Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
To investigate the benefits of utilising an AI system to enhance the efficiency of obstetric scan training. A randomised controlled study was conducted at the First Affiliated Hospital of Sun Yat-sen University. Residents were recruited and randomly assigned to either a AI-assisted training group or a conventional training group from September 2022 to April 2023. Each participant underwent a four-cycle practice scan training program, performing scans on 20 pregnant volunteers at gestational weeks 18-32 in each cycle, focusing on acquiring and interpreting specific standard views. At the end of each cycle, a test evaluated trainees' ability to obtain standard views without AI assistance, and image quality was rated by both trainees themselves and an expert (in a blind manner) based on local expert consensus. The primary outcome measured the number of cycles required for each trainee to meet standards (expert ratings of image quality ≥80%). Secondary outcomes included expert rating of image quality, disparity between trainees and expert ratings. A total of 32 residents with no prior obstetric ultrasound experience and 2720 pregnant volunteers were recruited. The AI-assisted group required significantly fewer training cycles than the non-AI-assisted group to meet quality requirements (p = 0.037). When comparing mean score differences, the AI-assisted training group exhibited superior ability in acquiring standard views compared to the conventional training group in the third (p = 0.012) and fourth (p < 0.001) stages. The disparity between trainees' self-acquired image ratings and expert ratings decreased with increasing training time. There was a significant difference in total rating disparity between trainees and expert between the two groups from the first to the fourth stage (p < 0.05). The utilisation of an AI-assisted system has the potential to improve training effectiveness, particularly for trainees without prior experience in acquiring and interpreting standard views during obstetric scans.
Homophony (i.e, multiple meanings expressed by the same form) is ubiquitous across the world’s languages. Despite its pervasiveness, not all instances of homophony are equally likely, which suggests that homophony is unlikely to be accidental. There is a growing body of literature which aims to thoroughly examine cross-linguistic regularities in patterns of homophony and explain these from constraints in language learning and use, both at the lexical and morphosyntactic levels. Here, we examine a specific case of homophony in pronominal paradigms, that is, the lack of a number distinction (singular vs plural) for a given person value (first, second and third), a phenomenon coined as horizontal homophony. Cysouw (2003) suggested that a lack of number distinction is more likely to be found in third person (i.e., 3SG=3PL) than in second (i.e., 2SG=2PL), and it is least frequently found in first person (i.e., 1SG=1PL). We refer to this generalisation as the Horizontal Homophony Hierarchy: 3 &gt; 2 &gt; 1 (where &gt; represents frequency inequality). This generalisation was nevertheless only made via qualitative description and by raw counts, and merely described without motivated explanation. In this study we take a step back and present additional evidence sup- porting the Horizontal Homophony Hierarchy. First, we as- certain the robustness of this typological tendency through a statistical analysis using the largest cross-linguistic database of pronominal paradigms to date (926 languages from 229 different families). Next, we explore whether the Horizontal Homophony Hierarchy has a corresponding learning cor- relate, which would indicate that this asymmetry is at least partly rooted in a cognitive bias. Specifically, we examine asymmetries in how easily adult humans learn different types of horizontal homophony in an artificial language learning experiment. The results from our typological analysis corroborate a hierarchy of horizontal homophony 3 &gt; 2 &gt; 1 in the world’s languages. However, our experimental results provide evidence against a learning bias underlying the hierarchy, thus suggesting that motivated explanations of the typology (if any) are more likely to be found in alternative pressures such as communicative need and efficiency.
Relevance of research. In today’s world, where information spreads at an incredible speed, the role of opinion leaders, people who have a significant influence on the audience and can shape their thoughts and behavior, becomes especially important. Despite the increase in Ukrainian-language content in the Internet space after the start of a full-scale invasion, the problem of the spread of language errors and non-compliance with language norms in the Ukrainian language, in particular, in the blogosphere and social networks, is gaining relevance. Young people are particularly susceptible to the influence of opinion leaders. Violation of language norms by these people can lead to the fact that young people will consider these mistakes as the norm, which determines the relevance of our research. This article is aimed at solving the problem and provides practical recommendations for both opinion leaders and every Ukrainian to prevent violations of language norms in the media space. The purpose. Conducting an analysis of violations of language norms that occur in the Ukrainian-language media space under the influence of opinion leaders, in particular TikTok and YouTube bloggers. Research methodology. A number of scientific approaches and methods were used in the research process: content analysis – to study the influence of opinion leaders in the media space on the language culture of Ukrainian society through social media classification method – for systematization of identified violations of language norms, which helped to understand the main problems of language culture and identify the main directions for further analysis and development of recommendations; methods of comparative and logical analysis – to identify cause-and-effect relationships between language disorders and their impact on the speech environment. The scientific novelty. A study of the influence of opinion leaders in the modern media space. The article reveals both the side effects of such influence and emphasizes the possible lowering of the status of the language and the degradation of linguistic culture due to the spread of linguistic errors and non-compliance with linguistic norms. The article contains specific practical recommendations for opinion leaders and the general public to prevent violations of language norms in the media space, which can contribute to raising the level of speech culture and preserving the linguistic identity of Ukrainian society. The conclusions. Violation of the language norms of the Ukrainian language by opinion leaders in the media space, among bloggers on the TikTok and YouTube platforms, is a rather serious problem that has many negative consequences: it can lead to distortion of content, incorrect perception of information by the audience and a decrease in the general level of linguistic culture among users, especially among young people. The recommendations provided in the article are aimed at improving the quality of bloggers’ speech and increasing the level of language literacy in the media space. All these factors highlight the importance of drawing attention to the issue of language literacy and adherence to language norms among opinion leaders in the media space, which may become a relevant topic for further research. The obtained conclusions should become the basis for the development of specific recommendations aimed at increasing the level of language culture in the media space and avoiding the negative impact of social media on Ukrainian society.
Abstract Purpose Previous discussions have characterized hookup culture as ambiguous by nature, but social psychological theory tells us people dislike ambiguity in practice. Meanwhile, a myriad of undefined relationship terms (e.g., talking to, hanging out, having a thing) arose and have remained in use. I examine (1) whether these different “situationship” labels have distinct affective meaning and (2) what that suggests for those occupying the concomitant identities (i.e., assess the behavioral and emotional consequences of being “someone in a _____ relationship”). Approach Using affect control theory and a sample of young adults in defined (N = 50) and undefined (N = 43) relationship types, I test if affective ratings of various relationship label identities are statistically distinct. I then computationally model social events with each relationship label as actor (X identity performs [behavior]), compare their differing levels of social discomfort, and empirically predict the emotions each identity would feel. Findings Undefined relationship labels are not synonymous. Correspondingly, the nature, emotions, and expected behaviors of the individuals with those labels' related relational identities are not equivalent. In cultural evaluation, all undefined relationship labels are lower than all defined relationship labels. In event simulations, predicted deflection levels and actor consequent emotions (how normative is it and how jarring does it feel) were patterned by the labels' cultural evaluation ratings, these correlate with relationship commitment level. Implications By interpersonal necessity, individuals make fine distinctions in shared meanings within a cultural context of constant redefinition. Physically and emotionally negative behaviors are culturally more expected and accepted in undefined contexts by the culturally-understood nature of – and shared perspectives of participants concerning – those relationships’ parameters.
