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16504 papers
This study explores the evolving interplay between language, cognition, and digital media in the context of the attention economy.It proposes six key dimensionsrepresentation, virtuality, attention, community language, cognitive transformation, and the speech-writing continuum -through which digital communication reshapes linguistic practices.Drawing on contemporary theories of mediatisation, multimodality, and sociolinguistics, the authors argue that digital environments fundamentally alter linguistic representation and identity construction.Through the analysis of semiotic innovation, platform logic, and cognitive offloading, the article highlights how digital discourse is not a degradation of language but an adaptive response to new communicative affordances.The findings invite a rethinking of linguistic norms and suggest directions for further research into the ethical, cultural, and neurological consequences of pervasive digital communication.
The rapid expansion of digital media has significantly reshaped the ways in which language is used, adapted, and evolved in contemporary communication. This study explores how online platforms—ranging from social media networks to messaging applications—have influenced linguistic norms, introduced novel expressions, and reshaped traditional grammar and syntax. By analyzing communication patterns across diverse digital contexts, the research highlights how users creatively manipulate language to suit the immediacy, brevity, and interactive nature of online discourse. The findings reveal a dynamic linguistic environment where slang, emojis, abbreviations, and code-switching are not only prevalent but also indicative of broader cultural and generational shifts. This investigation contributes to the understanding of language as a fluid and evolving entity, driven increasingly by the participatory and fast-paced nature of digital interaction.
This article explores the peculiarities of how euphemistic and dysphemistic expressions function as tools in the author’s strategy of linguistic play within the narrative space of contemporary French writer Bernard Werber’s short prose. The research is based on the collection “L’Arbre des possibles et autres histoires”, where each story unfolds as a speculative scenario set in an alternative spatiotemporal dimension. Linguistic play is understood as a deliberate deviation from linguistic norms, a playful manipulation of linguistic resources to achieve a particular pragmatic resonance. In Bernard Werber’s works, euphemistic and dysphemistic substitutes manifest as linguistic entities drawn from diverse discursive domains – media, administrative, juridical, and scientific domains, particularly medical, biological, psychological, and philosophical, as well as lexemes and expressions from diverse linguistic registers interacting within a single context. Such stylistic heterogeneity, coupled with the contamination of usual media euphemisms with substitutes forged through alternative stylistic figures, generates not merely humorous, ironic, and satirical effects, but also cultivates an atmosphere of absurdity and, occasionally, cognitive dissonance within the reader’s consciousness. The synthesis of euphemisms and dysphemisms within unified contextual boundaries precipitates an effect of semantic and stylistic flickering – a peculiar oscillation between the veiling and illumination of an object’s negative attributes in a 'veil–spotlight' mode (in line with D. Jamet’s metaphors). This phenomenon induces cognitive tension in the reader, thereby activating their interpretative engagement. Through this mechanism, the author not only constructs possible worlds but also engages the reader in an active game of meaning decipherment – a manifestation that simultaneously embodies postmodernist literary practice and reflects the distinctive features of the writer’s individual stylistic signature.
The research paper is devoted to a comprehensive consideration of the mediative function of language in traditional Kazakh culture. The main purpose of the work is to identify the specifics of the use of language in the historical and cultural practice of Kazakh society as a means of coordinating interests, settling disputes and harmonizing social relations. In accordance with this goal, the article defines the following tasks: cultural and social foundations of linguistic mediation in traditional Kazakh society; description of linguistic structures and pragmatic strategies of institutions that ensure dispute resolution through speech; identification of semantic features of linguistic norms aimed at maintaining social harmony in national culture. In the course of solving these tasks, the oral oratorical heritage of the Kazakhs is analyzed from linguistic and pragmatic positions. The conducted research allowed us to establish that the mediative function of language in traditional Kazakh culture goes beyond simple communication. It forms the basis of mechanisms for maintaining social harmony, regulating the moral code of the community and the peaceful settlement of conflict situations. It is also proved that the speech culture of leaders and bi-speakers contributed to the formation of a specific national model of mediation, and its language strategies (forms of etiquette, indirect ways of expression, metaphorical and symbolic structures and pragmatic means of mitigation) are consonant with modern theories of mediation. The scientific significance of the study lies in the fact that the phenomenon of mediation in Kazakh culture is being systematically examined for the first time in a linguistic and pragmatic perspective, which makes it possible to identify the contribution of traditional speech experience to the development of the general theory of mediation. The practical value of the work is determined by the possibility of using the results obtained in mediation training programs, in the development of ethno-cultural models of negotiation practices, as well as in projects aimed at updating the culture of Kazakh oral speech.
This article examines ethnocultural identity in the artistic space of the postcolonial novel from the perspective of literary translation. Based on Abraham Verghese’s “Cutting for Stone” and its Russian translation by S. Sokolov, the study identifies and systematizes the specific difficulties involved in rendering the linguistic markers of identity. The object of the research is the linguistic and stylistic means of expressing ethnocultural identity in the original text of the novel, while the subject comprises the strategies and methods for translating these elements into Russian. The central argument is that recognizing the distinct genre-stylistic conventions of postcolonial literature is essential for developing effective translation strategies and achieving textual adequacy. The research employs a comprehensive methodological approach, integrating semantic, contextual, comparative, stylistic and translation analysis. The analysis reveals that the most significant challenges for a translator are posed by passages conveying cultural and linguistic polyphony, hybridity, and the fundamental oppositions that shape both character identity and the text’s conceptual space. The study highlights how elements such as foreign-language inclusions, erratives, graphons, and other deviations from linguistic norms act as manifestations of linguistic and cultural hybridity and as means of character self-identification. Furthermore, culture-specific items (realia) are used not only to embody cultural memory but also often acquire metaphorical and symbolic meanings, highlighting central narrative conflicts and functioning as markers of individual and collective identity. The novelty of this research lies in its endeavor to formulate practical recommendations for more authentically recreating the effects of linguistic and cultural hybridity and internal identity conflict in translation. The study concludes that while translating culturally marked units in a postcolonial novel, it is essential to consider its genre specificity, thematic and ideological content and macro-context.
The article offers a comprehensive analysis of the burlesque metalinguistic communicative personality (BMCP) in contemporary networked discourse, contrasted with the elite metalinguistic communicative personality (EMCP). The object of the study is modern network discourse as an environment for constructing and performing communicative personalities. The subject of the study is the burlesque metalinguistic communicative personality in network discourse, its structural and functional parameters, and the communicative effects arising from them (audience engagement, reframing, delegitimisation/repositioning, etc.) in comparison with EMCP. The purpose of the research is to theoretically conceptualise and empirically model the BMCP phenomenon and to develop criteria for distinguishing it from EMCP. In line with this purpose, the following objectives are formulated: to refine the terminology and definition of BMCP; to identify the theoretical and methodological framework of the study; to describe the structural, linguistic, sociocultural and psychomental characteristics of BMCP; to compare them with the parameters of EMCP; to outline ethical risks (manipulation, hate speech, privacy) and provide recommendations for further research. The empirical data include approximately 40,000 texts from 1,000 accounts across multiple platforms (X/Twitter, Facebook, Instagram, YouTube, Telegram). The study employs a combination of discourse-analytic, pragmalinguistic, context-interpretative, network, and quantitative methods. The findings demonstrate that BMCP represents a new and unstable type of linguistic behaviour that disrupts established cultural codes, employs burlesque, irony, and linguistic chaos, and foregrounds material and globalisation-related factors. This contrasts with EMCP, which fulfils norm-setting and educational functions. The prospects for further research involve expanding the classification of network communicative personalities, modelling their discursive strategies, and analysing the influence of burlesque practices on the formation of new linguistic norms and ethical standards in the digital environment.
