Kinds Of Contexts Research Articles

SlowFastFormer for 3D human pose estimation

3D human pose estimation in videos aims at locating the human joints in the 3D space given a temporal sequence. Motion information and skeleton context are two significant elements for pose estimation in videos. In this paper, we propose a SlowFastFormer (slow-fast transformer) network where two branches with different input rates are composed to encode these two different kinds of context. For the slow branch, skeleton context is well learned at a higher frame rate. For the fast branch, motion information is captured at a lower frame rate. Through these two branches, different kinds of context are encoded separately. We fuse these two branches at a later stage to fully utilize the skeleton context and motion information. Afterwards, a blending module is developed to promote the message exchange among multiple branches. In the blending stage, different kinds of context information are exchanged and feature representation is enhanced consequently. Lastly, a hierarchical supervision scheme is tailored where predictions of different levels are inferred in a progressive manner. Our approach achieves competitive performance with lower computation complexity on several benchmarks, i.e., Human3.6M, MPI-INF-3DHP and HumanEva-I.

Landscapes of Hope

Our article aims to offer counter-narratives to the risks and hardships of digital youth by scrutinizing how hope is present in youth’s lives in different online environments and everyday practices. We trace young people’s landscapes of hope by asking what kind of hopes and ideas of the digital future young people have about online environments and how they practice and cherish hope. To achieve these objectives, we draw on both qualitative and quantitative data produced in 2021–2022 among Finnish ninth graders. Our findings emphasize that young people’s online landscapes of hope are oriented toward the future, and they are in a constant state of co-becoming with different kinds of contexts, agencies, practices, and intensities.

A tale about facts and opinions: The impact of a drama intervention on middle-school students´ information literacy

Today, huge amounts of data are produced, collected, and presented in all kinds of contexts. The ability to critically examine and evaluate information and arguments in relation to empirical evidence is often referred to as information literacy. It is of utmost importance that students are adequately scaffolded to develop this ability, to be able to become democratic citizens. The study presented combines learning science and drama to explore whether this approach can make 6 grade students more aware of certain aspects of information literacy, such as false balance, the burden of proof, and filter bubbles. Half of the students watched a play and participated in a pedagogical follow-up before answering a questionnaire. The other half answered the questionnaire before the intervention. Results show that students watching the play had grasped the core of the more tangible questions, writing more elaborated and relevant answers than students in the control group.

Refining History for Future-Aware Neural Machine Translation

Neural machine translation uses a decoder to generate target words auto-regressively by predicting the next target word conditioned on a given source sentence and its previously predicted target words, i.e, its translation history, which suffers from two limitations: 1) the prediction of next word depends heavily on the quality of its history information. Moreover, the discrepancy between training and inference exacerbates this limitation; 2) this left-to-right decoding way cannot make full use of the target-side future information, which leads to the issue of unbalanced outputs. On the one hand, we alleviate the first limitation with a history-refining module, which learns to examine the quality of each history word by assigning it a confidence score. The confidence score is further used as a gate to control the amount of its word embedding flowing to the decoder. On the other hand, we attack the second limitation with a future-foreseeing module, which learns the distribution of future translation at each decoding time step. More importantly, we further propose refining history for future-aware NMT since the two modules can be closely incorporated as they focus on different kinds of context. Experimental results on various translation tasks with different scaled datasets, including WMT English <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\leftrightarrow$</tex-math></inline-formula> {German, French, Romanian}, show that our proposed approach achieves significant improvements over strong Transformer-based NMT baselines.

Exploring Pandemics Events on Twitter by Using Sentiment Analysis and Topic Modelling

At the end of 2019, while the world was being hit by the COVID-19 virus and, consequently, was living a global health crisis, many other pandemics were putting humankind in danger. The role of social media is of paramount importance in these kinds of contexts because they help health systems to cope with emergencies by contributing to conducting some activities, such as the identification of public concerns, the detection of infections’ symptoms, and the traceability of the virus diffusion. In this paper, we have analysed comments on events related to cholera, Ebola, HIV/AIDS, influenza, malaria, Spanish influenza, swine flu, tuberculosis, typhus, yellow fever, and Zika, collecting 369,472 tweets from 3 March to 15 September 2022. Our analysis has started with the collection of comments composed of unstructured texts on which we have applied natural language processing solutions. Following, we have employed topic modelling and sentiment analysis techniques to obtain a collection of people’s concerns and attitudes towards these pandemics. According to our findings, people’s discussions were mostly about malaria, influenza, and tuberculosis, and the focus was on the diseases themselves. As regards emotions, the most popular were fear, trust, and disgust, where trust is mainly regarding HIV/AIDS tweets.

