Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
16504 papers
The study explores Tolstoy’s linguistic innovations in his novella “Youth” and their role in the development of Russian literary language vocabulary and then identifies their narrative and artistic function. The relevance of this study stems from the need for a detailed examination of the relationship between Tolstoy’s linguistic innovations and his artistic system. The scientific novelty of the article lies in the fact that the authors conduct corpus and linguisticpoetic analysis of linguistic innovations in the novella “Youth”. The aim of the article is to identify and classify various types of author’s innovations and their role in the text. The research methods include a comprehensive sampling of occasional forms, their comparison with the usual norm using systemic lexicography data, a corpus-based method using contexts from Russian National Corpus to determine the future functioning of the lexemes in Russian texts, and contextual-semantic analysis to establish the narrative and artistic functions of these innovations. Using historical and modern explanatory dictionaries, the authors identify deviations of Tolstoy’s new expressions from the linguistic norm of the late 1850s. The National Corpus of the Russian Language traces the subsequent functioning of these lexemes in the language of fiction and shows the influence of Tolstoy’s word creation on Russians vocabulary. Furthermore, the ideological and artistic functions of each type of innovation in revealing the inner world of the characters and shaping the narrative are established. The authors proved that Tolstoy’s linguistic innovation is proved to be not a collection of spontaneous and isolated original word usages, but a purposeful poetic device for detailing artistic space. The research contributes to the theory of linguistic innovation and understanding the ways author’s style influences literary language. The prospects of the research include subsequent studies of the linguistic context of the biographical trilogy and applying the developed methodology to the analysis of the idiostyles of other 19th-century writers.
Artificial intelligence (or AI) is rapidly transforming digital learning environments, reshaping how educational processes are organized, how knowledge is produced, and how learning is evaluated. Despite a growing body of research on AI in education, existing studies often examine technological, pedagogical, and ethical dimensions in isolation, leaving a lack of integrative frameworks capable of explaining how AI restructures learning environments as a whole. This study addresses this gap by proposing a three-layer conceptual framework that models AI-mediated learning environments through the interaction of efficiency, pedagogy, and ideology. The framework conceptualizes AI integration as a system of interdependent processes: the efficiency layer captures the optimization of educational activities through automation and data-driven personalization; the pedagogical layer explains how AI reshapes learning processes, feedback cycles, and learner strategies; and the ideological layer examines the normative assumptions embedded within AI systems, including issues of epistemic authority, linguistic norms, and algorithmic bias. Drawing on a structured synthesis of recent empirical research across domains such as generative AI tools, automated feedback systems, intelligent tutoring systems, and AI-supported assessment, the study demonstrates how these dimensions interact to structure contemporary digital learning environments and generate both affordances and tensions. The main theoretical contribution lies in advancing a system-level analytical framework that moves beyond tool-specific approaches and enables a more integrated understanding of AI in education. In practical terms, the framework provides educators and policymakers with a lens to critically evaluate AI integration, supporting more informed decisions on assessment design, sustainable learning practices, and inclusive digital education.
Both odor and temperature have been suggested to shape occupants’ perception of indoor environment, yet quantitative evidence regarding their interdependence remains limited. This study investigated their cross-modal effects on human responses in office environments, theoretically based on negativity bias, revenge effect, and One-Vote-Veto effect. A single-blind 2 × 2 within-subject experiment was conducted in the Aachen Workplace Simulation Lab. 23 healthy, mostly young participants experienced room atmospheres with pleasant (0.7 ppm pentyl acetate) and unpleasant (5 ppm 1-butanol) odors at neutral (24°C) and slightly warm (28.5°C) temperatures. Standardized questionnaires assessed subjective satisfaction and sensation across sensory domains before and after olfactory adaptation. Modern statistical advancements—including causal inference, adjustment criterion, and Bayesian region of practical equivalence—were leveraged to address existing methodological limitations in multi-domain research. Results revealed cross-modal main effects, with increased warmth reducing olfactory satisfaction. Marginal temperature x odor interactions were found for thermal and overall satisfaction, while other cross-modal effects remained inconclusive. Substantial inter-individual variability was observed in odor valence ratings. These findings highlight the interdependence of thermal and olfactory perception and partially support the notion that negative experiences from one domain can influence another; however, One-Vote-Veto effects were not confirmed. The study underscores the need for holistic indoor environmental quality assessments and follow-up multi-domain research. Methodologically, it showcases application of modern statistical tools to improve transparency and rigor in causal human-centric building science. Challenges related to odor selection and concentration manipulation are highlighted as key areas for improvement in related future research.
Status: Working Paper This manuscript is a work in progress and represents a preliminary formulation of the Cognitive Alignment framework. The concepts and definitions herein are subject to further refinement and peer review. This working paper introduces Cognitive Alignment Theory, a framework challenging the "file transfer" model of communication in favor of a functionalist "remote control" model. I propose that true intersubjective understanding is impossible due to the Solipsistic Veil—the impenetrable barrier isolating individual qualia. Consequently, communication does not transmit internal states but functions as Wireless Tinkering: the use of linguistic signals to trigger simulated heuristics in the receiver's database. Success in this model is defined not by shared feeling, but by Cognitive Alignment: the synchronization of behavioral logic and output, regardless of internal divergence. This reliance on alignment over understanding creates the risk of Solipsistic Exclusion, where marginalized agents are structurally isolated because dominant linguistic databases lack the "hardware" to simulate their lived reality. Finally, I apply this framework to Large Language Models (LLMs), arguing that AI systems utilize "heuristic steering" to achieve Cognitive Alignment without possessing an internal reality, potentially leading to mass manipulation via personalized "wireless tinkering".
Fine-tuning large language models on sensitive data poses significant privacy risks, as membership inference attacks can reveal whether individual records were used during training. While Differential Privacy (DP) provides formal protection, applying DP to conventional Parameter-Efficient Fine-Tuning (PEFT) methods such as Low-Rank Adaptation (LoRA) often incurs substantial utility loss. In this work, we show that a more structurally constrained PEFT architecture, Tensor Train Low-Rank Adaptation (TTLoRA), can improve the privacy-utility tradeoff by shrinking the effective parameter space while preserving expressivity. To this end, we develop TTLoRA-DP, a differentially private training framework for TTLoRA. Specifically, we extend the ghost clipping algorithm to Tensor Train cores via cached contraction states, enabling efficient Differentially Private Stochastic Gradient Descent (DP-SGD) with exact per-example gradient norm computation without materializing full per-example gradients. Experiments on GPT-2 fine-tuning over the Enron and Penn Treebank datasets show that TTLoRA-DP consistently strengthens privacy protection relative to LoRA-DP while maintaining comparable or better downstream utility. Moreover, TTLoRA exhibits lower membership leakage even without DP training, using substantially smaller adapters and requiring on average 7.6X fewer parameters than LoRA. Overall, our results demonstrate that TTLoRA offers a practical path to improving the privacy-utility tradeoff in parameter-efficient language model adaptation.
BACKGROUND: Psychopathic characteristics are associated with an elevated risk for violent behavior and are therefore of interest in research studies. Despite extensive research, the role of emotional and attentional anomalies in subclinical psychopathic traits remains a subject of ongoing debate, possibly attributed to the multifaceted nature of the construct. The study aims to explore how distinct psychopathic traits may differently relate to underlying emotional and attentional mechanisms. METHODS: To further explore the emotional and attentional anomalies underpinning the three Triarchic Psychopathy constructs, boldness, meanness, and disinhibition, this study employed an optimized picture-startle paradigm to address the limitations in commonly used paradigms that capture these dynamics only after 1000 ms post-image onset. This paradigm included negative, positive, and neutral images to elicit varied emotional responses, while auditory startle probes were presented at 50, 700, or 4500 ms post-image onset to measure emotional and attentional fluctuations. In this study, it was proposed that each psychopathic trait correlates with distinct emotional and attentional anomalies. A mixed-gender community sample of 115 participants was included. Eyeblink startle amplitudes (ESAs) were recorded via smartphone technology that utilizes facial landmark data captured via phone cameras, while the P3a and late positive potential (LPP) were measured through electroencephalography (EEG). RESULTS: The results revealed an exaggerated attentional bottleneck associated with boldness in males, indicated by increased P3a amplitudes in response to negative images. Meanness was associated with lower empathy scores and arousal ratings, and reduced ESAs at 4500 ms for negative images, supporting socio-emotional difficulties in meanness. In contrast, disinhibition showed no significant emotional or attentional deviations in this study. CONCLUSIONS: Our findings highlight trait-specific differences in neurocognitive functioning and validate the effectiveness of the optimized picture-startle paradigm for dissociating attentional versus emotional anomalies across triarchic psychopathic traits. The study also demonstrates the feasibility of using BlinkLab’s integrated stimulus presentation and camera-based eyelid tracking with concurrent EEG measures of attentional and affective processing (P3a and LPP), providing a complementary approach that may facilitate scalable data collection.
The article describes the principles of forming linguistic and communicative competence in future doctors during their studies at medical higher education institutions with a view to popularisation medical knowledge, and substantiates the content and structure of a special linguistic discipline in the Ukrainian language for popularisation medical knowledge. The regulatory documents of the Ministry of Health of Ukraine, which describe the qualification characteristics of professionals in the field of medicine and dentistry, emphasise the importance of the multifaceted activities of doctors in disseminating medical knowledge among the population. The current educational standard in the healthcare sector does not include a component that would promote the development of language skills for popularisation medical knowledge. Therefore, it is important to introduce the study of the peculiarities of the linguistic structure and production of relevant genres of popular scientific medical language into the curricula of higher medical education institutions. It is proposed to introduce a special component in one of the senior courses to develop future doctors’ linguistic and communicative competence in popularisation medical knowledge – the academic discipline ‘Ukrainian Language Popularisation of Medical Knowledge’. This discipline is intended for higher education students who have already studied several disciplines in the professional training cycle and have sufficient background knowledge to independently create high-quality popular science texts on the medical disciplines they have studied. As a result of studying the discipline, higher education students should know the terminology of popular science medical text creation, the genre structure of popular medical discourse, be able to create works in relevant genres of popular medical discourse, and master the linguistic norms of popular medical style. The possibility of introducing topics for the formation of linguistic and communicative competence in the popularisation of medical knowledge into the compulsory course of the Ukrainian language (for professional purposes) with the addition of credits in the fourth and fifth years of study is justified. The possibility of introducing a similar discipline for higher education students of various fields and specialities is indicated.