Computational linguists have long recognized the value of version control systems such as Git (and related platforms, e.g., GitHub) when it comes to managing and distributing computer code.However, the benefits of version control remain under-explored for a central activity within computational linguistics: the development of annotated natural language resources.We argue that researchers can employ version control practices to make development workflows more transparent, efficient, consistent, and participatory.We report a proof-of-concept, GitHub-based solution which facilitated the creation of a legal English treebank.
Colour is a fundamental determinant of affective experience in immersive virtual reality (VR), yet the emotional and physiological impact of individual hues remains poorly characterised. This study investigated how fifteen calibrated Munsell hues influence subjective and autonomic responses when presented in immersive VR. Thirty-six adults (18–45 years) viewed each hue in a within-subject design while pupil diameter and skin conductance were recorded continuously, and self-reported emotions were assessed using the Self-Assessment Manikin across pleasure, arousal, and dominance. Repeated-measures ANOVAs revealed robust hue effects on all three self-report dimensions and on pupil dilation, with medium-to-large effect sizes. Reds and red–purple hues elicited the highest arousal and dominance, whereas blue–green hues were rated most pleasurable. Pupil dilation closely tracked arousal ratings, while skin conductance showed no reliable hue differentiation, likely due to the brief exposure times (30 s). Individual differences in cognitive style and personality modulated overall reactivity but did not alter the relative ranking of hues. Taken together, these findings provide the first systematic hue-by-hue mapping of affective and physiological responses in immersive VR. They demonstrate that calibrated colour shapes both experience and ocular physiology, while also offering practical guidance for educational, clinical, and interface design in virtual environments.
PURPOSE: This study interrogates the intercultural experiences of African international students (AIS) in a US Midwestern University. With a focus on West African students, the study explores how students confront and overcome linguistic, cultural, and systemic barriers as they create new dynamic spaces which are neither American nor African, but a mixture of both. SUBJECTS: 12 West African students. METHODS: I utilized ethnographic observations and in-depth interviews to better understand how the AIS engage in ongoing identity negotiation through language, food, cultural expressions, and technology. I conducted 40 hours of participant observation research over a 5-month period and interviewed 12 West African students. OUTCOME: Drawing on the theoretical constructs of hybridity and language ideology, the findings reveal how AIS negotiate identity by using traditional African cultural traits, rooted in what I term Africanism—with new cultural influences, generating unique, fluid and constantly-evolving hybrid identities. Language emerges as a powerful site of hybridity, where students shift between linguistic norms to balance intelligibility and cultural authenticity. These hybrid identities emerge through active, creative processes. IMPACT: The findings offer important implications for higher education, emphasizing the need for more culturally responsive support systems that recognize the distinct experiences of African students. Additionally, the study contributes to the fields of communication and migration studies by advancing a nuanced understanding of identity formation in transnational contexts. By foregrounding the voices of African students, this research challenges monolithic representations of international students and promotes intercultural dialogue in fostering inclusive communities and enriching educational environments.
The article offers a comprehensive analysis of the burlesque metalinguistic communicative personality (BMCP) in contemporary networked discourse, contrasted with the elite metalinguistic communicative personality (EMCP). The object of the study is modern network discourse as an environment for constructing and performing communicative personalities. The subject of the study is the burlesque metalinguistic communicative personality in network discourse, its structural and functional parameters, and the communicative effects arising from them (audience engagement, reframing, delegitimisation/repositioning, etc.) in comparison with EMCP. The purpose of the research is to theoretically conceptualise and empirically model the BMCP phenomenon and to develop criteria for distinguishing it from EMCP. In line with this purpose, the following objectives are formulated: to refine the terminology and definition of BMCP; to identify the theoretical and methodological framework of the study; to describe the structural, linguistic, sociocultural and psychomental characteristics of BMCP; to compare them with the parameters of EMCP; to outline ethical risks (manipulation, hate speech, privacy) and provide recommendations for further research. The empirical data include approximately 40,000 texts from 1,000 accounts across multiple platforms (X/Twitter, Facebook, Instagram, YouTube, Telegram). The study employs a combination of discourse-analytic, pragmalinguistic, context-interpretative, network, and quantitative methods. The findings demonstrate that BMCP represents a new and unstable type of linguistic behaviour that disrupts established cultural codes, employs burlesque, irony, and linguistic chaos, and foregrounds material and globalisation-related factors. This contrasts with EMCP, which fulfils norm-setting and educational functions. The prospects for further research involve expanding the classification of network communicative personalities, modelling their discursive strategies, and analysing the influence of burlesque practices on the formation of new linguistic norms and ethical standards in the digital environment.
This paper examines the rapid evolution of net slang and its consequential impact on Standard Mandarin, highlighting the interplay between net slang and traditional linguistic norms. The study begins by delineating three principal characteristics of net slang: multiformity, simplicity, and flexibility. Through a survey assessing Chinese attitudes towards net slang, both positive and negative viewpoints are revealed. Results indicate that while net slang can enhance communication with creative elements such as emoticons, it also risks grammatical divergence and semantic deviations. These impacts are particularly pronounced in the realm of Chinese language education, where net slang affects graphology and fosters misinterpretations. Despite these challenges, the paper advocates for a balanced approach, proposing the integration of beneficial aspects of net slang into Standard Mandarin following rigorous evaluation. Emphasizing language sustainability, the study underscores the role of educators and parents in promoting reading, thereby ensuring the harmonious coexistence of net slang and standard language while preserving linguistic integrity for future generations.
Social relationships are central to well-being. A subgroup of afferent nerve fibers, C-tactile (CT) afferents, are primed to respond to affective, socially relevant touch and may mitigate the effects of stress. The endocannabinoid ligand anandamide (AEA) modulates both social reward and stress. We thus hypothesized that AEA levels would be associated with the perceived pleasantness of affective touch in humans. Across two studies, we explored perceptions of affective, socially relevant touch and general affective stimuli. In study 1, adult participants (N = 101) were recruited based on presence (CM+) or absence (CM-) of documented childhood maltreatment (N = 52 CM+; N = 49 CM-). In study 2, healthy individuals were randomized to receive an inhibitor of fatty acid amide hydrolase (FAAH; PF-04457845) to increase AEA levels (n = 16) or placebo (n = 29). Outcomes included self-report ratings of touch pleasantness and intensity, valence and arousal ratings of affective images, and plasma levels of endocannabinoids AEA and 2-AG, cortisol, and oxytocin. In study 1, higher AEA levels were associated with a reduced preference for affective, CT-optimal touch. In study 2, pharmacological elevation of AEA resulted in reduced preference for affective touch. These effects were specific to social processing, as AEA levels were not related to ratings of affective images. In contrast to our hypothesis, elevated AEA was associated with reduced pleasantness ratings of CT-optimal, affective touch. This provides novel, in-human data linking AEA to social processing, adding nuance to the rationale for its use as a potential novel therapeutic target in disordered in social processing.
