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The current study examined how adolescents respond to emotionally arousing images that are considered age-appropriate, such as sports, food, and threatening animals. Prior research in adults has shown a mismatch between subjective arousal ratings and the late positive potential (LPP) for pleasant images, and we aimed to test whether this discrepancy is also present in adolescents. The results showed a larger LPP in response to unpleasant, compared to pleasant, contents. However, comparisons across the different emotional contents showed that the concordance between subjective and neural engagement varies depending on the emotional contents of the scenes. Specifically, images of threatening animals were rated high in emotional arousal and prompted the largest LPP in adolescents, while images of sad people and images of mundane activities were rated lower in emotional arousal and prompted the smallest LPP responses. However, adolescents showed significant divergence in their responses to pleasant images depicting food and sport: despite being rated high in emotional arousal, these images elicited relatively small LPPs. These results highlight the challenges of selecting emotional pictures to assess neuroaffective responses to pleasant and unpleasant pictures in adolescents. To overcome these challenges, future studies may adopt experimental paradigms that will allow researchers to measure neuroaffective responses not just in free-viewing contexts but also during anticipation and reception of actual rewards (and punishments).
Introduction: Neurodegenerative diseases like progressive supranuclear palsy (PSP) present challenges concerning their diagnosis. Neuroimaging using magnetic resonance (MRI) may add diagnostic value. However, modern techniques such as volumetric assessment using Voxel-Based Morphometry (VBM), although proven to be more accurate and superior compared to MRI, have not gained popularity among scientists in the investigation of neurological disorders due to their higher cost and time-consuming applications. Conventional brain MRI methods may present a quick, practical, and easy-to-use imaging rating tool for the differential diagnosis of PSP. The purpose of this study is to evaluate a string of existing visual MRI rating scales and signs regarding their impact for the diagnosis of PSP. Materials and Methods: The population study consisted of 30 patients suffering from PSP and 72 healthy controls. Each study participant underwent a brain MRI, which was subsequently examined by two independent researchers in a double-blinded fashion. Fifteen visual rating scales and signs were evaluated, including pontine atrophy, cerebellar atrophy, midbrain atrophy, aqueduct of Sylvius enlargement, cerebellar peduncle hyperintensities, enlargement of the fourth ventricle (100% sensitivity and 71% specificity) and left temporal lobe atrophy (97% sensitivity and 78% specificity). Conclusions: Enlargement of the Sylvius aqueduct, enlargement of the fourth ventricle and atrophy of both temporal lobes together with the presence of morning glory and hummingbird signs can be easily and quickly distinguished and identified by an experienced radiologist without involving any complex analysis, making them useful tools for PSP diagnosis. MRI visual scale measurements could be added to the diagnostic criteria of PSP and may serve as an alternative to highly technical and more sophisticated quantification methods.
BACKGROUND: Social anxiety disorder (SAD) in youth is associated with significant psychosocial impairments; however, the cognitive and neural mechanisms that maintain it, particularly during childhood and adolescence, remain underexplored. Cognitive models emphasize the role of altered face processing, and neutral facial expressions may be perceived as threatening. Due to their ambiguous nature, contextual cues may play a particularly important role in interpretation. METHODS: We presented neutral child faces paired with social context information varying in valence (negative, neutral, positive) while continuous EEG was recorded. Subjective valence ratings and neural responses (P100, N170, and LPP) were assessed in children and adolescents aged 10-15 years with SAD (n = 53), clinical controls with specific phobias (SP; n = 41), and healthy controls (HC; n = 61). RESULTS: Overall, context information affected both the subjective and neural responses to neutral faces in all children and adolescents, for example, more negative ratings for negatively contextualized faces. Further, participants with SAD generally rated all faces as more negative compared to HCs. Neurally, they showed lower N170 amplitudes compared to both control groups in response to all neutral faces, independent of the context valence. However, only younger children (aged 10-12 years) with SAD showed higher LPP amplitudes than younger HCs. CONCLUSIONS: Processing biases seem to be already present in children and adolescents with SAD, both at the subjective and neural level. Social context information influences neutral face processing but is independent of psychopathology. Future studies examining age effects are needed to investigate whether childhood reflects a particularly sensitive period for the development of processing biases.
This article examines the pragmatic functions of intensifiers in English and Uzbek media texts, focusing on how lexical and phraseological means are used to strengthen meaning, guide interpretation, and influence audience perception. Intensifiers such as scalar adverbs, extreme adjectives, reduplication, evaluative expressions, and emotionally loaded phraseological units are analyzed within their communicative contexts. The study reveals that English media typically employs controlled, graded forms of intensification to shape evaluative tone subtly, while Uzbek media relies more heavily on expressive and culturally embedded intensifiers to create emotional resonance. By comparing these patterns, the research highlights how linguistic structure, cultural norms, and media strategies determine the pragmatic roles of intensifiers in shaping stance, persuasion, dramatization, and ideological framing.
Vocabulary acquisition is essential to second language learning, as it underpins all core language skills. Accurate vocabulary assessment is particularly important in standardized exams, where test items evaluate learners' comprehension and contextual use of words. Previous research has explored methods for generating distractors to aid in the design of English vocabulary tests. However, current approaches often rely on lexical databases or predefined rules, and frequently produce distractors that risk invalidating the question by introducing multiple correct options. In this study, we focus on English vocabulary questions from Taiwan's university entrance exams. We analyze student response distributions to gain insights into the characteristics of these test items and provide a reference for future research. Additionally, we identify key limitations in how large language models (LLMs) support teachers in generating distractors for vocabulary test design. To address these challenges, we propose the iterative selection with self-review (ISSR) framework, which makes use of a novel LLM-based self-review mechanism to ensure that the distractors remain valid while offering diverse options. Experimental results show that ISSR achieves promising performance in generating plausible distractors, and the self-review mechanism effectively filters out distractors that could invalidate the question.
This study examined linguistic deviances (LDs) as stylistic resources in the Nigerian music industry, through a semiotic analysis of Adeleke’s “Funds” and Apata’s “Hustle”. Linguistic deviance, a hallmark of creative language use in artistic expression, is explored here as a deliberate semiotic act that encodes cultural, ideological, and socio-economic meanings within the contemporary Nigerian popular music. A qualitative research design was adopted in the analysis of the selected songs. The study draws from Barthes’ semiotic theory of denotation, connotation, and myth, as well as Leech and Short’s stylistics theory as frameworks for unpacking how deviation from linguistic norms constructs stylistic identity and social commentary. Findings from the study showed that LDs in both songs transcend mere artistic play; they index resistance to linguistic hegemony, assert sociolectal authenticity, and project the artists’ personae as voices of economic struggle and self-affirmation. The results further showed that LDs are deliberate strategies that enhance rhythm, meaning, and cultural identity. The use of code-switching by the artists fosters hybridity, slang, and neologisms that reflect youth culture, while NPE ensures inclusiveness. Repetition and phonological stylization are also found to strengthen emphasis and musicality. The study, while concluding that LDs are powerful stylistic and semiotic devices that enrich Nigerian music, negotiate cultural identity, and index the lived realities of the youth, recommends that further research be conducted across other artists and genres, as well as the documentation of emerging linguistic innovations in other African music. This study has implications for theoretical studies and contributes to the growing body of scholarship at the intersection of stylistics, semiotics, and sociolinguistics, highlighting how popular music mediates between local linguistic practices and global stylistic trends.