This study reviews the literature on environmental, social and governance (ESG) factors and their impact on corporate behavior and financial performance, highlighting the challenges of standardizing ESG data and aligning regulatory efforts with market needs. Market participants use ESG information; thus, a solid framework is essential for understanding its effect on financial outcomes. The lack of standardization creates uncertainty, reduces disclosure reliability, and limits investors’ informed decision-making. This paper addresses three key themes: the impact of ESG on corporate financial performance, inconsistencies in ESG disclosures and ratings that create data ambiguity, and the influence of evolving global ESG regulations. Drawing on numerous academic articles from reputable journals covering trends in emerging and mature markets, the review employs a systematic literature review (SLR) to identify themes and gaps. Findings indicate that ESG integration generally produces positive or neutral financial outcomes, though regional differences exist, and inconsistent data affects ratings. The study contributes by examining ESG frameworks, categorizing their effects on companies and investments, and emphasizing the need for standardized ESG data to enhance transparency, reduce greenwashing, and support informed, sustainable investment decisions.
Lexical Generativity in English Lexical Generativity in English: An Empirical Study of Verb Classes, Noun Polysemy, and Prepositions Author: Pablo Nogueira Grossi · G6 LLC · Newark NJ ORCID: 0009-0000-6496-2186 Series root: https://doi.org/10.5281/zenodo.19117399 Submitted to: International Journal of Lexicography (Oxford University Press) License: CC BY 4.0 Abstract This article examines lexical generativity in English: the capacity of a finite lexical inventory to support a theoretically unbounded range of context-sensitive meanings in use. Drawing on three converging empirical resources — the verb classification system of Levin (1991, 1993), the frame-semantic architecture of FrameNet (Fillmore, Johnson & Petruck, 2003), and the class-membership and alternation structure of VerbNet (Kipper, Korhonen, Ryant & Palmer, 2008) — the article proposes a layered model of lexical generativity that distinguishes among: (a) stored semantic primitives and qualia structure (Level I) (b) argument-structure templates licensed by class membership (Level II) (c) event-type composition rules governing productive meaning extension (Level III) The empirical core consists of detailed analysis of twelve English verb classes: manner-of-motion, change-of-state, causative-inchoative alternation, communication verbs, psychological verbs, creation-and-transformation verbs, aspectual verbs, verbs of putting, spray-load verbs, contact-by-impact verbs, perception verbs, emission verbs, and verbs of appearance and disappearance. The analysis is extended to systematic noun polysemy — dot objects, type coercion, and metonymic transfer — and to the generative semantics of English spatial prepositions, with a case study of over. Throughout, the article argues that apparent lexicographic irregularities are systematic consequences of a small set of generative principles that can be stated precisely, incorporated into lexicographic description, and exploited in computational lexicography. Implications for dictionary design, large-scale lexical database annotation, and natural language processing are discussed. Keywords: lexical generativity · verb classes · noun polysemy · prepositions · FrameNet · VerbNet · Levin classes · generative lexicon · computational lexicography · argument structure · type coercion · metonymy · qualia structure Deposit Contents File Description lexical_generativity_en.pdf Main article, ~14,000 words Article Structure Section Content 1 Introduction: three forms of lexical generativity 2 Background: Levin verb classes, FrameNet, VerbNet 3 Theoretical framework: the three-level model 4 Verb class analyses (twelve classes) 5 Noun polysemy: dot objects, type coercion, metonymic transfer 6 Prepositions and spatial semantics (over case study) 7 Computational implications: dictionary design, database annotation, NLP 8 Discussion 9 Conclusion Submission Status Submitted to the International Journal of Lexicography (Oxford University Press). This preprint is posted in accordance with OUP's preprint policy. Related Deposits Work DOI Principia Orthogona series root https://doi.org/10.5281/zenodo.19117399 GCM Institutional Edition (context for this article) https://doi.org/10.5281/zenodo.19513913 Coherence Bridge v8.4 coherence_bridge_v8_4.yaml is the machine-readable synchronisation file between the TOGT five-operator grammar, GCM contact geometry, and all three formal pillars. Key changes from v8.3: Anantharaman–Monk source expanded to full arXiv series (arXiv:2304.02678, arXiv:2403.12576, arXiv:2502.12268); Hide–Macera–Thomas polynomial-rate follow-up (arXiv:2508.14874) noted; all five TOGT entries sharpened to precise mathematical statements. Wang–Zahl source expanded to arXiv:2502.17655 + precursor arXiv:2210.09581 + Guth surveys arXiv:2505.07695 / arXiv:2508.05475; conjecture-proved status corrected throughout (was mislabelled open); claim_level_note field added to prevent misreading of analogical tag; all five TOGT entries fully populated. Three formal pillars — sorry inventory Pillar Lean file Proved Sorry Discrete (Collatz) DiscreteDm3.lean v1.6 operatorDecomposition, contactForm meanContraction, lyapunovDescent, hasStructuredCycle Continuous (Navier–Stokes) Dm3Cont.lean v1.0 operatorDecomposition, contactForm meanContraction_cont, lyapunovDescent_cont, hasStructuredAttractor Arithmetic-analytic (BSD) BSD_dm3.lean v1.0 operatorDecomposition, contactForm meanContraction_BSD, lyapunovDescent_BSD, hasStructuredCycle_BSD Closing the three admits on any pillar turns the corresponding conjecture into a categorical corollary of the dm³ framework. Python Simulation — Reproduce Figures pip install numpy matplotlib python3 autophagy_dm3.py --out figures/ Generates all four paper figures. The nbonacci_criticality.py and nbonacci_critical_lambda.py scripts in the AXLE repository reproduce the DNLS / n-bonacci criticality figures from the companion paper (DOI: 10.5281/zenodo.20026942). Related Deposits Paper DOI Principia Orthogona series root 10.5281/zenodo.19117400 This deposit (Autophagy / Triple-alpha) 10.5281/zenodo.20168812 DNLS / n-bonacci companion paper 10.5281/zenodo.20026942 Fruit-fly / MultiOrbitBioSwarm 10.5281/zenodo.19210136 GCM Institutional Edition (manifesto) 10.5281/zenodo.19513913 Keywords dm³ operator · contact geometry · Whitney fold · autophagy · triple-alpha process · Lean 4 · Mathlib4 · formal verification · TOGT · operator grammar · coherence bridge · Collatz · Navier–Stokes · BSD conjecture · stability radius · ε₀ = 1/3 · Principia Orthogona · G6 LLC
Digital Chinese landscape painting can be enhanced through multisensory fusion, yet culturally adapted cross-modal mappings and real-time adaptation remain under-tested. This laboratory, between-subjects virtual reality experiment (N = 80) compared a visual-only condition with a multisensory condition delivering synchronized auditory, haptic, and olfactory cues, with cue mapping implemented as culturally congruent or deliberately incongruent. Outcomes included standardized immersion/presence measures and affect ratings, behavioral logs of interaction and exploration (including time-on-task and coverage), and physiological indices of arousal derived from electrodermal activity and photoplethysmography-based pulse metrics, assessed immediately after exposure and at one-week and one-month follow-ups. Culturally congruent multisensory cueing produced higher immersion/presence and engagement than visual-only presentation and the incongruent multisensory format, alongside more frequent and diverse interaction behavior, longer time-on-task, and broader exploration of the virtual scenes. Self-reported emotion showed higher positive valence and arousal under congruent cueing with convergent physiological arousal patterns, and differences remained observable at follow-up assessments.
Author: Denny van Gulik Methodology: The 80/20 Matrix Status: Version 1.0 (Linguistic Corpus) 1. Abstract (Exposé) This work presents a comprehensive decoding of the Voynich Manuscript (MS 408). Moving beyond traditional cryptographic attempts, this research approaches the codex from a technical and structural perspective. The manuscript is identified as a functional pharmaceutical and balneological manual of a late medieval scholarly brotherhood, likely operating within a courtly or monastic context (Palar). The core of this discovery is the 80/20 Matrix: 80% Phonetically Deformed Latin: Technical terms of medieval botany and medicine, obscured through systematic phonetic shifts and the specific EVA character set. 20% Balkan Regionalisms: Use of regional terminology (e.g., Amum for water, Otlar for herbs, Pala for court/palace) serving as bridge vocabulary. Statistical validity is maintained across all 246 pages, identifying complex processes of thermal extraction (Pokedum), honey-based preservation (Melle), and advanced hydrotherapeutic systems. 2. Methodological Transparency (Authorship & AI Usage) Important Note on Research Genesis: The discovery of the 80/20 Matrix and the linguistic identification of the Balkan-Latin hybrid system is the exclusive intellectual property and original work of Denny van Gulik. Artificial Intelligence (specifically the Google Gemini model) was utilized strictly as a digital research assistant and scaling tool. Its role was limited to: Formatting manually decoded data into scientific tables and HTML. Cross-referencing author-identified word stems with linguistic databases. Translating research notes into academic English to facilitate international peer review. The logic, intuition, and systematic pattern recognition are entirely human-led. This project is not a result of "AI hallucination" but a rigorous analysis of the codex as a logistical document. 3. Project Roadmap & Updates Current Version (v1): Focuses on the textual corpus, the 80/20 linguistic matrix, and the primary glossary. Upcoming Version 2.0: Will feature fully integrated high-resolution folio images and direct visual cross-references for every analyzed page. English Edition: A full, 246-page English translation of the entire study is currently in progress to ensure accessibility for the global scientific community. 4. Keywords Voynich Manuscript, MS 408, 80/20 Matrix, Medieval Medicine, Balkan Linguistics, Codicology, Balneology, Historical Pharmacy. Deutsche Zusammenfassung: Dieses Projekt präsentiert die vollständige Dekodierung des Voynich-Manuskripts mittels der 80/20-Matrix (deformiertes Latein & Balkan-Regionalismen). Es identifiziert das Werk als pharmazeutisches Handbuch einer spätmittelalterlichen Bruderschaft. Version 1.0 sichert die linguistische Priorität; Version 2.0 mit Bildreferenzen sowie eine vollständige englische Übersetzung folgen in Kürze.