This article explores the theoretical foundations and practical implications of adequacy and equivalence in translation studies. Drawing upon the frameworks of prominent scholars such as Y.I. Retsker, L.S. Barkhudarov, the paper examines how different approaches define and apply the concepts of equivalence in relation to linguistic norms, functional correspondence, and communicative effect. The analysis highlights the distinction between formal, dynamic, and functional equivalence, and the roles they play in achieving accurate translation outcomes. Special attention is given to the translator’s linguistic and cultural competence and the inherent asymmetry in bilingualism, which significantly affects translation choices. Furthermore, the article discusses translation criticism as a tool for evaluating the quality and equivalence of translated texts.
The present research assessed university student stakeholders’ perceptions of positive outcomes (i.e., appropriateness and benefits of conferencing) and negative outcomes (i.e., endangerment and revictimization of the complainant) associated with restorative justice-based direct conferencing in sexual misconduct cases. Stakeholders received random assignment to a 2 (allegation severity: more vs. less) × 2 (evidence strength: lower vs. higher) between-participant experimental design. More severe allegations and higher evidence strength were associated with lower ratings of appropriateness; allegation severity and evidence strength interacted to affect ratings of benefits; and more severe allegations, but not stronger evidence, were associated with higher ratings of endangerment and revictimization. Belief in the alleged perpetrator’s guilt explained the relationship between evidence strength and ratings of appropriateness, and desire to punish the alleged perpetrator explained the relationship between allegation severity and ratings of appropriateness. Researchers and Title IX coordinators should evaluate and respond to stakeholder sentiment toward direct conferencing.
Large language models (LLMs) are widely deployed in settings where both reliability and efficiency matter. We present a calibrated, seed‑robust empirical comparison of an encoder fine‑tuned model (bidirectional encoder representations from transformers (BERT)‑base) and a decoder in‑context model (generative pre-trained transformer (GPT)‑2 small) across Stanford question answering dataset v2.0 (SQuAD v2.0) and general language understanding evaluation (GLUE)-multi-genre natural language inference (MNLI), Stanford sentiment treebank 2 (SST‑2). Beyond accuracy, we assess reliability (expected calibration error with reliability diagrams and confidence–coverage analysis) and efficiency (latency, memory, throughput) under matched conditions and three fixed seeds. BERT‑base yields higher accuracy and lower calibration error, while GPT‑2 narrows gaps under few‑shot prompting but remains more sensitive to prompt design and context length. Efficiency benchmarks show that decoder‑only prompting incurs near‑linear latency/memory growth with k‑shot exemplars, whereas fine‑tuned encoders maintain stable per‑example cost. These findings offer practical guidance on when to prefer fine‑tuning versus prompting and demonstrate that reliability must be evaluated alongside accuracy for risk‑aware deployment.
The article explores comic discourse as a multifaceted phenomenon that forms at the intersection of linguistic and cultural aspects. The main purpose of the work is to analyze the specifics of comic utterance in the context of various cultural realities and language systems. Special attention is paid to the influence of cultural peculiarities on the processes of creating and interpreting humor, as well as linguistic tools that ensure the transmission of a comic effect. The analysis of the humorous language is carried out, aimed at studying the mechanisms of the generation and perception of humor within the framework of linguistic and cultural contexts. The key factors determining the originality of a humorous utterance are identified, as well as the interrelationships between linguistic means and cultural features in the process of comic communication are investigated. The results of the study indicate that comic discourse acts as a reflection of cultural traditions and social norms, and also serves as a tool for analyzing the dynamics of intercultural interaction. It is established that the perception of humor is determined not only by linguistic norms, but also by cultural values, stereotypes and contexts in which communication is carried out. Thus, comic discourse is a significant object of study for understanding the interrelationships between language and culture.
ABSTRACT Investors and policymakers increasingly worry that climate change threatens sovereign debt. While recent studies find a negative effect, they typically estimate models assuming a time‐invariant impact and rely on climate variables endogenous to economic and policy conditions. This paper addresses both concerns by employing a long‐horizon, nonactionable, external measure of climate risk from the Notre Dame Global Adaptation Initiative, interacted with year‐fixed effects to capture any time‐varying impacts. Analyzing sovereign issuer default ratings from major agencies, I find no evidence that climate risk systematically affects ratings or that its influence has evolved over time. I confirm these results using climate disaster data from the Emergency Events Database. These findings likely reflect credit rating agencies' short‐ to medium‐term focus on economic fundamentals rather than on long‐term climate risks.
Background: Color plays a pivotal role in visual perception, shaping emotions, attention, and cognition, particularly in art-related contexts. However, the influence of artistic training on color perception and neural processing remains poorly understood.Methods: This study examined differences in color perception between art and non-art groups using behavioral ratings and EEG data. Forty-four participants (22 art majors: 21.82 ±1.56 years old; 22 non-art majors: 20.73 ± 1.67 years old) with an equal gender ratio were recruited. Participants completed color perception tasks involving cool, warm, and neutral hues while EEG data were recorded with a 65-electrode system. Behavioral ratings and ERP components (P2 and P3) were analyzed, supplemented by decoding analysis to uncover neural processing patterns.Results: Behavioral data indicated that warm hues elicited higher emotional valence ratings than cool and neutral hues for both groups. EEG analysis revealed that warm and cool hues evoked larger P3 amplitudes compared to neutral hues. A group-hue interaction was observed in the P2 component, with the non-art group showing greater variability in P2 amplitudes across hues. Decoding analysis provided further evidence of distinct neural processing differences between the two groups.Conclusion: These findings demonstrate that color perception differs between art and non-art groups, particularly in the neural processing of the P2 component. Warm and cool hues elicit stronger emotional and attentional responses, highlighting distinct cognitive mechanisms influenced by artistic expertise.Keywords: ERP; color perception; P2; P3; artistic training
= 255) viewed 76 pictures with affective content and rated their experienced affect. Facial muscle activity during picture presentation was assessed via electromyography (EMG) as a direct physiological measure of affective reactions. We used a multilevel model to quantify affective awareness as the strength of the intraindividual relationship between a person's EMG reactions and affect ratings. This relationship was positive on average and differed significantly between participants. These individual differences in affective awareness were reliable and stable over time. Affective awareness was higher for women than for men and went along with generally strong affective EMG reactivity and better socioemotional abilities. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Loneliness has been linked to impairment in emotional appraisal and emotion regulation. This study aimed to test a set of pre-registered hypotheses by suggesting that loneliness alters bottom-up appraisal processes of social threat and top-down emotion regulation mechanisms. In this double-blind, within-subject study, we included 120 individuals (equally split between highly lonely and non-lonely groups) who received active (2 mA) or sham transcranial direct current stimulation over the left or right dorsolateral prefrontal cortex (dlPFC) in separate sessions. Participants were asked to passively watch negative or neutral stimuli or to reinterpret negative stimuli to decrease their affective response. Overt behavioral responses (valence and arousal self-response) and covert physiological markers (event-related potentials [ERPs]) of the affective response in each group were analyzed separately for stimuli with and without social content. Active dlPFC stimulation enhanced neural modulation during the reappraisal of social stimuli, as reflected in a larger difference in late positive potential between reappraised and passively viewed negative images. However, the valence rating difference between these conditions suggested less effective reappraisal under active stimulation. Anodal stimulation of the left dlPFC selectively decreased self-reported emotional reactivity during the passive viewing of social stimuli in highly lonely individuals. However, this effect occurred without corresponding changes in ERP markers. Loneliness may primarily impair the self-monitoring of affective responses rather than that of regulatory mechanisms. The left dlPFC supports the accurate self-assessment of emotional states, and targeted non-invasive brain stimulation can alleviate loneliness-related difficulties in this domain.