Researchers often assess processes underlying human perception by measuring participants’ judgements of image stimuli. However, traditional methods for quantifying subjective judgements, such as Likert scales, sliding scales, and pairwise comparisons, are vulnerable to biases or demand extensive time and resources from researchers and participants. The present study compared the efficiency, reliability, and validity of these established methods against the Fast Image Rating Experiment (FIRE), our force-choice-based paradigm for assessing perceptions of visual stimuli. When used to rate image preference and naturalness, the FIRE was five times faster than established methods, highly reliable, and valid. FIRE achieved high reliability in less than half the time required to reach equivalent reliability with the Likert or sliding scale, which could save researchers thousands of dollars. The scalability and cost-effectiveness of the FIRE make it a valuable resource for supporting large-scale behavioral science.
Emotions exert an immense influence over human behavior and cognition in both commonplace and high-stress tasks. Discussions of whether or how to integrate large language models (LLMs) into everyday life (e.g., acting as proxies for, or interacting with, human agents), should be informed by an understanding of how these tools evaluate emotionally loaded stimuli or situations. A model's alignment with human behavior in these cases can inform the effectiveness of LLMs for certain roles or interactions. To help build this understanding, we elicited ratings from multiple popular LLMs for datasets of words and images that were previously rated for their emotional content by humans. We found that when performing the same rating tasks, GPT-4o responded very similarly to human participants across modalities, stimuli and most rating scales (r = 0.9 or higher in many cases). However, arousal ratings were less well aligned between human and LLM raters, while happiness ratings were most highly aligned. Overall LLMs aligned better within a five-category (happiness, anger, sadness, fear, disgust) emotion framework than within a two-dimensional (arousal and valence) organization. Finally, LLM ratings were substantially more homogenous than human ratings. Together these results begin to describe how LLM agents interpret emotional stimuli and highlight similarities and differences among biological and artificial intelligence in key behavioral domains.
This study investigates differences in artificial intelligence (AI) literacy and adoption between engineering students and faculty in a Middle Eastern higher-education institution. Parallel surveys were administered to undergraduate engineering students (N = 73) and faculty members (N = 20), each rating their familiarity with 20 AI tools covering learning, coding, productivity, and engineering applications. An AI Literacy Index was computed by assigning numerical values to familiarity ratings (A = 2, B = 1, C = 0) and normalizing the total to a 0–1 scale. Results from Welch’s t-test indicated that students demonstrated significantly higher literacy than faculty (0.454 vs. 0.356, p ≈ 0.042). Students also reported strong AI adoption for academic tasks (71.2%) and high perceived learning benefits (83.6%). Conversely, faculty expressed substantial concern about student over-reliance on AI (90%) while indicating readiness for professional development through AI training workshops (75%) and reporting assessment redesign efforts (75%). Overall, the findings highlight a meaningful literacy and perception gap with implications for engineering pedagogy, curriculum development, and assessment practices. Recommendations are provided to support the alignment of student and faculty AI competencies within engineering programs.
Abstract The “sleep to forget and sleep to remember” hypothesis states that sleep attenuates the emotional tone of a memory while strengthening its factual content. However, previous experimental research has yielded inconsistent results, associating sleep with the reduction, enhancement, or maintenance of the emotional tone of memories. Although the hypothesized process may necessitate multiple nights of sleep, most studies have relied on single-night protocols. To address this, we further investigated whether immediate sleep diminishes emotional reactivity triggered by memory reactivation after one week. In a karaoke paradigm, we recorded participants’ singing of two songs and played back one of their recordings (rec1) to induce an embarrassing episode either in the early afternoon (delayed sleep group; N = 25) or the evening (immediate sleep group; N = 25). One week later, we assessed participants’ emotional reactions to the re-exposed recording (rec1) and a newly introduced recording (rec2). Emotional reactivity was assessed using facial blushing as a primary physiological measure and subjective ratings of embarrassment, valence, and blushing. Sleep was monitored using diaries. While the embarrassing episode was successfully induced, Bayesian mixed-effects models revealed reduced facial blushing and more negative valence ratings from initial exposure to re-exposure (rec1) after both a shorter and longer interval to sleep. These changes were nonspecific to the reactivated recording (rec1) and were also observed for the new recording (rec2). Other subjective measures remained unchanged. This study demonstrates that neither the time interval to sleep following encoding nor memory reactivation influenced long-term emotional reactivity, leaving sleep’s role in emotional memory processing elusive.
Social touch from a close companion, such as a friend, can effectively buffer stress, an effect modulated by the nature of the social relationship. However, the neural mechanisms underlying this modulation, particularly the dynamics between interacting brains, remain poorly understood due to a lack of suitable open data. We present a functional near-infrared spectroscopy (fNIRS) hyperscanning dataset from 47 female dyads (24 friend pairs, 23 stranger pairs) who jointly viewed negative and neutral images under touching and no-touching conditions. The dataset includes raw and preprocessed fNIRS data, trial-by-trial emotional valence and arousal ratings, and extensive trait- and state-based questionnaire data. Technical validation, including power spectral density analysis, confirms our preprocessing pipeline effectively yields high-quality signals. A preliminary validation analysis of the dataset confirms that interpersonal touch effectively buffers against negative emotional experiences by enhancing inter-brain synchrony. This rich, multi-modal dataset is publicly available on the Open Science Framework and provides a unique resource for investigating how social relationships shape the neurobehavioral dynamics of social support.
The article presents the results of a cross-cultural affective images perception study by Americans and Russians and reveals the degree of cultural factor influence on the stimuli assessment by American and Russian men and women. The hypothesis is that assessments of affective images by American and Russian respondents will have statistical differences due to the linguistic and cultural specificity of the ethnic groups; it is also assumed there are cross-cultural gender differences in the assessment. The study used the method of psycholinguistic questioning with seven-point scaling. 84 images from the open American database of affective images (“Open Affective Standardized Image Set”) were used as research material. The respondents were 34 men and 58 women. The results of the analysis did not show significant cross-cultural differences in ratings of affective images with reference to valence type or emotional evaluation/response. In general, Americans and Russians had a similar distribution of image ratings. However, a statistically significant difference has been found in the ratings of images with different valence types (P < 0.001). Negative and positive images were rated higher by Russians in terms of emotional evaluation, in contrast to Americans, most of whose emotional responses had neutral ratings. There was also a statistically significant difference in the ratings of different thematic images (P < 0.05). Nature images were rated by Russians as causing a feeling of comfort, while Americans noted their neutral impact on them. Images of objects, on the contrary, received the opposite ratings from the respondents. Moreover, cross-cultural gender differences have been revealed between Russian and American women in image ratings based on emotional evaluation and valence parameters (P < 0.05). Russian women rated most of the images as having a positive or negative impact, while the majority of American women’s ratings tended to be neutral. This confirms the influence of the emotional stimulus, valence type, image theme, as well as gender factor on the processing of emotionally coloured units by representatives of different cultures.
