Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
There is a consensus among researchers and educators that teachers’ language register (LR) influences learners’ cognitive development. While previous studies have examined how teachers’ professionalism in relation to LR is evaluated by educational experts and researchers, this study was motivated by the need to understand the perceptions of parents, teachers, and teacher-trainees regarding the contribution of LR to teachers’ professionalism in intercultural environments. In this mixed-methods study, 308 participants were asked to rate teacher professionalism based on one of three written reflections, identical in content but differing in LR level. The study was conducted in Israel, a multilingual society in which Hebrew is the official language of instruction but is a second language for many teachers and learners. This context, shaped by ongoing immigration, adds an important cultural lens to the investigation. Unlike previous studies, the findings in this research showed that very few participants considered LR an important component of teacher professionalism. Instead, they emphasised proficiency in other areas, particularly teacher knowledge, cultural awareness, and responsiveness to learners’ needs. This study offers global implications for teacher education in increasingly multicultural and multilingual societies, suggesting that perceptions of professionalism prioritise cultural competence and pedagogical adaptability over formal linguistic norms.
Abstract This study investigates the multifunctionality of the Turkish discourse connective ve ‘and’ in simultaneous interpreting from Turkish into Turkish Sign Language (TİD) in broadcast news. Using a corpus of interpreted news texts, it examines how this polyfunctional connective is transferred across modalities. Drawing on Halliday and Hasan’s cohesion model and the Penn Discourse Treebank typology, the study identifies discourse relations expressed by ve — such as elaboration, temporality, causality, and comparison — and analyzes how they are conveyed in TİD through explicit signs, implicit marking, or omission. Most relations are preserved, though often implicitly, reflecting the economy principle in signed languages. Manual signs used to express ve, including ve -1 and palm-up, vary systematically with relation type. This points to a cross-modal tendency for explicit realization under increased processing demands. As the data derive from hearing interpreters rather than native Deaf signers, the findings reflect interpreter-mediated strategies rather than monolingual Deaf discourse norms.
Considering the trends towards universalization and differentiation in procedural law, the paper hypothesises that similar patterns exist in the language of procedural law. It identifies the need to study the linguistic and textological distinctiveness of the texts of the Criminal Procedure Code, Civil Procedure Code, Arbitration Procedure Code, and Administrative Procedure Code. The study reveals certain features of the language of these laws in terms of semantics, grammar, vocabulary, syntax, and textology. Examples of homonymy, synonymy, oxymoron, violations of linguistic norms in terms of spelling and correct word order, the use of identical headings, combining heterogeneous elements into structural elements of a normative legal act, and lexical patterns are given. The normative meaning of headings is revealed; examples reflecting the problems of the structure of procedural laws are given. The author names the striking textual feature of the Criminal Procedure Code of the Russian Federation, namely Art. 5, which includes the definition of the main terms used in the law. The syntactic complication of the language of procedural laws has been noted in recent years. The lexical features of individual procedural laws are revealed, demonstrating their substantive originality. An assumption is made about the influence of the quality and features of the normative legal language on the language of judicial acts and the language of legal science.
Abstract This article empirically investigates the semantic meaning of ‘wh-exclamatives’ (e.g., What a view!). Previous literature has identified three distinct meaning components of wh-exclamatives: ±mirativity (speaker’s surprise), ±noteworthiness (degree of a referent’s characteristic), and ±valence (speaker’s strong positive or negative evaluation of the referent). In Study 1, participants (n = 50) rated the felicity of wh-exclamatives in contexts manipulated by these three meaning components. The findings indicate that ±noteworthiness and ±valence, but not ±mirativity, influence the felicitous use of wh-exclamatives. Study 2 (n = 80) examines the role of wh-exclamatives as linguistic valence setters, investigating how the construction interacts with the inherent valence of discourse referents (valence of a referent in isolation) to determine the overall valence of embedded referents in a valence rating study. The results reveal that wh-exclamatives have a polarity-conforming valence-strengthening function, enhancing the positivity of positive referents and the negativity of negative ones. Neutrally valenced referents are preferentially positivized, indicating a constructional positivity bias.
Anatomical education has historically relied on binary terminology, reinforcing the conflation of sex, gender, and gender identity through long-standing social and linguistic norms. To better include gender and sex diverse students and to respect the delineations between gender and sex, educators are incorporating diversity into their courses through educational primers; however, there is a lack of literature on the subject. Thus, this study explores learners' perceptions and attitudes about adding sex and gender diversity into anatomical education programs at a Canadian university. A total of 73 participants responded to a survey informed by grounded theory, and descriptive statistics are used for analysis. Nearly half of learners felt their overall educational experience was enhanced by the inclusion of sex and gender diversity content in their anatomy course and around half of learners felt more knowledgeable about inclusive language. Some learners were inspired to begin using inclusive language following their anatomy course. Overall, these findings suggest that integration of gender and sex diversity could be well-received and valued by anatomy students for humanistic skill development. Emerging themes requiring qualitative insights, including learners' definitions of "inclusive language" and the viability of peer-based learning, will be explored in future work.
Abstract Recognizing others’ emotions is central to social interaction. Traditional biological psychology infers emotional responding via laboratory measures, whereas contemporary computer vision algorithms claim to identify emotions unobtrusively from facial video. However, the validity of such algorithms for classifying spontaneous emotional responses occurring without explicit communicative intent remains debated. We compared established psychophysiological measures (EEG, facial EMG, EDA activity) with the open-source facial behavior toolkit OpenFace for classifying participants’ spontaneous responses during free viewing of happiness-inducing, disgust-inducing, and neutral pictures. Participants provided valence and arousal ratings and later selected the basic emotion that best matched their reaction which served as the classification criterion. Using within-participants single-trial support vector machine (SVM) classification, EEG achieved the highest accuracy (40%), followed by facial EMG (37%); OpenFace reached 36%. All methods except EDA exceeded chance performance (33.3%) and were lower compared to human raters (48%). Predictions declined slightly for across-participants SVMs, being at chance for OpenFace and EDA. The results indicate that in principle both, psychophysiological measures and video-derived facial action units, can capture diagnostically relevant aspects of emotional responding during picture viewing, but that their performance is limited when expressions are spontaneous and not produced for communicative purposes. Inter-individual variability in expressivity and physiological responding likely contributes to these limitations and should be considered when deploying automatic emotion recognition in research or applied settings.
Closely related languages written in different scripts expose little surface overlap to multilingual models, limiting cross-lingual transfer. We compare two approaches to script unification: the general-purpose uroman romanizer and the family-specific Common Turkic Script (CTS). We train matched fastText models on transliterated Wikipedia corpora from 11 Turkic languages and evaluate them on WikiANN named entity recognition and Universal Dependencies part-of-speech tagging. CTS and uroman show no significant difference on NER, while both substantially outperform the official monolingual fastText baselines. POS results reveal no universal winner: language-specific differences are associated with the cross-lingual character n-gram coverage induced by each representation, while within-language coverage becomes more important when target-language supervision is available. Although CANINE-c achieves higher overall POS averages, the substantially simpler fastText-based systems remain competitive on several treebanks. Overall, the effectiveness of script unification depends on the language, the induced subword overlap, and the available supervision.
The Nigerian Salafi Discourse Corpus (NSDC) is a purpose-built corpus of 5,791 Facebook posts (2,485,963 words; 2,518,453 tagged tokens; 149,431 sentences) published by Nigerian pages and profiles between 2015 and 2025. The corpus was assembled from eight keyword-filtered exports of the Meta Content Library (Salafis, Salafism, Salafiyyah, Ahlus-Sunnah, Sunni, Wahabism, Wahabiyyah, Salafool) and processed through a fully documented, machine-verified pipeline: schema validation, three-pass deduplication, Unicode normalisation and script-based noise removal, SGML-annotated corpus assembly, cross-keyword merging, and calendar-year segmentation. This release contains three artefacts: (1) the cleaned corpus (one UTF-8 file per post, SGML metadata tags, one sentence per line); (2) the tagged vertical corpus (Penn Treebank part-of-speech and lemma, 15 semantic fields, 15 discourse strategies), in the vertical format used by Sketch Engine and CQP; and (3) the corpus segmented by calendar year for diachronic analysis.