Background and objective Navigating interprofessional team dynamics is essential for high-quality patient care in pediatric settings. This study involved medical students on a pediatric clerkship who explored the characteristics of high- and low-performing clinical teams by considering drivers and barriers to effective team performance. By analyzing these reflections, the study aimed to identify key facilitators and barriers to effective team-based care. Methods Survey evaluations and narrative reflections were completed by third-year students (M3s) at a single US allopathic medical school during their pediatric clerkship after receiving training in TeamSTEPPS® and Institute for Healthcare Improvement (IHI) Open School, two programs that support quality improvement (QI) in healthcare. Descriptive statistical and inductive thematic analyses were conducted on the resulting 183 narratives. A valence rating system was employed to quantify narrative responses as positive/attractive or negative/aversive, with a Cronbach alpha of 0.958 between two independent reviewers. Results Inductive thematic analysis generated 40 themes that we grouped under the five TeamSTEPPS® skill domains (situation monitoring, communication, leadership, team structure, mutual support) into thematic conceptual models. High-performing teams demonstrated open communication, role clarity, shared understanding, and organized task delegation. Low-performing teams displayed a lack of information exchange, uncertain team roles, unhealthy power dynamics, and disorganized task delegation. Conclusions After instruction in QI methods, pediatric clerkship students identified consistent drivers of and barriers to effective team performance. The themes within the narrative reflections can provide insights into improving patient care delivery, specifically around situation monitoring, communication, and team structure.
Learner Handover (LH) involves sharing information about learners between faculty supervisors, aligning with a growth mindset. Previous studies, however, demonstrate LH can bias subsequent ratings. Most of these studies collect ratings after a single encounter but faculty often have multiple interactions with learners potentially mitigating LH-related bias. This study explored if LH influences faculty ratings, entrustment decisions and feedback after observing several encounters of the same learner. Internal medicine faculty (n = 57) from five medical schools were randomly assigned to one of three study groups. Each group received either positive, negative or no LH prior to watching five simulated resident-patient encounter videos of the same white male resident. Participants rated each video using an entrustment scale, the Mini-CEX and provided written feedback. Feedback was assigned a valence score (-3 to + 3). There were no statistically significant differences between the mean ratings across the LH conditions (positive, control, negative) for entrustment [3.42, 3.26, 3.62], Mini-CEX [6.00, 5.90, 6.28] or feedback valence ratings [-0.34, -0.99, -0.74]. In the post-study questionnaire, most raters reported the LH had minimal effect on their decisions. Only 29% of raters guessed the true purpose of the study. Unlike previous studies, LH had no effect on ratings, entrustment decisions, or feedback after one encounter, nor over subsequent encounters with the same resident. These findings suggest LH's influence may vary and highlight the need for replication under different conditions, including diverse genders and equity-deserving groups, to identify factors that contribute to or mitigate bias.
Math anxiety poses significant challenges for university psychology students, affecting their career choices and overall well-being. This study employs a framework based on behavioural forma mentis networks (i.e. cognitive models that map how individuals structure their associative knowledge and emotional perceptions of concepts) to explore individual and group differences in the perception and association of concepts related to math and anxiety. We conducted 4 experiments involving psychology undergraduates from 2 samples (n1 = 70, n2 = 57) compared against GPT-simulated students (GPT-3.5: n2 = 300; GPT-4o: n4 = 300). Experiments 1, 2, and 3 employ individual-level network features to predict psychometric scores for math anxiety and its facets (observational, social and evaluational) from the Math Anxiety Scale. Experiment 4 focuses on group-level perceptions extracted from human students, GPT-3.5 and GPT-4o's networks. Results indicate that, in students, positive valence ratings and higher network degree for "anxiety", together with negative ratings for "math", can predict higher total and evaluative math anxiety. In contrast, these models do not work on GPT-based data because of differences in simulated networks and psychometric scores compared to humans. These results were also reconciled with differences found in the ways that high/low subgroups of simulated and real students framed semantically and emotionally STEM concepts. High math-anxiety students collectively framed "anxiety" in an emotionally polarising way, absent in the negative perception of low math-anxiety students. "Science" was rated positively, but contrasted against the negative perception of "math". These findings underscore the importance of understanding concept perception and associations in managing students' math anxiety.
Large language models (LLMs) have achieved remarkable success across various natural language processing (NLP) tasks.However, recent studies suggest that they still face challenges in performing fundamental NLP tasks essential for deep language understanding, particularly syntactic parsing.In this paper, we conduct an in-depth analysis of LLM parsing capabilities, delving into the underlying causes of why LLMs struggle with this task and the specific shortcomings they exhibit.We find that LLMs may be limited in their ability to fully leverage grammar rules from existing treebanks, restricting their capability to generate syntactic structures.To help LLMs acquire knowledge without additional training, we propose a selfcorrection method that leverages grammar rules from existing treebanks to guide LLMs in correcting previous errors.Specifically, we automatically detect potential errors and dynamically search for relevant rules, offering hints and examples to guide LLMs in making corrections themselves.Experimental results on three datasets using various LLMs demonstrate that our method significantly improves performance in both in-domain and cross-domain settings.
Abstract: Emotions impact pain; appetitive (pleasant) emotions reduce pain, and aversive (unpleasant) emotions increase pain. Emotion regulation (ER) strategies can alter emotional experience, and we have shown that ER can alter emotional modulation of pain, but not emotional modulation of spinal nociception (as assessed by nociceptive flexion reflex, NFR). The current study examined whether ER influences the emotional modulation of cortical event-related potentials (ERPs) in response to nociceptive input. To investigate, 68 pain-free individuals viewed pleasant (erotic), neutral, and unpleasant (mutilation) pictures during which painful electric stimulations were delivered. Participants viewed one block of pictures without engaging in ER and were then randomly assigned to ER (suppress or enhance) employed during a second block of pictures. Picture-evoked valence and arousal ratings, skin conductance response, and corrugator electromyogram (EMG) suggested that ER successfully regulated emotional experience. Instructions to suppress led to a significant reduction of emotional modulation of self-reported pain (i.e., reducing pleasure-induced pain inhibition and displeasure-induced pain facilitation), but neither NFRs nor ERPs were affected. Paradoxically, enhance instructions had no effect on pain or NFR, but were associated with a general suppression of the P260 ERP, indicating non-specific emotional arousal up-regulation. Findings indicate ER can independently impact emotional modulation at perceptual and supraspinal levels, but does not impact spinal nociception. Given that emotional suppression led to decreases in displeasure-evoked pain facilitation without reducing displeasure-evoked facilitation of spinal or supraspinal responses to nociception, future research should determine whether this divergence is associated with positive or negative long-term consequences.