Central emotion theories assume that during threatening and dangerous events the human face signals a prototypical, distinct, and universally recognized expression of fear which can be accurately decoded by conspecific perceivers. Due to the importance of fear expressions, an unusually large body of research has been dedicated to exploring their evolutionary origins, neurobiological mechanisms, and clinical significance. However, these studies typically utilize highly recognizable posed actor portrayals presumed to closely resemble the diagnostic physical appearance of real-life fearful faces. Here, we challenge this diagnosticity assumption. Following context-dependent frameworks (Barrett, 2017), we hypothesized that extrafacial context (e.g., situational information, body posture, etc.) plays a far greater role in fear communication than the signal of the isolated face. In 12 preregistered experiments (N = 4,180), we examined the perception of authentic, real-life videos documenting a diverse range of intense fear-inducing situations (e.g., height jumping, physical attacks, exposure to phobia triggers). Participants viewed the face alone, the context with no face, or the full video while various response methods of emotion perception were tested (forced choice, open-ended, multiple emotion scales, valence-arousal ratings). Across experiments, videos of the faces alone failed to communicate fear in a reliable manner. In sharp contrast, context with no faces, and faces with context were clearly and robustly perceived as fearful, with medium to large effect sizes. These findings suggest that despite the undisputed importance of perceiving fear reactions, facial expressions alone bear minimal diagnostic value, while context plays a critical role in real-life fear perception.
Code-switching presents a complex challenge for syntactic analysis, especially in low-resource language settings where annotated data is scarce. While recent work has explored the use of large language models (LLMs) for sequence-level tagging, few approaches systematically investigate how well these models capture syntactic structure in code-switched contexts. Moreover, existing parsers trained on monolingual treebanks often fail to generalize to multilingual and mixed-language input. To address this gap, we introduce the BiLingua Parser, an LLM-based annotation pipeline designed to produce Universal Dependencies (UD) annotations for code-switched text. First, we develop a prompt-based framework for Spanish-English and Spanish-Guaraní data, combining few-shot LLM prompting with expert review. Second, we release two annotated datasets, including the first Spanish-Guaraní UD-parsed corpus. Third, we conduct a detailed syntactic analysis of switch points across language pairs and communicative contexts. Experimental results show that BiLingua Parser achieves up to 95.29% LAS after expert revision, significantly outperforming prior baselines and multilingual parsers. These results show that LLMs, when carefully guided, can serve as practical tools for bootstrapping syntactic resources in under-resourced, code-switched environments. Data and source code are available at https://github.com/N3mika/ParsingProject
The article presents a comprehensive analysis of the impact of Internet memes and social media discourse on the evolution of contemporary English, focusing particularly on the processes of lexical innovation, semantic shift, and pragmatic adaptation of linguistic units.In the digital age, communication increasingly takes place through multimodal platforms such as TikTok, Twitter/X, Instagram, and Reddit, which serve as powerful instruments of sociolinguistic dynamics.These platforms not only facilitate the rapid dissemination of slang and emerging expressions but also create new contexts in which users engage in collective linguistic creativity.Internet memes are interpreted as cultural and semiotic units that combine text, imagery, audiovisual effects, and situational context, ensuring the effective circulation and consolidation of new linguistic forms within the global communication space.The article emphasizes that memes function as mechanisms of social identification and linguistic play, reflecting the values, moods, and trends of youth subcultures.The study demonstrates that memes are not merely reflections of linguistic change but active catalysts of language evolution, fostering the emergence of new lexical items, neologisms, and grammatical patterns.The growing influence of Internet culture is shown to shape new norms of speech behavior, where the boundaries between spoken and written, formal and informal language are increasingly blurred.The linguistic transformations driven by digital environments reveal a profound reconfiguration of English lexis, syntax, and pragmatics, as well as a reconsideration of the role of context in communication processes.The conclusion highlights the necessity of an interdisciplinary approach to this phenomenon,
The present dissertation examines the role of context-specific simulations in influencing the complexity of affective experiences, drawing on a constructivist approach to emotion. To link literatures on mental simulation and emotion, in Chapter 1 a connection is made through the grounded theories of cognition. Chapter 2 describes the development of a novel dataset consisting of context-dependent stimuli (i.e., 1,381 picture-word cues derived from 320 pictures-only stimuli) validated through online experiments (NExp1= 1,934; NExp2 = 403). Hence, an investigation of how contextual information influences the affective experience is illustrated, revealing that context more often enhances affective complexity by widening, rather than narrowing, the variation in the between-subject valence ratings. Chapter 3 employs a set of stimuli selected from Chapter 2 in a lab-based experiment in which participants (N = 30) rated affect intensity, and reported which emotions and bodily sensations experienced in response to generating both mental images and verbal thoughts. Mental imagery was found to enhance emotion complexity as reflected in the richness of the reports provided, with affect intensity and autobiographical recall accounting for the effect. Finally, in Chapter 4 the influence of mental imagery on emotion complexity will be studied across the imagery spectrum. To this end, in an online experiment participants (N = 72) completed measures of imagery vividness, alexithymia and gave written reports on how they feel when experiencing emotions at varying levels of valence and arousal, to obtain indexes on the complexity of emotion conceptualization. In line with the predominant literature, the more vivid the visual mental imagery of participants, the less alexithymia was reported, i.e., the less impaired is the process of emotion conceptualization. As highlighted in the final chapter (Chapter 5), overall the present dissertation contributes to deepening the study of the relationship between mental imagery and emotion. Assuming variation as inherent to emotion, consistently through different experimental designs, methods, languages and indexes, it is shown how context-specific simulations enrich the emotional sphere, by enhancing the complexity of affective experiences.
OBJECTIVES: If task-irrelevant sounds are present when someone is actively listening to speech, the irrelevant sounds can cause distraction, reducing word recognition performance and increasing listening effort. In some previous investigations into auditory distraction, the task-irrelevant stimuli were non-speech sounds (e.g., laughter, animal sounds, music), which are known to elicit a variety of emotional responses. Variations in the emotional response to a task-irrelevant sound could influence the distraction effect. The goal of this study was to examine the relationship between the arousal (exciting versus calming) or valence (positive versus negative) of task-irrelevant auditory stimuli and auditory distraction. Using non-speech sounds that have been used previously in a distraction task, we sought to determine whether stimulus characteristics of arousal or valence affected word recognition or verbal response times (which serve as a measure of behavioral listening effort). We anticipated that the perceived arousal and valence of task-irrelevant stimuli would be related to distraction from target stimuli. DESIGN: In an online listening task, 19 young adult listeners rated the valence and arousal of non-speech sounds, which previously served as task-irrelevant stimuli in studies of auditory distraction. Word recognition and verbal response time data from these previous studies were reanalyzed using the present data to evaluate the effect of valence or arousal stimulus category on the distraction effect in quiet and in noise. In addition, correlation analyses were conducted between ratings of valence, ratings of arousal, word recognition performance, and verbal response times. RESULTS: The presence of task-irrelevant stimuli affected word recognition performance. This effect was observed generally in quiet and for stimuli rated as exciting (in noise) or calming (in quiet). The presence of task-irrelevant stimuli also affected reaction times. Background noise increased verbal response times by approximately 35 msec. In addition, all task-irrelevant stimuli, regardless of valence or arousal category, increased verbal response times by more than 200 msec relative to the condition with no task-irrelevant stimuli. Valenced stimuli caused the largest distraction effect on response times; there was no difference in the distraction effect on verbal response times based on the stimulus arousal category. Correlation analyses between valence ratings and dependent variables (word recognition and reaction time) revealed that, in quiet, there was a weak, but statistically significant, relationship between valence ratings (absolute deviation from neutral) and word recognition scores; the more valenced a stimulus, the more distracting it was in terms of word recognition performance. This significant relationship between valence and word recognition was not evident when participants completed the speech task in noise. There was no relationship between stimulus ratings (arousal or valence) and reaction time in quiet or in noise. CONCLUSIONS: Valenced (positive and negative) or exciting task-irrelevant non-speech sounds can negatively affect word recognition and increase listening effort. Future study should consider the emotional content of task-irrelevant stimuli when evaluating potential distraction effects.