We describe the UppsalaNLP submission to the EvaLatin dependency parsing shared task.We explore using an out-of-the-box parser in combination with multi-treebank training on Latin and multilingual training on other ancient languages.Adding additional languages yields only small gains, but the results vary across treebanks and genres, with the largest positive effect for poetry.Our systems perform best in the shared task for prose but are less competitive for poetry, indicating the need for genre adaptation.
Abstract Virtual reality (VR) is increasingly adopted across various fields, due to its ability to immerse people in virtual environments (VEs) and induce emotions. A key factor in this experience is the sense of presence, which is the feeling of being in the VE and the perceived realism of the experience. While prior research has demonstrated the importance of presence in driving emotional outcomes, gaps remain in understanding how the type of VEs and individual differences may influence this relationship. The present study addressed these gaps by comparing the strength of the relationship between presence and emotional outcomes across fear-inducing and relaxation-inducing VEs. The study also investigated whether this relationship was moderated by individual differences such as trait absorption and neuroticism. 125 participants were randomly assigned to one of two VEs. Participants completed baseline assessments, experienced the VE, then completed post-test assessments. Emotional outcomes were assessed through subjective emotional valence and arousal ratings. Results showed that the relationship between presence and emotional arousal was significantly stronger in the fear-inducing VE than in the relaxation-inducing VE. Furthermore, trait absorption and neuroticism significantly moderated the relationship between presence and emotional valence in only fear-inducing VEs. No moderation effects were found for the relationship between presence and emotional arousal. The study points that the relationship between presence and emotional outcomes is not consistent and may be influenced by the type of VE, trait absorption, and neuroticism. These findings provide theoretical and practical implications for designing effective VEs for various applications.
The current study examines how the presentation of separable components of rapport building in forensic interviews with children affect lay perceptions of both the child victim and defendant guilt. Mock jurors will read a forensic interview in which a child either alleges sexual abuse by an adult male perpetrator or does not. Interviews will either contain a ground rules phase or only a brief introduction. Thus, the study adheres to a 2 (ground rules: present or absent) x 2 (disclosure: present or absent) between-subjects design). Effects of ground rules on perceptions of defendant guilt are not expected. However, it is expected that disclosure will affect ratings of defendant guilt. It is also expected that both ground rules and disclosure will affect perceptions of the child. It is expected that the child will be perceived more positively than when both are present.
Language change is continuous and vital for the sociocultural adaptation and status development of language varieties. Perhaps the most important linguistic feature of Nigerian English language change is semantic extension which refers to the process whereby terms already existing in English (standard English) acquire new meanings. This paper investigated the usage of semantic extension in Nigerian English (NIE), the social motivations responsible for such semantic innovations and the relevance of linguistic innovations for the description and teaching of English in Nigeria. Using descriptive qualitative research design, data for the research were collected using naturally occurring language forms while other information sources included print and social media, educational, political and religious institutions. It was found that semantic extension in Nigerian English is rule-governed, based on culture, multilingualism, technological innovations, socio-economic experiences and indigenous conceptual framework. The data further revealed that the semantic extensions are sociolinguistically recognized by educated users of Nigerian English and linguistic norm and not mere linguistic deviation from Standard English. It was observed that semantic extension promotes lexical reduction, language creativity and the institutionalization of Nigerian English as a variety of the World Englishes paradigm. It was recommended that Nigerian English new lexical items should be incorporated into English textbooks and dictionaries, Nigerian English lexical innovations should form the basis for the teaching of English in Nigeria.
This seminar paper, written in 1984, examines the divergent conceptions of 'Sprachkultur' (language culture) in the German Democratic Republic (GDR) and the Federal Republic of Germany against the background of their differing political systems and world-views. As a contemporary document of German division, the paper offers insights into the ideologically shaped linguistics of the Cold War. The study first analyses the fundamental differences between the Marxist-Leninist and the pluralist-liberal understandings of politics, scholarship, and culture. Taking as its starting point the concept of the Prague School of linguistics, which in the 1930s developed the first scholarly grounded programme of language culture, it traces the later instrumentalisation of this approach in the linguistics of the GDR. Whereas in the GDR 'Sprachkultur' served as a state educational programme for the formation of the 'socialist personality', in the Federal Republic a descriptive, pluralist approach emerged, one that recognises differing linguistic norms as of equal worth. The paper shows how linguistic concepts are shaped by their social framework conditions, and argues that, despite the shared socio-economic structures of modern industrial societies, the differing political systems gave rise to fundamentally distinct conceptions of language cultivation and language policy. As a historical document, the paper vividly attests to the communicative conflicts and ideological barriers that impeded scholarly exchange between East and West. This is a translation of the original paper published under doi 10.5281/zenodo.21925229. It was generated with the aid of Claude.Ai.
This dataset contains data from 135 on-line and 16 off-line participants for the Pilot Test, 42 participants for EXP1, another 42 participants for EXP2, and 8 participants for EXP3. The Pilot Test established the VR environment conditions. Red and blue colors were selected based on arousal and valence ratings. EXP1 used a seated cognitive matching task under two conditions(Red/Blue). Emotion&Perception data were collected before and after the VR experience for Affective response and room appraisal. Objective measures include total matching score, number of fails, and time taken per level for Task Performance. Subjective measures include task workload, spatial perception, cybersickness, preference, and perceived room size/FoV. EXP2 used a physical block-stacking task under two conditions(Red/Blue). Emotion&Perception data were collected before and after the VR experience for Affective response and room appraisal. Objective measures include number of stacked blocks, dynamic movement, error distance, and error rotation for Task Performance. Subjective measures follow EXP1. EXP3 used a rhythm game task under a 2×2 design of color (red/blue) and task type (cognitive/physical). Objective measures include game score and number of good cuts. Subjective measures include task workload and cybersickness. The dataset includes questionnaire from the Sim-TLX, SP-IE, and Simulator Sickness Questionnaire (SSQ), collected during the VR experience.
Inside a modern language model sits a single internal direction that tracks how positive or negative a sentence feels. We show how to find this valence axis (V-axis) from just 9 emotion category names plus 50 short narrative paragraphs per emotion -- about 1,500 fewer labels than the usual supervised approach -- and that the same direction appears in vision, audio, and human-brain encoders never jointly trained. The recipe: embed nine emotion-anchored story sets in a frozen encoder, take the top principal direction of the nine averaged embeddings. Projecting new inputs onto it captures 93% of supervised performance on SST-2 (Llama-3-8B-Instruct, AUC 0.772 vs. 0.828), correlates with human valence ratings on 11,811 EmoSet images at r=0.636, reaches AUC 0.906 on ESC-50 audio (p<2.2e-15), and AUC 0.720+/-0.055 on EEG from 123 subjects (p<3.65e-8). The direction is mechanistically active: ablating it collapses sentiment accuracy by 5.5-37.2 pp across three LLMs vs. at most 0.88 pp for matched random directions (z>12). A 2-parameter classifier trained on text labels transfers to images (AUC 0.961), audio (0.764), and brain recordings (0.828) without target-modality labels; a generic 16-D subspace stays at chance (0.525). The recipe is bounded to continuous attributes -- seven tests on categorical concepts return near-chance -- and steering is family-specific (Llama/Mistral yes, Qwen/Gemma no).
To better understand the relationship between social anxiety and excessive reassurance seeking, the current experimental study will focus on the interpersonal consequences of reassurance seeking from the reassurance provider's perspective. In the current study, we aim to answer the following research questions: 1. How does excessive reassurance seeking affect the quality of reassurance provided over multiple attempts for reassurance? 2. Does the closeness of the relationship (close other versus acquaintance) moderate the quality of the reassurance provided? 3. How does the reassurance provider’s momentary emotional experience (i.e., Self-Assessment Maniken emotional valence and arousal ratings after each trial) change across successive reassurance attempts, and is this trajectory moderated by relationship condition (close other vs. acquaintance)? 4. What are the emotional and interpersonal consequences of excessive reassurance seeking based on the perspective of the reassurance provider? Specifically, how will providing reassurance multiple times impact the reassurance provider, in terms of their negative and positive affect, their perception of the interaction task, and feelings of relationship closeness with the interaction partner after the task? In general, will the reassurance provider experience emotional and interpersonal strain after providing excessive reassurance? 5. Will emotional and interpersonal strain for the provider be greater when imagining providing reassurance to an acquaintance or a close other? Using an online design, participants are randomized to either an imagined close other or acquaintance condition. In each condition, participants are prompted to provide repeated reassurance to a central character whose reassurance-seeking attempts are scripted by the researchers to align with social anxiety themes. All participants also complete various ratings and survey questionnaires.