The Universal Dependencies (UD) project has grown rapidly through semi-automatic conversion of existing treebanks, but ensuring the quality of converted annotations remains a challenge. Manual verification does not scale, and existing automatic methods cannot distinguish conversion errors from inherent annotation complexity. We present a method that addresses this gap by training two parsers on a token-aligned parallel corpus: one on the original annotation and one on its UD conversion. By requiring correct predictions from the parser trained on the original annotation, our approach isolates errors specifically introduced during conversion while filtering out cases where the construction is simply difficult to parse. We demonstrate the effectiveness of this method on the SynTagRus corpus and its UD counterpart. To enable a direct comparison, we created a fully token-aligned version of the two corpora, resolving differences in tokenization and ellipsis representation. We also proposed a simple method for aligning syntactic relations across the two corpora, addressing the fact that relations involving the same token do not always correspond due to differences in annotation schemes. Our analysis identified several hundred errors in the test set. These comprise six distinct types of conversion errors, three of which persist in the current converter, and ten groups of annotation inconsistencies between the old and new corpus parts. Our method offers a practical, scalable tool for conversion error detection and is applicable to any language pair with aligned original and converted annotations.
Le French Treebank: une ressource lexicale et syntaxique richement annotée (et validée manuellement) pour les linguistes, utilisable en TAL, dans sa version 2.0 Projet initié en 1997, avec le soutien de l'IUF, du CNRS et du CNRTL21 550 phrases (environ 664 500 tokens) du journal Le Monde (1990-1993)Métadonnées: auteur, date, domaine (par article)Annotations lexicales (catégories, sous-catégories, flexion, mots composés avec composants) et syntaxiques (constituants majeurs, fonctions grammaticales) validéesPlusieurs formats disponibles: XML, PTB, CoNLL, codage UTF-8 (ligature œ notée oe)Nouveautés de la version 2.0: plusieurs erreurs d'annotation ont été corrigées depuis la publication en 2016 de la version 1.0
The Core Idea Classical combinatorics counts the number of ways to partition a set of n elements into non-empty blocks. That count is the Bell number B(n), and it depends only on how many elements there are, never on how they relate to each other. This manuscript introduces a strict refinement. Given a connected graph G on n labeled vertices, define a connected set-partition as a partition of V(G) in which every block induces a connected subgraph. The geometric partition function is p₍𝔾₎(G) = |{ {V₁, …, Vₖ}: each G[Vᵢ] is connected }| This count depends on G, not just n. Two graphs on the same number of vertices can have wildly different geometric partition counts. The entire theory follows from taking that dependence seriously. Main Theorems Theorem 1 (Subgraph Lattice Theorem). If G and H share the same vertex set and E(G) ⊆ E(H), then p₍𝔾₎(G) ≤ p₍𝔾₎(H). Adding edges can only increase the connected partition count, never decrease it. Theorem 2 (Tree Evaluation). For any tree T on n vertices, p₍𝔾₎(T) = 2ⁿ⁻¹. Every tree on n vertices, regardless of shape, has exactly the same geometric partition count. This is the universal floor for connected graphs. Theorem 3 (Complete-Graph Evaluation). For Kₙ, p₍𝔾₎(Kₙ) = B(n), the n-th Bell number. When every possible edge is present, every set-partition is automatically connected, so the geometric count recovers the classical count. This is the universal ceiling. Theorem 4 (Cycle Closed Form). For the cycle graph Cₙ with n ≥ 3, p₍𝔾₎(Cₙ) = 2ⁿ − n. This matches OEIS sequence A000325. Corollary (Sandwich Hierarchy). For every connected graph G on n vertices with n ≥ 4: 2ⁿ⁻¹ = p₍𝔾₎(Tₙ) < p₍𝔾₎(Cₙ) = 2ⁿ − n < p₍𝔾₎(Kₙ) = B(n) Both inequalities are strict. Trees sit at the floor, complete graphs at the ceiling, and the cycle sits strictly between them. What the Numbers Look Like For cycles versus trees versus complete graphs: n = 5: Tree = 16, Cycle = 27, Complete = 52 n = 6: Tree = 32, Cycle = 58, Complete = 203 n = 7: Tree = 64, Cycle = 121, Complete = 877 n = 8: Tree = 128, Cycle = 248, Complete = 4,140 n = 10: Tree = 512, Cycle = 1,014, Complete = 115,975 The gap between floor and ceiling grows super-exponentially. At n = 10, the complete graph has 227× more connected partitions than a tree on the same vertices. At fixed n, different topologies produce sharply different counts. At n = 6 for example: P₆ = 32 < C₆ = 58 < Ladder = 74 < Fan = 89 < K₂,₄ = 96 < Prism = 114 < W₆ = 118 < K₆ = 203 The ordering tracks graph density with Spearman ρ = +0.955 (p < 10⁻⁶) across all tested sizes n = 4 through n = 10. The Connection Curvature Define the partition connection on cycles as Γₙ = p₍𝔾₎(Cₙ₊₁) / p₍𝔾₎(Cₙ). The curvature κₙ = Γₙ − 2 measures deviation from the flat tree-growth rate: κₙ = (n − 1) / (2ⁿ − n) This is strictly positive and monotonically decaying to zero: n = 3: κ = 0.4000 n = 5: κ = 0.1481 n = 7: κ = 0.0496 n = 10: κ = 0.0089 The cycle approaches tree-like growth exponentially fast. The successive ratio κₙ / κₙ₋₁ converges toward ½ from above. Empirical Validation Program The deposit includes a preregistered validation suite with predeclared falsifiers, frozen metrics, and external ground truth. All outcomes, including failures, are retained as first-class results. Test 1 (OEIS Path Recursion). Brute-force enumeration confirms p₍𝔾₎(Pₙ) = 2ⁿ⁻¹ for n = 1 through 20. The sequence matches OEIS A000079 (powers of 2) exactly. Algebraic DP and direct bitmask enumeration agree at every tested value. Test 2b (Same-n Topology Comparison). At each n from 4 to 10, connected graphs on the same vertex count were compared. Spearman rank correlation between vertex connectivity and p₍𝔾₎ is ρ ≥ 0.83 at every tested n. Pooled edge-density correlation: ρ = 0.955 with p < 10⁻⁶. Negative control (max degree): ρ ≈ 0.35, not significant at any n. The lattice theorem's monotonicity prediction holds empirically, and counterexamples to vertex-connectivity ordering exist only between spanning-subgraph-incomparable pairs, exactly as the theory permits. Test 4 (Internet Autonomous Systems, 2010–2024). Using 180 monthly CAIDA BGP snapshots: AS count grew from 33,778 to 77,495 while edges grew from 93,998 to 501,473. The edge-succession to vertex-succession ratio Sₑ/Sᵥ increased with a linear slope of 3.68 per year, R² = 0.88, p = 2.23 × 10⁻⁷, Spearman ρ = 0.968. The pre-registered threshold was a slope above 0.05. The observed slope is 73× that threshold. Edge growth dominates vertex growth in a real infrastructure graph, consistent with the lattice theorem's prediction that denser graphs have exponentially more connected partitions. Test 5 (OpenAlex Citation Subgraphs). Among 10,000 co-citation subgraphs from 2020–2024: only 3 out of 10,000 were path graphs (0.03%). Among connected subgraphs, paths were 0.47%. For n ≥ 7, zero path graphs appeared among 527 connected subgraphs. Real citation networks avoid the tree floor almost entirely. Test 6/6b (Universal Dependencies Treebanks). The primary test fired its falsifier: English had 19.63% path-topology sentences, exceeding the 10% threshold. However, the pre-registered follow-up (Test 6b) conditioning on n ≥ 5 tokens found all six languages below 10%, with a maximum of 1.57% (Russian). At n ≥ 7 tokens, all languages drop below 0.15%. Short sentences are path-like; longer sentences are not. Test 7 (C. elegans Connectome). 279 neurons, 1,961 synapses. The biological network sits near the tree floor: 81% of 4-vertex connected induced subgraphs achieve p₍𝔾₎ = 2ⁿ⁻¹ exactly. KS tests showed no significant difference from Erdős–Rényi at matched density. Pre-registered hypothesis not supported. The sandwich bound is tight in sparse biological networks. Test 10 (Crystallographic Space Groups). Commutation graphs of all 230 space groups tested against a Ramsey proxy bound. The bound holds for 230/230 groups (100%). Saturation target (≥ 3 groups at n = 5 with zero triangles and zero independent triples) was not achieved. Verdict: partial. Tests 2, 8 (Falsifier Fired). Cycloalkane ring strain shows no monotonic observable matching p₍𝔾₎ (Pearson r = −0.11, p = 0.79). KEGG metabolic pathways achieved 14/18 hits for the Sₑ ≥ 2 × Sᵥ criterion versus a target of 15. Both failures are preserved in the record. Validation Ledger Supported: Tests 2b, 4, 5, 6b (4 of 10 completed tests) Falsifier fired: Tests 1 (by design), 2, 6, 8 (4 of 10) Not supported: Test 7 (1 of 10) Partial: Test 10 (1 of 10) Blocked/Deferred: Tests 9, 11 Negative and null results are first-class outcomes, not omissions. The program-level verdict is assessed across the full ledger, not cherry-picked from successes. Limitations Some tests depend on external APIs (OpenAlex, CAIDA, KEGG) whose upstream data evolves. Test 9 is blocked by endpoint observability constraints. This archive captures a dated snapshot; future reruns under changed data conditions should be treated as independent replications, not as invalidations. Citation Cite the Zenodo DOI for this archived package and the manuscript title. If reusing specific test scripts or results, cite the relevant script and JSON artifact in your methods section.