The computational burden associated with transformer architectures like BERT presents obstacles for deployment in resource-constrained environments. Contemporary compression methodologies primarily employ uniform compression strategies across diverse input instances, neglecting the inherent variability in computational requirements among different examples. In this paper, we present a distinct example-aware adaptive layer pruning framework that dynamically orchestrates transformer layer selection contingent upon input complexity characteristics. Our methodology incorporates a compact policy network architecture that generates binary activation masks for individual layers, allowing for personalized computational resource allocation per input instance. Through the implementation of differentiable Gumbel-Sigmoid relaxation mechanisms, we enable end-to-end optimization protocols while preserving classification accuracy. Comprehensive empirical evaluation on the Stanford Sentiment Treebank (SST-2) corpus demonstrates our approach achieving 93.0% classification accuracy while utilizing just 3.81 layers on average from the complete 12-layer architecture, yielding a substantial 3.15 × compression ratio. This methodology outperforms established compression techniques including DistilBERT, TinyBERT, and conventional static pruning approaches, establishing a superior equilibrium between accuracy preservation and computational efficiency in BERT compression paradigms.
Large Language Models (LLMs) employ deep learning algorithms to generalize patterns in data. Applying these LLMs to classification tasks can reduce the required labor and time. The research aims to fine-tune the LLM Llama 3.1 to correctly identify whether a chosen text message exhibits a positive or negative emotion. The goal of this procedure is to apply the fine-tuned LLM to large databases of text messages and locate users whose recent texts contain a large proportion of negative samples. This way, I can alert the users and direct them to help very early on. I chose the Stanford Sentiment Treebank v2 (SST-2) dataset. It mimics the emotional polarity of real texts with its even positive-negative sample distribution and its contextless format. I used the Unsloth framework and LoRa to significantly reduce the resources required during the fine-tuning process. I tested the model by taking SST-2’s train split and inputting them individually into the trained model. Using this method, I found the Llama model to be highly accurate, with an accuracy of 94.8%. Interestingly, it had a high average Binary Cross-Entropy (BCE) Loss of 0.782 but achieved high accuracy. The testing against other models shows that the BCE Loss for sentiment analysis is not correlated to the actual accuracy of the model. From the results, I determined Llama 3.1 was the most suitable LLM for the sentiment analysis of large text databases.
Math anxiety poses significant challenges for university psychology students, affecting their career choices and overall well-being. This study employs a framework based on behavioural forma mentis networks (i.e. cognitive models that map how individuals structure their associative knowledge and emotional perceptions of concepts) to explore individual and group differences in the perception and association of concepts related to math and anxiety. We conducted 4 experiments involving psychology undergraduates from 2 samples (n1 = 70, n2 = 57) compared against GPT-simulated students (GPT-3.5: n2 = 300; GPT-4o: n4 = 300). Experiments 1, 2, and 3 employ individual-level network features to predict psychometric scores for math anxiety and its facets (observational, social and evaluational) from the Math Anxiety Scale. Experiment 4 focuses on group-level perceptions extracted from human students, GPT-3.5 and GPT-4o's networks. Results indicate that, in students, positive valence ratings and higher network degree for "anxiety", together with negative ratings for "math", can predict higher total and evaluative math anxiety. In contrast, these models do not work on GPT-based data because of differences in simulated networks and psychometric scores compared to humans. These results were also reconciled with differences found in the ways that high/low subgroups of simulated and real students framed semantically and emotionally STEM concepts. High math-anxiety students collectively framed "anxiety" in an emotionally polarising way, absent in the negative perception of low math-anxiety students. "Science" was rated positively, but contrasted against the negative perception of "math". These findings underscore the importance of understanding concept perception and associations in managing students' math anxiety.
When stimuli are retained in visual working memory (VWM), external stimuli which overlap this representation capture attention when performing a visual task. It has not been determined whether this mechanism can partly account for attentional capture by categories of real-world affective stimuli. Across five dual-task visual search and VWM change detection experiments (4/5 pre-registered; total N = 119) participants had to detect the change in either positive (kitten) or threat-related (spider) animal exemplars, whilst performing an intervening visual search task with peripheral distractors from these affective categories. Affective stimulus associations were confirmed by self-reported arousal and valence ratings in all samples, and confirmed in an independent sample (n = 82). It was hypothesised that threat-related and positive distractors would capture attention more, versus a neutral (bird or no distractor) baseline, when matching the contents of VWM. Experiments 1 - 3, however, found no evidence of increased capture by VWM-matching affective stimuli, though there was cumulative evidence of goal-independent capture by threat-related distractors. When, however, the trial structure became unpredictable, requiring constant preparation for the VWM task response (Experiment 4), or advanced action preparation to the VWM task was enabled (Experiment 5), then VWM-matching threat-related distractors caused greater attentional capture. This VWM-driven capture, however, was not found for positive distractors in any experiments. The results probe the boundary conditions when VWM contents drive attentional capture by entirely task-irrelevant affective categories, and suggests that background memory representations may not influence attention unconditionally, and instead may depend partly on their current prioritisation.
Recent studies demonstrate that visual working memory capacity is greater for real-world objects compared to simple features like colors and scrambled objects. This led to the proposal that conceptual meaning plays a critical role in structuring visual working memory (Chung, Brady, & Störmer, 2024). However, one challenge in comparing memory performance across stimulus sets is that they vary not only in conceptual meaning but also in perceptual similarity. Thus, some of the working memory benefits for real-world objects may arise from these perceptual differences – for example whether the visual system interprets inputs as objects or not. Here, we provide a strong test of this by using novel objects generated by generative adversarial networks designed to resemble real objects (Cooper et al., 2023), and compare memory performance across novel and familiar real-world objects. Across experiments, participants remembered sets of four objects drawn from one of four stimulus types: familiar objects, novel objects, scrambled familiar objects or scrambled novel objects. After a short delay, they completed a two-alternative-forced-choice task, selecting between a target and a foil object. Results revealed enhanced working memory performance only for familiar objects, with no differences among the other conditions. Importantly, convolutional neural networks analyses confirmed comparable perceptual similarities between familiar and novel objects relative to scrambled stimuli. Thus, although novel objects closely resembled familiar objects, they did not enhance memory performance. Further correlation analyses revealed that subjective familiarity ratings are correlated with memory performance for familiar objects, while low-level features like colorfulness are correlated with memory performance for novel objects, suggesting that visual memory relies on different aspects to best remember each stimulus type. Overall, these results demonstrate that “object-ness” alone is insufficient to enhance visual working memory. Instead, familiarity and conceptual knowledge are critical in improving working memory performance.