Front mid-vowel phonemes /e/ and /ɛ/ are contrastive in Gallego, while Spanish contains the phoneme /e/ and English contains the phoneme /ɛ/. This study investigates how Language Mode, Language Dominance, and L3 proficiency in Spanish-Gallego early bilinguals affect front mid-vowel production in L3 English. Language Mode (Grosjean 1985) represents the real-time activation of a speaker’s languages and the associated processing frameworks, heavily influenced by environmental and psychosocial factors. We manipulate participants' Language Modes using story-retelling and sentence-reading tasks across their languages. The resulting Euclidean distances between vowel tokens will be measured and analyzed against Bilingual Language Profile (Birdsong, Gerken, and Amengual 2012) Language Dominance ratings and self-reported English proficiency. We expect to find that participants with higher proficiency in English will have greater distinction between /e/ and /ɛ/ phonemes across all three languages, that stronger Language Dominance of Gallego over Spanish will correlate with greater distinction between these phonemes, and that activation of Gallego or English Language Mode will also correlate with a greater distinction on average for speakers. We anticipate that participants with low self-reported English proficiency will see greater distinction between these phonemes in the Gallego Language Mode conditions, but not within English Language Mode, following Escudero's (2005) Second Language Linguistic Perception model and it's extension to phonological production as proposed by Casillas and Simonet (2018).
The article describes texts generated by artificial intelligence, with an emphasis on Ukrainian-language material, which remains understudied. The aim of the study was to identify specific identifying characteristics of AI texts by comparing their semantic, structural, and stylistic parameters with texts written by humans. The study combined systematic analysis and synthesis, a comparative approach, content analysis, and quantitative linguistic methods (Type–Token Ratio, syntactic complexity analysis by T-unit), as well as semantic modeling, fact verification, and semantic-stylistic analysis. It has been proven that Ukrainian-language AI texts formally meet the basic criteria of textuality (cohesion, coherence, articulation), which are implemented through the probabilistic combination of templates rather than the author’s cognitive and communicative activity. Typical markers of machine generation have been identified: template composition (introduction – main part (3–5 subtopics) – conclusion), homogeneous paragraphs of “average” length, predominance of direct word order, presence of passive constructions, excessive frequency of formal connectors, structural and lexical monotony, errors in word usage. Semantic analysis revealed a combination of formal correctness with factual “hallucinations,” low information density, a predominance of neutral style, superficial, statistically determined expressiveness, and emotional masking. It was concluded that texts generated by artificial intelligence constitute a separate linguistic phenomenon with its own set of characteristics, which requires a special typology and a flexible, updatable analysis methodology. The risks to linguistic norms, speech culture, and information security are emphasized, as well as the need to develop critical competence in users regarding the perception of AI content.
Abstract This chapter focuses on Les sons du français, Passy’s seminal work, which appeared in twelve editions. It traces the evolution of his scientific thinking through the revisions and additions made across these editions. Beyond a detailed overview of the segmental system, the chapter offers an in-depth analysis of Passy’s original views on stress—particularly initial stress—and the prosodic structure of verse, the palatal nasal consonant, schwa, and liaison behaviour. The chapter demonstrates that both schwa and liaison patterns have remained remarkably stable since Passy’s time. It also takes into account variation across different speech registers and highlights Passy’s progressive approach to variation and linguistic norms in language teaching.
The early posterior negativity (EPN) is a mid-latency event-related potential (ERP) component reliably enhanced by emotionally arousing visual cues. Recent work suggests that modulation of the EPN might depend to some extent on evocative cues featuring animate content. We tested this possibility by recording EEG while 80 participants viewed pleasant, neutral, and unpleasant scenes depicting people, objects, or landscapes. People and object scenes were selected to be comparable in composition and arousal ratings, to enable a direct assessment of the impact of scene animacy, separate from emotional intensity. Results showed robust EPN modulation by emotional content across both people and object scenes, with no significant interaction across arousal-matched scenes. This finding further dissociates the EPN from proximal event-related potential components associated with face and body perception and supports its value as an early marker of emotional perception, reliably driven by emotional intensity across multiple domains of visual cues.
Teacher creativity plays a central role in fostering creative learning environments. However, most evaluations of creativity training focus on performance outcomes and self-report measures rather than changes in underlying cognitive organisation. We investigated whether an eight-month certified teacher-training course based on the Scientific Creativity in Practice (SCIP) framework was associated with changes in Austrian secondary teachers’ creative performance, semantic organisation, and professional mindsets. Seventeen teachers completed pre- and post-training assessments, including the Alternative Uses Task, Verbal Fluency, Word-Sentence-Construction, Behavioural Forma Mentis associations with valence ratings, and written reflections. We assessed originality in the AUT with two independent AI-based systems. Semantic and affective changes were modelled through cognitive networks, mindset streams, and measures of emotional framing. At POST, teachers had higher AUT originality scores and generated largely different concepts than at PRE. They produced broader conceptual repertoires and larger semantic networks, although other structural changes differed across tasks. Affective changes were more modest. Positive valence predominated at both measurement points and became slightly more common, while negative valence declined. Separate PRE and POST mindset streams showed substantial pathway turnover but remained predominantly positive. These findings suggest that creativity training may support changes in how teachers organise and connect professional knowledge, and does not only impact how creatively they perform. Furthermore, our findings show that cognitive network analyses can complement traditional creativity assessments by revealing changes in semantic organisation and professional mindsets that remain invisible in performance scores alone.
Embodied theories of language emphasize the role of sensorimotor experience in linguistic knowledge. Central to testing these theories is the creation of large datasets of linguistic norms, which contain judgments about a word's sensorimotor associations and can be used to predict human behavioral or brain data - sometimes in contrast to competing variables, such as those derived from distributional language models. Yet many of these datasets contain judgments about words in isolation, despite the fact that most words are ambiguous, making it difficult to determine which meaning of a word is characterized by its rating (e.g., "wooden table" vs. "data table"). In the current work, we introduce a new lexical resource (directly inspired by the Lancaster sensorimotor for 112 English words, each rated in four different contexts (448 sentences total). We demonstrate: first, that these ratings encode overlapping but distinct information from the Lancaster sensorimotor norms; second, that decontextualized ratings likely reflect the more dominant meaning of ambiguous words; third, that homonyms have more distinct sensorimotor profiles than polysemes; fourth, that the contextualized sensorimotor distance between two uses of an ambiguous word predicts human judgments about semantic relatedness; and fifth, that ratings derived from GPT-4 align reasonably well with human judgments. We conclude by suggesting that contextualized ratings like these can be used both to inform competing theories of semantic representations and also to evaluate or "probe" the ability of LMs to recover sensorimotor information.
In this research paper, the author studied the English youth slang language. The subject of the study is a number of difficulties in identifying patterns and factors contributing to the updating and subsequent classification of the slang vocabulary. The research material was based on popular slang units proposed by ChatGPT. The objective existence of this phenomenon is in little doubt, but its characteristics are characterized by instability and dynamism. There is a gradual blurring of the boundaries of the literary and linguistic norm, which is accompanied by the active penetration of slang elements into various functional styles. Since slang does not fit into the traditional structure of the book language, this causes certain difficulties in its use and linguistic interpretation. Based on foreign literature, four factors and eight sources of the appearance of the replenishment of the vocabulary of youth slang in English were identified. In a comprehensive and detailed description, methods of theoretical research were used, contextual analysis: analysis of usage on platforms, etymological analysis: tracing origin, classification of mechanisms (by types of word formation and source), comparative analysis: usage in similar communities of different countries. The novelty of the research lies in a comprehensive approach to studying not only the structural and semantic characteristics of slang, but also the socio-cultural factors that determine its dynamics. The article is of interest for a deeper understanding of the linguistic creativity of young people, and may also help clarify theoretical ideas about ways to replenish the vocabulary of the English language in the digital age. The study of these processes not only enriches our understanding of language, but also allows us to trace the profound socio-cultural changes reflected in the daily speech of young people.