Introduction Sleep loss is common during the perinatal period; however, few studies have assessed potential consequences of insufficient sleep for postnatal emotional responding, a key contributor to parenting behaviors with implications for parent-infant bonding and mental health. To generate hypotheses for future work assessing perinatal sleep and emotion-related outcomes, this pilot study explored whether prenatal sleep duration predicted postnatal emotional responding in a sample at risk for postpartum depression. Methods Participants were 9 birthing parents with a prior mood disorder who were not in a current episode at enrollment. We estimated sleep with actigraphy collected for one week at 33 weeks’ gestation and at 2 and 6 weeks postpartum. Following each week, participants completed an emotional evaluation task, rating the valence and arousal of standardized images from the International Affective Picture System (IAPS). We tested whether average prenatal (33 weeks) nighttime sleep duration predicted concurrent and future responsiveness to emotional images, quantified by participants’ reaction times and arousal/valence ratings. Results Shorter prenatal sleep duration predicted faster reaction times, both concurrently and at 2 weeks postpartum (ps≤.05), as well as lower arousal ratings for negative images at 2 and 6 weeks postpartum (ps≤.043). Conclusions In this small sample of birthing parents at risk for postpartum depression, shorter prenatal sleep duration predicted faster reactions to emotional stimuli and blunted arousal responses to negative images. Although preliminary, these findings justify further study of the role of prenatal sleep in postpartum emotional responses and how these factors may impact parent-infant outcomes.
Introduction: Gestalt perception refers to the cognitive ability to perceive various elements as a unified whole. In our study, we delve deeper into the phenomenon of Gestalt recognition in visual cubist art, a transformative process culminating in what is often described as an Aha moment. This Aha moment signifies a sudden understanding of what is seen, merging seemingly disparate elements into a coherent meaningful picture. The onset of this Aha moment can vary, either appearing almost instantaneously, which is in line with theories of hedonic fluency, or manifesting after a period of time, supporting the concept of delayed but more in-depth meaningful insight. Methods: We employed pupillometry to measure cognitive and affective shifts during art interaction, analyzing both maximum pupil dilation and average dilation across the trial. The study consisted of two parts: in the first, 84 participants identified faces in cubist paintings under various conditions, with Aha moments and pupil dilation measured. In part 2, the same 84 participants assessed the artworks through ratings in a no-task free-viewing condition. Results: Results of part 1 indicate a distinctive pattern of pupil dilation, with maximum dilation occurring at both trial onset and end. Longer response times were observed for high-fluent, face-present stimuli, aligning with a delayed but accurate Aha-moment through recognition. Additionally, the time of maximum pupil dilation, rather than average dilation, exhibited significant associations, being later for high-fluent, face-present stimuli and correct detections. In part 2, average, not the time of maximum pupil dilation emerged as the significant factor. Face-stimuli and highly accessible art evoked stronger dilations, also reflecting high clearness and negative valence ratings. Discussion: The study underscores a complex relationship between the timing of recognition and the Aha moment, suggesting nuanced differences in emotional and cognitive responses during art viewing. Pupil dilation measures offer insight into these processes especially for moments of recognition, though their application in evaluating emotional responses through artwork ratings warrants further exploration.
Music surrounds us, and there is no denying that music in visual media can shape and evoke emotions. Yet, understanding how musical preference influences emotions through audio and visual stimuli remains an important task. To address this task, we investigated the role of musical preference effect on perceived emotions induced through music and visual stimuli (i.e., animation), using a 7-point scale for valence-arousal ratings and physiological responses in electroencephalogram (EEG) band power. The perceived emotions are categorized into four states: happiness, calmness, fear, and sadness. One emotional state contains 4 sessions: (1) Preferred Music, (2) Unfamiliar Music, (3) Preferred Music+Animation, and (4) Unfamiliar Music+ Animation. Behavior-wise, the rating results showed that the presence of preferred music resulted in higher perceived valence ratings, particularly in happiness. However, no stimulus had a significant effect on perceived arousal ratings and satisfaction ratings. Physiologically, the EEG indexes showed that the presence of preferred music appears to affect an increase in alpha power across various emotions except sadness, whereas unfamiliar music seems to affect beta power, particularly in happiness and calmness. Overall, these findings supported that musical preference is an affective factor reflecting the levels of valence and alpha power in EEG. Nevertheless, our findings did not confirm a significant difference between only preferred music and combining it with animation. Interestingly, we also found that participants were more likely to be attracted to and perceive positive (i.e., happiness and calmness) emotions easily through preferred music and/or visual stimuli than negative (i.e., fear) emotions.
We investigate the rate at which algorithms for pre-training language models have improved since the advent of deep learning. Using a dataset of over 200 language model evaluations on Wikitext and Penn Treebank spanning 2012-2023, we find that the compute required to reach a set performance threshold has halved approximately every 8 months, with a 95% confidence interval of around 5 to 14 months, substantially faster than hardware gains per Moore's Law. We estimate augmented scaling laws, which enable us to quantify algorithmic progress and determine the relative contributions of scaling models versus innovations in training algorithms. Despite the rapid pace of algorithmic progress and the development of new architectures such as the transformer, our analysis reveals that the increase in compute made an even larger contribution to overall performance improvements over this time period. Though limited by noisy benchmark data, our analysis quantifies the rapid progress in language modeling, shedding light on the relative contributions from compute and algorithms.
Outdoor programs involving recreational physical challenges are becoming increasingly popular for training and development purposes among adults, but rigorous studies investigating their effectiveness remain scarce. A randomized controlled trial was conducted to evaluate the effects of an outdoor adventure-based program on measures of self-efficacy, resilience, risk-taking propensity, and perceived stress. Participants were randomly assigned either to an intervention condition (half-day high ropes course) or a wait-list control group. Measures were taken at baseline and four days post-intervention and on the day to measure intervention perceptions. Significant increases in self-efficacy and risk-taking propensity were observed for the intervention arm compared to the control arm. Greater intervention engagement and affective valence ratings were associated with self-efficacy change. These findings highlight the practical relevance of adventure-based experiences for organizations and educational institutions seeking to enhance young adults' self-confidence. Additionally, they emphasize the importance of tailoring interventions to individual needs and ensuring positive participant experiences to achieve desired outcomes.
The article focuses on orographic appellatives and oronyms derived from anatomical terms in the Yakut language through metaphorization. Given that the Yakut oronymy is endangered due to several sociolinguistic and socio-economic reasons, collecting, systematizing, studying, and preserving this specific layer of the Yakut toponymic lexicon in linguistic databases is relevant. We have identified more than 80 anatomical terms that contributed to the Yakut oronymy development. We divided the Yakut anatomical vocabulary used as orographic appellatives into two groups: 1) lexemes denoting the external parts of human and animal bodies and 2) lexemes denoting the internal organs of humans and animals. The comparative analysis covered the following anatomical terms: atax ‘leg’, bas ‘head’, sürex ‘heart’, tumus ‘nose; beak’, kulgaax ‘ear’, töbö ‘head’, meyii ‘brain’, emiy ‘udder’. The comparison has demonstrated a substantial similarity in the anatomical vocabulary used as orographic appellatives in the Turkic languages. However, some Turkic languages feature divergence in terms of content, possibly resulting from the influence of contact languages (related and unrelated). The abundance and variety of metaphorical anatomical terms in different Turkic languages may also be due to the physical and geographical features of the terrain on which they function. Given the above, the anatomical vocabulary can be considered an additional source for understanding the formation patterns and features of the Turkic-Mongolian geographical vocabulary of Siberia.
Modern formal approaches to syntax propose different underlying structures for coordinate constructions. At the same time, none of them describe the entire set of properties of coordination, including variable predicate agreement in number (and gender). The goal of the paper is to define the internal organization of coordinate phrases. As the study of examples from the Russian treebank demonstrates, in addition to the previously known factors, the choice of agreement strategy is also influenced by the linear length of conjuncts and the distance between them and the verbal head. Additionally, the strategy of matching the nearest (and not necessarily the first) conjunct is relevant for Russian. We present and analyze the corpus data and conclude that there is no hierarchical organization in coordination. This lets us elaborate on some general ideas about syntactic derivation put forward by Noam Chomsky.