As a means of communication for the Uzbek people, the Uzbek language continues to fulfill a social function even today. This, in turn, serves to ensure comprehensive communication among members of the nation. The onomastic system of the Uzbek language is a vast, multifaceted linguistic phenomenon rich in content, with its components intricately interconnected. The study of onomastic units found in literary texts is one of the pressing issues in linguistics. In this regard, it is important to analyze the lexical-semantic and stylistic features of anthroponyms used in literary texts. Furthermore, the contribution of Uzbek linguists, writers, and poets to the current development of the Uzbek language is invaluable. Thanks to their efforts, strict linguistic norms are established in many areas of the Uzbek language, and examples of linguistic usage in communication processes are provided. This article discusses the role of onomastic units used in the style of literary works written in the Uzbek literary language. It examines the semantic types and distinctive features of such units.
Artificial intelligence (AI) models can sense subjective affective states from facial images. Although recent psychological studies have indicated that dimensional affective states of valence and arousal are systematically associated with facial expressions, no AI models have been developed to estimate these affective states from facial images based on empirical data. We developed a recurrent neural network-based AI model to estimate subjective valence and arousal states from facial images. We trained our model using a database containing participant valence/arousal states and facial images. Leave-one-out cross-validation supported the validity of the model for predicting subjective valence and arousal states. We further validated the effectiveness of the model by analyzing a dataset containing participant valence/arousal ratings and facial videos. The model predicted second-by-second valence and arousal states, with prediction performance comparable to that of FaceReader, a commercial AI model that estimates dimensional affective states based on a different approach. We constructed a graphical user interface to show real-time affective valence and arousal states by analyzing facial video data. Our model is the first distributable AI model for sensing affective valence and arousal from facial images/videos to be developed based on an empirical database; we anticipate that it will have many practical uses, such as in mental health monitoring and marketing research.
Universal Dependencies (UD) have garnered notable focus for the systematic assessment of cross-lingual methods in the task of dependency parsing. In this article, we present our initiative toward the development of a dependency treebank for the resource-poor language: Nepali, within the framework of UD. To this end, we have mapped the Nepali treebank to the UD scheme. A detailed mapping procedure tailored to meet the requirements of the Nepali language has been outlined with examples. Experiments on dependency parsing with the UD-mapped Nepali treebank achieved UAS and LAS scores of 78 and 63.1, respectively.
Purism has played a significant role throughout the history of written Slovene. It has been directed at both external and internal threats to the language. Chief among the former have been German, the dominant language of the region, which has influ- enced the Slovene vernacular at all linguistic levels, and Serbo-Croatian, which served as the de-facto idiom of inter-ethnic communication in the former Yugoslavia. Xeno- phobic purism has succeeded in removing most German loanwords from the standard language and replacing them with loanwords from other Slavic languages and calques. Inasmuch as the majority of the German loanwords have been retained in the spoken vernacular this has had the net effect of distancing the standard language from the respective vernacular. On the other hand, the attempt to remove the numerous syntactic and phraseological calques based on German models has been generally unsuccessful in practical terms. However, the puristic reaction to these covert influences has served an important symbolic function in emphasizing a sense of Slovene linguistic identity in the linguistic consciousness of the Slovene speech community. Serbo-Croatian lexical elements, on the other hand, have posed a particularly intractable problem for Slovene purists. This was primarily because in the nineteenth century the Croatian abstract lexicon played a major part in providing standard Slovene with acceptable replacements for internationalisms and Germanisms. Secondly, because of a common involvement in Yugoslavia and the close genetic relationship between Slovene and Serbo-Croatian it was often difficult in practice to identify Serbo-Croatian material in Slovene with any degree of certainty. Indeed, a systematic, dispassionate identification of such material remains as one of the many tasks confronting Slovene scholarship in the years of political independence. Internally, purists have at various times attempted to archaize and Slavicize the orthography and morphology of the standard language. This has fostered a spirit of hypercorrection and pendantry in some Slovene linguistic circles. On the other hand, the strain of ethnographic purism, which goes back to the seminal figure of Jernej Kopitar, has served as an antidote to both archaization and Slavization of Slovene by seeking justification for the norms of standard Slovene in the contemporary dialects. This helps to explain why puristic intervention in standard Slovene can be generally characterized as moderate and free of excesses. Nevertheless, it is equally clear that the puristic debate, which has resounded in the times of Trubar, Kopitar, Cop, and Pregeren right down to the present day, will continue to be a significant factor as the Slovene standard language seeks to define its role on the new socio-political stage of the Slovene-speaking territory.
This study explores the sociopragmatic functions of taboo language in two contrasting Balinese speech communities: Tenganan Pegringsingan Village and Denpasar City. Using a qualitative descriptive approach supported by non-participant observation, semi-structured interviews, and discourse documentation, the research examines how speakers employ taboo expressions to negotiate politeness, express emotion, and perform social identity. Grounded in Brown and Levinson’s Politeness Theory (1987), Locher and Watts’s concept of relational work (2005), and Culpeper’s notion of impoliteness (2011), the analysis reveals a clear sociocultural divergence. In Denpasar, taboo words function as expressive and relational tools that reinforce solidarity, humor, and affective intensity within peer-based interactions. In contrast, Tenganan’s linguistic norms constrain the use of taboo expressions to maintain ritual purity, respect, and social hierarchy. Componential analysis further uncovers that Denpasar’s taboo lexicon emphasizes emotional intensity and pragmatic versatility, while Tenganan’s reflects moral restraint and symbolic caution. The findings demonstrate that taboo language, far from being mere linguistic deviance, operates as a culturally situated pragmatic resource that mirrors each community’s values, power dynamics, and communicative ideologies.