BACKGROUND: Around one in five people who use cannabis develop a cannabis use disorder (CUD) during their lifetime. Attentional bias toward substance-related stimuli is theorised to drive substance-seeking behaviour, contributing to the development of addiction and relapse. There is mixed evidence of cannabis-related attentional bias in individuals with CUD and its association with cannabis quantity, CUD severity, and confounders (e.g., alcohol, nicotine use). We aimed to examine cannabis attentional bias in non-treatment-seeking adults with a CUD (n = 74) versus controls (n = 30), and in relation to levels of cannabis and nicotine use, adjusting for alcohol use. METHODS: Attentional bias was measured using a visual probe task. To detect attentional bias differences between groups (CUD, controls), we ran linear mixed-effect models with reaction times (RTs) to cannabis versus neutral images as the outcome variable, adjusting for intra-individual variability and stimulus onset asynchrony (SOA, 200/500 ms). Within the CUD group only, we explore the association between attentional bias and cannabis quantity, craving, Cannabis Use Disorder Identification Test - Revised (CUDIT-R) scores, image valence ratings, and nicotine use. All models were adjusted for alcohol use. RESULTS: No significant effects were found for group, cannabis quantity, craving, CUDIT-R scores, or nicotine use on attentional bias toward cannabis cues. CONCLUSION: Findings suggest that non-treatment seekers with CUD do not exhibit attentional bias to cannabis cues. Replication in treatment-seeking samples is needed to determine whether attentional bias has clinical relevance, using objective measures (e.g., eye tracking).
Introduction Parsed Early English Books Online - Text Creation Partnership (LDC2026T09) (EEBO-TCP) was developed by the Linguistic Data Consortium. It is a part-of-speech tagged and syntactically parsed version of the EEBO-TCP collection of Early Modern English texts. The corpus consists of 59,433 texts dating primarily from 1600-1700, with a smaller number of texts from earlier and later periods. Parsed EEBO-TCP was developed to support research in historical linguistics, the study of English syntax and language change, and natural language processing of historical texts. Data The corpus contains 48.6 million parsed sentences (trees) comprising more than 1.5 billion tokens. The parses were produced automatically using a parser trained on the Penn Parsed Corpus of Early Modern English, part of the Penn Parsed Corpora of Historical English (LDC2020T16). The automatically generated parses were not manually reviewed. Parsed EEBO-TCP includes the CorpusSearch 2 program and associated documentation. This tool allows users to search the data for syntactic structure, word sequences and words. An alternative version of CorpuSearch 2 for use on very large corproa is also included in this release. Text is provided in two formats: part-of-speech tagged text is presented as.pos files, and syntactically parsed text is presented as Penn Treebank-formatted.psd files. All text is UTF-8 encoded. Updates No updates at this time.
Dependency distance is a key measure of syntactic complexity and processing constraints, but as a scalar cannot capture how information is distributed between a head and dependent. We analyze dependency spans—the endpoints and intervening words—as position-aligned units. Interveners lie outside the binary dependency but constitute its sequential processing context. Using Universal Dependencies treebanks and XGLM-2.9B, we estimated word-level surprisal for distances 4–10 across 22 languages, yielding 154 mean curves. Dynamic time warping and clustering identified an approximately monotonic decline and a nonmonotonic contour with an initial decline, stable middle, and final rise. Membership was stable across distances in 20 languages; Russian had three Type 1 and four Type 2 curves, whereas German had six Type 1 and one Type 2 curve. Segmented models favored three stages for both types, differing mainly in the final stage. Principal component analyses revealed a more dispersed latent structure in the middle stage and concentration around fewer variables at the edges. The final-stage contrast was associated with dependency direction and verb roles. Dependency-span analysis thus complements dependency syntax with a position-sensitive account of linear realization, revealing cross-linguistic information patterns that dependency length alone cannot recover.
The proliferation of artificial intelligence (AI) technologies has transformed academic research practices across higher education institutions around the world. While AI-powered tools such as large language models, neural machine translation systems, and automated writing assistants offer significant opportunities for enhanced research productivity, they also pose complex ethical and linguistic challenges. These issues are particularly acute in multilingual and postcolonial academic contexts, where researchers are often required to navigate between multiple languages, traditions, and knowledge systems. This study explores the ethical implications of AI-assisted research in Algerian higher education and presents a context-sensitive framework for responsible AI use in multilingual hypothesis-based research. Using a convergent mixed-methods approach, this study examines the experience of 45 master students at the English department of Batna 2 University enrolled in a research methodology course. The results indicate that structured AI ethics education significantly improves students’ ethical decision-making skills, awareness of algorithmic bias, and their ability to engage critically with AI generated outputs. The study also demonstrates that mainstream AI systems tend to favor Anglophone linguistic norms, which could marginalize local epistemologies and multilingual scholarly practices. In response, this article proposes the Algerian AI Ethics Triade: a framework based on the principles of Transparency, Cultural Relevance, and Human Primacy. The framework offers practical recommendations for researchers, educators, and policymakers who want to incorporate AI into academic research without compromising integrity, linguistic diversity, and intellectual autonomy. The findings contribute to emerging discussions on responsible AI governance and offer implications for multilingual higher education systems across the Middle East and North Africa (MENA) region.
ABSTRACT Communication and language exist as complex and intertwined systems influenced by several overlapping dimensions that cannot be comprehended separately. In this research, the multi-dimensional nature of communication and language is explored using an interdisciplinary approach which considers linguistic aspects, sociocultural background, technological dimension, and cognition. The study employs a sequential mixed methods approach which includes the qualitative analysis of 48 cases of authentic communication (24 instances of face-to-face interaction and 24 examples of digital interaction) and the quantitative survey of 312 participants from three linguistic communities. Findings indicate that technological platforms have the potential to radically alter traditional linguistic norms by emphasizing sociocultural and cognitive components in such a way that hybrid linguistic practices develop. Multimodality, adaptive politeness, code-meshing, and platform-related linguistic features were used by participants in order to accomplish linguistic goals in different contexts of cognitive and sociocultural demands. Results from the factor analysis showed four correlated but independent dimensions that explained 68.4% of the variance, whereas results from multiple regression models showed significant predictors of technological factors on linguistic adaptation (β =.41, p <.001) and sociocultural adaptation (β =.37, p <.001). There was a significant negative correlation between cognitive load and communicative satisfaction in high-stakes intercultural digital communication. This paper points out some research gaps that still exist in terms of examining the combination of these aspects and presents a multidimensional approach. The results can be useful from a theoretical point of view and have several applications. Some limitations regarding the sample size and measuring the cognitive process are discussed.
Social media has significantly reshaped the linguistic practices of South India, giving rise to new forms of vocabulary, syntax, and hybridized expressions. This qualitative study examines the role of platforms such as WhatsApp, Instagram, and Twitter in facilitating a blend of regional languages like Kannada, Tamil, Telugu, and Malayalam with English, creating a unique digital vernacular. By employing interviews, focus group discussions, and content analysis of over 500 social media posts, the research delves into the sociolinguistic dynamics that drive these transformations. Findings reveal that digital communication is not only a space for creativity and identity assertion but also a reflection of socio-cultural shifts. The study identifies key patterns of code-switching, platformspecific adaptations, and the emergence of new linguistic norms, while also exploring generational perspectives on language evolution. This research underscores the importance of understanding digital language as a living, adaptive phenomenon that mirrors the region’s linguistic and cultural diversity. The implications extend to areas such as language education, digital literacy, and cultural preservation, offering a nuanced perspective on how social media redefines communication in multilingual contexts.