This study investigates the historical origins, linguistic diffusion, and socioeconomic impacts of cotton (Gossypium spp.) in the Indo-Pacific region. By reviewing secondary data from historical texts, linguistic databases, and archaeological reports, the research explores how Gossypium species, domesticated in both the Old and New Worlds, spread through complex trade networks and cultural exchanges. The study analyzes the dissemination patterns of cotton-related terminology across various language families and examines the socioeconomic effects of cotton cultivation and trade, including its influence on labor systems, economic structures, and cultural practices. While the findings highlight cotton’s significant role in shaping global markets and cultural inter-actions, the study’s limitations – such as its reliance on secondary sources, a two-month research duration, and a focus on a specific geographical area – warrant cautious interpretation. These constraints may limit the comprehensiveness and depth of the analysis, suggesting the need for future research to incorporate primary data collection, a broader geographical scope, and an extended study period. Despite these limitations, the study contributes to a nuanced understanding of cotton’s historical, economic, and cultural significance, emphasizing the need for sustainable agricultural practices in contemporary cotton production.
Kljub porastu jezikoslovnih raziskav govorjene slovenščine, ki si prizadevajo za popis številnih doslej prezrtih posebnosti govorjenega jezika v primerjavi s pisnim, metodologija tovrstnih razprav večinoma temelji na kvalitativni analizi razmeroma majhnih ter zvrstno ali demografsko omejenih vzorcev jezikovne rabe, kar omejuje ponovljivost raziskav in možnost posploševanja spoznanj na govorjeno slovenščino kot celoto. Kot eno izmed možnosti za premostitev tega problema v prispevku predstavljamo drevesnico govorjene slovenščine SST (angl. Spoken Slovenian Treebank), prostodostopni oblikoslovno in skladenjsko označeni reprezentativni vzorec referenčnega korpusa govorjene slovenščine Gos, in ponazarjamo njen metodološki potencial za nadaljnje korpusne raziskave govorjene slovenščine. Na primeru treh tipično govorjenih pojavov (samopopravljanja, diskurzni členki in dodani ujemalni pridevniški prilastki) prikažemo uporabo drevesnice SST za enostaven priklic številnih avtentičnih primerov rabe, na primeru analize pogostosti samopopravljanj glede na različne sporazumevalne okoliščine pa ponazorimo tudi njeno uporabnost za raznolike statistične analize jezikovne rabe. Poleg najpomembnejših prednosti drevesnice SST, kot so uravnoteženost, odprta dostopnost, ročna slovnična označenost in neposredna primerljivost z drugimi tovrstnimi korpusi po svetu, v sklepnem delu izpostavimo tudi nekaj omejitev, kot sta razmeroma majhna velikost ter robustna, v pisni jezik usmerjena označevalna shema.
The increasing volume of online reviews and tweets poses significant challenges for sentiment classification because of the difficulty in obtaining annotated training data. This paper aims to enhance sentiment classification of Twitter data by developing a robust model that improves classification accuracy and computational efficiency. The proposed method named Tree Hierarchical Deep Convolutional Neural Network optimized with Sheep Flock Optimization Algorithm for Sentiment Classification of Twitter Data (SCTD-THDCNN-SFOA) utilizes the Stanford Sentiment Treebank dataset. The process begins with pre-processing steps including Tokenization, Stop words Elimination, Filtering, Hashtag Removal, and Multiword Grouping. The Gray Level Co-occurrence Matrix Window Adaptive Algorithm is employed to extract features, such as emoticon counts, punctuation counts, gazetteer word existence, n-grams, and part of speech tags. These features are selected using Entropy-Kurtosis-based Feature Selection approach. Finally, the Tree Hierarchical Deep Convolutional Neural Network enhanced by the Sheep Flock Optimization Algorithm is used to categorize the Twitter data as positive, negative, and neutral sentiments. The proposed SCTD-THDCNN-SFOA method demonstrates superior performance, achieving higher accuracy and lesser computation time than the existing models, respectively. The SCTD-THDCNN-SFOA framework significantly improves the accuracy and efficiency of sentiment classification for Twitter data.
Abstract Translation shift which can be categorized as either “obligatory” or “optional” have been studied extensively in translation studies. When such shift occur at the macro-level, that is above the sentence level, a translation can then be said to have transitioned into what Stetting (1989, p. 374) described as “transediting”. Where transediting in journalism has received a considerable amount of attention in translation studies, examples of transedited literature are comparatively rare, and research on such transedited works is proportionate. This article analyzes the translation of the award-winning Uzbek novel The Eternal Wanderer as a notable example of a transedited work. Written by Isajon Sulton, a prolific Uzbek novelist, and translated by Christopher Fort, The Eternal Wanderer represents a notable example of a transedited work that is the product of a collaborative effort between author and translator. The novel is rich in its references to Islam as well as the native language, history, and culture of Uzbekistan, none of which are readily accessible for a Western audience that is not familiar with these things. As such, the translator, in his introduction to the book, notes that he worked with the author to edit as much as five to ten percent of the novel. The product of such a collaborative effort presents a unique opportunity for textual analysis in order to gain insights into literary transediting. A paratextual and qualitative content analysis was conducted to determine the types and levels of optional shift present in the translation in order to determine the extent of transediting and the motivations that underpinned each instance of transediting. The findings of the article indicate that at the word/phrase and sentence level, the translator opted to use shifts such as annotations, modifications, additions, and deletions to address disparate cultural and linguistic norms. At the paragraph and chapter level, large segments were deleted as part of the translator’s strategy to adapt the source material and produce a translation that is more accessible for its intended audience.
In the context of computational models of dependency syntax, most dependency treebanks have the restriction that any valid dependency tree must have exactly one edge coming out of the root node in addition to respecting the spanning tree constraints.Many algorithms for dependency tree sampling were recently proposed, both for sampling with and without replacement.In this paper we propose a new algorithm called Wilson Reject SWOR for the case of sampling without replacement by adapting the Wilson Reject algorithm originally created for sampling with replacement and combining it with a Trie data structure.Experimental results indicate the efficiency of our approach in the scenario of sampling without replacement from dependency graphs with random weights.
Abstract Semantic representation is the task of conveying the meaning of a natural language utterance by converting it to a logical form that can be processed and understood by machines. It is utilised by many applications in natural language processing (NLP), particularly in tasks relevant to natural language understanding (NLU). Due to the widespread use of semantic parsing in NLP, many semantic representation schemes with different forms have been proposed; Universal Conceptual Cognitive Annotation (UCCA) is one of them. UCCA is a cross-lingual semantic annotation framework that allows easy annotation without requiring substantial linguistic knowledge. UCCA-annotated datasets have been released so far for English, French, German, Russian, and Hebrew. In this paper, we present a UCCA-annotated Turkish dataset of 400 sentences that are obtained from the METU-Sabanci Turkish Treebank. We provide the UCCA annotation specifications defined for the Turkish language so that it can be extended further. We followed a semi-automatic annotation approach, where an external semantic parser is utilised for the initial annotation of the dataset, which is manually revised by two annotators. We used the same semantic parser model to evaluate the dataset with zero-shot and few-shot learning, demonstrating that even a small sample set from the target language in the training data has a notable impact on the performance of the parser (15.6% and 2.5% gain over zero-shot for labelled and unlabelled results, respectively).
