Pulsed Line Source Response of a Thin Sheet With High-Contrast Dielectric and Conductive Properties—A Time-Domain Analysis

published_or_final_versio

Effects of structure and meaning on cortical tracking of linguistic units in naturalistic speech

Recent research has established that cortical activity “tracks” the presentation rate of syntactic phrases in continuous speech, even though phrases are abstract units that do not have direct correlates in the acoustic signal. We investigated whether cortical tracking of phrase structures is modulated by the extent to which these structures compositionally determine meaning. To this end, we recorded electroencephalography (EEG) of 38 native speakers who listened to naturally spoken Dutch stimuli in different conditions, which parametrically modulated the degree to which syntactic structure and lexical semantics determine sentence meaning. Tracking was quantified through mutual information between the EEG data and either the speech envelopes or abstract annotations of syntax, all of which were filtered in the frequency band corresponding to the presentation rate of phrases (1.1–2.1 Hz). Overall, these mutual information analyses showed stronger tracking of phrases in regular sentences than in stimuli whose lexical-syntactic content is reduced, but no consistent differences in tracking between sentences and stimuli that contain a combination of syntactic structure and lexical content. While there were no effects of compositional meaning on the degree of phrase-structure tracking, analyses of event-related potentials elicited by sentence-final words did reveal meaning-induced differences between conditions. Our findings suggest that cortical tracking of structure in sentences indexes the internal generation of this structure, a process that is modulated by the properties of its input, but not by the compositional interpretation of its output

Masculine generic pronouns as a gender cue in generic statements

An eye-tracking experiment was conducted with speakers of Dutch (N = 84, 36 male), a language that falls between grammatical and natural-gender languages. We tested whether a masculine generic pronoun causes a male bias when used in generic statements—that is, in the absence of a specific referent. We tested two types of generic statements by varying conceptual number, hypothesizing that the pronoun zijn “his” was more likely to cause a male bias with a conceptually singular than a conceptually plural ante-cedent (e.g., Someone (conceptually singular)/Everyone (conceptually plural) with perfect pitch can tune his instrument quickly). We found male participants to exhibit a male bias but with the conceptually singular antecedent only. Female participants showed no signs of a male bias. The results show that the generically intended masculine pronoun zijn “his” leads to a male bias in conceptually singular generic contexts but that this further depends on participant gender

Structure-(in)dependent interpretation of phrases in humans and LSTMs

In this study, we compared the performance of a long short-term memory (LSTM) neural network to the behavior of human participants on a language task that requires hierarchically structured knowledge. We show that humans interpret ambiguous noun phrases, such as second blue ball, in line with their hierarchical constituent structure. LSTMs, instead, only do so after unambiguous training, and they do not systematically generalize to novel items. Overall, the results of our simulations indicate that a model can behave hierarchically without relying on hierarchical constituent structure

Hierarchy in language interpretation: Evidence from behavioural experiments and computational modelling

It has long been recognised that phrases and sentences are organised hierarchically, but many computational models of language treat them as sequences of words without computing constituent structure. Against this background, we conducted two experiments which showed that participants interpret ambiguous noun phrases, such as second blue ball, in terms of their abstract hierarchical structure rather than their linear surface order. When a neural network model was tested on this task, it could simulate such “hierarchical” behaviour. However, when we changed the training data such that they were not entirely unambiguous anymore, the model stopped generalising in a human-like way. It did not systematically generalise to novel items, and when it was trained on ambiguous trials, it strongly favoured the linear interpretation. We argue that these models should be endowed with a bias to make generalisations over hierarchical structure in order to be cognitively adequate models of human language

Government of Malawi's unconditional cash transfer improves youth mental

We explore the impacts of Malawi's national unconditional cash transfer program targeting ultra-poor households on youth mental health. Experimental findings show that the program significantly improved mental health outcomes. Among girls in particular, the program reduces indications of depression by about 15 percentage points. We investigate the contribution of different possible pathways to the overall program impact, including education, health, consumption, caregiver's stress levels and life satisfaction, perceived social support, and participation in hard and unpleasant work. The pathways explain from 46 to 65 percent of the program impact, advancing our understanding of how economic interventions can affect mental health of youth in resource-poor settings. The findings underline that unconditional cash grants, which are used on an increasingly large scale as part of national social protection systems in Sub-Saharan Africa, have the potential to improve youth mental wellbeing and thus may help break the vicious cycle of poverty and poor mental health

Government of Malawi's unconditional cash transfer improves youth mental

We explore the impacts of Malawi's national unconditional cash transfer program targeting ultra-poor households on youth mental health. Experimental findings show that the program significantly improved mental health outcomes. Among girls in particular, the program reduces indications of depression by about 15 percentage points. We investigate the contribution of different possible pathways to the overall program impact, including education, health, consumption, caregiver's stress levels and life satisfaction, perceived social support, and participation in hard and unpleasant work. The pathways explain from 46 to 65 percent of the program impact, advancing our understanding of how economic interventions can affect mental health of youth in resource-poor settings. The findings underline that unconditional cash grants, which are used on an increasingly large scale as part of national social protection systems in Sub-Saharan Africa, have the potential to improve youth mental wellbeing and thus may help break the vicious cycle of poverty and poor mental health

Smart urbanism in Barcelona: A knowledge-politics perspective

There is a risk in the ‘Smart City’ that plural forms of knowing the city become eclipsed by singular governance-oriented analyses produced through computational logics originating from undemocratic service providers. In light of this concern, this chapter considers three aspects of smart urbanism’s knowledge politics: i) the role of urban agencies – or understanding smart urbanism as a situated, socio-material practice; ii) the agency of smart city technologies’ materiality as well as the ownership and control of these technologies, and: iii) the political rationalities, values and assumptions embedded in smart city technologies’ design and use. Drawing on these insights, this chapter analyses smart knowledge politics in Barcelona, where the 2015 Council elections replaced a market-oriented political leadership enthusiastically implementing the Smart City with a political leadership whose origins in social movements and citizen democracy made it deeply sceptical towards smart urbanism. We analyse how this opened up space for different approaches to using technology in the city while at the same time giving rise to materially very different kinds of smart knowledge configuring technologies emphasizing citizen participation and democratic control of knowledge production. Indeed, political rationalities and smart knowledge configuring technologies intersected and co-evolved, rather than one informing the other unidirectionally

Local Analysis of Inverse Problems: H\"{o}lder Stability and Iterative Reconstruction

We consider a class of inverse problems defined by a nonlinear map from parameter or model functions to the data. We assume that solutions exist. The space of model functions is a Banach space which is smooth and uniformly convex; however, the data space can be an arbitrary Banach space. We study sequences of parameter functions generated by a nonlinear Landweber iteration and conditions under which these strongly converge, locally, to the solutions within an appropriate distance. We express the conditions for convergence in terms of H\"{o}lder stability of the inverse maps, which ties naturally to the analysis of inverse problems