The proliferation of artificial intelligence (AI) technologies has transformed academic research practices across higher education institutions around the world. While AI-powered tools such as large language models, neural machine translation systems, and automated writing assistants offer significant opportunities for enhanced research productivity, but also pose complex ethical and linguistic challenges. These issues are particularly acute in multilingual and postcolonial academic contexts, where researches are often required to navigate between multiple languages, traditions, and knowledge systems. This study explores the ethical implications of AI-assisted research in the Algerian higher education and presents a context-sensitive framework for responsible AI use in multilingual hypo thesis-based research. Using a convergent mixed-methods approach, this study examines the experience of 45 master students at the English department of Batna 2 University enrolled in a research methodology course. The results indicate that structured AI ethics education significantly improves students’ ethical decision-making skills, awareness of algorithmic bias, and their ability to engage critically with AI generated outputs. The study also demonstrates that mainstream AI systems tend to favor Anglophone linguistic norms, which could marginalize local epistemologies and multilingual scholarly practices. In response, the article proposes the Algerian AI Ethics Triade: a framework based on the principles of Transparency, Cultural Relevance, and Human Primacy. The framework offers practical recommendations for researchers, educators, and policymakers who want to incorporate AI into academic research scholarly without compromising integrity, linguistic diversity, and intellectual autonomy. The findings contribute to emerging discussions on responsible AI governance and offer implications for multilingual higher education systems across the Middle East and North Africa (MENA) region
Sentiment analysis can be considered a critical task in the field of Natural Language Processing (NLP). It is applied not only in product reviews but also in areas like healthcare, education, services assessment, and so on. While there have been remarkable advancements in building text-based sentiment models, the problem of the interaction between structured and unstructured data for sentiment analysis has not been addressed adequately. Specifically, current systems use scale ratings and descriptive texts separately without considering how one can complement the other. This chapter provides an in-depth discussion of the dual-channel sentiment model based on the Average Cumulative Rating Matrix Factorization (ACRMF) model presented in Kumar et al. [7]. In addition to utilizing internal review comments, namely structured numerical scale ratings, and external review comments, open-ended descriptive text, the approach creates a common sentiment score based on the normalized averaging method. The mathematical concepts underpinning the framework include Bayesian probability theory, the Naïve Bayes classifier, Part-of-Speech tagging, the Stanford Sentiment Treebank, and Recursive Neural Networks. Three research hypotheses are formulated, which are tested on two real datasets: Tourpedia and Kaggle Travel Review Rating. Experiments are conducted for two different train-test splits, three different cut-off values, and seven baseline methods. Under all experimental conditions, the dual-channel sentiment model outperforms its single-channel counterpart in a statistically significant way. This section is concluded with a limitations analysis and an outline for further research directions.
This is a structured service evaluation of Tonewise, an iOS communication-reflection tool grounded in Nonviolent Communication, currently in closed beta. The evaluation is positioned as a Phase 1 feasibility-and-acceptability study, with qualitative reflection as the primary endpoint and quantitative measures as secondary descriptive anchors. It is not a research study under the UK Health Research Authority (HRA) definition: it does not introduce a new intervention, does not aim to generalise beyond the product's user base, and does not require REC or HRA review. It is conducted in line with HCPC standards of conduct, performance and ethics, and the BPS Code of Human Research Ethics. This registration replaces an earlier withdrawn registration (https://osf.io/84cuk/overview), retired before any data collection because the design was substantially restructured following pre-launch review. The substantive changes are: TCCS reduced from 7 to 6 items; weekly battery rewritten as one objective tone-check count, one conditional affect rating, and one optional free-text note; DERS-16 dropped at close-out and retained at baseline only; six qualitative close-out prompts named; recommendation Likert added as primary acceptability endpoint; and analysis plan updated to qualitative-primary, secondary-quantitative-descriptive. No participant has consented and no data exists under the prior version. Approximately 10–15 fellow clinicians (registered psychologists, psychiatrists, and psychotherapists) will be recruited as evaluators. Participants use Tonewise in their own life over six weeks (12 May – 22 June 2026) and contribute data both as users (personal experience) and as clinicians forming a professional view of who in their practice, if anyone, the tool might be useful for. The primary endpoint is qualitative: a six-prompt close-out written reflection (around 600 words total) covering shifts over the six weeks, what helped, what didn't help or got in the way, clinical-view-for-whom, clinical-view-of-concerns, and an open final prompt. The primary acceptability endpoint is a likelihood-to-recommend Likert (0–10) paired with an open rationale, with explicit conflict-of-interest mitigating framing that invites low or critical ratings. Secondary quantitative endpoints are a 6-item study-specific Tonewise Communication Confidence Scale (TCCS, baseline-to-close-out paired); a weekly tone-check count read directly from the in-app home-screen counter (a rolling 7-day window); and a weekly conditional affect rating reflecting how messages that mattered landed after sending. The DERS-16 is administered at baseline only for sample characterisation, not repeated at close-out, given anticipated floor effects in this clinician sample and the qualitative-primary framing. Analysis follows reflexive thematic analysis (Braun & Clarke, 2019) for qualitative data, with a single coder, peer-clinician sense-check, and a reflexive coding journal kept throughout. Quantitative analysis is descriptive, with Wilcoxon signed-rank for paired TCCS change reported alongside explicit small-N caveats. The distribution of recommendation-likelihood ratings will be reported descriptively (median, IQR, full distribution) alongside thematic analysis of the open rationales. Weekly tone-check counts and conditional affect ratings will be reported as time-series, with attention to within-person trajectories rather than between-group means. Conflict of interest: the investigator (Dr Louise Legg, Counselling Psychologist, HCPC, Doctorate) is the founder and sole shareholder of Tonewise Limited (ICO registration ZC127716) and has a direct financial interest in the product's commercial success. This is declared on the participant information sheet, in this registration, and will be declared in all outputs. Outputs comprise an open-access preprint on PsyArXiv (target submission week of 11 August 2026), a plain-language summary returned to each participant before the preprint goes live, and a public summary on usetonewise.com. All findings, including null and negative results, will be reported transparently.
Sparse Mixture-of-Experts (MoE) routers commonly use the same scores both to select experts and to weight their already-computed outputs. We study whether these two roles, dispatch and aggregation, should be coupled. On pretrained OLMoE-1B-7B, we keep selected Top-8 expert IDs, expert computation, and total selected router mass fixed and change only within-set aggregation. A structured oracle improves full-horizon cross-entropy by 0.0160 +/- 0.0039 across three seeds; the router's top-scored expert is the counterfactual-best vertex only 17.2% of the time, with router-utility Spearman 0.030. We therefore train Fixed-Dispatch Adaptive Aggregation (FDAA), a 301K-parameter post-compute head optimized directly with the language-modeling objective while freezing the backbone, router, and experts. On OLMoE, FDAA improves fresh WikiText-103 test by Delta CE = -0.1523 +/- 0.0031 across three seeds, and mixed-domain training gives robust gains on WikiText-103, C4, and held-out Penn Treebank under frozen confirmatory evaluation. We also replicate the fixed-dispatch audit on DeepSeek-V2-Lite, which uses Top-6 routed experts plus shared experts. Best-vertex headroom remains significant on WikiText and C4, while router Top1 identifies the best selected expert in only 12.5% and 16.7% of audited examples. In a one-seed mixed-domain replication, FDAA improves locked WikiText and PTB, while C4 is statistically neutral. These results support a cross-architecture distinction between expert selection and expert commitment.
This dataset contains multimodal neuroimaging and physiological data from a study investigating the effects of Targeted Memory Reactivation (TMR) during REM sleep on emotional reactivity. Participants encoded affective images paired with sounds, received auditory cues during subsequent REM sleep, and were rescanned 48 hours later during arousal rating tasks in an fMRI scanner. The dataset includes structural and functional MRI, polysomnographic recordings with EEG during sleep, heart rate measurements, and behavioral ratings across three sessions spanning two weeks.
Abstract Depression is marked by blunted affective responses to context, which interoceptive accounts trace to altered neural representations of bodily states. Yet this evidence mainly concerns response magnitude, not how quickly affect is updated when contexts change. Here we tested whether depressive symptom severity is related to delayed affective updating, and whether cortical dynamics tracking cardiac states account for this delay. To this end, we applied a movie-watching paradigm with independently defined contextual shifts, continuous affect ratings, electroencephalography, and electrocardiography in individuals spanning a continuum of depressive symptoms. Combining deep representation learning and a dynamical systems framework, we quantified how quickly (speed) and how sharply (angle) cardiac-coupled cortical representations reorganized at each shift. Greater symptom severity predicted longer latency to enter the context-congruent affective state across contextual shifts, regardless of valence. In a cross-sectional mediation analysis, slower speed, but not angle, accounted for this association. This mediation was specific to depressive symptoms, contextual shifts, and cardiac-coupled neural dynamics. These findings extend the embodied account of depression from blunted affective intensity toward its inflexible updating at moments of contextual shift, and offer a broadly applicable framework for quantifying brain-body dynamics across affective dysfunctions.