Electroencephalogram (EEG) signals exhibit nonstationary dynamics with high temporal resolution but limited spatial resolution. A critical challenge lies in identifying stable neural states during rapid emotional transitions and decoding dynamic interregional interactions. To address this, we propose a dynamic microstate temporal graph attention network (DMT-GAT) that integrates transient EEG microstates with brain functional networks. First, EEG signals are segmented into four prototypical microstates (labeled as MS1, MS2, MS3, and MS4) via global field power peak detection and K-means clustering. Emotion-related microstates (MS3/MS4) are then selected through independent t-tests based on valence and arousal ratings. Next, a brain functional network is constructed by calculating phase-locked value synchronization specifically on the time series of MS3/MS4 microstates, capturing millisecond-scale interregional dynamics during emotional shifts. Frequency-domain features are integrated into the network nodes, forming graph-structured data. Finally, a GAT with multi-head mechanisms classifies emotions by adaptively weighting node interactions. On the DEAP dataset, our method achieves average accuracies of 99.19% (valence) and 99.26% (arousal). For the SEED dataset, it maintains a robust accuracy of 95.29%. Crucially, the DMT-GAT uniquely reveals prefrontal-amygdala interactions during emotional regulation, bridging the gap between dynamic brain networks and rapid neurodynamics. This work provides a novel framework for high-resolution emotion recognition and advances understanding of neural mechanisms underlying affective transitions.
The concordance between subjective and facial hedonic responses while eating is informative, both practically and theoretically. Recent psychophysiological studies reported that hedonic ratings during the consumption of gel-type food were negatively associated with facial electromyography (EMG) signals recorded from the corrugator supercilii and positively associated with those from chewing-related muscles. However, the relationships were tested in a static manner, and the dynamic subjective–facial concordance remains untested. Therefore, we investigated this by assessing participants’ dynamic valence ratings and recording their facial EMG from the corrugator supercilii, zygomatic major, masseter, and suprahyoid muscles while they chewed and swallowed gel-type food stimuli of various flavors. Cross-correlations with dynamic valence ratings were negative for corrugator supercilii EMG signals and positive for zygomatic major, masseter, and suprahyoid EMG signals during both chewing and swallowing. These findings indicate that subjective hedonic experiences and facial EMG signals are dynamically coupled. • Participants chewed and swallowed gel-type food stimuli of various flavors. • We measured their dynamic valence ratings and facial EMG (e.g., the corrugator supercilii). • Cross-correlations between valence ratings and EMG signals were found while chewing. • Similar cross-correlations between valence ratings and EMG signals were found while swallowing.
This study explores the linguistic phenomenon of code-mixing between Indonesian and English among Generation Z teenagers. It aims to analyze how the integration of English into daily conversations influences their speaking manners, including lexical choices, sentence structures, and sociolinguistic implications. A qualitative case study approach was employed, involving interviews, discourse analysis, and surveys among teenagers in urban areas. The findings indicate that code-mixing is used for stylistic expression, social identity formation, and digital communication adaptation. While it enhances bilingual proficiency, it also raises concerns about language shift and cultural identity. The study provides insights into the evolving linguistic patterns of Generation Z and their implications for language education and communication norms.
The fourth technological revolution in language, caused by the invention and active introduction of artificial intelligence into social life, leads to the reformatting of the modern media communication language space. The emergence of the technological dimension in media communication along with the humanitarian one leads to the fact that both the humanitarian communicative model and the technological one are formed and function in the linguistic space of media communication. In relation to the linguistic norm, two types of humanitarian communicative model can be distinguished, one of which is normative and the other creative. The authors of the normative model are professional journalists, the creative model is produced by the Internet users in the comment sections, and the users themselves become the ‘collective Pushkin of social networks’. The normative model in media communication is oriented towards linguistic, stylistic and communicative norms, which contributes to the preservation of the literary language in the media as an absolute communicative value. The creative model of the ‘collective Pushkin’ generates a creative usus that contributes to the renewal of language through the creative energy of its speakers. The norm in the creative model exists implicitly, and its conscious violation demonstrates the expressive possibilities of the national, not only literary language, contributes to filling lacunas, expanding the repertoire of stylistic means, creating a multimedia code in media communication, providing an opportunity to express emotional nuances. The technological model, authored by artificial intelligence, is based on the norms of literary language, as technological authorship in media is not widely advertised. The technological model is normative; its task is to mimic the humanitarian model of professional journalists. The coexistence of the author-journalist and the technological author (AI) in the linguistic space of modern media not only reformats this space in terms of norms and creativity, but also changes its humanitarian component, as it ceases to be unconditionally human.
This article describes the Extended Quranic Treebank (EQTB), a comprehensive, multi-layered, and computationally accessible linguistic resource for Classical Arabic (CA), meticulously developed to overcome the documented limitations of the original Quranic Treebank. Leveraging foundational data from established Quranic digital resources, EQTB features systematically expanded orthographic representations generated via algorithmic processing and validation; rigorously refined morphological annotations based on expanded expert-informed schemas, automated re-annotation, and manual curation; and critically, a novel, complete syntactic layer constructed through algorithmic conversion of prior graphical data, Deep Learning-based parsing achieving full coverage under a hybrid constituency-dependency framework, and expert validation. Encompassing the entire Quran (∼132,736 tokens), the dataset is structured in an adapted CoNLL-X format across 43 columns, detailing multiple orthographies, fine-grained morphology (45 tags), and complete hybrid syntax (140 tags/labels), complemented by auxiliary lexicons and schemas. EQTB offers significant reuse potential, providing crucial training/evaluation data for diverse CA NLP tasks (parsing, morphology, diacritization), supporting linguistic research, and enabling the development of advanced pedagogical tools and language technologies.
The author’s aim is to define the so-called linguistic norm of Middle Armenian using specially developed criteria and linguistic models, and to apply this framework to the study of Middle Armenian. This research presents a methodological and preliminary attempt to address this issue. The linguistic norm is considered essential for the Middle Armenian period, as this is the era in which various forms of Armenian emerge and gain broad usage. A linguistic norm represents the status of a language during a certain time – whether it is stable and systematic or unstable and disorganized. For this reason, the author proposes the following necessary criteria for defining the linguistic norm in Middle Armenian: a) absolute and relative, b) general (societal) and individual (private), c) written (literary) and oral (colloquial), d) comprehensive and segmented in time. The author concludes that it is impossible to define a single unified linguistic norm for the entire Middle Armenian period as one coherent system of rules. One must take into account its diversity and irregularities across centuries. Thus, it may be more appropriate to speak of a mixed type of linguistic norm - dominated by variations and inconsistencies - or to distinguish between multiple linguistic norms that together encompass all linguistic areas as a whole. The author also suggests adopting the regional linguistic feature as a criterion for the linguistic norm of Middle Armenian, which would clarify the localization of dialectal features according to specific regions.
Introduction. The article is devoted to the problems related to the gender reform of the German language. Started on the wave of feminist movement of the 70s of the XX century, the transition to gender-neutral language in recent decades has become one of the most discussed topics in both socio-political and scientific circles in Germany, dividing politicians, lawyers, linguists and ordinary citizens into supporters and opponents of gender-neutral language. Methodology and sources. The article examines legal documents regulating the use of a gender-neutral language, highlights the opinions of participants in the discussion about gender correctness, based on the “myth of the invisible woman”, analyzes gender-oriented transformations used in German, and identifies problems related to gender-oriented language correction. Results and discussion. The starting point of linguistic distortions in the field of gender politics was the confusion of the concepts of grammatical gender (Genus), biological sex (Geschlecht) and gender (Gender/ soziales Geschlecht). The refusal of gender reform proponents to use the forms of generic masculine gender (generisches Maskulinum), which includes a wide range of meanings, and the introduction of gender-oriented transformations into the language provoked problems in the field of linguistic word usage, associated with both distortion of meaning and violation of grammatical norms of the German language. Conclusion. Gender reform has had a significant impact on various spheres of public life in Germany. The gender reform of the German language, dictated by the political agenda, has generated many linguistic and extra linguistic problems. The proposed artificial language changes aimed at achieving gender neutrality actually complicate communication and lead to a violation of the linguistic norms of the German language.