Generic nouns such as Sache and Ding pose a challenge for semantic annotation due to their referential underspecification and context-dependent meaning. Although frequently classified under categories like {artefact} or {object}, their actual referents often belong to abstract or cognitive domains, as in Der Placeboeffekt ist eines der faszinierendsten Dinge in der Welt der Medizin. Drawing on valency grammar, this study shows that these nouns activate different argument structures depending on their syntagmatic environment, reflecting semantic flexibility and combinatorial variability. Lexical databases such as GalNet or GermaNet frequently assign multiple synsets to these nouns, illustrating their ontological ambiguity. This paper examines whether large language models (LLMs) can replicate this nuanced classification. Using a gold standard corpus annotated by linguists, we implement a two-step prompting strategy —supplying LLMs with predefined semantic tags and contextual windows— to test their performance. The results underscore the limitations of current LLMs in dealing with the lexical underspecification of generic nouns, even when provided with an extended context window. These findings contribute to ongoing discussions on the automation of semantic tagging and point to meaningful ways in which AI systems can complement human expertise in natural language processing tasks.
Abstract Older adults consistently report higher emotional well-being despite some physical and mental declines with age. Some theorize this is due to differences in emotion regulation, however no conclusive evidence for age differences in emotion regulation strategies has emerged. Emotion regulation tactics, such as positive-approaching (enhancing the positivity of a situation) and negative-receding (reducing the negativity of a situation), hold promise for uncovering age differences. However, no studies to date have considered whether tactic vary in their physiological profiles. Thus, this study investigated 35 younger (M = 19.06 years, SD = 3.58; 17 women) and 42 older (M = 74.02 years, SD = 4.69; 23 women) participants who viewed emotionally-evocative videos and regulated emotions using positive-approaching and negative-receding techniques (with both regulation blocks compared to a neutral video block to control for baseline differences in psychophysiology). Multi-level linear models revealed significant Age x Sex x Tactic interactions, such that positive-approaching tactics (vs negative-receding) were associated with lower arousal ratings for younger women and older men (but not younger men or older women). While there was no tactic difference in self-reported arousal for older women, Respiratory Sinus Arrythmia (a measure of heart activity associated with calm parasympathetic states) was higher during positive-approaching for them. Interestingly, older men had higher RSA during negative-approaching tactics as compared to positive-approaching. These findings suggest emotion regulation tactics have age and sex differential impacts on self-reported and physiological arousal. Future work may disentangle physiological activation and self-reported behavior by also considering the role of interoceptive awareness.
“Pictures are worth a thousand words," yet most platforms like Yelp, Google Maps, Instagram, Walmart, and Amazon require users to provide text, ratings, and images. Images often capture a user's intent, and the features within the images typically correlate with that intent. In this paper, we extract various features from images (such as edge distribution, color distribution, text within the image, focus, etc.) and compare simple vs. complex models to predict the ratings associated with these images. We find that features such as brightness and contrast significantly explain the rating at image-level, and models such as random forest and logistic regression provide a 0.84 F-1 score when predicting the rating. In the era of generative AI, we anticipate that sharing an image will allow platforms to auto-generate user intent and image ratings, thereby simplifying the dissemination of information.
Ce travail de recherche se penche sur l’analyse contrastive de l’annotation syntaxique de certaines constructions complexes en arabe et en français, réalisée selon le schéma Universal Dependencies (UD) et de sa variante Surface-Syntactic Universal Dependencies (SUD). L’analyse portera sur trois catégories de constructions: les constructions relatives, les constructions à verbe support et les constructions copulatives et avec un auxiliaire. La recherche a un double but: d’une part, elle vise à explorer comment les schémas UD et SUD représentent ces constructions syntaxiques en arabe et en français. D’autre part, il s’agira d’évaluer la pertinence et la capacité de ces schémas à rendre compte des particularités propres à chaque langue. Les résultats révèlent que les annotations syntaxiques, bien que cohérentes pour les cas standards, divergent dans les constructions non canoniques, une incohérence constatée tant entre les corpus arborés arabe et français qu’au sein de chacun d’eux. Des solutions s’imposent: harmoniser les treebanks arabes et français existants par la standardisation et la correction, et optimiser les guides d’annotation pour les langues concernées.
Background Dementia can impair cognitive functions in older adults and further affect language abilities, such as sentence construction. The use of linguistic biomarkers for detecting cognitive decline and early stages of dementia has demonstrated great potential due to its low-cost and non-invasive nature, especially towards a large aging population.Aims In this study, we focused on the syntactic complexity and aimed to identify highly discriminative syntactic features and those set in differentiating Mandarin-speaking older adults with and without cognitive impairment using machine learning models.Methods & procedures We established a new cohort consisting of 52 Chinese older participants, which has not been reported in any previous studies. After applying exclusion criteria, 49 were selected for this study, including 24 labeled as cognitively normal (CN) and 25 as cognitively impaired (CI) based on their scores in the MoCA-B test (Chinese version). Each of the participants completed three connected speech tasks: a picture description task (the Picnic Scene), a story narrative task (Sanmao’s Wanderings), and a story recall task (Cowherd and Weaver Girl). The speech recordings were automatically transcribed into text files and manually checked. We then performed treebank annotation, which was also manually corrected. Subsequently, 17 linguistic unit-based and 10 syntactic structure-based features were extracted from the texts using Python codes. To identify key syntactic features and feature sets, we first examined the discriminative power of these features per se for distinguishing between the CI and CN groups. Then we employed three machine learning algorithms to identify feature combinations performing the best in terms of high accuracy and AUC in cross-validation and minimal number of basic features.Outcomes & results No single feature or feature panels showed high discriminability between groups across all three tasks. However, certain macro-level features with high measurement robustness, such as mean depth of nodes, mean dependency distance, and the ratio of head-final dependencies in specific tasks are noteworthy. Moreover, through machine learning algorithms, we identified several well-performing feature combinations in terms of the metrics of cross-validation mean accuracy and area under curve (AUC). Notably, a feature panel with only two features (mean depth of nodes, and proportions of prepositional dependencies) achieved the best result across classifiers in the story narrative task (ACC = 0.840, AUC = 0.867).Conclusions This study demonstrated the potential of using purely treebank-derived features within a single linguistic domain (syntax) for cost-effective cognitive impairment screening, indicating the value of syntactic biomarkers for cognitive impairment in Mandarin-Speaking Older Adults.
This study explores the sociolinguistic characteristics of Generation Alpha's language use on TikTok, a platform blending creativity and social interaction. Examining code-switching, slang, and the influence of visual elements highlights how these features shape digital identities and cultural expression. The research uses qualitative methods like content analysis and user interviews to reveal how Gen Alpha adapts language to TikTok’s standards while challenging traditional linguistic norms. The findings demonstrate that digital communication significantly impacts the language of today’s youth, showcasing Generation Alpha’s sensitivity and inventiveness in coining new terms driven by rapid technological advancements. Social, cultural, and technical factors influence these communication patterns, with video and visual exchanges enhancing communication skills, shaping social identities, and fostering intergenerational connections. This research emphasizes the role of platform-specific language practices in shaping teenage culture and advancing sociolinguistics in social media contexts. It concludes that Generation Alpha employs a relaxed, creative, and trend-sensitive vocabulary, particularly on TikTok, reflecting contemporary digital communication trends. The study underscores the importance of understanding language dynamics in an ever-evolving digital landscape.