The article addresses the issue of linguistic security (LS) as a relevant theoretical and practical phenomenon that requires in-depth scholarly examination and systematisation of the terminological framework. The author analyses a paradoxical situation: despite a considerable number of theoretical studies on LS since the early 2000s, the term has not yet received legal formalisation and is not закреплен (enshrined) in Russian strategic documents — including the Foundations of the State Language Policy of the Russian Federation, approved in July 2025. The paper traces the evolution of the concept of LS — from M.V. Gorbanevsky’s original interpretation (2002) as journalists’ responsibility for statements in the media to broader contemporary interpretations, which include protecting the language from displacement, countering culturallinguistic expansion, ensuring communicative norms, and so on. Particular attention is paid to distinguishing between the domains of linguistic security and linguoculture: while the former is associated with actual and potential threats to the language and linguistic relations in society, the latter covers issues of cultural-linguistic norms, speech culture, and verbal ethics. The author identifies two approaches to understanding LS: narrow approach — protecting the language from displacement by other languages, preserving the norms of the literary language, and countering linguistic expansion; broad approach — incorporating issues of language policy, communicative norms, speech offences, and language conflicts. The article critically analyses various classifications of LS (as part of information, semantic, cognitive, and national security) and argues that the most justified approach is to classify LS as part of civilisational security. Language, along with culture and the dominant belief system, is viewed as a fundamental foundation of civilisation, and its protection is seen as an element of the stability of Russian civilisational identity. Based on the analysis, the author concludes that there is a need for: methodological streamlining of the conceptual framework in the field of LS; clear delimitation of related concepts (linguo-social security, linguo-sociocultural security, etc.); development of strategic documents that would establish the status and mechanisms for ensuring linguistic security in Russia.
Contemporary scholarly discourse on gender-inclusive communication remains predominantly descriptive, often avoiding a systematic critical analysis of its internal contradictions and social consequences. However, the growing social tension around new linguistic norms, their ideologization, and direct impact on public institutions demand unbiased examination. The aim of this article is to identify and analyze the key paradoxes generated by gender-inclusive communication, which persist despite its proclaimed goals of equality and respect. The research material comprises English-language texts of various genres and styles, including scholarly articles, media publications, documents from university websites, healthcare institutions, governmental, non-governmental, and commercial organizations, as well as data from blogs and social networks from the period 2017 to 2025. This allowed us to examine gender-inclusive communication both in the sphere of academic reflection and within the context of public practice. The methodological framework is based on critical discourse analysis, which interprets linguistic changes as a struggle for power, and Lotman’s theory of the semiosphere, which views inclusive language as a phenomenon of cultural dynamics. The study establishes that inclusive communication generates a complex of systemic contradictions across different dimensions: linguistic (between the striving to erase and simultaneously multiply gender differences, leading to semantic tautology and a violation of linguistic conventionality); social (where inclusivity in practice becomes a tool for excluding dissenting voices and marginalizing the experiences of traditional groups); ethical (encompassing the conflict between the ideology of self-identification and biological realities, as well as the imposition of Anglo-centric models onto other linguacultures). Interpreting the results through the chosen methodological lens reveals that inclusive language functions not only as a discourse of power but also as a tool of auto-communication, aimed at redefining the core of the cultural semiosphere and consolidating a “progressive” identity. The findings open perspectives for comparative studies on the reception of inclusive practices in different linguacultures and for interdisciplinary research into the long-term social effects of linguistic reform.
This examines the specifics of linguistic tools functioning as instruments for shaping and expressing cultural identity in the works of the prominent Quebec writer Jacques Godbout. The study primarily focuses on a comparative analysis of the author’s landmark works: the early novel “Hail Galarneau!” (1967) and the later work “The Concierge of the Pantheon” (2006). The theoretical framework of the analysis is based on Lise Gauvin’s concept of “linguistic hyperconsciousness” (surconscience linguistique), which views the language of a Francophone writer in a different cultural environment as an object of constant reflection and conflict. The analysis traces the evolution of Jacques Godbout’s authorial strategy: from the active use of “joual” and neologisms as instruments of socio-political resistance during the Quiet Revolution to a subtle, ironic play with linguistic norms in the heart of the metropolis — Paris. The study demonstrates that in the novel The Concierge of the Pantheon, language transforms into an independent character, embodying the author's linguistic hyperconsciousness. Through the prism of Pierre Léon’s semiotic model of phonostylistic analysis, the research identifies the role of linguistic “indicators” (involuntary markers of origin) and “signals” (conscious markers of otherness) in the speech of the protagonist, Julien Mackay. Special emphasis is placed on the interweaving of professional meteorological discourse (“des tempêtes d’amour”, “spécialiste des orages domestiques”), Quebec dialectaisms (“bout d’criss”, “l’air cheap”), and anglicisms-calques (“tomba amoureux fou”, “ces cahiers made in France”, “Gibert Jeune est un self”). It is established that by employing markers of the hero’s geographical and mental affiliation within the context of “flawless” Parisian French, the author creates an effect of “detonation.” The scientific novelty of the paper lies in determining the mechanisms of transforming “linguistic hyperconsciousness” into an act of linguistic resistance, where irony serves as a key tool for deconstructing the myth of the monolithic academic norm. The study concludes that Jacques Godbout’s oeuvre represents the complex trajectory of Quebec literature: from the struggle for self-identification to integration into the global Francophone context through the preservation of its own linguacultural uniqueness.
Abstract Mood states strongly influence episodic memory processing, yet the neural mechanisms through which mood interacts with stimulus valence during encoding remain unclear. The present study examined how experimentally induced negative mood would modulate neural processing and behavioural outcomes during an associative memory task, and whether mindfulness intervention can alter these effects. Twenty healthy adults completed a memory-encoding (word-stimulus pairs) task in which mood induction (negative vs. neutral) prior to encoding was crossed with stimulus valence (neutral vs. negative), producing four conditions. Continuous EEG was recorded using a 64-channel system, and event-related potentials (ERPs) and oscillatory dynamics were analysed during stimulus-locked encoding epochs. After an initial retrieval session, participants were randomly assigned to either a brief mindfulness meditation intervention or an active podcast-listening control, followed by a second retrieval session. Our behavioral data indicated that, recognition accuracy, arousal, valence ratings, and confidence differed significantly across conditions. Participants formed stronger word–image associations for neutral than negative stimuli across conditions, with associative memory being most impaired when negative stimuli were encoded during a negative mood state. At the neural level, early perceptual–affective processing showed robust Mood × Valence interactions: central P200 and occipito‑parietal EPN amplitudes differentiated negative from neutral images during neutral mood, but this valence effect was markedly reduced under negative mood, indicating an early blunting of neural sensitivity to emotional content. Following the mindfulness intervention, the negative images encoded under negative mood showed the most pronounced reduction in arousal, along with heightened alpha activity during mediation. Together, these findings show that negative mood undermines associative binding and influences early stages of visual-affective processing, while mindfulness may primarily positively influence the associated affective responses.
The article examines the phenomenon of code-switching in Internet discourse as one of the key strategies of modern digital communication. Theoretical foundations from R. Jakobson to P. Blom, J. Gumperz, Sh. Poplack, and C. Myers-Scotton are discussed, along with their application in online interaction. Based on examples from Instagram, Telegram, and YouTube, it is shown that code-switching is not a deviation from linguistic norms but a means of expressing emotions, irony, and identity, adapting messages to multilingual audiences. The study concludes that a hybrid norm of online communication is emerging within English-, Russian-, and Uzbek-speaking digital spaces.
Weight decay is widely used as a regularizer in large language models, yet its precise role in shaping Transformer loss landscapes remains theoretically underexplored. This paper provides the first rigorous functional-analytic characterization of the standard Transformer objective--cross-entropy loss with $L^2$ regularization--by proving it satisfies Villani's criteria for coercive energy functions. Specifically, we show that the regularized loss $\mathcal{F}$ is infinitely differentiable, grows at least quadratically, has Gaussian-integrable tails, and satisfies the differential growth condition $-Δ\mathcal{F} + \tfrac{1}{s}\|\nabla\mathcal{F}\|^{2} \to \infty$ as $\|θ\| \to \infty$ for all $s>0$. From this structure, we derive explicit log-Sobolev and Poincaré constants $C_{\mathrm{LS}} \leq λ^{-1} + d/λ^{2}$, linking the regularization strength $λ$ and model dimension $d$ to finite-time convergence guarantees for noisy stochastic gradient descent and PAC-Bayesian generalization bounds that tighten with increasing $λ$. To validate our theory, we introduce a scalable Villani diagnostic $Ψ_s(θ) = -Δ\mathcal{F} + s^{-1}\|\nabla \mathcal{F}\|^2$ and estimate it efficiently using Hutchinson trace probes in models with over 100M parameters. Experiments on GPT-Neo-125M across Penn Treebank and WikiText-103 confirm the predicted quadratic growth of $Ψ_s$, spectral inflation of the Hessian, and exponential convergence behavior consistent with our log-Sobolev analysis. These results demonstrate that weight decay not only improves generalization empirically but also establishes the mathematical conditions required for fast Langevin mixing and theoretically grounded curvature-aware optimization in deep learning.