Experienced provers’ uses of contexts while engaging in combinatorial proof of binomial identities

Combinatorial proofs of binomial identities involve establishing an identity by arguing that each side enumerates a certain set of outcomes. In this paper, we share results from interviews with experienced provers (mathematicians and upper-division undergraduate mathematics students) and examine one particular aspect of combinatorial proof, namely the kinds of contexts that experienced provers used to establish combinatorial proofs of binomial identities. Our findings show that overall, our participants used a variety of contexts in their work; we also demonstrate ways in which previous experiences influenced the contexts they chose, and we offer some instances in which features of a context supported their combinatorial proof production. We offer some theoretical implications of our work, and we conclude with a discussion of limitations and avenues for future work.

Characterizing science recreation workshops: the ‘guerrilla' of science communication

ABSTRACT Science Recreation Workshops (SRW) are engaging activities intended to create scientific experiences for participants, who play with natural phenomena while they explore, discover, discuss, and learn about them. They take people into a first-hand scientific adventure. SRW’s do not demand a lot of resources to develop, that is why SRW’s groups can operate ‘guerrilla-like’ tactics: with fast-moving and small-scale actions to get people to enjoy and learn science in all kinds of contexts. It is possible to take SRW’s to a wide variety of places: museums, parks, schools, public squares, streets, marginal neighborhoods, and small towns. It could be said that SRW’s present an interesting dichotomy: their versatility allows them to go where other science communication activities cannot reach, but they hardly appear in the literature on informal science education or public communication of science and technology. SRW’s have developed without barely having scholarly discussion about them, but this kind of work poses constraints for their development. Tasks such as improving their activities, training new practitioners, and impact evaluation demand for a solid bedrock. In this article, we intend to characterize SRW’s – alongside the organizations devoted to their development–, in an initial effort to spark discussion about them.

Solving the income-happiness paradox

Easterlin notes a contradiction in the data. While the cross-sectional data set shows that happiness is a positive monotonic function of income, the time-series data set of high income countries demonstrates that happiness does not rise with the rise of income. To solve the paradox, this paper proposes that each data set reveals a different facet of happiness. The cross-sectional data set asks people how they assess their current well-being in general. This question prompts people to contrast their current well-being with a well-being in the distant past. This explains why happiness tracks income. In comparison, the time-series data ask people how they feel at the moment. This question prompts people to contrast their current well-being with an aspired goal in the future. Their response is a function of the gap that exists between their current well-being and the aspired one. The gap is usually steady for high income countries and, hence, happiness is likewise steady, i.e., insensitive to the rise of income. The proposed solution highlights the operation of contextual assessment: we have two facets of happiness following the two kinds of context in operation.

Elements of Biblical Exegesis: A Basic Guide for Students and Ministers

Elements of Biblical Exegesis: A Basic Guide for Students and Ministers

In Trust We Trust: Epistemic Vigilance and Responsibility

ABSTRACT Much of what we know we know through testimony, and knowing on the basis of testimony requires some degree of trust in speakers. Trust is therefore very valuable. But in trusting, we expose ourselves to risks of harm and betrayal. It is therefore important to trust well. In this paper, I discuss two recent cases of the betrayal of trust in (broadly) academic contexts: one involving hoax submissions to journals, the other faking an identity on social media. I consider whether these betrayals suggest that we ought to be less trusting in contexts like these. I argue that we should not: the acquisition of knowledge is dependent on trust, and we cannot intentionally reduce the extent to which we trust in these kinds of contexts without risking destroying it utterly. Instead, we must trust in our epistemic networks and the way they work to filter out deception.