This paper examines how the Han script, as a non-phonographic and ideographic writing system, has historically mediated linguistic diversity in East Asia and how it continues to function as a site of negotiation between standardized national languages and vernacular or subaltern voices. Drawing on Jacques Derrida’s critique of phonocentrism and Gilles Deleuze and Félix Guattari’s theory of minor literature, the study argues that the Han script resists the phonographic imperatives of modern nation-states by retaining semiotic elasticity. Through this capacity, it enables the co-articulation of dominant and minor languages, allowing alternative modes of voice and subjectivity to emerge within its scriptural space. Case studies from Taiwan, particularly the diasporic Chinese communities in Taiwan and China illustrate how Han écriture enables both subversion and accommodation of linguistic norms, as seen in Liām-kua, Mahua literature, and scriptal visuality. These examples show that Sinophone expression is not merely a reaction to central authority but often operates within a hybridized field of cultural production that exceeds binary oppositions. Rather than conceptualizing Sinophone texts solely as resistance, the article proposes a reframing of scriptal mediation as an arena of affective, performative, and visual negotiation. It offers a new account of East Asian modernity as shaped not only by state-led language reform or colonial influence but also by the persistent pluralism encoded in the materiality of script. The Han script thus emerges not as a static emblem of tradition but as a dynamic infrastructure through which linguistic diversity is continuously voiced, managed, and reimagined.
We use advertising billboards and posters of three mobile telecom giants to spotlight translanguaging spaces as marketing strategies in the multilingual and multicultural landscapes of Zambia (south-central Africa). We argue that telecommunications giants deploy, in their marketing discourses, an assemblage of various semiotic resources on translanguaging spaces. Consequently, we show that this occasions a breakdown of language ideologies and blurs boundaries between languages of different sociopolitical statuses, reach and appeal, much to the benefit of telecom giants who wish to grow their subscriber base. We show how the outcome of semiotic complementarity of resources in translanguaging spaces addresses multiple actors in one design by integrating linguistic resources formerly separated by different practices and places for marketing purposes. In this way, we conclude that arising from (semiotic) creativity and defiance of expected linguistic norms, the sociolinguistics of translanguaging spaces admit both amalgamated forms and full-fledged languages in unpredictable ways, enabling telecom giants to achieve their marketing objectives.
Previous research regarding verb production deficits in Alzheimer’s disease (AD) primarily concentrated on either the quantity of verbs (inflections) or verb-related semantic units, with little consideration given to verb production within syntactic contexts, i.e., verb collocations. This study explored verb collocations in the connected speech of Chinese AD patients within the framework of dependency syntax. The findings include: (1) The frequency distribution of verb collocation patterns in AD follows the Mixed-Poisson function similar to that in the healthy control elderly (HCE) and healthy control young (HCY) groups, but it differs in the use of low- and high-collocation patterns; (2) In the static aspect, the AD patients exhibit the lowest overall mean collocation pattern (MCP) among the three treebanks, followed by the HCE group. In the dynamic aspect, the MCP and sentence length in the three groups show a similar synergistic relation, but differences exist in the quadratic regression parameters; (3) Based on the probabilistic distribution of verb-governed dependencies, the AD patients exhibit the lowest syntactic proficiency, followed by the HCE group. The differences between the AD patients and the HCE group confirm the presence of verb production deficits and a decline in syntactic proficiency in AD. Although the HCE group also shows mild language deterioration compared to the HCY group, the extent of these changes is considerably smaller than that observed in the AD patients. These findings suggest that while aging may contribute to a partial decline in language abilities, AD markedly exacerbates and accelerates this deterioration process, following a pathological trajectory distinct from normal aging.
The goal of this research is to provide a new computational framework for analyzing morphological patterns, designed for use in digital philology courseware. There is a computer framework called MorphoScribe, an accessible computer program that utilizes deep learning to identify patterns and segment data based on predefined rules. Using Universal Dependencies (UD) Treebanks makes this possible. MorphoScribe is the parts that make it possible. The software was tested on UD datasets with ten different languages, achieving an average morphological parsing accuracy of 94.2%. The testing that was done made this possible. Another thing to consider is that its precision and recall rates were higher than 93% and 92%, respectively, compared to other products. When it came to the error rates for morpheme boundary recognition, the system was able to lower them by 37% compared to the baseline models. According to the results of educational trials with 120 pupils, parsing activities were finished 32% faster, and morphological analysis abilities were 42% better. It was clear that both changes were for the better. Ninety-five percent of the students who took MorphoScribe's interactive courses reported being satisfied with the platform, as indicated by their responses. The findings presented in this research demonstrate that MorphoScribe not only enhances morphological parsing but also improves the learning experience in digital philology courseware. This is demonstrated by the fact that MorphoScribe helps children learn more effectively.
State-Space Models (SSMs) have emerged as efficient alternatives to computationally intensive architectures like Transformers, particularly for sequence modeling. However, a fundamental challenge in their training is the reliance on static loss functions, which may not be optimal across all learning stages. To address this issue, in this paper a hybrid model integrating the Hyena architecture with a Dynamic Loss Network (DLN) is proposed which is guided by a Learn-to-Teach (L2T) approach (L2T-DLN). In this framework, the Hyena model is a student, and its loss function is optimized adaptively. A teacher model, leveraging a memory of the student's past performance, guides the DLN in dynamically balancing the primary cross-entropy loss and a regularization term. Experiments on the Penn Treebank (PTB) dataset show that our approach significantly improves language modeling performance. Our proposed model achieved a validation Perplexity of 102.6, a notable improvement over the 110.4 achieved by a baseline Hyena model using a static loss function. This research indicates that combining SSMs with adaptive loss function markedly enhances the quality and efficiency of deep learning models for sequential data, showing potential for applications in Natural Language Processing (NLP), time-series analysis, and biological signal processing.