Importance: Posttraumatic stress disorder (PTSD) is marked by the contrasting symptoms of hyperemotional reactivity and emotional numbing (ie, reduced emotional reactivity). Comprehending the mechanism that governs the transition between neutral and negative emotional states is crucial for developing targeted therapeutic strategies. Objectives: To explore whether individuals with PTSD experience a more pronounced shift between neutral and negative emotional states and how the intensity of emotional numbing symptoms impacts this shift. Design, Setting, and Participants: This cross-sectional study used hierarchical bayesian modeling to fit a 5-parameter logistic regression to analyze the valence ratings of images. The aim was to compare the curve's slope between groups and explore its association with the severity of emotional numbing symptoms. The study was conducted online, using 35 images with a valence range from highly negative to neutral. The rating of these images was used to assess the emotional responses of the participants. The study recruited trauma-exposed individuals (witnessed or experienced life-threatening incident, violent assault, or someone being killed) between January 17 and March 8, 2023. Participants completed the PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) (PCL-5). Exposure: On the basis of DSM-5 criteria (endorsing at least 1 symptom from clusters B and C and 2 from D and E), participants were categorized as having probable PTSD (pPTSD) or as trauma-exposed controls (TECs). Main Outcomes and Measures: The main outcome was the slope parameter (b) of the logistic curve fitted to the valence rating. The slope parameter indicates the rate at which emotional response intensity changes with stimulus valence, reflecting how quickly the transition occurs between neutral and negatively valenced states. The secondary outcome was the association between emotional numbing (PCL-5 items 12-14) and the slope parameter. Results: A total of 1440 trauma-exposed individuals were included. The pPTSD group (n = 445) was younger (mean [SD] age, 36.1 [10.9] years) compared with the TEC group (mean [SD] age, 41.5 [13.3] years; P <.001). Sex distribution (427 women in the TEC group vs 230 in the pPTSD group) did not significantly differ between groups (P =.67). The pPTSD group exhibited a steeper slope (mean slope difference, -0.255; 89% highest posterior density [HPD], -0.340 to -0.171) compared with the controls. Across all individuals (n = 1440), a robust association was found between the slope and emotional numbing severity (mean [SD] additive value, 0.100 [0.031]; 89% HPD, 0.051-0.15). Additional analysis controlling for age confirmed the association between emotional numbing and transition sharpness (mean [SD] additive value, 0.108 [0.032]; 89% HPD, 0.056-0.159), without evidence of an age-related association (mean [SD] additive value, 0.031 [0.033]; 89% HPD, -0.022 to 0.083). Conclusions and Relevance: These findings support that individuals with PTSD undergo rapid transitions between neutral and negative emotional states, a phenomenon intensified by the severity of emotional numbing symptoms. Therapeutic interventions aimed at moderating these swift emotional transitions could potentially alleviate PTSD symptoms.
Social mediator robots have shown potential in facilitating human interactions by improving communication, fostering relationships, providing support, and promoting inclusivity. However, for these robots to effectively shape human interactions, they must understand the intricacies of interpersonal dynamics. This necessitates models of human understanding that capture interpersonal states and the relational affect arising from interactions. Traditional affect recognition methods, primarily focus on individual affect, and may fall short in capturing interpersonal dynamics crucial for social mediation. To address this gap, we propose a multimodal, multi-perspective model of relational affect, utilizing a conversational dataset collected in uncontrolled settings. Our model extracts features from audiovisual data to capture affective behaviors indicative of relational affect. By considering the interpersonal perspectives of both interactants, our model predicts relational affect, enabling real-time understanding of evolving interpersonal dynamics. We discuss our model's utility for social mediation applications and compare it with existing approaches, highlighting its advantages for real-world applicability. Despite the complexity of human interactions and subjective nature of affect ratings, our model demonstrates early capabilities to enable proactive intervention in negative interactions, enhancing neutral exchanges, and respecting positive dialogues. We discuss implications for real-world deployment and highlight the limitations of current work. Our work represents a step towards developing computational models of relational affect tailored for real-world social mediation, offering insights into effective mediation strategies for social mediator robots.
The subjective experience of emotions is linked to the contextualized perception and appraisal of changes in bodily (e.g., heart) activity. Increased emotional arousal has been related to attenuated high-frequency heart rate variability (HF-HRV), lower EEG parieto-occipital alpha power, and higher heartbeat-evoked potential (HEP) amplitudes. We studied emotional arousal-related brain-heart interactions using immersive virtual reality (VR) for naturalistic yet controlled emotion induction. Twenty-nine healthy adults (13 women, age: 26 ± 3) completed a VR experience that included rollercoasters while EEG and ECG were recorded. Continuous emotional arousal ratings were collected during a video replay immediately after. We analyzed emotional arousal-related changes in HF-HRV as well as in BHIs using HEPs. Additionally, we used the oscillatory information in the ECG and the EEG to model the directional information flows between the brain and heart activity. We found that higher emotional arousal was associated with lower HEP amplitudes in a left fronto-central electrode cluster. While parasympathetic modulation of the heart (HF-HRV) and parieto-occipital EEG alpha power were reduced during higher emotional arousal, there was no evidence for the hypothesized emotional arousal-related changes in bidirectional information flow between them. Whole-brain exploratory analyses in additional EEG (delta, theta, alpha, beta and gamma) and HRV (low-frequency, LF, and HF) frequency bands revealed a temporo-occipital cluster, in which higher emotional arousal was linked to decreased brain-to-heart (i.e., gamma→HF-HRV) and increased heart-to-brain (i.e., LF-HRV → gamma) information flow. Our results confirm previous findings from less naturalistic experiments and suggest a link between emotional arousal and brain-heart interactions in temporo-occipital gamma power.
Abstract The exact nature of French liaison as a phonological or morphological alternation is still debated. Under the phonological analysis, liaison is allophony: liaison consonants are special phonemes that alternate between a consonant allophone and zero (e.g., [t] ∼ ∅), the zero allophone being derived from the consonant phoneme through deletion (/t/ → ∅). Under the morphological analysis, liaison is allomorphy: liaison words have two underlyingly listed allomorphs, a consonant-final allomorph and a shorter allomorph that lacks this consonant (e.g., grand ‘great’ /gʁɑ̃t, gʁɑ̃/). This paper uses evidence from lexical statistics to arbitrate between these two analyses. The form without liaison consonant (and with deletion, under the phonological analysis) has been found in previous research to become less likely with increasing lexical frequency. The paper shows that this is problematic for the phonological analysis of French liaison, as deletion typically applies more frequently in high-frequency words across languages. The paper further shows, using evidence from a large lexical database, that words involved in liaison alternations generally have lower type frequency but higher token frequency than non-liaison words when phonotactic and morphological effects on lexical frequency are controlled for. This result is in line with the predictions of the morphological analysis, as allomorphy typically involves a relatively small number of words that occur frequently. Due to its empirical nature, this argument constitutes to date one of the strongest arguments in favor of the morphological analysis.
Social power can activate behavior toward goal attainment. In the context of romantic and sexual relationships, social power may facilitate competitor derogation tactics and self-promotion tactics to attract a partner. We hypothesized that perceived invulnerability to harm would provide a pathway linking social power to competitor derogation, whereas self-perceived mate value would provide a pathway linking social power to self-promotion. Findings from 218 participants (Mage = 38 years) revealed that experimentally manipulated social power enhanced perceived invulnerability, which in turn was positively associated with competitor derogation. Social power did not affect ratings of self-perceived mate value. Women more strongly endorsed self-promotion in pursuit of a short-term (vs. long-term) relationship, whereas men’s ratings did not vary by relationship goal. Our findings suggested that social power may influence goal-directed thinking and behavior in the context of romantic and sexual relationships.