Multiple Context Learning Networks for Visual Question Answering

A novel Multiple Context Learning Network (MCLN) is proposed to model multiple contexts for visual question answering (VQA), aiming to learn comprehensive contexts. Three kinds of contexts are discussed and the corresponding three context learning modules are proposed based on a uniform context learning strategy. Specifically, the proposed context learning modules are visual context learning module (VCL), textual context learning module (TCL), and visual-textual context learning module (VTCL). The VCL and TCL, respectively, learn the context of objects in an image and the context of words in a question, allowing object and word features to own intra-modal context information. The VTCL is performed on the concatenated visual-textual features that endows the output features with synergic visual-textual context information. These modules work together to form a multiple context learning layer (MCL) and MCL can be stacked in depth for deep context learning. Furthermore, a contextualized text encoder based on the pretrained BERT is introduced and fine-tuned, which enhances the textual context learning at the feature extraction stage of text. The approach is evaluated by using two benchmark datasets: VQA v2.0 dataset and GQA dataset. The MCLN achieves 71.05% and 71.48% overall accuracy on the test-dev and test-std sets of VQA v2.0, respectively. And an accuracy of 57.0% is gained by the MCLN on the test-standard split of GQA dataset. The MCLN outperforms the previous state-of-the-art models and the extensive ablation studies examine the effectiveness of the proposed method.

Los estereotipos étnicos en Ab urbe condita: un estado de la cuestión

This paper proposes a state of the matter on the scholarship about ethnic stereotypes in Ab urbe condita from the classic work by Walsh written in 1961 to nowadays. With this goal in mind, the paper is divided in five parts. The first part shows how the analyses of the subject matter became more complex as the ethnographic tradition with which Livy dealt, as well as the Roman identity and the notion itself of stereotype became an issue. In the second part, this article criticizes binary conceptions of otherness and suggests a wider gradation of it. The third part deals with some interesting observations made by Moore in 1989 that were later disregarded. In the fourth, it reviews Levene’s suggestion based on ethnic identity studies that we should look for a non-Romancentric view within Livy’s work. Finally, it studies the relevance of considering three kinds of contexts —the genre of the work, episodic and temporal frameworks— while analyzing the ethnic stereotypes in Ab urbe condita.

Diversity of learning-induced synaptic plasticity at dorsal CA1 synapses: a possible underlying mechanism of contextual memory formation

We expose various kinds of context in our everyday lives and hence contextual memory is critically important for us. Since hippocampus is a major area for processing contextual memory, it needs to encode different components of various contexts such as ‘what’, ‘where’ and ‘when’, etc. However, the underlying mechanism by which the hippocampus differentially encodes various kinds of contextual information is interesting but not yet revealed completely. Since long-term potentiation (LTP) had been discovered and believed to be mechanism of learning, many studies were conducted to investigate the underlying detailed mechanism of memory formation by using various LTP induction protocols. By combining HSV-mediated in vivo gene delivery with in vitro patch-clamp recordings, it was found that LTP can induce plastic changes such as delivery of GluA1-containing AMPA receptor to the dorsal CA1 synapses of the hippocampus and also the causal relationship between this AMPA receptor delivery and learning was discovered. Then it was found that learning induced synaptic plasticity with diverse pattern highlighting the importance of this diversity in contextual memory formation. Here, we mostly review the studies which used hippocampal-dependent learning paradigm (inhibitory avoidance task) for better comparison and mapping of the concept about how learning induced diversity of synaptic plasticity at dorsal hippocampal CA1 synapses and how this diversity may become responsible as an underlying mechanism of contextual memory formation. We found that contextual learning induces synaptic plasticity at CA1 neurons with synapse-specific diversity, input-specific diversity, subregion- or subfield-specific diversity, episode-specific diversity but only a few studies revealed their functional significance. For complete understanding of learning-induced diversity of synaptic plasticity, it demands further studies for investigation of their functional correlation to learning performance by using new highly promising approaches like optogenetic techniques and cell-specific self-entropy analysis, etc.