Language plays a crucial role in digital communication, and platforms like Instagram serve as key spaces for self-expression. This study investigates graphological deviations in Instagram captions, focusing on typography, spelling and grammar, and punctuation to understand their impact on written communication in social media. This research adopted a qualitative descriptive approach, analyzing captions from English Language Education Department students' Instagram accounts to identify and categorize graphological deviations. Data collection involved selecting captions with deviations in spelling, punctuation, and typography, followed by analysis using theories from Verdonk (2002) and Simpson (2004). The findings reveal that graphological deviations are intentionally employed to enhance aesthetics, convey emotions, and establish a relaxed, informal tone. Three main categories emerged: (1) Spelling and Grammar, which featured informal abbreviations and creative word formations and accounted for 10 instances; (2) Punctuation, where unconventional uses of quotation marks, ellipses, and dashes added emphasis and emotional depth, with 7 instances identified and (3) Typography, where unique fonts, emojis, and text layouts enhanced visual appeal, with 4 instances recorded. While such deviations may reduce clarity and professionalism, they significantly shape message reception in social media contexts. The study concludes that graphological deviations are a stylistic choice prioritizing aesthetics and emotional engagement over linguistic norms. Future research can explore their visual and emotional impact, typographic effectiveness, and multilingual adaptations in digital media.
This paper presents an approach to integrating Latin inflected forms and corpus attestations within a Linked Open Data (LOD) framework, enhancing interoperability between Wikidata and the LiLa knowledge base. Building on the PrinParLat lexicon of Latin verb principal parts, we generate the complete set of inflected forms for over 8,000 verbs, encoded as RDF in a dedicated Wikibase instance. These forms are linked to the Index Thomisticus Treebank (ITTB), whose morphologically annotated tokens are related to corresponding forms based on segmental identity, lemma alignment, and mapped morphological features. Our generation and linking process achieves over 95% coverage of ITTB verbal tokens, demonstrating the robustness of our pipeline even for Medieval Latin data. By aligning Paralex, Wikidata, and LiLa ontologies, we ensure semantic interoperability and facilitate future integration into Wikidata. Beyond Latin, this workflow provides a reproducible model for linking inflectional paradigms and corpus attestations in other languages.
The overall goal of this article is to contrast the different theorisations of norms in linguistics. Starting from the branches of structural linguistics, the article shows how linguistic norms are conceived in anthropological linguistics. Whereas the former separates linguistic usage from the speakers and tries to describe and analyse the linguistic structures which form different linguistic norms, the fields of anthropological linguistics as well as qualitative sociolinguistics and pragmatics focus on the contextually bound social functions and ideological implementations of the linguist signs that linguistic norms consist of. This way, linguistic norms can be understood more broadly as norms of conceiving and structuring social behaviour of which linguistic behaviour forms an integral part. Consequently, the social functionality of norms and the signs they consist of are theorised in this article. In order to demonstrate their social underpining, the example « J’aime right ton accent » in Acadian French will be analysed in more detail.
Word order difference between source and target languages is a major obstacle to cross-lingual transfer, especially in the dependency parsing task. Current works are mostly based on order-agnostic models or word reordering to mitigate this problem. However, such methods either do not leverage grammatical information naturally contained in word order or are computationally expensive as the permutation space grows exponentially with the sentence length. Moreover, the reordered source sentence with an unnatural word order may be a form of noising that harms the model learning. To this end, we propose an Implicit Word Reordering framework with Knowledge Distillation (IWR-KD). This framework is inspired by that deep networks are good at learning feature linearization corresponding to meaningful data transformation, e.g. word reordering. To realize this idea, we introduce a knowledge distillation framework composed of a word-reordering teacher model and a dependency parsing student model. We verify our proposed method on Universal Dependency Treebanks across 31 different languages and show it outperforms a series of competitors, together with experimental analysis to illustrate how our method works towards training a robust parser.
Just-in-time adaptive interventions (JITAIs) have the aim to provide individualized interventions at optimal moments in time. A complex systems approach suggests that moments of instability may be such an optimal moment in time. In this study, we tested whether a micro-JITAI was more effective when applied during affective instability, as identified in real time from ecological momentary assessment data. We analyzed data from 70 participants who reported their momentary affect 5 times per day during a 60-day period. Instability was identified in real time from the exponentially weighted moving standard deviation (EWMSD) of their momentary affect ratings. The pleasant activity selector was applied as micro-intervention during periods of instability as well as during semi-random control periods. The results showed that the micro-intervention was not effective in improving positive affect. Moreover, the EWMSD appeared very sensitive to negative outlying values of momentary affect, instead of solely to enlarged fluctuations (the hypothesized indicator of instability). We discuss the implications for future studies that aim to test the effectiveness of JITAIs during instability.
Este trabalho apresenta a compilação, a adaptação ortográfica e a anotação morfossintática da variante do nheengatu falada na região do rio Solimões no século XIX. O nheengatu, única língua viva descendente do tupi antigo, assim como muitas línguas minoritárias, não dispunha de corpora anotados sintaticamente até 2022, ano em que foi lançado o treebank UD_NheengatuCompLin na coleção Universal Dependencies (UD). As etapas aqui descritas indicam a expansão desse treebank, contribuindo para o fortalecimento dos recursos disponíveis para a descrição linguística e o processamento computacional do nheengatu.
This research introduces a framework for comparative evaluation of human-curated versus AI-generated affective images using a multimodal AI agent. The dataset (N=80 pictures) includes a selection of 40 human-curated images from the Open Affective Standardized Image Set (OASIS), and a set of 40 synthetic images generated specifically for this study. The synthetic dataset was created by prompting the “GPT Image 1” model, a specialized image generation model built on GPT-4o, with the goal to represent four target emotional states—Excitement, Frustration, Boredom, and Relaxation. A custom AI agent was deployed to rate all images along the valence and arousal dimensions of the affective circumplex model. Statistical analyses were performed to compare: (1) human vs agent image ratings for OASIS and (2) the agent’s ratings of the AI-generated image set and OASIS. The findings indicate that the AI agent reliably aligned with the human ratings and that GPT-4o can serve as both a generator and evaluator of affective content, thus supporting scalable, human-free validation pipelines. This approach contributes to the field of affective computing by enabling rapid generation and analysis of emotionevoking stimuli, with potential applications in experimental psychology and mental health.