This paper introduces the Cosine-Gated Long Short-Term Memory (CGLSTM), a novel architecture that integrates a cosine similarity-based gate with the vailla LSTM framework to improve sequence prediction accuracy. It addresses long-term dependencies in sequence data. Through experiments across multiple datasets and tasks such as the adding problem, MNIST and Fashion-MNIST classification, IMDB sentiment analysis, and language modelling on the Penn Treebank, the CGLSTM's performance is evaluated against LSTM, Gated recurrent unit, Recurrent Attention Unit, and Transformer models. Additionally, its effectiveness is demonstrated in the SocNavGym environment, highlighting its potential for real-world applications. Results show the CGLSTM model's superior capability in complex sequences, providing evidence that the integration of cosine similarity into LSTM leads to a 17% improvement in predictive accuracy and efficiency, offering a promising solution for various deep learning applications.
Math anxiety poses significant challenges for university psychology students, impacting career choices and well-being. This study introduces a framework based on behavioral forma mentis networks (i.e., cognitive models mapping how individuals structure their associative knowledge and emotional perceptions of concepts) to explore individual and group-differences in the perception and association of concepts related to math and anxiety. We conducted 4 experiments involving psychology undergraduates from 2 samples (n1 = 72, n2 = 79) compared against GPT-simulated students (n3 = 300). Experiments 1, 2, and 3 employ individual-level network features to predict psychometric scores for math anxiety and its facets (observational, social and evaluational) from the Math Anxiety Scale. Experiment 4 focuses on group-level perceptions extracted from students’ and GPT-3.5’s networks. Results indicate that, in students, positive valence ratings and higher network degree for “anxiety” together with negative ratings for “math” can predict higher total and evaluational math anxiety. In contrast, human models do not work on GPT-based data because of differences in simulated networks and psychometric scores compared to humans. These results were reconciled also with differences found in the ways that high/low subgroups of simulated and real students framed semantically and emotionally STEM concepts. High math-anxiety students collectively framed “anxiety” in an emotionally polarizing way, absent in the negative perception of low math-anxiety students. “Science” was rated positively but contrasted against the negative perception of “math”. These findings underscore the importance of understanding concept perception and associations in managing students’ math anxiety.
The objective of this study is to analyze the strategies employed in translating English movie titles into Thai within the Monomax Application. A total of 501 English movie titles spanning the decade of 2011 and 2020 were examined because a decade provides clear guidelines for data collection, analysis, and interpretation. The strategies for translating film titles into Thai conducted by Thongwan (2012) served as a framework for this study. The findings revealed that all 10 translation strategies were employed as follows respectively: 1) naming a new name regardless of the old name, 2) naming a new name based on the original name, 3) partial translation and adding Thai language, 4) partial transliteration and adding Thai language, 5) all translation and adding Thai language, 6) all transliteration and adding Thai language, 7) all transliteration without adding Thai, and 8) all translation without adding Thai language. Meanwhile, the last two which are 9) partial transliteration without adding the Thai language and partial translation without adding the Thai language were found used only once per each. Notably, the translated movie titles in Thai often featured distinctive and attractive elements, such as rhyme and alliteration. These findings corresponded to Nida & Taber (1974) translation theory that translation process is related to purpose and cultural linguistic norms. Future studies could explore the reception and perception of these translated titles among Thai audiences, shedding light on which strategies resonate most effectively and why.
In this paper, we present a study of transformerbased Named Entity Recognition (NER) as applied to Ancient Greek texts, with an emphasis on retrieving personal names.Recent research shows that, while the task remains difficult, the use of transformer models results in significant improvements.We, therefore, compare the performance of four transformer models on the task of NER for the categories of people, locations and groups, and add an out-of-domain test set to the existing datasets.Results on this set highlight the shortcomings of the models when confronted with a random sample of sentences.To be able to more straightforwardly integrate domain and linguistic knowledge to improve performance, we narrow down our approach to the category of people.The task is simplified to a binary PERS/MISC classification on the token level, starting from capitalised words.Next, we test the use of domain and linguistic knowledge to improve the results.We find that including simple gazetteer information as a binary mask has a marginally positive effect on newly annotated data and that treebanks can be used to help identify multi-word individuals if they are scarcely or inconsistently annotated in the available training data.The qualitative error analysis identifies the potential for improvement in both manual annotation and the inclusion of domain and linguistic knowledge in the transformer models.
Starting Sign Language Research from Scratch Rachel I. Mayberry (bio) Perhaps the best way to illustrate the environment of sign language research when I began my graduate studies at McGill University is to note the physical labor involved. There were no internet or digital archives, and I spent a lot of time in the library searching for books and journals after first figuring out which floor and shelf the item's Dewey Decimal number pointed to. Journals could not be checked out, so notes had to be taken by hand, or exact change was required for xeroxing, if you could locate a machine. Statistical data analysis by computer was possible, but only by mainframe because desktops hadn't been invented yet. Videotaping of sign language was possible using huge reel-to-reel and then cassette recorders on large carts with heavy TVs and only somewhat less-bulky cameras and recording equipment. My first sign language experiment was for a course titled Language and Thought with Professor John Macnamara (1977). I compared concreteness ratings for English words with iconicity ratings for their ASL translations, which I gathered from sign-naïve undergraduate students. To create the experiment, I spliced reel-to-reel black-and-white videotape by hand with a razor blade and then used special tape to rearrange the segments for the experiment. I analyzed the data with paper, pencil, and a calculator. Manuscript preparation was tedious too, requiring typing everything out on paper, including tables, and making figures by hand with graph paper and either drawing them or using press-on symbols and letters. I have wondered how many [End Page 263] potential researchers might have gotten lost along this trail of work. But my father always said that I was stubborn, so I slogged through. More important than the labor, however, were the teachers and scholars who helped me along the way. Before attending McGill University, I had attended Washington University, where I came across the dictionary of signs with black-and-white photographs that Stokoe, Casterline, and Croneberg (1976/1965) had compiled using a coding system they had devised to represent sign structure. This was the only research I located in the library to help me explain sign language to the then-director of the Central Institute for the Deaf (CID), Richard Silverman (of Davis and Silverman 1978), who had asked me to teach him sign language once a week and made me promise not to tell a soul because sign language was forbidden. The institute included an oral school for deaf children, a speech and hearing clinic, graduate programs in deaf education, audiology, speech pathology, and research programs and faculty who primarily studied the sensory, perceptual, and motor mechanisms underlying speech and hearing. I have little memory of our meetings, except that he encouraged me to pursue sign language research by saying, "If we were to use sign language tomorrow, what should we expect from our students, from our teachers? You could study that." The idea was as intriguing as it was daunting. As a child, I hated questions about sign language and my parents' deafness from hearing adults, because I didn't know how to answer them. I worked as a dormitory assistant at CID while doing my master's degree. The experience reminded me daily of how imperative sign language was. Meals in the dining room were family style, and I was responsible for a table of eight students ranging in age from five to sixteen, all of whom were deaf and none of whom knew any sign language, and it was forbidden to sign to them. Some of the students could speak intelligibly and understood speech, but many others could not. There was a lot of gesturing and exaggerated oral gesticulation, and the students were good at helping one another understand what was being said among themselves and the staff. Saturday mornings, I was responsible for doing arts and crafts projects with the older students, some of whom spoke intelligibly and some who could not. Sunday afternoons, I was responsible for the "baby boys," the youngest [End Page 264] boys in the dorm, ages four to five. Another graduate student and I...