El lugar de la competencia digital en la enseñanza y aprendizaje de lenguas segundas y extranjeras

The globalized Information Society that has been taking shape in the 21st century with advances in new technologies requires its members to have a series of key skills, among which digital competence stands out as part of the capacity for permanent and autonomous learning. The Covid pandemic that we have been going through for almost three years has highlighted the need to train people in digital competence in order to continue carrying out their personal, educational and professional activities in all kinds of contexts and circumstances. The consultation of catalogues, bibliometric databases and digital repositories, such as Scopus, Dialnet or Recolecta, has allowed us to verify the interests that the subject arouses in the scientific community, particularly within the area of education. Thus, there is interest in identifying those digital skills that the teacher must master, in outlining the ICT skills that students need to acquire at each educational level, or in developing activities based on the specific use of applications or digital resources (use of blogs, wikis, social networks, gamification, etc.) for second and foreign language teaching.Using a fundamentally qualitative methodology, with a descriptive-interpretative epistemological orientation based on documentary analysis, the objective of this paper is to analyse the concept of digital competence and verify the place it occupies in the process of second and foreign language acquisition, especially following the publication of the complementary volume of the Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR) in 2020. To this end, a conceptual delimitation has been introduced between competence digital and a series of concepts related to it, such as digital literacy, information literacy or media competence, very present in contemporary academic, scientific, political and economic discourse; the concept of digital competence, understood as a macrocompetence, has been organized in the various (sub)competences it is made up of, and we examine the place that digital competence occupies in each person’s set of competences and in relation to the communication skills, mainly within the field of second and foreign language acquisition. After this systematic review, we conclude that, although the contributions of the complementary volume of the CEFR are undoubtedly important, they are specifically limited to audiovisual comprehension and online interaction, hence we end by proposing language activities that take into consideration all language skills and all channels of communication.

Where Covid metaphors come from: reconsidering context and modality in metaphor

ABSTRACT Pandemics such as Covid-19 are often described in terms of “wars” or “waves” and “troughs.” But this imagery has its potential shortcomings, and therefore a great many researchers and commentators argue that we are thinking about the coronavirus pandemic the wrong way, suggesting replacing the war or ocean analogy with a better or particularly appropriate one, wildfire. Yet, the rarely asked question is: Where do Covid-19 metaphors come from? This type of metaphorical creativity, the so-called context-induced metaphors, has been somewhat systematically investigated in linguistic metaphor research, but not in the literature on nonverbal and multimodal metaphor. I argue that for context-induced creativity to be fully appreciated we need to move beyond verbal metaphors, or verbal manifestations of metaphor, and consider factors that commonly produce creative multimodal metaphors. Will the evidence from multimodality confirm or challenge the linguistic findings? There may be other major possible sources of metaphorical creativity, ones based more on visual or multimodal thinking, but which have not been identified before because data from non-linguistic behavior had not been examined. I thus show that there is a real gap in the literature in that respect and my study of political cartoons fills this both in terms of data and theory. In this article, I will limit myself to the discussion of six motivational forces or contextual factors (in no order of importance): (1) the immediate physical environment, (2) the immediate cultural context, (3) the immediate social setting, (4) knowledge about the major elements participating in the discourse, (5) physical resemblance between the source and target concepts, and (6) word plays and literalizations of famous proverbs and idioms in a language. Sometimes these factors work singly, but often in combination. It is argued that these kinds of context, albeit involved in discourse production and comprehension, do not control discourse as cognitive context models do. Particularly interesting is that among the thousands of books and articles on knowledge, so little is said on the discursive sources of knowledge (besides perception, personal experience, etc.), also about other cultures. The possible implications of this study for metaphor theory, multimodality, and intercultural communication are discussed.

Thom Roberts Reads Crowns

At Studio A, a supported studio for neurodiverse artists, the prolific painter, performer, photocopier, and installation artist Thom Roberts frequently reaches out to connect with friends and fellow artists by running his hands across the backs of their heads; “reading” their crowns. It’s a blessing I have been lucky enough to receive countless times over the course of my ethnographic engagement with Studio A, and as my relationship with Thom has developed. During my research, I have witnessed Thom read crowns in all kinds of contexts, from pubs to art galleries, in a performance artwork that could also be understood as an experimental artist talk. Here, I trace the narrative of this facet of Thom’s practice. I consider how such embodied encounters have the potential to open avenues of communication and connection between people who might experience the world in very different ways.