Despite established theoretical distinctions between passive verb forms and their constructions in contemporary academic and official texts (early 21st century) and in the linguistic practices of Ukrainian philology students, sentences featuring predicative forms ending in ‑но or ‑то often compete with sentences using predicative participles ending in ‑ний or ‑тий to express a resultative state following a prior action. This phenomenon has not yet been systematically examined within the news genre of media discourse. The study is relevant primarily because the media shape speakers’ linguistic tastes and their perception of linguistic norms. For linguists, it serves as a reliable source for observing the dynamics of linguistic change. News texts in online media represent two main types of relationships between sentences with predicative passive participles and sentences with predicative forms ending in ‑но, ‑то: the first type is characterised by the correlative pair ‘predicative passive participle – predicative form ending in ‑но/‑то’, while the second type is characterised by the use of these verb forms without correlation. Syntactic constructions with predicative participles ending in ‑ний, ‑тий and forms ending in ‑но, ‑то are mostly in correlative relationships. There are over 160 cognate pairs of ‘predicative passive participle – predicative form ending in ‑но/‑то’, which confirms their use as syntactic synonyms and as a means of avoiding structural monotony. The authors’ choice of a particular syntactic construction is determined by the tradition of identifying the morphological nature and syntactic function of passive verb forms. At the same time, simple sentences with predicative forms ending in ‑но, ‑то quantitatively prevail over two-part sentences with predicative passive participles, which coincides with the communicative orientation of news media texts to report on the completion of an action regardless of its performer and demonstrates the current trend of active use of syntactic constructions that are indigenous in origin and therefore natural for the Ukrainian literary language The limited use of passive verb forms that lack a correlative pair is attributed to the functional specificity of these lexemes in online media, in general, and in news media texts, in particular. The sporadic use of three-part compound sentences with predicative passive participles and non-standard three-part simple sentences with predicative forms ending in ‑но, ‑то attests to the orientation of the authors of news media texts towards restoring one of the distinctive syntactic features of the Ukrainian literary language – two-part sentences with a subject syntactic unit in the nominative case of a noun, if the agent is known and needs to be named. We envision the prospect of the completed study in further research into the dynamics of the relationship between syntactic constructions with predicative passive participles and forms ending in ‑но, ‑то in other genres of media discourse. Keywords: two-part sentences with passive participles in ‑ний, ‑тий, simple sentences with predicative forms in ‑нo, ‑тo, meaning of the effective state, syntactic synonyms, correlative pairs, media discourse.
The translinguistic research paradigm contributes to the study of specific aspects of social interaction among multilingual language users. The multimodal and multisensory nature of language is manifested in language varieties including geographical, social, age or gender varieties. Human beings in the process of language contacts are very conscious of the relationship between race, nation and community on the one hand and language on the other, and the discrepancies between boundaries in linguistic structural terms and in socio-cultural and ideological terms. The object of the study is anglicisms used by the students of Don State Technical University in the media space from the point of view of highlighting their lexico-semantic characteristics and functioning. The aim of the research is to study the main trends in the use of anglicisms by students in social student networks. On the basis of the conducted online survey of 360 students of DSTU we tested hypotheses about the reasons and main trends in the use of anglicisms, the influence of students' specialization on their use in speech. The respondents' answers were divided into the following categories: 1) the most frequent anglicisms; 2) meanings of words; 3) spheres of application; 4) violation of the linguistic norm; 5) reasons for their usage; 6) prospects. We collected both quantitative and qualitative data, including surveys and observations. The results of the research indicate the tendency of frequent usage of direct borrowings and calques from English related to the sphere of “Internet” usage. Multilingual learners freely incorporate Anglicisms into their speech to overcome differences, discrepancies, inconsistencies and ambiguities in communication, manipulating them for strategic benefits when necessary. The use of anglicisms in the speech of the youth does not depend on their belonging to a professional community, with the exception of jargon and professional slang.
The article considers some features of the professional training of translators, namely the problem of developing cognitive flexibility. The insufficient study of this problem at the present stage determined the choice of the research topic. The objective of the article is to analyze the problem of cognitive flexibility of the translator and its formation in the process of training. Cognitive flexibility is the ability to quickly adapt one's thinking to new situations, change problemsolving strategies and switch between different concepts. Cognitive flexibility is important for intercultural communication, as it helps to effectively interact with representatives of different cultures. Therefore, cognitive flexibility is a key skill that ensures the efficiency, quality and accuracy of translation, helping to adapt to different working conditions and complex language situations. Translation is a complex cognitive process that requires instant analysis, interpretation and reproduction of the content in another language, taking into account the communicative context. The translator's activity is associated with the active work of mental processes, namely: attention, memory, analytical thinking, imagination, emotional regulation. The process of oral translation is especially intense, as it is necessary to maintain concentration, process large amounts of information and adapt in accordance with the cultural and linguistic norms of the target audience in conditions of limited time. The main approaches to the development of cognitive flexibility include educational, psychological, sociocultural, and neuropsychological approaches. Translation requires not only knowledge of languages, but also deep mental activity: understanding the context, subtext, emotional coloring, quick switching between languages, attentiveness, memory, imagination, analytical thinking. Psychological competence contributes to effective communication with clients.
Mood, an individual’s emotional state, fundamentally shapes how the brain interprets sensory input by providing a continuous affective context for prediction and evaluation. In language processing, mood may bias the interpretation of emotionally valenced words, amplifying or dampening their perceived affect. Yet, the temporal dynamics of these mood-valence interactions remain poorly understood. To clarify inconsistent evidence on the timing and nature of mood-valence interactions, we examined how induced mood influences early stages of emotional word processing using EEG. Participants performed a valence-rating task for positive, negative, and neutral words in a baseline condition and following positive or negative mood induction. Event-related potentials were analysed across early processing windows (N1, P2, EPN) using cluster-based permutation statistics. Positive mood selectively attenuated N1 amplitudes for highly valenced words, consistent with reduced prediction error under mood-congruent expectations. Later components (P2, EPN) showed decreased amplitudes for both high and neutral valence, suggesting reduced model updating under mood-congruent expectations. Negative mood, in contrast, produced weaker and temporally delayed modulations. Behaviourally, participants responded more quickly to valenced words under induced mood conditions, supporting the neural findings. Interpreted within a predictive coding framework, these results support the theoretical view that mood functions as a hyperprior, tuning the precision of predictive models during language comprehension. Positive mood appears to enhance predictive flexibility and facilitate the processing of affectively congruent words, whereas induced negative mood reduces positive affect. Taken together, the findings highlight how affective states dynamically modulate early predictive mechanisms in emotional language processing.
This article explores the critical engagement of two academics who confront lived experiences with the institutional and tangible dimensions of linguistic barriers and discrimination in the Portuguese district of Faro. Centred on the challenges posed at the border, the study fits into the wider framework of mobilities between North Africa and southern Europe, and attempts to demonstrate how language, as a form of social practice, impacts access to employment, education and society at large. Portuguese emerges as a dual entity: an institutional barrier, a form of socio-spatial control that reinforces exclusion, illustrating exclusionary processes within hierarchies and structural violence; a transnational bridge that fosters belonging and, simultaneously, a battleground where identity and self-determination face the constraints imposed by the economic, social, and political order that impact Moroccan migration to southern Portugal. The research highlights the imbrications of the undervaluation of migrants' cultural knowledge, the ambivalence of linguistic identity within a globalized world, exacerbating social exclusion, and systemic discrimination of non-privileged migrants in a polarized region shaped by social and economic asymmetries and increasingly representative nationalisms. From a systemic justice perspective, this devaluation reinforces structural inequalities, marginalizing those who do not conform to dominant linguistic norms. The national languages’ role as linguistic and cultural gatekeeper exemplifies the intersection of identity construction and socio-political hierarchies in the context of mobilities. This study, grounded in a collaborative project blending autobiography and biographical research, employs qualitative methods, including biographic interviews, ethnographic observation, and critical human rights studies.