Recent advances in deep learning and Vision-Language Models (VLM) have enabled efficient transfer to downstream tasks even when limited labelled training data is available, as well as for text to be directly compared to image content. These properties of VLMs enable new opportunities for the annotation and analysis of images. We test the potential of VLMs for landscape scenicness prediction, i.e., the aesthetic quality of a landscape, using zero- and few-shot methods. We experiment with few-shot learning by fine-tuning a single linear layer on a pre-trained VLM representation. We find that a model fitted to just a few hundred samples performs favourably compared to a model trained on hundreds of thousands of examples in a fully supervised way. We also explore the zero-shot prediction potential of contrastive prompting using positive and negative landscape aesthetic concepts. Our results show that this method outperforms a linear probe with few-shot learning when using a small number of samples to tune the prompt configuration. We introduce Landscape Prompt Ensembling (LPE), which is an annotation method for acquiring landscape scenicness ratings through rated text descriptions without needing an image dataset during annotation. We demonstrate that LPE can provide landscape scenicness assessments that are concordant with a dataset of image ratings. The success of zero- and few-shot methods combined with their ability to use text-based annotations highlights the potential for VLMs to provide efficient landscape scenicness assessments with greater flexibility.
Accurate terminology translation is crucial for the global dissemination and comprehension of Traditional Chinese Medicine (TCM). This study addresses the pressing issue of inconsistent TCM terminology, which has led to significant confusion and misinterpretation among scholars and practitioners worldwide. The primary objective of this research is to evaluate the effectiveness of Hu Gengshen’s theoretical framework in ensuring precise and culturally appropriate translations of TCM diagnostic method terms. Hu Gengshen’s framework emphasizes three essential dimensions of translation: communicative, linguistic, and cultural. The communicative dimension focuses on aligning translations with the target audience’s linguistic norms, ensuring the translated terms are accessible and understandable. The linguistic dimension preserves the original structure and style of TCM terminology while adapting it to the target language, maintaining technical accuracy. The cultural dimension guarantees that translations respect and reflect the original cultural context, enhancing cultural sensitivity and relevance. This study employs Hu Gengshen’s framework to assess translations from authoritative TCM sources. The analysis reveals that 146 out of 152 evaluated terms meet the rigorous standards set by the framework across all three dimensions. This finding demonstrates the framework’s effectiveness in producing accurate and culturally sensitive translations. The implications of this research are significant. By validating Hu Gengshen’s framework, the study provides a practical tool for improving the clarity and precision of TCM terminology in international academic and clinical contexts. This enhancement facilitates better global engagement with TCM practices, bridging communication gaps and fostering a deeper understanding of TCM principles and methodologies. The study highlights the framework’s value in addressing translation challenges and advancing the global dissemination of TCM.
Over the past decades the term compliance has become increasingly widely used globally, making its way into national languages. The same is true for Russian academic discourse were compliance (or its Russian analogue “комплаенс”) has become common in a number of areas ranging from business and law to healthcare. This trend as well as cultural practices of revitalizing the social role of religion, which can also be viewed as a form of compliance, substantiate the relevance of this study. The word compliance with the meaning of agreement, accordance and self-restriction has been known in the English language since the 13th century. During the Reformation it notably referred to agreement with people of other beliefs. The purpose of this study is to trace the use of the term and describe its functioning today by analyzing forms corresponding to compliance, especially those with religious connotations. The following goals are set: 1) to describe the linguistic and etymological peculiarities of compliance in various cultural contexts and to specify the grounds for its understanding as a broader concept; 2) to trace the transformation of the concept from religious to secular and to compare personal and group identity markers; 3) to identify the specifics of the cultural practice of compliance as voluntary consent of group and personal religiosity on the example of creative writing; 4) based on texts by A. P. Chekhov to establish the features of the modern cultural optics of compliance in relation to the cultural phenomena of the past; 5) to highlight the key features of reading the works of A. P. Chekhov from the perspective of compliance. The research materials include data from dictionaries and encyclopedias, the linguistic database National Corpus of the Russian Language and selected works by A. P. Chekhov. The work, based on anthropological, axiological, and hermeneutic approaches, uses the methods of discourse analysis and narrative analysis, as well as the biographical method. The return to the broader meaning of the concept of compliance is associated with the peculiarities of the current cultural situation, requiring special attention to the coordination of both secular and religious aspects at group and personal levels. Firstly, in Russian this is fixed by referring to the English term compliance, which goes back to the Latin word complere. Secondly, the conceptual apparatus for describing and understanding religion has been historically developed as a series of forms representing normative aspects of the religious (confessional) identity of the elites of a particular historical period in a particular geographic region. Folk and authored interpretations have been relegated to the realm of marginal superstitions and heresies for thousands of years. Thirdly, the so-called Age of Magazines and Writers opened up new possibilities and ways of representing the deepest experiences of an individual author in literary work that connects the individual with the universal, the intimate with the public, and the instantaneous with the eternal, sometimes giving rise to works that receive worldwide recognition (A. P. Chekhov). However, reflection on this process has become possible relatively recently; Finally, by using the example of the works of A. P. Chekhov, to review compliance of literature and religion in a writer’s work, it has allowed us to highlight the specifics of his artistic realism, based on the techniques of mirror image, and inscribing the conventional magic of personal writing in the time of the religious understanding of culture. As a result, the conclusion is substantiated that the globally recognized work of A. P. Chekhov can be interpreted as an example of the presentation of religion as living religiosity, i.e. the universal social and personal phenomenon of constructing successful practices of supervising the unknown (N. Luhmann), forming historically special institutional and vernacular forms of their unique personal experience.
Pre-trained Language Models (PLM) have enabled a cost-effective approach to handling various downstream applications via Parameter-Efficient-Fine-Tuning (PEFT) techniques. In this context, service providers have introduced a popular fine-tuning-based product service known as Model-as-a-Service (MaaS). This service offers users access to extensive PLMs and training resources. With MaaS, users can fine-tune, deploy, and utilize their customized models seamlessly, leveraging a one-stop platform that allows them to work with their private datasets efficiently. However, this service paradigm has recently been exposed to the possibility of leaking user private data. To this end, we identify the data privacy leakage risks in MaaS-based PEFT and propose a Split-and-Privatize (SAP) framework, mitigating the privacy leakage by integrating split learning and differential privacy into MaaS PEFT. Furthermore, we propose Contributing-Token-Identification (CTI), a novel method to balance model utility degradation and privacy leakage. As a result, the proposed framework is comprehensively evaluated, demonstrating a 65% improvement in empirical privacy with only a 1% degradation in model performance on the Stanford Sentiment Treebank dataset, outperforming existing state-of-the-art baselines.
The subject of this study is the functioning of English-language borrowings (Anglicisms) in the Ecuadorian national version of the Spanish language based on examples of their use in the texts of local mass media. The object of the study is the texts of the Ecuadorian media, in particular news articles published on the websites of the most widely read newspapers in Ecuador. The paper examines such issues as the sociolinguistic influence of English on Ecuadorian Spanish, the frequency and nature of the use of Anglicisms in it, as well as their dissemination through the media. Special attention is paid to the analysis of specific examples of the use of Anglicisms in journalistic texts, which allows us to identify key trends in their functioning. In this study, Anglicisms are considered as one of the factors influencing the development of the Spanish language in Ecuador. The study uses methods of content analysis and qualitative analysis of examples of the use of Anglicisms in Ecuadorian journalistic texts, which revealed the frequency of their use and their role in the formation of modern linguistic norms. The relevance of the chosen topic is dictated by the fact of the increasing influence of Anglicisms on Ecuadorian Spanish. The Spanish language variant, which is widespread in the territory of the Republic of Ecuador, currently seems to be less studied in comparison with the neighboring Latin American variants. Thus, there is a need to conduct a study of the main trends in its development. It follows from this that the novelty of the work lies in the implementation of a comprehensive sociolinguistic analysis of English-language borrowings used in the Ecuadorian media, which contributes to the formation of a deeper understanding of the processes underlying the formation and functioning of the Ecuadorian national version of the Spanish language. The results of the study showed that Anglicisms are actively penetrating into various spheres of Ecuadorian society, acting as a social marker and reflecting the influence of Western culture on the local population.