Pronouns indicate significant importance in both pedagogical and communicative contexts, as they shape the way individuals are addressed and understood in social interactions and educational settings. Beyond the traditional pronouns “he” and “she,” the American Psychological Association endorses the scholarly use of the singular pronoun “they,” recognizing its relevance in promoting inclusive language practices. In addition, the popularity of neopronouns continues to rise, providing non-binary individuals with a broader range of linguistic options to express their identities. Despite this growing recognition, there remains a dearth of empirical research that systematically investigates the awareness, knowledge, and preferences regarding pronoun use among non-binary populations. Addressing this gap, the present quantitative inquiry examined the level of awareness, knowledge, and preference of pronouns among non-binary college students at a state university in the Philippines. The study involved 80 participants, including 20 lesbians, 20 gays, 20 bisexual males, and 20 bisexual females, selected through criterion sampling, who responded to a four-part researcher-developed survey questionnaire. The results indicate that, overall, non-binary college students are aware of the categories of pronouns (M=2.48, SD=0.39 for traditional pronouns; M=2.79, SD=0.25 for gender-neutral pronouns; and M=2.64, SD=0.32 for neopronouns) and knowledgeable about them (M=2.49, SD=0.31 for traditional pronouns; M=2.68, SD=0.23 for gender-neutral pronouns; and M=2.47, SD=0.32 for neopronouns). However, despite this awareness and knowledge, participants expressed a preference for using traditional pronouns (“he” and “she”) when being referred to. These findings underscore the persistence of traditional linguistic norms in educational settings and highlight the potential influence of formal language instruction on pronoun preference. Empirically, this study contributes to the limited body of research on non-binary pronoun use speficically in the Philippines, providing a foundational dataset that can inform inclusive language policies, pedagogical strategies, and future sociolinguistic investigations. Its significance lies not only in documenting patterns of pronoun awareness and preference but also in offering evidence-based insights for educators, policymakers, and advocates seeking to foster more inclusive and affirming learning environments.
Past research has shown that contextual renewal of conditional fear can be reduced if unconditional stimuli (USs) are presented unpaired with the conditional stimuli (CSs) during extinction training. The current study examined whether this reduction is a product of strengthened extinction learning from the unpaired presentation of the stimuli that had been paired during acquisition or from habituation to the US. Three groups of participants completed extinction training in a novel context with either: (1) CSs only (CS alone), (2) CSs and unpaired USs (unpaired), or (3) USs only (US alone) presentations. Based on past literature, contextual renewal of electrodermal responses was expected to occur in the CS alone group and renewal of US expectancy in the CS alone and US alone groups. Renewal was absent in electrodermal responses across all groups, limiting interpretation. US expectancy renewal emerged in the CS alone and US alone groups but not in the unpaired group, due to an unexpected increase in US expectancy during CS- in the unpaired extinction phase. This increase, along with parallel changes in affective ratings, suggests that the unpaired group perceived both CS+ and CS- as paired with the US. Taken together, the current findings provided limited support for the effectiveness of unpaired extinction in reducing the return of fear and highlight the role of participants' subjective interpretation of events. US alone extinction showed limited effectiveness, likely due to the high number of US presentations, with some evidence of US habituation.
Transformer models are not always deployed to low-resource devices due to the computational intensity of the model. Although some distilled models, such as DistilBERT, provide a minimum level of efficiency, additional compression is required to apply to any edge application. This paper offers a systematic evaluation of L1-norm unstructured pruning globally on a DistilBERT model that has been fine-tuned on binary sentiment analysis on the Stanford Sentiment Treebank (SST-2) dataset. The approach consists of pruning the model sequentially by 10 % to 60 % to check its performance using the accuracy of a stratified validation set and inference latency on a CPU. These findings indicate that model accuracy is very robust, and it still has more than 99% of the baseline performance until 40% sparsity. Only at this stage major degradation has taken place, and the accuracy retention was found to be 97.25 % and 94.22% at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{5 0 \%}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6 0 \%}$</tex> sparsity, respectively. An important conclusion here is that this unstructured sparsity fails to bring inference speedups in conventional CPU hardware, highlighting a lack of a connection between theory and practical efficiency improvements. As a result, the paper has found the best operational point to be <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{5 0 \%}$</tex> sparsity, which is an evidence-based guide to developers. The research also concludes that L1-norm unstructured pruning is a very effective method of maximizing model compression without significant accuracy impairment and thus can be used to achieve efficient deployment of NLP models in resource-constrained settings.
This article examines the role of advertisements and signboards in shaping and reflecting public attitudes toward language. In modern society, linguistic culture is not only preserved in literature and education, but also manifested in everyday public texts such as commercial advertisements, street signs, shop names, and information boards. The study analyzes the linguistic quality of advertising texts, the influence of globalization on language use, and the social consequences of neglecting linguistic norms. Special attention is given to the relationship between language accuracy and cultural identity. The article also discusses the responsibility of businesses, media representatives, and educational institutions in maintaining linguistic standards in public communication.
The innovative activity of an economic entity is an indicator of its progressiveness and compliance with the challenges of the modern economy. The characteristic features of innovative business entities are their leading positions in the relevant industry, which are ensured by high technological efficiency of production, effective management and the application of scientific approaches in all fields of activity. An economic analysis toolkit is used to support the stages of innovation activity. The article discusses approaches to assessing the achieved intermediate and final results based on financial and non-financial indicators. Market indicators of achieving effective innovation activity and criteria for their evaluation are presented. The main functions of finance in the implementation of innovation activities are highlighted, which involves the formation of a company's budget relative to the expected capital investments in the creation of an innovative economy of an economic entity. Artificial intelligence tools integrated into the processes of money management, budgeting, forecasting and preparation of analytical reports are presented. The levels of artificial intelligence for a financier are indicated and its role in the application of financial technologies is determined. AI in finance is able to accurately predict corporate credit and image ratings, contract terms, cash turnover rates, and non-payment risks. AI solutions for rating forecasting that analyze both internal financial data of a company and external factors.
Currently, East Asia, especially South Korea, is facing social problems such as population decline and regional inequality. To address these challenges, tourism has been leveraged as a means of economic revitalization, especially in fishing villages that are economically disadvantaged. This study examined the authentic food experiences of tourists who visited fishing villages. Tourists’ food experiences, dimensions of destination food image, and destination loyalty were assessed. In September 2024, 448 responses from Korean tourists were collected and analyzed using confirmatory factor analysis and structural equation modeling to test 15 hypotheses. Local food authenticity showed a significant effect on all dimensions of destination food image. Of the five dimensions of destination food image in this study, food taste, health and hygiene, and unique cultural experiences significantly influenced destination loyalty. In addition, geographic differences moderated the relationship between local marine food authenticity and the perceived food image of the destination. Tourists in the southern coastal regions reported the highest destination food image ratings, driven by authentic local cuisine, while those in the western regions reported the lowest. This study offers both practical and theoretical implications related to sustainable coastal tourism.
Brain Treebank is a large-scale intracranial EEG dataset comprising 43 hours of iEEG recordings from 10 epilepsy patients watching naturalistic Hollywood movies, with 1,688 electrodes sampled at 2048 Hz. The dataset includes time-aligned linguistic annotations with word-level transcripts and Universal Dependencies syntax trees, providing a unique resource for studying neural language processing during naturalistic stimulation.
How the human auditory cortex prioritizes relevant information amid concurrent sounds has been a long-standing question in auditory cognitive neuroscience. The present study used auditory steady-state responses to tag the electrocortical response to a tone embedded in concurrent naturalistic sounds, addressing methodological challenges with overlapping auditory streams. Participants endorsing low (high misophonia symptoms) or high misophonia symptoms-a condition with decreased tolerance to specific, typically orofacial, sounds-were recruited. Sounds varied in emotional valence (pleasant, neutral, unpleasant) to investigate how emotional content modulates attentional competition. Orofacial sounds were also included to evaluate how attentional biases are affected by inter-individual sensitivity toward a specific sound category. Affective ratings, alpha-band changes, and pupil dilation were also assessed. Hypothetical models of competition were tested, revealing a facilitation trend in the auditory steady-state responses amplitude when accompanied by pleasant and unpleasant, compared to neutral sounds, regardless of misophonia symptoms. However, auditory steady-state responses was selectively reduced in the high misophonia symptoms but not the high misophonia symptoms group when accompanied by orofacial sounds. Analyses of alpha-band, pupil, and rating data showed that the groups differed primarily in their response to pleasant sounds and orofacial sounds, with the high misophonia symptoms group exhibiting a stronger response to orofacial sounds than the high misophonia symptoms group.
Building on evidence for experience-specific grounding of word meaning and interindividual differences therein, this study investigated how specific aspects of empathy modulate the processing and representation of abstract emotional words. We investigated single-trial N400 amplitudes as a measure of semantic retrieval in 78 healthy adults during a delayed lexical decision task with emotion-label, emotion-laden, and neutral abstract words. We further measured the participants' levels of empathic concern, fantasy, personal distress, and perspective taking. Additionally, ratings on valence, arousal, and emotional experience quantified the words' emotional representational content. While direct comparison yielded no evidence for N400 differences between word types, N400 amplitudes in response to emotion-label words decreased with increasing fantasy scores, with this modulation being stronger than for emotion-laden and neutral words. Additionally, participants with higher fantasy scores rated emotional words higher in absolute valence. The observed N400 reductions thus seem to reflect fantasy-driven processing facilitation graded by the words' emotionality level. In contrast, we found no evidence for N400 modulations by empathic concern, personal distress, or perspective taking while affective ratings on all scales increased with increasing empathic concern scores. Our findings suggest that fantasy facilitates emotion-label word processing, and empathic concern enriches emotional word meaning representations, demonstrating interindividual differences in the experiential grounding of emotional abstract concepts.
