Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
Parsing, i.e., identifying the underlying hierarchical structure of natural language expressions is important for several natural language processing applications. In recent times Machine Learning (ML) approaches have been developed for this study for many languages. Most of the effective techniques require an annotated corpus of the language for training and validation. For the Manipuri language of the Tibeto-Burman family, neither such a corpus nor a grammar framework to automatically analyse and represent the structure of sentences exists yet. This study proposes a Context-Free Grammar (CFG) that provides the framework to represent the structure of Manipuri sentences. This paves the way for parsing Manipuri sentences using CFG-based parsers for various applications and to conveniently build a Treebank for developing ML-based parsers for Manipuri. The rules of the proposed CFG are handcrafted after extensive analysis of the structure of Manipuri sentences. The grammar covers simple, compound, complex and compound-complex sentences. For evaluation, we induce an Earley's parser with the proposed CFG and test it over a collection of sentences that covers the possible varieties of structure. A recognition rate of 83.20% achieved in these experiments indicates the effectiveness of the proposed grammar.
This study examined involuntary capture of attention, overt attention, and stimulus valence and arousal ratings, all factors that can contribute to potential attentional biases to face and train objects in children with and without autism spectrum disorder (ASD). In the visual domain, faces are particularly captivating, and are thought to have a 'special status' in the attentional system. Research suggests that similar attentional biases may exist for other objects of expertise (e.g. birds for bird experts), providing support for the role of exposure in attention prioritization. Autistic individuals often have circumscribed interests around certain classes of objects, such as trains, that are related to vehicles and mechanical systems. This research aimed to determine whether this propensity in autistic individuals leads to stronger attention capture by trains, and perhaps weaker attention capture by faces, than what would be expected in non-autistic children. In Experiment 1, autistic children (6-14 years old) and age- and IQ-matched non-autistic children performed a visual search task where they manually indicated whether a target butterfly appeared amongst an array of face, train, and neutral distractors while their eye-movements were tracked. Autistic children were no less susceptible to attention capture by faces than non-autistic children. Overall, for both groups, trains captured attention more strongly than face stimuli and, trains had a larger effect on overt attention to the target stimuli, relative to face distractors. In Experiment 2, a new group of children (autistic and non-autistic) rated train stimuli as more interesting and exciting than the face stimuli, with no differences between groups. These results suggest that: (1) other objects (trains) can capture attention in a similar manner as faces, in both autistic and non-autistic children (2) attention capture is driven partly by voluntary attentional processes related to personal interest or affective responses to the stimuli.
There are only a few previous EEG studies that were conducted while the audience is listening to live music. However, in laboratory settings using music recordings, EEG frequency bands theta and alpha are connected to music improvisation and creativity. Here, we measured EEG of the audience in a concert-like setting outside the laboratory and compared the theta and alpha power evoked by partly improvised versus regularly performed familiar versus unfamiliar live classical music. To this end, partly improvised and regular versions of pieces by Bach (familiar) and Melartin (unfamiliar) were performed live by a chamber trio. EEG data from left and right frontal and central regions of interest were analysed to define theta and alpha power during each performance. After the performances, the participants rated how improvised and attractive each of the performances were. They also gave their affective ratings before and after each performance. We found that theta power was enhanced during the familiar improvised Bach piece and the unfamiliar improvised Melartin piece when compared with the performance of the same piece performed in a regular manner. Alpha power was not modulated by manner of performance or by familiarity of the piece. Listeners rated partly improvised performances of a familiar Bach and unfamiliar Melartin piece as more improvisatory and innovative than the regular performances. They also indicated more joy and less sadness after listening to the unfamiliar improvised piece of Melartin and less fearful and more enthusiastic after listening to the regular version of Melartin than before listening. Thus, according to our results, it is possible to study listeners' brain functions with EEG during live music performances outside the laboratory, with theta activity reflecting the presence of improvisation in the performances.
Though machine learning algorithms are able to achieve pattern recognition from the correlation between data and labels, the presence of spurious features in the data decreases the robustness of these learned relationships with respect to varied testing environments. This is known as out-of-distribution (OoD) generalization problem. Recently, invariant risk minimization (IRM) attempts to tackle this issue by penalizing predictions based on the unstable spurious features in the data collected from different environments. However, similar to domain adaptation or domain generalization, a prevalent non-trivial limitation in these works is that the environment information is assigned by human specialists, i.e. a priori, or determined heuristically. However, an inappropriate group partitioning can dramatically deteriorate the OoD generalization and this process is expensive and time-consuming. To deal with this issue, we propose a novel theoretically principled min-max framework to iteratively construct a worst-case splitting, i.e. creating the most challenging environment splittings for the backbone learning paradigm (e.g. IRM) to learn the robust feature representation. We also design a differentiable training strategy to facilitate the feasible gradient- based computation. Numerical experiments show that our algorithmic framework has achieved superior and stable performance in various datasets, such as Colored MNIST and Punctuated Stanford sentiment treebank (SST). Furthermore, we also find our algorithm to be robust even to a strong data poisoning attack. To the best of our knowledge, this is one of the first to adopt differentiable environment splitting method to enable stable predictions across environments without environment index information, which achieves the state-of-the-art performance on datasets with strong spurious correlation, such as Colored MNIST.