The Korean adnominal ending \texttt{ETM} occurs in diverse noun-modifying constructions, including relative-clause-like modifiers, adjectival and copular forms, bound-noun constructions, and lexicalized expressions. This paper argues that \texttt{ETM} is not a direct marker of relative-clause structure, but a morphological exponent shared by several adnominal constructions. We propose a corpus-based typology that distinguishes these constructions using predicate type, auxiliary structure, argument-structural compatibility, head-noun restriction, and lexicalized patterns. We operationalize the typology as a construction-sensitive annotation layer for the KLUE dependency treebank, implemented through an ordered rule-based procedure and evaluated by manual validation. Productive relative-clause-like uses account for 39.4\% of the analyzed instances; the remainder consists mainly of adjectival, copular, bound-nominal, modal, temporal, and collocational constructions. The findings show that Korean relative-clause-like modification cannot be identified from adnominal morphology alone.
Abstract Transcendental Logic (TL) offers a mathematisation of the unsayable background-reality ( noumenal domain, N-domain) that underlies the logical models ( phenomenal domain, P-domain). According to TL, the N-domain is unsayable not because it is unstructured or inaccessible, but because its structure is governed by the laws of orthomodular logic. In contrast, the P-domain represents reality as a structure of clearly distinct units of meaning; thus, its structure is governed by the laws of classical bivalent logic. This immediately raises two questions: on what basis does TL claim that the N-domain is governed by orthomodular logic, and into what kind of structure the N-domain is organised? The answer lies in TL’s philosophical roots – namely, in Béla Weissmahr’s transcendental metaphysics. His central logical method is dialectic, which governs both the structure of the N-domain and the N-P relation. The structure of the N-domain is analogia entis (the analogy of Being): a dynamic network of analogical-dialectical relations among beings. TL argues that Weissmahr’s dialectic can be expressed in orthomodularity (a dialectical pair is a pair of non-commuting elements), and thus formalises analogia entis as the structure of the N-domain. In Weissmahr’s spirit, TL argues that the dynamic-analogical relations among beings store the information later articulated in the P-domain as structured meaning. The act of this articulation is what TL calls univocalisation. Importantly, TL does not conceive of univocalisation as an act of cognition performed by a particular cogniser. Rather, TL understands univocalisation as the articulation capability of the relational structure itself – independent of any subject or agent. This article does not present the whole of TL, but only its philosophical and algebraic underpinnings. One of its central achievements is the distinction between two interpretations of analogia entis – a structural one and a respective one – and the exposition of their internal relation. In this context, respectivity refers to the algebraic formalisation of the relations among beings as determined by a particular respect. It provides the basis for both relational information storage and univocalisation. The corresponding theorems and proofs are presented in the Appendix. TL thus occupies a new position on the map of logical inquiry. It does not investigate the inferential or linguistic norms of valid reasoning, but rather how meaning is univocalised from the underlying N-domain – understood as analogia entis.
Abstract Major depressive disorder (MDD) is associated with variation across several linguistic features, including more negative tone, less positive tone, greater use of first-person pronouns, and reduced use of affiliation words. This research has largely relied on analyzing texts from clinical samples, autobiographical reports of negatively valenced content, or unprompted narratives. This represents a significant gap in the literature, as large-scale language datasets (e.g., social media) increasingly capture individuals with depressive symptoms outside of MDD who express both positive and negative self-relevant content. However, whether linguistic features vary with depressive symptoms outside the context of MDD and whether these associations differ based on the emotional valence of the recalled content (i.e., positive vs. negative) remains unclear. In the present study, undergraduate students ( N = 457) were randomly assigned to write about a sad or happy personal experience in as much detail as possible. We assessed negative tone, positive tone, first-person pronoun usage, and affiliation words using the Linguistic Inquiry and Word Count (LIWC) program. Greater depressive symptoms were associated with more negative tone and more first-person pronoun usage (i.e., greater self-focus) in the negative condition, as hypothesized, but depressive symptoms were not associated with linguistic features in the positive condition. Depressive symptoms did not relate to positive tone or use of affiliation words. Findings suggest that social-emotional biases present in depression may pertain to the processing of negative but not positive personal events and hold implications for identifying depressive symptoms in non-clinical and clinical settings and large linguistic databases.
Earlier studies of affect in spoken Finnish have largely been based on acted emotional expression, a relatively small number of speakers, and a narrow linguistic scope paired with predefined emotional categories. While previous studies have reported consistent findings related to acoustic–phonetic features associated with both expression and perception of affect in Finnish, no study has investigated how these findings generalize to spontaneous Finnish spoken by a wide range of non-professional speakers. The current study investigates how affect is encoded in acoustic–phonetic features of spontaneous Finnish. By using a recent large-scale affective speech corpus containing spontaneous speech from thousands of individuals with differing backgrounds and with subjective listener ratings of valence and arousal, we first test whether findings from studies with acted speech generalize to spontaneous Finnish. We also report results from an exploratory analysis with a wider range of speech features. As a result, we find that the intonation, voice quality, and rhythmic findings from studies of acted speech largely replicate in spontaneous speech. In addition, we find statistically significant relationships between affective ratings and several new speech features. In general, the mean of log-F0, speaking rate, the mean and variance of jitter, shimmer, harmonics-to-noise ratio, and variance of the difference of F0 harmonics were found to have the highest correlations in relation to arousal. In the case of valence, the mean of log-F0 and the mean and variance of HNR showed the highest correlations. Overall, the results demonstrate how affective information is richly encoded in various aspects of Finnish speech.
Abstract Cities are experienced in motion, yet urban soundscape research has largely assumed stationary viewpoints, overlooking the perceptual role of the walking perspective. Here, we show that this mismatch fundamentally blinds us to how walking views reshape urban soundscape perception. Using a within-subject, repeated-measures audiovisual design, 34 participants evaluated 18 urban streets under standing-view (SV) and walking-view (WV) conditions paired with identical binaural audio, providing both continuous real-time affective ratings and retrospective soundscape evaluations. We found that, first, rapid perceptual stabilisation occurred: taking the standing view as the baseline, real-time affective responses under the walking view initially diverged but consistently converged within the first 10 s across all participants and streets. Second, despite this early stabilisation, the walking perspective reshaped overall perceptual outcomes by selectively reweighting the salience of urban sounds. Among streets showing significant effects, transient sounds, including alarms and sirens, became more salient, whereas continuous background sounds, including traffic and human activity, became less salient. The walking perspective also polarised overall sound environmental evaluations, making positively evaluated streets more positive and negatively evaluated streets more negative, while reducing inter-individual variability. These findings demonstrate that the walking perspective is an active component of urban soundscape perception, shaping both the temporal dynamics of perceptual adaptation and the overall perceptual weighting of urban sound environments, with broader implications for understanding how environmental perception unfolds in motion.
Cement and concrete account for around 8% of global CO2 emissions and remain among the most hard-to-abate sectors, alongside steel and chemicals. Demand for these materials is projected to grow substantially over the coming decades, particularly across the Global South, driven by rapid urbanization and infrastructure development. While numerous decarbonization technologies and strategies have emerged and are being implemented, the absence of quantitative, context-specific definitions of low-carbon concrete make it difficult to quantify the extent of decarbonization, especially in developing economies. Using India as an illustrative case, where cement production is projected to grow roughly five-fold by 2070, this perspective examines why low-carbon concrete ratings and definitions applied in the developed world cannot be directly implemented in developing-country contexts. It also proposes a phased strategy towards quantitative definitions for the organized and unorganized concrete sectors. This offers a practical pathway to closing the definitional gap that currently limits the efficacy and accounting of cement and concrete sector decarbonization efforts in the global south.
The aim of the paper is to present a first attempt at annotating Information Structure roles in syntactic treebanks of the Universal Dependencies collection, discussing theoretical considerations and practical methodological questions while presenting our core annotation principles.We focus on constructions in which Topic or Focus is overtly marked through (morpho)syntactic means.The proposed annotation is illustrated using examples from five languages: Wolof, Japanese, Tundra Nenets, Hungarian, and Italian.