This article examines the stylistic features of modern Uzbek translations of William Shakespeare’s works, focusing on the ways translators preserve and adapt the playwright’s artistic language. Special attention is given to lexical choices, syntactic structures, figurative expressions, and cultural adaptation in contemporary Uzbek renditions of Shakespearean drama and poetry. The study analyzes how translators balance fidelity to the original text with the norms and expressive possibilities of the Uzbek language. By comparing selected passages from the source texts and their modern Uzbek translations, the research identifies dominant stylistic strategies such as domestication, poetic transformation, and semantic equivalence. The article also highlights the challenges posed by Shakespeare’s archaic language, metaphorical density, and rhetorical devices, and evaluates how these elements are reinterpreted for modern Uzbek readers. The findings demonstrate that modern translations tend to prioritize readability and cultural accessibility while striving to maintain Shakespeare’s aesthetic and emotional impact. The study contributes to translation studies by offering insights into cross-cultural literary translation and the development of Uzbek Shakespearean scholarship.
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<p>This study aims to compare the translation quality of Arabic texts from <em>Mulakhkhas Qawa’id Al-Lughah Al-‘Arabiyyah</em> by Fuad Ni'mah, translated by Abu Ahmad Al-Mutarjim and by the machine translation tool QuillBot.Ai. A qualitative descriptive approach is employed, using Peter Newmark's translation theory as the analytical framework, particularly focusing on the aspects of accuracy, acceptability, and clarity. The data consists of vocabulary and sentence structures analyzed to evaluate how well each translator conveys the original meaning of the text into Indonesian.The findings reveal that the human translator performs better in preserving the context, structure, and intended meaning of the original text. In contrast, QuillBot.Ai tends to produce meaning distortion and lacks conformity to proper linguistic norms in Indonesian. This suggests that although machine translation can assist in translation tasks, human intervention remains crucial, especially in translating scientific and religious texts.This study contributes to the understanding of the limitations of machine translation and recommends further research into human-machine collaboration in translation practices.</p>
Alexithymia is a multi-faceted personality trait associated with particularities in emotion processing and regulation. While alexithymia total scores have frequently been used to explain these particularities, recent models suggest a differentiated role of specific alexithymia facets at specific emotion processing stages. In this study, we investigated whether alexithymia total scores and facets moderate the effect of emotional salience on valence ratings, arousal ratings and correct emotion recognition. Ninety-four non-clinical participants provided valence and arousal ratings as well as discrete emotion labels for 160 pictures of emotional facial expressions varying in morphing intensity (40%, 60%, 80% and 100% emotion intensity) and discrete emotion type (happy, angry, disgusted, sad, fearful). Alexithymia levels were measured with the Toronto Alexithymia Scale (TAS-20). Our results show that alexithymia total scores moderate arousal and emotion recognition at lower salience levels. Higher alexithymia total scores were associated with higher arousal ratings and higher emotion recognition probability, but only at 40% morphing intensity, which partially supports the over-responding model of alexithymia. In addition, we found contrasted effects of alexithymia facets. Taken together, these results highlight the importance of focusing on emotional salience perception in alexithymia.
The primary challenge in studying children's and adolescents' emotional issues lies in reliably and effectively eliciting their emotional states in research settings, a process that is essential for understanding the development and regulation of emotions across childhood and adolescence. Current research in this field predominantly employs situational induction, facial expression paradigms, and audiovisual stimuli as the main approaches to evoke emotional responses in young participants. While these methods have provided valuable insights, a critical limitation of existing pediatric emotion elicitation techniques is their adult-centric design framework, which often fails to fully account for the developmental origins, contextual factors, and age-specific characteristics of children's and adolescents' emotional experiences. In response to this limitation, the present study advocates for a child-centered research approach that explicitly prioritizes the emotional experiences of youth, aiming to enhance ecological validity by designing stimuli that are closely aligned with the everyday social and environmental contexts in which children and adolescents naturally experience emotions. Furthermore, given the current lack of culturally appropriate and developmentally tailored image databases for socio-emotional elicitation in young populations, this research seeks to construct a child-validated image library capable of safely and effectively eliciting emotional responses. The resulting database is intended to provide a reliable experimental platform that can be used to investigate the mechanisms of emotional processing in youth and to support subsequent interventions and programs aimed at promoting emotional health and socio-emotional development. Two empirical studies were conducted to establish and validate the Chinese Child-Adolescent Affective Picture System (CCAAPS). In Study 1, semi-structured interviews with children and adolescents from Shandong and Anhui provinces in China were analyzed using grounded theory to identify principal sources of emotion in daily life. A total of 20 participants, balanced by gender and aged 6–18 years, provided narratives highlighting a range of emotional triggers. Findings revealed that interpersonal interactions—particularly school-based social contexts—constituted the primary emotional triggers. These qualitative insights were systematically coded to extract keywords that guided the selection of images for the database. Study 2 recruited a total of 491 participants, aged between 6 and 18 years. Each participant was asked to evaluate a set of 311 socio-emotional images that had been preselected based on the findings from Study 1. The images were rated along three distinct emotional dimensions—valence, arousal, and motivational intensity—using a revised 5-point Likert scale. Analysis of the subjective ratings revealed statistically significant differences among positive, neutral, and negative images across all three dimensions (p <.001 for all comparisons), demonstrating that the images were capable of eliciting differential emotional responses in a manner consistent with their intended affective categories. Furthermore, the internal consistency of participants’ ratings was assessed using Cronbach’s alpha, yielding coefficients exceeding 0.85 for each dimension. These results indicate that the image ratings were reliable across participants and that the emotional dimensions measured were internally coherent. The CCAAPS has several implications. First, as a standardized tool grounded in children’s real-life experiences, it provides a link between laboratory paradigms and everyday emotional phenomena, supporting research on emotion recognition, affective processing, emotion-related psychopathology (e.g., depression, anxiety), interpersonal regulation, and antisocial behaviors such as bullying. Second, it can be applied in socio-emotional learning (SEL) to provide culturally appropriate materials for empathy training and emotion regulation interventions in educational contexts. Third, by providing a validated, developmentally appropriate, and culturally adapted affective picture system, the CCAAPS enhances methodological infrastructure for developmental affective science in China. In conclusion, the present research contributes both conceptually and practically to the study of youth emotions by constructing the first child-centered, culturally adapted affective picture system for Chinese children and adolescents. The CCAAPS establishes an ecologically valid resources for investigating socio-emotional experiences, enriches the toolkit for researchers. This work therefore provides an essential infrastructure for future studies seeking to understand, support, and promote the emotional health of Chinese youth.
The purpose of the article is to describe the concept “acquaintance” to improve the people’s understanding of semiotic means of meeting people in Ukraine, Great Britain and the USA spreading them to the social norms of communication and international collaboration. The research engages the comparative analysis of people’s verbal or nonverbal means of meeting people in Ukraine, Great Britain and the USA, lexical semantics, interpretation, conceptual analysis which reveal the cultural stereotypes of different nations. People contact due to their origin, likings, knowledge of conventions and social situations. Verbal and nonverbal semiotics in implied senses can orient, prevent, provoke or stimulate acquaintance. The fatic function (of meeting people comprises cognitive, emotional and social (conventional) information. Communication performs various functions in life disclosing the implied senses of symbols and sayings: security, warning, calling, agreeing or refusing, relaxing or straining, pleasing or displeasing, attracting or repulsing, etc. Verbal and nonverbal signals can stimulate or provoke acquaintance, they can be deceiving or misunderstood. Observing meeting traditions in Ukraine, GB and USA one can notice the similar requirements of good disposition in words and face, some difference in expressions and nonverbal signals. The concept “acquaintance” reflects the space, time and person reference. In meeting traditions in Ukraine, GB and USA the similar requirements of good attitude are observed as the principal cultural element at the core of the concept as well as difference in verbal and nonverbal reference.. Changes in the conceptual semantics can be determined as mutual penetration of the contact making traditions in communication.