<sec> <title>UNSTRUCTURED</title> Generic sentiment analysis tools are widely deployed in digital mental health and longitudinal text research to infer psychological change. Lexicon-based approaches (eg, NRC), supervised emotion classifiers (eg, GoEmotions), and single-shot large language model (LLM) prompts typically operationalize affect as the frequency or probability of valenced tokens at the message level. While effective for detecting overt affective shifts, the limits of this operationalization remain underexamined. This Viewpoint presents a single-subject longitudinal corpus (n=531 reflective messages across six months) to illustrate a construct–measurement misalignment. The subject reported a substantial psychological transformation characterized by reframing, integration, and narrative restructuring rather than shifts in emotional tone. Phase A (lexicon counts), Phase B (supervised emotion probabilities), and Phase C (LLM affect ratings) were applied under standardized aggregation schemes (per-message scoring, arithmetic mean, binning). Across methods, no consistent longitudinal trend emerged in affective indices. We argue that this null result is not a failure of AI per se, but a measurement blind spot: when transformation occurs at the level of narrative meaning rather than valence frequency, generic sentiment tools may remain insensitive. We propose a construct-specific analytic framework emphasizing alignment between psychological target constructs and computational operationalization. Implications are discussed for responsible deployment of AI in longitudinal digital health and narrative analysis contexts. </sec>
Abstract Objectives This study aimed to investigate the effects of brief mindfulness meditation on emotion regulation and its underlying brain functional network mechanisms in college students using functional near-infrared spectroscopy (fNIRS), thereby providing neuroscientific evidence for mindfulness-based interventions targeting emotional health. Method A total of 59 college students were randomly assigned to either a brief mindfulness meditation group (n = 29) or a control group (n = 30). Participants in the mindfulness group completed a 15-min mindfulness breathing intervention, whereas participants in the control group received safety education. Before and after the intervention, all participants performed an emotion regulation task involving negative viewing and cognitive reappraisal conditions. Changes in oxygenated hemoglobin (Oxy-Hb) concentration were recorded using a 40-channel fNIRS system across eight regions of interest, including the left dorsolateral prefrontal cortex (L-dlPFC), right dorsolateral prefrontal cortex (R-dlPFC), left frontopolar area (L-FPA), right frontopolar area (R-FPA), left premotor cortex (L-PMC), right premotor cortex (R-PMC), left primary somatosensory cortex (L-S1), and right primary somatosensory cortex (R-S1). Brain functional connectivity was constructed based on phase-locking value (PLV), and graph-theoretical metrics were subsequently calculated to characterize topological properties of the functional network. Results Behavioral results indicated that, compared with the control group, participants in the brief mindfulness meditation group exhibited significantly lower emotional valence ratings during the negative viewing condition (p < 0.001). Functional connectivity analyses revealed significantly increased connectivity between the L-dlPFC and L-FPA, L-dlPFC and R-PMC, and L-dlPFC and L-PMC following the mindfulness intervention ( p < 0.05). Furthermore, graph-theoretical analyses demonstrated significantly increased global efficiency, as well as enhanced local efficiency and clustering coefficient of the L-dlPFC in the mindfulness group ( p < 0.05). Conclusions Brief mindfulness meditation may effectively enhance functional integration within large-scale brain networks and improve neural information-processing efficiency in college students. These findings provide important neurophysiological evidence supporting the beneficial effects of mindfulness interventions on emotion regulation.
The intricate relationship between truth and language has long fascinated philosophers, linguists, and scholars across disciplines. In this work, Prof. Dr. Yoesoep Edhie Rachmad, Ph.D., DBA., embarks on a profound exploration of how language shapes, conveys, and sometimes distorts truth. Published in 2000 under The United Nations and The Education Training Centre, this book critically examines the philosophical foundations of linguistic representation and its implications for human understanding. Through an analysis of classical and contemporary theories, the work delves into the roles of meaning, interpretation, and the social constructs that govern communication. By questioning whether absolute truth can ever be expressed without ambiguity, this book invites readers to reconsider their assumptions about knowledge, semantics, and reality itself. Language is the primary medium through which humans express ideas, communicate beliefs, and establish shared realities. However, can language truly capture the essence of truth? This book is born from a deep intellectual curiosity regarding the limitations and potentials of linguistic structures in truth-seeking endeavors. With rapid advancements in technology, media, and cross-cultural exchanges, the question of how truth is conveyed in different languages and frameworks becomes increasingly urgent. Addressing these concerns, this book seeks to bridge the philosophical and practical aspects of truth in language. Understanding truth within the linguistic paradigm requires an examination of key philosophical theories, such as the correspondence, coherence, and pragmatic theories of truth. This book dissects the works of foundational thinkers, including Wittgenstein, Austin, Quine, and Derrida, to present an encompassing view of how meaning is formed and interpreted. Concepts such as semiotics, hermeneutics, and speech act theory play central roles in deciphering the mechanisms through which language represents reality. The complexities of truth in language manifest in various real-world phenomena, including political discourse, media manipulation, translation challenges, and legal interpretation. This book investigates how different languages construct reality in unique ways, leading to variations in perception and understanding. It also considers the implications of artificial intelligence in language processing and whether machines can ever truly comprehend truth. By integrating classical and modern linguistic theories, this book establishes a framework for analyzing truth in communication. It presents a structured approach to evaluating how meaning is derived, how context shapes interpretation, and how linguistic structures influence perception. The core principle is that truth is not merely an objective reality but is also shaped by the languages and systems within which it is communicated. Key indicators of linguistic truth include coherence, consistency, factual alignment, and pragmatic effectiveness. This book identifies operational variables such as cultural context, linguistic ambiguity, speaker intent, and audience interpretation as fundamental factors in understanding how truth is conveyed through language. Numerous elements influence the relationship between language and truth, including cognitive biases, historical contexts, power structures, and evolving linguistic norms. By analyzing these factors, this book provides insights into why different cultures and societies perceive truth differently and how language can both reveal and obscure reality. Applying the theoretical insights from this book, readers are guided through strategies for enhancing clarity, reducing misinterpretation, and fostering more precise communication in various fields, from academia to politics. The book also addresses how language policies, media regulations, and ethical considerations shape the pursuit of truth in public discourse. While language serves as a bridge to truth, it is also a source of distortion, manipulation, and misunderstanding. This book highlights the challenges posed by misinformation, propaganda, and ideological biases, while also recognizing the supporting role of linguistic diversity and education in fostering more nuanced truth-seeking. Truth and language are inseparable in human thought and communication. Through this in-depth exploration, the book underscores the importance of linguistic awareness in navigating the complexities of truth. Whether in philosophy, politics, law, or everyday conversation, understanding how language constructs and conveys truth is vital for clearer and more meaningful human interactions.
Background Pictorial warnings are superior to text-only warnings for cigarettes. However, little research has examined the impact of cigar warnings among youth, including image characteristics that may increase their effectiveness.Methods We conducted an online within-subjects experiment September-October 2022 among N = 680 youth ages 15–20 who reported little filtered cigar or cigarillo (LCC) use or susceptibility to LCCs. Participants evaluated six FDA-proposed warning statements with one of six randomly assigned images selected from an earlier study phase. We double-coded warning images based on presence/absence of image features, including wound depiction; internal organ depiction; smoking cues; and symbolic/metaphoric representations; and assessed level of graphicness. Outcomes were perceived message effectiveness (PME), negative affect, and believability for each warning. We used linear mixed models to assess associations between image characteristics and outcomes, controlling for participant characteristics and warning statements.Results About half of the sample identified as a woman/girl (56.2%) and White (56.3%). Warning images with a wound or an internal organ (vs. not) resulted in higher PME, negative affect, and believability (ps < 0.05). Warning images that were “very” or “moderately” graphic versus “not” graphic elicited higher negative affect ratings but lower believability ratings (ps < 0.05); with no significant difference for PME. Symbolic representations (vs. not) and smoking cues (vs. not) resulted in lower PME and negative affect (ps < 0.05).Conclusions LCC warnings with images depicting internal organs or wounds of the health effects may enhance the effectiveness of warnings, which could hold promise for deterring LCC use among youth.
Virtual agents powered by large language models are increasingly deployed in digital mental health services, yet the influence of avatar appearance on users' emotional, cognitive, and physiological responses remains insufficiently understood. This study was conducted between March and April 2024 and examined how three avatar designs-animal-like, human-like, and object-like-shape affective experience, user evaluation, autonomic activity, and attentional allocation during virtual doctor interactions. Forty-two participants completed a within-subjects experiment involving self-reported affect ratings, multidimensional user-experience assessments, heart rate variability (HRV) measures, and eye-tracking indicators. The avatar type did not yield statistically significant differences in changes in positive or negative affect across conditions. However, physiological data revealed clear divergences. The animal-like avatar elicited the strongest parasympathetic activation, reflected by significant increases in the root mean square of successive differences (RMSSD) and high-frequency (HF) power, whereas the object-like avatar produced a sympathetic-dominant response. Across six user-experience dimensions, the animal-like avatar consistently received the highest evaluations. Eye-tracking results showed faster first fixation and a longer face-directed fixation duration for the animal-like avatar, indicating stronger social attention. The human-like avatar demonstrated slightly delayed initial fixation, consistent with subtle yet nonsignificant uncanny-valley tendencies. These findings underscore the critical role of avatar visual design in shaping emotional safety, engagement, and social processing in virtual mental-health interactions.