: Increasing research has applied nature-based interventions to improve mental well-being and productivity in offices. However, how typical design characteristics, such as plant quantity and window view access, support attention restoration following ego-depletion in open-plan offices remains unclear. Furthermore, studies conducted in Chinese offices remain particularly scarce. This study conducted four randomised controlled experiments within a virtual open-plan office to investigate the restorative effects of indoor plant quantity and access to nature and urban window views on participants’ performance following ego-depletion. Furthermore, the effects of these interventions were compared. The four experiments included 132 (58.3% female), 126 (57.9% female), 134 (57.4% female), and 96 (52.1% female) participants, respectively. Their performances were measured using biometric sensors (physiological indices: heart rate variability (HRV) & electrodermal activity (EDA)), Psychomotor Vigilance task and Stroop tests (cognition), Positive and Negative Affect Schedule (mood), and a self-developed questionnaire (affective qualities & satisfaction). Results revealed that indoor plants (all amount levels) improved HRV and lowered EDA following ego-depletion; however, they did not affect mood and cognition. Furthermore, only a large amount enhanced affective qualities. In addition, medium and high access to nature window views reduced EDA and improved affective qualities. However, only high and medium window access increased positive and reduced negative mood, respectively. Access to urban window views improved HRV and affective qualities, while only medium access lowered EDA. Thus, plants were superior to window views in physiological and attentional restoration, whereas window views elicited higher positive affective ratings.
The recitation of the Qurʾān occupies a central position in the ritual and devotional life of Muslims. In Arabic, this practice is commonly referred to as tilāwat al-Qurʾān and its origins go back to the time of the Prophet Muḥammad. Qurʾānic recitation is a required component of the five daily prayers (ṣalāt), with both Sunni and Shiʿi Muslims regularly reciting al-Fātiḥah, the opening chapter of the Qurʾān, along with additional verses or chapters. Today, most Muslim communities recite the Qurʾān according to the reading attributed to ʿĀṣim ibn Abī al-Najūd (d. 744), as transmitted by Ḥafṣ ibn Sulaymān al-Asadī (d. 796). However, within the Sunni qirāʾāt tradition, there are ten canonical readings, including that of ʿĀṣim. Each of these readings is known as qirāʾah (plural: qirāʾāt). In this entry, "canonical" refers to the ten qirāʾāt recognized within the Sunni qirāʾāt tradition. This canonical status, however, was not established all at once. The seven readings first achieved it through Ibn Mujāhid's selection, while the additional three attained canonical status through later scholarship, especially the works of Ibn al-Jazarī. The term "shawādhdh" (singular: "shādhdh"), here used broadly for non-canonical readings, denotes readings that fall outside these ten, whether because they failed to meet one or more of the established criteria for acceptance, namely a sound chain of transmission (isnād), conformity with the orthography of the ʿUthmānic codices, and adherence to Arabic linguistic norms, or because they did not attain wide recognition among qirāʾāt scholars. The seven qirāʾāt achieved canonical status and became central to Qurʾānic recitation after Ibn Mujāhid (d. 936) selected them, in al-Sabʿa fī al-qirāʾāt, from among the numerous variant readings circulating in his time. The compilations of 25 readings by Abū ʿUbayd al-Qāsim ibn Sallām (d. 838) and 22 readings by Ibn Jarīr al-Ṭabarī (d. 923) attest to the significant plurality of variant readings circulating in the ninth and tenth centuries. Ibn Mujāhid selected seven qirāʾāt from Mecca, Medina, Basra, Damascus, and Kufa on the basis of transmission, consistency with the ʿUthmānic codices, conformity to Arabic linguistic norms, and broad recognition among qirāʾāt scholars. His decision to exclude less well-known readings from his compilation significantly shaped how later scholars approached the study and recitation of other variant readings. For instance, some scholars, such as Ibn ʿAṭiyya (d. 1147) and al-Nawawī (d. 1277), explicitly stated that readings outside the seven qirāʾāt constitute non-canonical readings and are impermissible for recitation during the daily prayers, although other scholars continued to recognize the validity of additional readings that later came to be counted among the canonical readings. Ibn Jinnī (d. 1002) similarly categorized readings beyond the seven as non-canonical, noting that he refrained from reciting them to prevent their dissemination among the broader community. In his al-Fihrist, Ibn al-Nadīm (d. 995) also classifies the readings into two main groups: the seven readings and non-canonical readings. Even though Ibn Mujāhid pioneered the canonization of the seven readings, it was the Andalusian scholars who played a key role in consolidating and disseminating the seven qirāʾāt across broad regions of the Islamic world through their works on the seven readings. For instance, most of the works on the seven qirāʾāt referenced by Ibn al-Jazarī in the introduction to his famous work al-Nashr were authored by Andalusian scholars. In particular, al-Taysīr by al-Dānī (d. 1053) and al-Ḥirz al-Amānī (also known as al-Shāṭibiyya) by al-Shāṭibī (d. 1194) have remained foundational texts in qirāʾāt education on the seven readings to the present day. Al-Sakhāwī (d. 1245), a student of al-Shāṭibī, and his commentary on al-Ḥirz al-Amānī were instrumental in establishing al-Ḥirz al-Amānī's reputation among qirāʾāt scholars. Regarding the prominence these works achieved among qirāʾāt scholars, al-Mashīnī, in his Madrasat al-Tafsīr fī al-Andalus, a work devoted to Andalusian contributions to Qurʾānic scholarship, observes that upon examining biographical entries in Ibn al-Jazarī's Ṭabaqāt al-Qurrāʾ (Biographies of qirāʾāt Scholars), one frequently encounters phrases such as "He read al-Taysīr with so-and-so" or "He memorized the Shāṭibiyya," from which al-Mashīnī concludes that al-Andalus occupied a particularly prominent position in the field of qirāʾāt. In light of the widespread influence of al-Shāṭibiyya and al-Taysīr, Ibn al-Jazarī explained that one reason for composing his work on the ten qirāʾāt was that people had almost come to believe that the only accepted readings were the seven contained in al-Shāṭibiyya and al-Taysīr. Ibn al-Jazarī was not the first scholar to write on the ten qirāʾāt. More than ten scholars from the tenth to the fifteenth century, including Ibn Mihrān al-Iṣbahānī (d. 992) and Ibn Siwār al-Baghdādī (d. 1103), composed works on the ten readings. However, these works did not succeed in establishing the study of the ten qirāʾāt as a widely adopted standard in qirāʾāt curricula in the way that Ibn al-Jazarī's work did from the fifteenth century onward. Ibn al-Jazarī recounts that when ʿAbdallāh b. ʿAbd al-Muʾmin al-Wāsiṭī (d. 1339) traveled to Damascus intending to teach the ten readings, local qirāʾāt scholars sought to prevent him through judicial intervention on the grounds that he sought to teach readings beyond those found in al-Shāṭibiyya and al-Taysīr. The selection of the seven readings by Ibn Mujāhid in the tenth century, combined with the Andalusian scholars' works on the seven qirāʾāt, significantly strengthened the preference for the seven qirāʾāt in both Qurʾānic recitation and qirāʾāt education. This preference extended across Muslim laypeople as well as scholars from the tenth to the fifteenth centuries. Nevertheless, throughout this period, a number of scholars continued to transmit and defend the additional three readings alongside the seven.