Machine learning relies heavily on language modeling to understand detailed information in modern applications of natural language processing. In addition, Deep learning methodologies have gained traction in various fields. Recurrent neural networks have emerged as powerful tools in this context, excelling at sequence modeling. Notably, Long-Short-Term Memory (LSTM) layers have become fundamental to language modeling. Additionally, Temporal Convolutional Networks (TCNs) are a recent and promising addition to Deep Learning. Meanwhile, meta-heuristic optimization has been adopted in several research areas due to its effectiveness. This study proposes a TCN-based language model, optimized by the Arithmetic Optimization Algorithm (AOA). AOA is used in this study to optimize parameters for LSTM and TCN models. The proposed language model is compared with the Exponential Linear Unit LSTM and the Binary Input Gate Recurrent Unit, two important models in modern language processing. The performance of these models is examined and compared using the Penn Treebank (PTB) dataset. The obtained results highlight the ability of AOA to accelerate the convergence of parameters during training and highlight the better performance of the proposed model. By improving Sparse Categorical Cross Entropy loss and perplexity, the proposed model outperforms other models in the PTB language modeling task.
<div> We address the challenge of syntactic parsing for Urdu, a morphologically rich language, and present state-of-the-art results for both constituency and dependency parsing. This paper offers four major contributions: 1) the conversion of the CLE-UTB phrase structure treebank into a dependency treebank by developing language-specific head-word and phrase-to-dependency label mapping rules; 2) a novel sequence labeling scheme that transforms the parsing task into a unified representation; 3) the training of contextualized word representations on a large 220 million tokens Urdu corpus collected from the web; and 4) development of parsing framework using two learning paradigms, single-task and multi-task learning. Several post-processing rules are applied to improve the quality of the automatically converted dependency structure treebank. The proposed sequence labeling scheme enables the use of a shared architecture that learns the syntactic structures from both grammatical structures simultaneously and hence improves generalization. Experiments show that the multi-task learning setup significantly enhances parsing performance, achieving an F1 score of 91.39 for constituency parsing (an improvement of 3.29 points) and a labeled attachment score of 85.69 for dependency parsing (an improvement of 1.49 points). These results demonstrate that learning cross-task representations provides measurable benefits and advances the state of syntactic parsing for Urdu. </div>
This study explores how pitch, dynamics, vibrato levels, and their interactions influence the emotional perception of violin tones. Using 32 violin notes, 62 participants provided valence and arousal ratings on a 9-point Likert scale and binary responses for 16 emotional categories. Results show that pitch was the most influential factor, with higher pitches increasing arousal. Vibrato levels had multifaceted effects, enhancing arousal while reducing valence. Dynamics played a less prominent role but revealed that louder sounds increased valence and unexpectedly decreased arousal. Interaction effects demonstrated that vibrato extent's influence on arousal was moderated by both pitch and dynamics. Additionally, an analysis of low-level acoustic features, such as loudness and vibrato rate, revealed significant correlations with emotional responses. For instance, higher vibrato rates were associated with increased arousal, while attack time had subtle effects on valence. Observations across the 16 emotional categories highlighted distinct quadrant-specific trends. For example, high-arousal emotions were primarily influenced by loudness and vibrato, while low-valence emotions were more sensitive to attack and decay times. These findings provide nuanced insights into the interplay of acoustic features in shaping emotional experiences, contributing to research in music cognition and emotional processing.
Facial expressions provide critical details about social partners' inner states. We investigated whether event-related potentials (ERP) related to the visual processing of facial expressions are modulated by participants' perceived arousal and valence at the stimulus level. ERPs were recorded while participants (N = 80) categorized the gender of faces expressing fear, anger, happiness, and no emotion. Participants then viewed each face again and rated them on arousal and valence using 1-9 Likert scales. For each participant, ratings of each unique face were linked back to corresponding ERP trials. ERPs were analyzed at all time points and electrodes using hierarchical mass univariate statistics. Three different ANOVA models were employed: the original emotion model, and models with valence or arousal ratings as trial-level regressors. Results from models with ratings highly overlapped with the original model, although they were more temporally restricted. The N170 component was the most impacted by arousal and valence ratings, with four out of six emotion contrasts revealing significant valence or arousal interactions. Emotion effects on the P2 component were mostly unrelated to ratings. On the EPN component, only two contrasts related to both arousal and valence ratings. Thus, ERP emotion effects are related to participants' perceived arousal and valence of the stimuli, although this association depends on the contrast analyzed. These findings, their limitations, and generalizability are discussed in reference to existing theories and literature.
The article provides a comprehensive analysis of Viktor Gavrilov's idiosyncrasy as a modern Ugra writer with a unique, hybrid style close to the Leningrad underground. Special attention is paid to the «language game» technique, as one of the dominant ones in some works from the collection “Times. Coda”. Based on the interpretations of the approaches of several scientific schools, based on the material of the poem “(M)art”, the characteristic features of Gavrilov's poetics, synthesizing elements of playful postmodernism and existential lyrics, are comprehensively investigated. The methodological basis of the research combines elements of structural analysis (identification of lexical and syntactic features) and an intertextual approach (identification of allusions and reminiscences). Special attention is paid to parody strategies (the use of reduced vocabulary, neologisms, allusions to classical texts), existential motives (freedom, time, creative act), a specific synthesis of colloquial intonation and philosophical reflection. The results of the study demonstrate that Gavrilov's idiosyncrasy is characterized by a dialectic of playful and serious principles, intertextual saturation, semantic polyphony, and a special type of lyrical subject. These artistic techniques allow the writer to show his linguistic freedom, to manipulate the norms of language to create an aesthetic and expressive effect. The analysis contributes to the study of the poetics of modern writers, the transformations of postmodern text in Russian literature, and the specifics of modern idiosyncrasy. The scientific novelty of the work consists in introducing the texts of a modern Ugra author into scientific circulation, identifying the features of the regional idiosyncrasy and influences, and determining the place of Viktor Gavrilov's work in the modern literary process. The article reflects a holistic approach to the study of regional text, which corresponds to modern trends in the study of individual works in the general Russian literary process.
This article examines the linguistic, cultural, and pragmatic features of euphemisms in English and Uzbek discourse. Euphemisms—lexical units used to soften or obscure potentially offensive, taboo, or socially sensitive concepts—play a significant role in interpersonal communication and cultural norms. The study provides a comparative analysis of the semantic domains in which euphemisms most frequently occur, including death, illness, bodily functions, age, appearance, and socio-political issues. It also highlights the structural and pragmatic mechanisms of euphemism formation such as metaphor, metonymy, generalization, borrowing, and periphrasis. The findings indicate that while both languages employ euphemisms to maintain politeness and preserve social harmony, English tends toward institutionalized formulaic expressions, whereas Uzbek euphemisms are more culturally loaded and value-oriented. The article concludes that euphemisms reflect national mentality, linguistic worldview, and social etiquette norms.