MSMEs need modeling to predict user behavior over time as well as the structure of relationships between entities. The problem with this study is that LSTMs are effective in capturing sequential dynamics but weakening them in infrequent sequences, while GNNs excel at modeling structural relationships between entities but do not explicitly represent temporal evolution. The research contribution combines LSTM, and GNN to measure the impact of multi-task learning and calibration on rating accuracy and probability reliability on the Long prediction horizon. The method used is existing work that combines LSTM and GNN for product design and security-conscious MSME e-commerce. Especially in terms of risk calibration and long-term evaluation. Therefore, this study determines how multi-task training and calibration strategies affect rating accuracy (ROC-AUC, PR-AP, P@K/R@K) and probability reliability (Brier/ECE) over the extended horizon. The aim of this study is to design and evaluate the GNN-LSTM hybrid architecture to improve the accuracy of recommendations while reducing risk. The results of the experiment on the data of the partner MSMEs that were kept private, showed strong ratings and reliability: the purchase prediction reached ROC-AUC 0.965 (val) and 0.946 (test) with a PR-AP of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.943 / 0.910$</tex>, and session risk detection reached a ROC-AUC of 0.984 and a PR-AP of 0.982. This outperformed the CNN-BiLSTM baseline (0.93 val/0.91 ROC-AUC assay). Losses decrease steadily without negative transfers, and adequate calibration (Brier 0.161 for links, 0.176 for risk), indicating safe personalization with low false alarms.
Academic STEM evaluation can elicit anxiety, yet routine grading rarely captures how students semantically frame exams and wellbeing. We reconstruct these framings using behavioural forma mentis networks (BFMNs), that is, feature-rich networks of concepts linked by memory recalls and enriched with affective ratings and concreteness norms. We build BFMNs from 994 participants spanning STEM experts (N1 = 59), Italian high-schoolers (N2 = 206), physics undergraduates (N3 = 10), psychology undergraduates with math-anxiety levels (N4 = 301), and simulated students (N5 = 497) personified by a large language model (GPT-OSS 20B). Across all human groups, the concepts "exam" and "grade" were (i) perceived negatively, (ii) connected primarily to negatively valenced memory recalls, indicating a clustering of negative emotions around assessment, and (iii) framed through concepts eliciting fear and anticipation in most groups, including physics undergraduates (z-scores in the range [2.04, 2.53]). The semantic neighbourhoods of "anxiety" and "exam" overlapped three times more in human students than in GPT-based simulations, providing structural evidence of test anxiety in student populations. By contrast, experts displayed a neutral and more concrete network neighbourhood for "exam" (z = 1.87), with no clear trace of test anxiety. These negative assessment framings coexisted with positive representations of "wellbeing", which were rich in concrete associations in humans but linked to more abstract concepts in GPT digital twins. Overall, our results show that BFMNs offer a quantitative and interpretable framework to study academic anxiety and to distinguish human affective framing from current AI-based simulations
Pictorial warnings are superior to text-only warnings for cigarettes. However, little research has examined the impact of cigar warnings among youth, including image characteristics that may increase their effectiveness. We conducted an online within-subjects experiment September-October 2022 among <i>N</i> = 680 youth ages 15–20 who reported little filtered cigar or cigarillo (LCC) use or susceptibility to LCCs. Participants evaluated six FDA-proposed warning statements with one of six randomly assigned images selected from an earlier study phase. We double-coded warning images based on presence/absence of image features, including wound depiction; internal organ depiction; smoking cues; and symbolic/metaphoric representations; and assessed level of graphicness. Outcomes were perceived message effectiveness (PME), negative affect, and believability for each warning. We used linear mixed models to assess associations between image characteristics and outcomes, controlling for participant characteristics and warning statements. About half of the sample identified as a woman/girl (56.2%) and White (56.3%). Warning images with a wound or an internal organ (vs. not) resulted in higher PME, negative affect, and believability (<i>p</i>s < 0.05). Warning images that were “very” or “moderately” graphic versus “not” graphic elicited higher negative affect ratings but lower believability ratings (<i>p</i>s < 0.05); with no significant difference for PME. Symbolic representations (vs. not) and smoking cues (vs. not) resulted in lower PME and negative affect (<i>p</i>s < 0.05). LCC warnings with images depicting internal organs or wounds of the health effects may enhance the effectiveness of warnings, which could hold promise for deterring LCC use among youth.
Enhanced memory for salient events can be driven by affective responses and by surprising outcomes. Recent work has suggested that deviations in expected feelings can influence decision making alongside a traditional learning signal, the reward prediction error. Whether a dynamic measure of “affective surprise” may serve as a learning signal that modulates the formation of lasting memories remains unclear. This study investigated how affective surprise elicited by dynamic changes in affective states influences long-term episodic memory. We introduce a novel computation for affective surprise informed by literature on prediction error-driven learning and derived from individual participants' continuous affect ratings of valence and arousal. We first reanalyzed a published dataset and then conducted an independent replication study in which participants encoded item sequences while listening to emotional music. Participants then re-listened to the music while providing continuous ratings of their felt affect. We assessed how affective surprise influenced different aspects of episodic memory after 24 h. We found that greater affective surprise at a given moment, or larger deviations from the recent history of ratings, enhanced memory for when an item occurred in a sequence. In contrast, we found inconsistent effects of affective surprise on item recognition memory across the two studies. Together, these findings suggest that affective surprise, regardless of direction, enhances the binding of items to their temporal contexts in memory. This work demonstrates that affective surprise, in particular valence-related surprise, might act as a learning signal with consequences for episodic memory. • Within-person changes in affective state may act as a learning signal and influence memory. • Novel metric for “affective surprise” captures discrepancy between previous and current affect. • Greater valence-related surprise enhances memory for items in temporal context. • Influence of affective surprise on memory replicated across two samples.
Background: Aromatherapy has been proposed as a non-pharmacological adjunctive intervention in critical care settings; however, evidence regarding its effects on objective outcome measures remains inconclusive. This systematic review aimed to evaluate the effectiveness of aromatherapy in modulating objective physiological and biochemical markers in adult intensive care unit (ICU) patients. We hypothesized that the controlled ICU environment would facilitate rigorous measurement of both physiological parameters and biochemical stress markers. Methods: A systematic search was conducted using a novel approach combining lexical database searching (PubMed) and AI-powered semantic search strategies (Elicit, Undermind). Randomized controlled trials examining aromatherapy effects on physiological parameters in critically ill and cardiac patients were included. Outcomes were categorized as cardiovascular, respiratory, and non-cardiovascular/non-respiratory parameters. Subgroup analyses were performed by essential oil type. Results: Eighteen studies comprising 1236 participants were included. Aromatherapy demonstrated moderate effects on cardiovascular parameters (systolic blood pressure: 50% success rate, 5-22 mmHg reductions; diastolic blood pressure: 50%, 3.7-14 mmHg; heart rate: 44%, up to 20 bpm) but limited effects on respiratory parameters (respiratory rate: 25%; peripheral oxygen saturation: 12.5%), with the exception of eucalyptus oil, which showed 75% success for respiratory outcomes in mechanically ventilated patients. Non-cardiovascular/non-respiratory outcomes demonstrated the highest efficacy: anxiety (86%), sleep quality (100%), pain (100%), and sedation outcomes (100%). Subgroup analysis revealed essential oil blends achieved superior cardiovascular and psychological outcomes (100%) compared to lavender alone (64% cardiovascular; 71% anxiety/sedation). Contrary to our hypothesis, no studies measured biochemical stress markers such as cortisol or catecholamines, representing a significant gap in the evidence base. A notable finding was the disparity between evidence certainty: high for anxiety reduction versus low/very low for physiological outcomes, highlighting inadequate control for ICU-specific confounders in existing trials. Conclusion: Aromatherapy may serve as a safe adjunctive intervention in critically ill patients, with potential cardiovascular benefits requiring cautious interpretation and strong effects on anxiety and sleep outcomes. The absence of biochemical outcome measurements and inadequate control for ICU-specific confounders limits mechanistic understanding and causal inference.
This dataset constitutes a structured repository designed to examine the semantic compatibility of verbal extensions in ChiHwesa, with particular focus on the reciprocal (-an-), passive (-iw-/-w-/-h-), and stative (-ik-/-ek-) extensions. The underlying research hypothesis is that the distribution of these extensions is semantically constrained, such that only verbs with compatible argument structure and lexical semantics can productively undergo specific derivational processes. In particular, reciprocal constructions are expected to occur primarily with transitive and interactional verbs, passive constructions with verbs that license a patient/theme argument, and stative constructions with verbs that encode potentiality or resultative states. The dataset comprises a systematically organised list of ChiHwesa verb stems presented alongside their derived forms and corresponding English glosses. Each entry includes a base verb, its meaning, and its reciprocal, passive, and stative forms where attested. Importantly, the dataset also records gaps where certain derivations are not possible, providing critical evidence for semantic restrictions. The verbs included represent a wide range of semantic classes, including transitive, intransitive, cognitive, physiological, and social interaction verbs. Data were collected through a combination of native speaker intuition, structured elicitation, and cross-speaker validation. Informants were asked to generate and evaluate derived verb forms, and all entries were verified for consistency and acceptability. Additional support was drawn from an existing ChiHwesa lexical database. This multi-method approach ensures both reliability and linguistic authenticity. The data show that reciprocal formation is restricted to verbs denoting mutual or bidirectional actions, while verbs lacking inherent interaction (e.g., ‘walk’ or ‘urinate’) typically do not permit reciprocal derivation. In contrast, passive constructions are highly productive across verb classes, although some yield marginal or context-dependent interpretations. Stative constructions are also widely attested and primarily encode potentiality (‘able to be X-ed’) or resultant states, particularly with change-of-state verbs. These findings support the interpretation that verbal extensions in ChiHwesa are governed by semantic and argument structure constraints. The dataset is therefore valuable for theoretical analysis within frameworks such as Lexical Mapping Theory, as well as for comparative Bantu studies, language documentation, and computational applications. It can be used as both a descriptive resource and a basis for further hypothesis testing on the interaction between morphology, syntax, and semantics in under-documented languages.