Multisensory integration influences emotional perception, as the McGurk effect demonstrates for the communication between humans. Human physiology implicitly links the production of visual features with other modes like the audio channel: Face muscles responsible for a smiling face also stretch the vocal cords that results in a characteristic smiling voice. For artificial agents capable of multimodal expression, this linkage is modeled explicitly. In our study, we observe the influence of visual and audio channel on the perception of the agent’s emotional state. We created two virtual characters to control for anthropomorphic appearance. We record videos of these agents either with matching or mismatching emotional expression in the audio and visual channel. In an online study we measured the agent’s perceived valence and arousal. Our results show that a matched smiling voice and smiling face increase both dimensions of the Circumplex model of emotions: ratings of valence and arousal grow. When the channels present conflicting information, any type of smiling results in higher arousal rating, but only the visual channel increases the perceived valence. When engineers are constrained in their design choices, we suggest they should give precedence to convey the artificial agent’s emotional state through the visual channel.
The fight against HIV is one of the targets in our century. Thus, among the HIV-infected patients, one of the most dangerous and outstanding with its complications is those with lung pathologies. According clinical staging of the disease, such patients may present Tuberculosis, Pneumocystis jirovecii, Cytomegaloviruses, Candidiasis, Toxoplasmosis etc. The research by scientific research institute of lung disease was carried out among the inpatient individuals in amount of 48.37 (77%) of them were presented with tuberculosis and 11 (23%) with Interstitial Lung Disease (ILD). Studies were presented on HIV-positive patients who were divided by the randomization techniques. Among 37 patients with tuberculosis, 29 (78%) had AFB (acid fast bacillius) with Gexpert, HAIN methods, 6 (22%) were diagnosed by imaging methods (HRCT, chest X-ray) and serum ADA level. According to previous studies, there were no correlations between serum ADA level elevations at HIV-positive patients (p value 0.05). Among 11 patients presented with ILD Pneumocystis jirovecii were detected at 5 (45%), 3 (27.5%) were presented with daily mortality, 3 took a Co-Trimaxozole therapy diagnosed by imaging methods. Clinical effectiveness was approved by the presence of pneumocystis origin. At the second stage of the study was found a correlation between different Cd4 cell count and imaging rating. Thus, among total number of 119 HIV-positive patients, 38 (32%) had infiltration zones, 53 (44%) had a destruction, 20 (17%) dissemination, 8 (7%) mediastinal lymphadenopathy. Statistic results p value 0.000424, thus there is direct correlation.
Recent impressive improvements in NLP, largely based on the success of contextual neural language models, have been mostly demonstrated on at most a couple dozen high- resource languages. Building language mod- els and, more generally, NLP systems for non- standardized and low-resource languages remains a challenging task. In this work, we fo- cus on North-African colloquial dialectal Arabic written using an extension of the Latin script, called NArabizi, found mostly on social media and messaging communication. In this low-resource scenario with data display- ing a high level of variability, we compare the downstream performance of a character-based language model on part-of-speech tagging and dependency parsing to that of monolingual and multilingual models. We show that a character-based model trained on only 99k sentences of NArabizi and fined-tuned on a small treebank of this language leads to performance close to those obtained with the same architecture pre- trained on large multilingual and monolingual models. Confirming these results a on much larger data set of noisy French user-generated content, we argue that such character-based language models can be an asset for NLP in low-resource and high language variability settings.
We present a recurrent neural network memory that uses sparse coding to create a combinatoric encoding of sequential inputs. The network is trained using only local and immediate credit assignment. Despite this constraint, results are comparable to networks trained using deep backpropagation or BackProp Through Time (BPTT). With several examples, we show that the network can associate distant cause and effect in a discrete stochastic process, predict partially-observable higherorder sequences, and learn to generate many time-steps of video simulations. Typical memory consumption is 10-30x less than conventional RNNs, such as LSTM, trained by BPTT. One limitation of the memory is generalization to unseen input sequences. We additionally explore this limitation by measuring next-word prediction perplexity on the Penn Treebank dataset.