В преподавании китайского письма автоматизированная проверка искусственного интеллекта (ИИ) стала широко используемым инструментом: она позволяет быстро выявлять грамматические ошибки и проблемы с выбором лексики в сочинениях студентов. Однако обратная связь ИИ часто носит механический характер и затрудняется адекватный ответ на потребности студентов в области логики написания, культурного выражения и креативного мышления. Эффективное сочетание этих двух инструментов с целью их взаимодополнения стало актуальной педагогической задачей, требующей глубокого изучения. Данное исследование углубленно анализирует механизмы взаимодополнения и способы интеграции ИИ и обратной связи учителя в реальных педагогических условиях. На основе глубинных интервью с 150 обучающимися изучена логика выбора студентов между автоматизированной проверкой ИИ и ручной проверкой учителя. Результаты исследования показали, что ИИ демонстрирует высокую эффективность при исправлении языковых форм, тогда как учитель выполняет незаменимую роль в области продвижения логики, культурного выражения и т.п. Авторы исследования считают, что при использовании ИИ для повышения эффективности процесса обучения необходимо уделять особое внимание развитию логического мышления студентов, чтобы технология действительно служила педагогическим целям. Практические данные подтверждают, что такое сотрудничество человека и машины не только усиливает осознание студентами языковых норм, но и способствует развитию их мышления и уверенности в написании сочинений. Однако технология остается вспомогательным инструментом: фундаментальное повышение качества обучения продолжает зависеть от глубокого понимания учителем потребностей студентов и постоянного вовлечения в образовательный процесс. In the teaching of Chinese writing, AI-powered automated evaluation has become a commonplace tool. It promptly identifies grammatical and lexical errors in student compositions. However, AI-generated feedback tends to be mechanistic and often fails to adequately address learners’ needs in areas such as writing logic, cultural expression, and creative thinking. How to effectively integrate these two approaches and achieve complementarity has thus emerged as a significant pedagogical issue that warrants in-depth exploration. This study investigates the complementary mechanisms and integration strategies between AI evaluation and teacher feedback within authentic teaching contexts. Through in-depth interviews with 150 learners, the research analyzes the rationale behind students’ preferences when they choose between AI-generated and instructor-provided feedback. The findings indicate that AI excels in the efficient correction of linguistic form, whereas teachers play an irreplaceable role in the development of logical coherence and cultural expression. The study argues that while AI can be leveraged to improve efficiency, greater emphasis should be placed on the guidance of students to strengthen their logical thinking, which ensures that technology genuinely serves pedagogical objectives. Empirical evidence shows that such human–machine collaboration not only enhances students’ awareness of linguistic norms but also promotes their cognitive development and writing confidence. Nevertheless, technology remains an auxiliary instrument. The fundamental improvement of teaching quality ultimately depends on teachers’ deep understanding of their students and their sustained investment in the educational process.
The presence of clinically significant clutter is a core diagnostic indicator of hoarding disorder. Ideally, the assessment of clutter in a dwelling requires direct visual inspection or reliance on photographs to provide ratings using a validated measure, which is labor-intensive, subjective, and only approximately repeatable. A Clutter Image Rating (CIR) scale was proposed to improve clutter-assessment consistency, but still requires ”manual” comparison of a living space to a set of reference images. Automatic clutter classification from images would be a useful decision-support proxy, yet the task is difficult because labeled data are limited, labels are ordinal, and neighboring CIR levels can differ only by subtle changes in object density, obstruction, and stacking. The most successful clutter-assessment method to date is based on the Vision Transformer (ViT). In this work, we improve on the RGB-only ViT baseline through partial transformer updating, tuned optimization, and geometry-preserving augmentation, while keeping the benchmark’s loss function and evaluation protocol unchanged. On the HINDER-2025 clutter-image dataset, this tuning improves performance by 6.28 percentage points in classification accuracy, while an additional DINOv2 initialization further boosts the accuracy by 1.01 percentage points. We also investigate whether clutter prediction can be improved by fusing auxiliary cues derived from the same RGB image, without requiring new manual annotations to enlarge the dataset. We evaluate the impact of structural cues from object detection, semantic cues from clutter-focused image masking, and volumetric cues from relative depth estimation. The structural and semantic cues provide modest gains over the tuned RGB baseline, while the volumetric cue provides the largest improvement. With DINOv2 initialization, the model using RGB+Depth reaches 63.42% accuracy, improving over the RGB-only ViT baseline by 9.96 percentage points. Impressively, this model achieves 96.27% accuracy within ±1 from the ground truth, which is important in practice since professionals acknowledge challenges in assigning exact CIR values. Effectively, this level of accuracy suggests that an automated algorithm can serve as a reliable proxy for assessment by professionals, thus potentially leading to reduced labor costs, elimination of subjectivity and precise repeatability.
This article examines Akhmet Baitursynuly’s views on the nature of language, the art of speech, and the cognitive structure of human consciousness from the perspective of contemporary cognitive linguistics. The study analyzes the concepts of “reason,” “imagination,” and “emotion” proposed by the scholar as the fundamental components of human cognition and reveals their significance in explaining the psychological and cognitive foundations of linguistic knowledge. Particular attention is paid to the interrelation between language and culture, as well as to the role of language in preserving and shaping national identity, worldview, and cultural values. The article demonstrates that Baitursynuly provided a profound interpretation of the relationship between language, thought, and consciousness. Furthermore, such notions as perception, figurative representation, and mental retention are examined in relation to modern cognitive-linguistic processes, including conceptualization, metaphorization, information processing, and evaluation. The paper also discusses the scholar’s ideas concerning verbal art, authorial style, linguistic norms, and the principle of “speech law” (lebiz zany), emphasizing their theoretical relevance for contemporary linguistic research. The findings suggest that Baitursynuly’s scholarly heritage constitutes one of the intellectual foundations of cognitive linguistics in Kazakh linguistics, while his language-based conception of cognition remains highly relevant to modern linguistic studies.
The English language, traditionally viewed as monolithic and monocentric, now evolves into diverse varieties embedded in unique communities of practice. The expansion of online communication has further informed this evolution, giving rise to virtual spaces where members negotiate shared meanings, identities, and linguistic norms. This paper explores language use within an online networking business community of practice in the Philippines. Drawing on theories of Communities of Practice (COP) and Cultural Models, it examines how English is positioned in relation to the members’ cultural models and how community-specific jargons function as markers of identities. Through in-depth interviews and analysis of actual online conversations and social media posts, the study reveals that group members use English and local languages in dynamic linguistic strategies, such as code-switching and translingual practices, to construct and perform their identities within the group. The findings further reveal the role of English as a tool for empowerment and a marker of identity in digital spaces, hence emphasizing the need for a more inclusive understanding of language use in contemporary online communities.
There is increasing recognition of the value of multi-agency approaches to support people with hoarding difficulties. This service evaluation describes and presents preliminary evaluation data for an innovative multi-agency partnership in Wales supporting people with hoarding difficulties. The preliminary service evaluation analysed routine usage and outcome data recorded between January 2024 to July 2024. This included the number of individuals receiving support, referral acceptance rates, demographics of referrals and a range of service outcomes including changes in the quantity of possessions in living spaces, measured using the Clutter Image Rating (CIR) scale, and achievement of service objectives. The service was well-utilised, with 53% achieving positive outcomes upon discharge. The quantity of possessions in living spaces decreased from clinical threshold in 71% of participants from pre- to post-intensive support. The findings are considered in relation to the evidence base for multidisciplinary approaches for hoarding difficulties and the implications for service delivery. Mae gwerth dulliau amlasiantaethol o gefnogi pobl ag anawsterau celcio yn cael ei gydnabod fwyfwy. Mae’r astudiaeth gwerthuso gwasanaeth hon yn disgrifio ac yn cyflwyno data gwerthuso rhagarweiniol ar gyfer partneriaeth amlasiantaeth arloesol yng Nghymru sy’n cefnogi pobl ag anawsterau celcio. Roedd y gwerthusiad rhagarweiniol o’r gwasanaeth yn dadansoddi data defnydd a chanlyniadau arferol a gofnodwyd rhwng mis Ionawr 2024 a mis Gorffennaf 2024. Roedd hyn yn cynnwys nifer yr unigolion sy’n cael cymorth, cyfraddau derbyn atgyfeiriadau, demograffeg atgyfeiriadau ac amrywiaeth o ganlyniadau gwasanaeth gan gynnwys newidiadau yn nifer yr eiddo mewn mannau byw, wedi’u mesur gan ddefnyddio graddfa Sgorio Delwedd Annibendod (CIR), a chyflawni amcanion y gwasanaeth. Roedd defnydd y gwasanaeth yn dda, gyda 53% yn sicrhau canlyniadau cadarnhaol ar ôl cael eu rhyddhau. Gostyngodd nifer yr eiddo mewn mannau byw o drothwy clinigol ymysg 71% o gyfranogwyr cyn cael cymorth dwys ac ar ôl ei gael. Ystyrir y canfyddiadau yng nghyswllt y sylfaen dystiolaeth ar gyfer dulliau amlddisgyblaethol o ran anawsterau celcio a’r goblygiadau ar gyfer darparu gwasanaethau.