Multi-thread hierarchical deep model for context-aware sentiment analysis

Real-time messaging and opinion sharing in social media websites have made them valuable sources of different kinds of information. This source provides the opportunity for doing different kinds of analysis. Sentiment analysis as one of the most important of these analyses gains increasing interests. However, the research in this field is still facing challenges. The mainstream of the sentiment analysis research on social media websites and microblogs just exploits the textual content of the posts. This makes the analysis hard because microblog posts are short and noisy. However, they have lots of contexts which can be exploited for sentiment analysis. In order to use the context as an auxiliary source, some recent papers use reply/retweet to model the context of the target post. We claim that multiple sequential contexts can be used jointly in a unified model. In this article, we propose a context-aware multi-thread hierarchical long short-term memory (MHLSTM) that jointly models different kinds of contexts, such as tweep, hashtag and reply besides the content of the target post. Experimental evaluations on a real-world Twitter data set demonstrate that our proposed model can outperform some strong baseline models by 28.39% in terms of relative error reduction.

English in the Linguistic Landscape of Thailand: A Case Study of Public Signs in Hat Yai

During the last decades, English has become an international language in all kinds of contexts, including business and tourism, and Asian linguistic landscapes are a good reflection of this phenomenon. This paper focuses on Thailand and the city of Hat Yai, where a corpus of 165 public signs were collected. These were analysed quantitatively to discuss the functions that English performs in public domains, and also qualitatively, by means of a multimodal analysis, to observe the Thai and English prominence in the case of multilingual signs. The results show the importance of English, not only as an international communicative tool, but also as a language of prestige and media impact. Furthermore, some features of written Thai English or Tinglish were found in some signs, which may confirm the early stages of development of a possible new emerging variety of World Englishes.

Idioms in Context: Evidence from a Time Cloze-Response Study

Summary This article reports on two timed cloze-response experiments which examine the impact of context on idiom recognition. Study 1 presented participants with the beginnings of Polish VP idioms without any prior context. Cloze probabilities and response times for idiom continuations were measured to establish the idiom recognition point (IRP) for each idiom. In Study 2, we used the same idioms in two kinds of contexts: (i) supporting a figurative meaning and (ii) supporting a literal meaning. Cloze probability and response times were measured at the IRP and one word before and after it. The figurative meaning of idioms was automatically activated at the IRP independently of the type of context. Additionally, the figurative context did not move the IRP to an earlier position, whereas in the literal context the responses were significantly slower at the IRP as compared to the figurative context condition. Such a finding indicates that, irrespective of the literal context, the comprehenders automatically activated the figurative meaning of an idiom at the IRP, but they had to discard it later. The literal meaning was computed from the literal meanings of idiom constituents stored in idiom lexical representation, which was computationally costly.

\u2018Motivational work\u2019: a qualitative study of preventive health dialogues in general practice

BackgroundThe aim of this article is to explore preventive health dialogues in general practice in the context of a pilot study of a Danish primary preventive intervention ‘TOF’ (a Danish acronym for ‘Early Detection and Prevention’) carried out in 2016. The intervention consisted of 1) a stratification of patients into one of four groups, 2) a digital support system for both general practitioners and patients, 3) an individual digital health profile for each patient, and 4) targeted preventive services in either general practice or a municipal health center.MethodsThe empirical material in this study was obtained through 10 observations of preventive health dialogues conducted in general practices and 18 semi-structured interviews with patients and general practitioners. We used the concept of ‘motivational work’ as an analytical lens for understanding preventive health dialogues in general practice from the perspectives of both general practitioners and patients.ResultsWhile the health dialogues in TOF sought to reveal patients’ motivations, understandings, and priorities related to health behavior, we find that the dialogues were treatment-oriented and structured around biomedical facts, numeric standards, and risk factor guidance. Overall, we find that numeric standards and quantification of motivation lessens the dialogue and interaction between General Practitioner and patient and that contextual factors relating to the intervention framework, such as a digital support system, the general practitioners’ perceptions of their professional position as well as the patients’ understanding of prevention —in an interplay—diminished the motivational work carried out in the health dialogues.ConclusionThe findings show that the influence of different kinds of context adds to the complexity of prevention in the clinical encounter which help to explain why motivational work is difficult in general practice.