Exposure-based therapy is effective in treating anxiety, but a return of fear in the form of relapse is common. Exposure is based on the extinction of Pavlovian fear conditioning. Both animal and human studies point to increased arousal during immediate compared to delayed extinction (>+24 h), which presumably impairs extinction learning and increases the subsequent return of fear. Impaired extinction learning under arousal might interfere with psychotherapeutic interventions. The aim of the present study was to investigate whether arousal before extinction differs between extinction groups and whether arousal before extinction predicts the return of fear in a later (retention) test. As a highlight, both the time between fear acquisition and extinction (immediate vs. delayed) and the time between extinction and test (early vs. late test) were systematically varied. We performed follow-up analyses on data from 103 young, healthy participants to test the above hypotheses. Subjective arousal ratings and physiological arousal measures of sympathetic and hypothalamic pituitary adrenal axis activation (tonic skin conductance and salivary cortisol) were collected. Increased pre-extinction arousal in the immediate extinction group was only confirmed for subjective arousal. In linear regression analyses, none of the arousal measures predicted a significant return of fear in the different experimental groups. Only when we aggregated across the two test groups, tonic skin conductance at the onset of extinction predicted the return of fear in skin conductance responses. The overall results provide little evidence that pre-extinction arousal affects subsequent extinction learning and memory. In terms of clinical relevance, there is no clear evidence that exposure could be improved by reducing subjective or physiological arousal.
further explains how these feelings work: as properties of individuals' perceptual experiences, these feelings influence perception. Notably, this hypothesis based on affective feelings with different valences has been substantiated, whereas the existing evidence is not compelling enough. Moreover, whether specific affective feelings can be experienced as properties of target perception remains unclear. Addressing these two issues deepens our understanding of the nature of emotional representation. Hence, we investigated the affective realism hypothesis based on affective feelings with different valences and specific emotions, comparing it with the affective misattribution hypothesis. In Experiment 1, we examined the effects of affective feelings with various valences on targets' perception through the AM (1a) and CFS paradigms (1b). In Experiment 2, we investigated the effects of affective feelings with anger, sadness, and disgust using similar methods. Results from Experiments 1a and 1b consistently indicated significant differences in valence ratings of neutral faces under emotional contexts with varying valences. Experiment 2a revealed significant differences in specific emotion ratings of neutral faces under different specific emotional contexts in the AM paradigm, whereas such differences were not observed in the CFS paradigm in Experiment 2b. We concluded that affective feelings with different valences, rather than specific emotions, can be experienced as inherent properties of target perception, validating the affective realism hypothesis. These findings supported the view that the nature of emotional representation should be described as affective dimensions.
Subjective feelings are thought to arise from conceptual and bodily states. We examine whether the valence of feelings may also be decoded directly from objective ecological statistics of the visual environment. We train a visual valence (VV) machine learning model of low-level image statistics on nearly 8000 emotionally charged photographs. The VV model predicts human valence ratings of images and transfers even more robustly to abstract paintings. In human observers, limiting conceptual analysis of images enhances VV contributions to valence experience, increasing correspondence with machine perception of valence. In the brain, VV resides in lower to mid-level visual regions, where neural activity submitted to deep generative networks synthesizes new images containing positive versus negative VV. There are distinct modes of valence experience, one derived indirectly from meaning, and the other embedded in ecological statistics, affording direct perception of subjective valence as an apparent objective property of the external world. The authors show that affective valence is tied to visual processing. They identify a direct route from visual features to valence experience, separate from higher-order conceptual processing, highlighting the role of visual perception in affect.
Introduction Strength training (ST) is a strategy to enhance quality of life through increased strength, muscle hypertrophy, and functional capacity. Training systems are associated with manipulation of volume and intensity, generating different stimuli, such as Rest-Pause (RP) and Sarcoplasmic Stimulating Training (SST). These systems induce greater mechanical and physiological stress, leading to increased strength and muscle hypertrophy. However, the metabolic and psycho-affective effects of advanced systems in experienced practitioners remain inconclusive. The purpose of the study is to analyze the acute effects of RP, SST, and Traditional (TMS) systems on metabolic and psycho-affective responses in adult men. Methods This experimental crossover study assessed 15 subjects (30.38 ± 2.06 years; 88.40 ± 6.50 kg; 1.74 ± 0.07 cm) experienced in ST, evaluated under TMS, RP, and SST during flat bench press and leg press 45° exercises. Body composition, muscular strength via 1-RM testing, lactate concentration (LAC), and psycho-affective measures (Rating of Perceived Exertion-RPE; Visual Analog Scale-VAS; Feeling Scale-FS) were determined. Statistical analysis was performed using the Minitab software, with p ≤ 0.05, IC-95%). Results The finals results showed SST exhibited a 38.10% lower LAC concentration post-training session compared to TMS, while RP showed 37.20% lower LAC concentration than TMS post-session. Average RPE values for RP and SST were higher (8.50 ± 1.10 and 8.60 ± 0.90, respectively) than TMS (6.00 ± 1.10). VAS displayed higher average values for RP and SST (8.00 ± 2.00 and 8.00 ± 1.00, respectively) compared to TMS (5.00 ± 1.00), with affective ratings indicating positive values for TMS and values between 0 and −5 for RP (40%) and SST (60%) post-training sessions, suggesting that RP and SST induced less affective response than TMS. Discussion The results lead to the conclusion that manipulation of training volume and intensity led to higher RPE and pain (VAS). The data suggest that inappropriate prescription of these systems could lead to greater displeasure, leading us to hypothesize that a higher likelihood of discontinuation from strength training programs would occur, suggesting that greater repetition volumes (RP and SST) should be targeted at individuals with a higher training level.
Single-pilot operations are already in place within military aircraft, small modes of commercial passenger transportation, and cargo operations. NASA, aircraft manufacturers, and airlines are collaborating on projects that birth safe and efficient single-pilot operation suitable technology for commercial airliners. A stipulated number of cabin crew is required per number of passengers on commercial airliners for safety, security, and medical purposes. The purpose of this pilot study was to determine what scales are valid to assess factors that affect a cabin crew’s willingness to operate on single pilot operations. With the selection of appropriate scales, such findings could aid industry regulators, government bodies, and airlines with training programs, educational conferences, and procedural development. The pilot study surveyed members of the cabin crew population using voluntary response sampling. The cabin crew was presented with a survey that collected demographic data, affect ratings, technology acceptance model perceptions, personality traits, and willingness to operate scores. The validity of the scales was tested using Cronbach’s Alpha in SPSS, and the usability of the survey instrument was assessed. The affect scale was shown not to be valid. In a follow-up study, the aim will be to use a survey containing the six remaining valid scales and collect demographic data to determine which predictors will be significant in a regression model.
The I-PACE model suggests that Internet-use disorders result from the interplay of individual vulnerabilities and cognitive and affective processes. As in substance use disorders, Pavlovian conditioning processes are attributed a key role. However, and despite progress in identifying individual vulnerabilities, factors influencing appetitive conditioning remain poorly understood. We therefore conducted a Pavlovian conditioning experiment in which individuals with risky as well as non-problematic use of either gaming or buying-shopping applications learned to associate different abstract stimuli with either gaming or buying-shopping. Regression analyses were used to identify individual characteristics influencing awareness of the experimental contingencies, speed of acquisition of awareness and the magnitude of the conditioned emotional responses regarding pleasantness and arousal ratings of the stimuli. Results demonstrated successful Pavlovian conditioning and an attentional bias towards reward-predicting cues. Awareness of the experimental contingencies was linked solely to cognitive abilities, while the speed of acquisition of awareness and the magnitude of conditioned responses was influenced by specific personality characteristics, experiences of compensation from using the application and severity of problematic use. Importantly, certain characteristics specifically predicted the magnitude of the conditioned response towards gaming, while others specifically predicted the response towards buying-shopping, highlighting differing vulnerabilities. These findings underscore the importance of targeted interventions and prevention strategies tailored to these specific vulnerability factors. Further implications and limitations are discussed.