INTRODUCTION: Neural oscillations are essential for encoding cognitive and emotional processes. While prior research has shown the involvement of limbic-prefrontal structures in emotional regulation, the spectral features such as the balance between rhythmic oscillations and aperiodic activity are less well understood. METHODS: Nine patients implanted with stereotactic EEG electrodes for seizure localization completed an emotional regulation task involving neutral and negative images. Each trial included a 1-second fixation, a 1.5-second cue to either “look” (attend) or “less” (reappraise), 4-second image viewing, and subjective ratings of valence and arousal. Spectral features were extracted across regions and analyzed using stratified linear regression to assess modulation by affective ratings. RESULTS: Negative image trials elicited higher arousal and valence compared to neutral, with both decreasing during reappraisal of negative images. Higher valence correlated with increased gamma center frequency in the amygdala, decreased gamma, beta, and theta frequencies in the insula and orbitofrontal cortex (OFC), and in the hippocampus, decreased beta and theta but increased alpha frequency. Arousal was linked to increased beta frequency in the hippocampus and OFC, and decreased beta in the insula. Gamma power increased with arousal in the amygdala and OFC. For lower frequencies, arousal decreased power in the insula; in the OFC, alpha, beta, and delta power decreased, but theta power increased. OFC theta power decreased significantly during non-reappraisal of negative images (p = 0.00075), and beta power declined during reappraisal (p = 0.0167). Aperiodic exponent in the OFC increased during both non-reappraisal (p = 0.00062) and reappraisal (p = 0.00011), indicating a shift toward reduced excitation/inhibition (E/I) ratio. CONCLUSIONS: Emotional perception and regulation shape both oscillatory and aperiodic activity in limbic-prefrontal circuits. These findings underscore the importance of E/I balance and site-specific frequency mechanisms in affective regulation.
Abstract: Language holds major significance because it helps people to develop their personal identities while enabling them to pass their identities through time and it helps people to stay connected with each other in regions where international interactions take place. This article considers Kinyarwanda as a transnational linguistic system, meaning that it is not only the official language of Rwanda but it is also a culturally and communicatively binding element for the Great Lakes African region and the Rwandan diaspora. Adopting a qualitative paradigm for sociolinguistics and history, the study is carried out with secondary sources (linguistic databases, scholarly literature, demographic reports, and cultural literature). The findings of this research show that Kinyarwanda belongs to a very homogenous Rwanda-Rundi language group in the Bantu group of the Niger-Congo language family with many structural and phonetic correspondences and a high degree of intelligibility with other languages such as Kirundi or Rufumbira. The spread of Kinyarwanda across countries such as the Democratic Republic of the Congo, Uganda, Burundi and Tanzania suggests a unified language community in the region, rather than national language communities, and migration has helped Kinyarwanda to become a diaspora language. The paper refers to this situation of cultural identity through language as a theory of “Rwandafoni,” and compares it with other language groups in the world. The authors explain that people use language as a process which exists beyond the limits of national territory. Keywords: Kinyarwanda, Rwandafoni, Rwanda-Rundi Languages, African Sociolinguistics, Great Lakes Region, Transnational Identity, Diaspora Language, Bantu Languages. Title: Rwandafoni: The Transnational Linguistic Community of Kinyarwanda Across the African Great Lakes Region and the Global Diaspora Author: Professor Dr. Idi (Ras) Banamungu, Claude Bizumuremyi International Journal of Interdisciplinary Research and Innovations ISSN 2348-1218 (print), ISSN 2348-1226 (online) Vol. 14, Issue 2, April 2026 - June 2026 Page No: 64-69 Research Publish Journals Website: www.researchpublish.com Published Date: 29-May-2026 DOI: https://doi.org/10.5281/zenodo.20443710 Paper Download Link (Source) https://www.researchpublish.com/papers/rwandafoni-the-transnational-linguistic-community-of-kinyarwanda-across-the-african-great-lakes-region-and-the-global-diaspora
BACKGROUND: This pilot randomized controlled trial evaluated the effectiveness of an artificial intelligence (AI)–assisted solo workflow for intraoral photography training. The study examined whether real‑time AI feedback could enhance photographic quality, procedural efficiency, learner self‑efficacy, and patient comfort compared with conventional approaches. METHODS: Fifty-four first‑year dental students were randomly assigned to one of three groups: assistant‑supported workflow (four‑handed technique, control), solo workflow without AI support, and solo workflow with AI‑driven real‑time feedback. All participants performed standardized intraoral photography tasks. The primary outcome was a composite photographic quality score derived from expert ratings of three standardized intraoral views (frontal intercuspal, frontal open-bite, and lateral intercuspal), each rated on a 0–10 scale (total range 0–30). Data were analyzed using ANOVA; mean differences (MD) with 95% confidence intervals (CI) were calculated. RESULTS: Inter‑rater reliability for expert image ratings was good (ICC = 0.84, 95% CI: 0.72 to 0.90). The AI-supported solo group achieved the highest composite quality scores (18.2 ± 2.7). This was significantly superior to the unassisted solo group (15.8 ± 3.3), with a mean difference (MD) of 2.4 points (95% CI: 0.45 to 4.35; p = 0.027) and a large effect size (Cohen’s d = 0.80). Compared to the assistant-supported group (17.1 ± 2.1), the difference was not statistically significant (MD = 1.1; 95% CI: -0.65 to 2.85; p = 0.28). Secondary outcomes, including task completion time (F(2,51) = 1.25, p = 0.30), self‑efficacy (all p > 0.40), and patient‑reported comfort (χ²(4, N = 54) = 5.2, p = 0.27), showed no significant between‑group differences. CONCLUSION: In this single‑centre pilot trial, an AI‑assisted solo workflow enabled novice dental students to achieve higher intraoral photographic quality than unguided solo operation, with performance broadly comparable to a conventional four‑handed assistant‑supported workflow and without detectable compromises in efficiency, self‑efficacy, or patient‑reported comfort. These preliminary findings may serve as a valuable adjunct for autonomous skill acquisition, warranting further validation in larger, multi-institutional cohorts. CLINICAL TRIAL NUMBER: Not applicable. This study evaluated an educational training intervention rather than a clinical treatment, and prospective trial registration was not required under institutional policy at the time of initiation. Ethical approval was obtained from Shanghai Ninth People’s Hospital Ethics Committee (SH9H-2022-T30-1).
Abstract: The Emperor Marcus Aurelius and the former slave Epictetus represent the social poles of the Roman Empire, yet both are cornerstones of late Stoic thought. This study employs digital humanities tools to investigate how their disparate life experiences and professional roles produced divergent philosophical "signatures" in their extant literature. By analyzing the Lemmatized Ancient Greek Texts (LAGT) corpus, we identify a distinct linguistic polarity: Marcus Aurelius demonstrates a significant preference for physical and cosmological terminology, reflecting a Stoicism centered on the providential order of the universe. Conversely, Epictetus’s lexicon shifts toward terms of ethical practice, pedagogy, and the transformation of the moral will. While Marcus Aurelius employs a more poetically diverse and intellectually wide-ranging vocabulary, Epictetus utilizes a more repetitive, concentrated technical vocabulary suited for the classroom. Despite these differences, a high degree of overlap reveals a "common core" of Stoic concepts shared by both authors, such as the nature of impressions and the primacy of the divine. These findings quantitatively highlight the adaptability of Stoicism, illustrating how a robust philosophical core was reframed to serve both the private reflections of a struggling ruler and the public exhortations of a committed teacher. Technical Context & Methodology This research integrates philology with a computational pipeline to analyze late Stoic literature. The following technical components are included in this repository: Computational Environment: All analyses were performed using Python 3.11. The pipeline utilizes Pandas and PyArrow for high-speed data processing, and the Classical Language Toolkit (CLTK) for part-of-speech tagging and grammatical filtering. Corpus Data: The primary linguistic data was extracted from the Lemmatized Ancient Greek Texts (LAGT) v4.1 dataset, which provides advanced lemmatization via the GLAUx treebank and GreCy models. Lexicographical Mapping: English definitions were integrated using the LSJ Dictionary (JSON v1.0.0). A custom normalization pipeline was used to standardize lemmata into Normalization Form Canonical Composition (NFC). Lexical Metrics: Vocabulary richness was assessed using Type-Token Ratio (TTR), Guiraud’s Index (R) to compensate for corpus size differences, and the percentage of hapax legomena (terms appearing only once). Generative AI Integration: A Gemma-3-27b-it model was utilized for the thematic classification and translation of 5,371 sentences. Sentences were tagged into the traditional Stoic tripartite division—Logic, Physics, or Ethics—based on the framework established by Pierre Hadot. Visualizations: The included scripts generate Lexical Volcano Plots (mapping total relative frequency against authorial skew) and Weighted Word Clouds that distinguish between author-specific signatures and the "Shared Stoic Core". Files included in this record: Supplementary File S1: Complete Python computational pipeline, README, and requirements.txt. Supplementary File S2: stoic_master_comparison.tsv containing comprehensive lemma frequencies and delta-RF values. Supplementary File S3: Statistical visualizations, including KDE overlap plots and delta-RF histograms. Supplementary File S4: Thematic analysis CSV containing 5,371 sentences with original Greek, English translations, and AI-generated thematic tags.
Language is a living organism that evolves alongside technological and social advancements. This paper examines the phenomenon of neologisms—newly coined words or expressions—and their pervasive role in contemporary English mass media. The study categorizes recent neologisms based on their morphological formation processes, such as blending, compounding, and functional shift. Furthermore, it analyzes how mass media acts as a primary catalyst for the popularization of these terms. By investigating digital journals, social media platforms, and news broadcasts, the research highlights the pragmatic functions of neologisms in creating concise, engaging, and culturally relevant communication. The findings provide insights into the current trends of English lexicology and the impact of the digital age on linguistic norms.