodium <120 mg/100 g. One‐third of common foods in Australia met all four of the ‘per 100 g’ nutrient criteria.Conclusions: The majority of respondents had a set of nutrient criteria for educating consumers about reading and understanding nutrition information panels. The most common nutrient criteria allowed sufficient number of foods to choose from, suggesting that the four most common ‘per 100 g’ nutrient criteria are suitable for use with consumers.

There are several advantages of administering primary systemic therapy (PST) instead of adjuvant therapy in the management of early breast cancer patients: (a) PST allows for a quantifiable evaluation of the sensitivity or resistance of any treated case and (b) the response assessment offers the opportunity to "cross over" to a different regimen for an individual patient, leading to more flexible, "tailored" therapies. Indeed, these advantages are tenable if one assumes that the primary tumor response serves as a surrogate marker of the efficacy of PST in terms of survival. Unfortunately, this has not yet been validated. The data that are actually available show that both clinical complete response (cCR) and pathological (p)CR have prognostic significance. pCR after chemotherapy has a greater prognostic impact than cCR; however, it is frequently observed in a subset of tumors-such as those that are estrogen receptor negative, are human epidermal growth factor receptor positive, and have elevated proliferative activity-but occurs rarely in their human epidermal growth factor receptor-2/neu counterparts. cCR is more sensitive than pCR, but its assessment presents many hindrances. cCR after chemotherapy can predict early on which tumors are destined to undergo pCR, suggesting a role for this endpoint guiding further treatment decisions early on. The pCR rate in small randomized PST studies comparing chemotherapy with chemotherapy plus trastuzumab was able to predict the difference in survival observed in large, randomized adjuvant trials with a similar study design. Conversely pCR cannot predict the outcome benefit of patients undergoing different hormonal therapies. In conclusion, pCR may be a reliable surrogate endpoint for PST efficacy in a subset of patients undergoing chemotherapy.

How to best integrate linguistic and perceptual processing in multi-modal tasks that involve language and vision is an important open problem. In this work, we argue that the common practice of using language in a top-down manner, to direct visual attention over high-level visual features, may not be optimal. We hypothesize that the use of language to also condition the bottom-up processing from pixels to high-level features can provide benefits to the overall performance. To support our claim, we propose a U-Net-based model and perform experiments on two language-vision dense-prediction tasks: referring expression segmentation and language-guided image colorization. We compare results where either one or both of the top-down and bottom-up visual branches are conditioned on language. Our experiments reveal that using language to control the filters for bottom-up visual processing in addition to top-down attention leads to better results on both tasks and achieves competitive performance. Our linguistic analysis suggests that bottom-up conditioning improves segmentation of objects especially when input text refers to low-level visual concepts. Code is available at https://github.com/ilkerkesen/bvpr.