This scientific article investigates the necessity of adhering to linguistic norms and existing editorial principles when editing literary translations from foreign languages, taking into account the shared aspects of translation and editorial criteria. The study focuses on the quality of editing the Uzbek translation of the novel The Alchemist, compared to its English and Russian versions. It examines issues such as preserving the semantic features of the text during the editing process and provides suggestions and recommendations for addressing shortcomings that arise in the editorial process.
Transformer models are the state-of-the-art in Natural Language Processing (NLP) and the core of the Large Language Models (LLMs). We propose a transformer-based model for transition-based dependency parsing of free word order languages. We have performed experiments on five treebanks from the Universal Dependencies (UD) dataset version 2.12. Our experiments show that a transformer model, trained with the dynamic word embeddings performs better than a multilayer perceptron trained on the state-of-the-art static word embeddings even if the dynamic word embeddings have a vocabulary size ten times smaller than the static word embeddings. The results show that the transformer trained on dynamic word embeddings achieves an unlabelled attachment score (UAS) of 84.17% for Urdu language which is ≈3.6% and ≈ 1.9% higher than the UAS scores of 80.56857% and 82.26859% achieved by the multilayer perceptron (MLP) using two static state-of-the-art word embeddings. The proposed approach is investigated for Arabic, Persian and Uyghur languages, in addition to Urdu, for UAS scores and the results suggest that the proposed solution outperform the MLP-based approaches.
The Kyrgyz language, as a low-resource language, requires significant effort to create high-quality syntactic corpora. This study proposes an approach to simplify the development process of a syntactic corpus for Kyrgyz. We present a tool for transferring syntactic annotations from Turkish to Kyrgyz based on a treebank translation method. The effectiveness of the proposed tool was evaluated using the TueCL treebank. The results demonstrate that this approach achieves higher syntactic annotation accuracy compared to a monolingual model trained on the Kyrgyz KTMU treebank. Additionally, the study introduces a method for assessing the complexity of manual annotation for the resulting syntactic trees, contributing to further optimization of the annotation process.
This study investigates the factors influencing consumers' intentions to purchase overseas travel packages via social media in Thailand, with a focus on consumer trust and perceived risks. A mixed-methods approach was employed, combining qualitative and quantitative research techniques. In the qualitative phase, the Fuzzy Set Delphi Method was applied to gather expert consensus from 19 participants. For the quantitative phase, a survey was conducted among 600 individuals who had experience purchasing overseas travel packages on social media in Thailand. First-order and second-order confirmatory factor analyses were used to examine the relationships between eight identified factors: social media influencer, e-WOM, trust, perceived risk, brand image, rating review, personal attitude, and destination image. The results indicate that trust and perceived risk are the most significant factors affecting purchase intention. Trust plays a crucial role in customers' decision-making processes, while perceived risk influences their tendency to avoid purchasing packages if the risk is perceived as high. The insights gained from this study contribute to the understanding of factors influencing purchase intentions for overseas travel packages through social media in Thailand, providing valuable information for travel agencies to develop effective marketing strategies.
Purpose The purpose of this study was to examine the global perceptions of social equity in the fine dining business model as a result of the surprise announcement for the 2024 planned closure of the Michelin three-star restaurant, Noma. Design/methodology/approach This study used critical discourse analysis to inductively analyze 91 source documents retrieved through a lexical database search. The analysis yielded five overarching themes and six subthemes. Findings Findings from this study serve as a benchmark in retrospect for capturing a rapidly accelerating global conversation from January to March 2023 around the long-term viability and social sustainability of the fine dining business model. Research limitations/implications Against the backdrop of labor challenges in the restaurant industry due to the Covid-19 pandemic and its aftermath, the announced closure of Noma precipitated criticism of the stage (unpaid intern) system and the intense pressures of attaining and maintaining Michelin star status. Practical implications Results from the discourse analysis suggest certification for fine dining restaurants, perhaps through the Michelin Guide, for demonstrating a commitment to social sustainability as a qualifier to achieve a Michelin star. Social implications Findings from this research reveal a palpable change in societal tolerance for a more socially sustainable fine dining restaurant business model that advances equitable solutions for its workers while assuring the economic sustainability of restaurants. Originality/value This study drew upon a foodscape lens to reveal a juxtaposition between well-executed environmentally sustainable initiatives in the fine dining business model and the threats to the social sustainability among its workers.
BACKGROUND The consistency of pancreatic apparent diffusion coefficient (ADC) values and intravoxel incoherent motion (IVIM) parameter values across different magnetic resonance imaging (MRI) devices significantly impacts the patient’s diagnosis and treatment. AIM To explore consistency in image quality, ADC values, and IVIM parameter values among different MRI devices in pancreatic examinations. METHODS This retrospective study was approved by the local ethics committee, and informed consent was obtained from all participants. In total, 22 healthy volunteers (10 males and 12 females) aged 24-61 years (mean, 28.9 ± 2.3 years) underwent pancreatic diffusion-weighted imaging using 3.0T MRI equipment from three vendors. Two independent observers subjectively scored image quality and measured the pancreas’s overall ADC values and signal-to-noise ratios (SNRs). Subsequently, regions of interest (ROIs) were delineated for the IVIM parameters (true diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction) using post-processing software. These ROIs were on the head, body, and tail of the pancrease. The subjective image ratings were assessed using the kappa consistency test. Intraclass correlation coefficients (ICCs) and mixed linear models were used to evaluate each device’s quantitative parameter values. Finally, a pairwise analysis of IVIM parameter values across each device was performed using Bland-Altman plots. RESULTS The Kappa value for the subjective ratings of the different observers was 0.776 (P < 0.05). The ICC values for inter-observer and intra-observer agreements for the quantitative parameters were 0.803 [95% confidence interval (CI): 0.684-0.880] and 0.883 (95%CI: 0.760-0.945), respectively (P < 0.05). The ICCs for the SNR between different devices was comparable (P > 0.05), and the ICCs for the ADC values from different devices were 0.870, 0.707, and 0.808, respectively (P < 0.05). Notably, only a few statistically significant inter-device agreements were observed for different IVIM parameters, and among those, the ICC values were generally low. The mixed linear model results indicated differences (P < 0.05) in the f -value for the pancreas head, D -value for the pancreas body, and D -value for the pancreas tail obtained using different MRI machines. The Bland-Altman plots showed significant variability at some data points. CONCLUSION ADC values are consistent among different devices, but the IVIM parameters’ repeatability is moderate. Therefore, the variability in the IVIM parameter values may be associated with using different MRI machines. Thus, caution should be exercised when using IVIM parameter values to assess the pancreas.
Dependency length minimization is a universally observed quantitative property of natural languages. However, the extent of dependency length minimization, and the cognitive mechanisms through which the language processor achieves this minimization remain unclear. This research offers mechanistic insights by postulating that moving a short preverbal constituent next to the main verb explains preverbal constituent ordering decisions better than global minimization of dependency length in SOV languages. This approach constitutes a least-effort strategy because it's just one operation but simultaneously reduces the length of all preverbal dependencies linked to the main verb. We corroborate this strategy using large-scale corpus evidence across all seven SOV languages that are prominently represented in the Universal Dependency Treebank. These findings align with the concept of bounded rationality, where decision-making is influenced by 'quick-yet-economical' heuristics rather than exhaustive searches for optimal solutions. Overall, this work sheds light on the role of bounded rationality in linguistic decision-making and language evolution.