Abstract Quantitative 23 Na magnetic resonance imaging (MRI) provides tissue sodium concentration (TSC), which is connected to cell viability and vitality. Long acquisition times are one of the most challenging aspects for its clinical establishment. K‐space undersampling is an approach for acquisition time reduction, but generates noise and artifacts. The use of convolutional neural networks (CNNs) is increasing in medical imaging and they are a useful tool for MRI postprocessing. The aim of this study is 23 Na MRI acquisition time reduction by k‐space undersampling. CNNs were applied to reduce the resulting noise and artifacts. A retrospective analysis from a prospective study was conducted including image datasets from 46 patients (aged 72 ± 13 years; 25 women, 21 men) with ischemic stroke; the 23 Na MRI acquisition time was 10 min. The reconstructions were performed with full dataset (FI) and with a simulated dataset an image that was acquired in 2.5 min (RI). Eight different CNNs with either U‐Net–based or ResNet‐based architectures were implemented with RI as input and FI as label, using batch normalization and the number of filters as varying parameters. Training was performed with 9500 samples and testing included 400 samples. CNN outputs were evaluated based on signal‐to‐noise ratio (SNR) and structural similarity (SSIM). After quantification, TSC error was calculated. The image quality was subjectively rated by three neuroradiologists. Statistical significance was evaluated by Student’s t‐test. The average SNR was 21.72 ± 2.75 (FI) and 10.16 ± 0.96 (RI). U‐Nets increased the SNR of RI to 43.99 and therefore performed better than ResNet. SSIM of RI to FI was improved by three CNNs to 0.91 ± 0.03. CNNs reduced TSC error by up to 15%. The subjective rating of CNN‐generated images showed significantly better results than the subjective image rating of RI. The acquisition time of 23 Na MRI can be reduced by 75% due to postprocessing with a CNN on highly undersampled data.
Techniques that detect sentence similarity have been a very important domain of research and lately many such techniques have been successfully implemented. With the use of Natural Language Processing (NLP) these techniques have been implemented more efficiently. The concept of semantic analysis is very significant in determining sentence similarity. The model proposed in this paper, deploys a NLP based methodology that works on the Sentence Involving Compositional Knowledge (SICK) dataset. The proposed methodology considers the set of sentencesto be a subset of words and it is split based on the semantic and syntactic structure. A lexical database is used by this model, unlike methods deployed by other models. This is followed by the computation of the word order vector. When this NLP based method is tested on the dataset, the accuracy obtained is 82.7% on the basis of mean absolute error. The obtained results are better than the previously used methods. Also, the proposed method is computationally faster than the existing methods.
An extensive epidemiological literature indicates that increased exposure to tobacco retail outlets (TROs) places never smokers at greater risk for smoking uptake and current smokers at greater risk for increased consumption and smoking relapse. Yet research into the mechanisms underlying this effect has been limited. This preliminary study represents the first effort to examine the neurobiological consequences of exposure to personally relevant TROs among both smokers (n = 17) and nonsmokers (n = 17). Individuals carried a global positioning system (GPS) tracker for 2 weeks. Traces were used to identify TROs and control outlets that fell inside and outside their ideographically defined activity space. Participants underwent functional MRI (fMRI) scanning during which they were presented with images of these storefronts, along with similar store images from a different county and rated their familiarity with these stores. The main effect of activity space was additive with a Smoking status × Store type interaction, resulting in smokers exhibiting greater neural activation to TROs falling inside activity space within the parahippocampus, precuneus, medial prefrontal cortex, and dorsal anterior insula. A similar pattern was observed for familiarity ratings. Together, these preliminary findings suggest that the otherwise distinct neural systems involved in self-orientation/self-relevance and smoking motivation may act in concert and underlie TRO influence on smoking behavior. This study also offers a novel methodological framework for evaluating the influence of community features on neural activity that can be readily adapted to study other health behaviors.
We present the first supertagging-based parser for linear context-free rewriting systems (LCFRS). It utilizes neural classifiers and outperforms previous LCFRS-based parsers in both accuracy and parsing speed by a wide margin. Our results keep up with the best (general) discontinuous parsers, particularly the scores for discontinuous constituents establish a new state of the art. The heart of our approach is an efficient lexicalization procedure which induces a lexical LCFRS from any discontinuous treebank. We describe a modification to usual chart-based LCFRS parsing that accounts for supertagging and introduce a procedure that transforms lexical LCFRS derivations into equivalent parse trees of the original treebank. Our approach is evaluated on the English Discontinuous Penn Treebank and the German treebanks Negra and Tiger.
The purpose of this study was to investigate a more effective direction of pragmatic education by exploring the process of acquiring speech in the communication experience of Vietnamese language learners. Therefore, the study conducted in-depth interviews with seven Vietnamese language learners. The in-depth interviews focused on the process of pragmatic failure or speech acquisition, which emerged from the learner’s communication experience. The result of the study showed that Vietnamese language learners experienced a variety of pragmatic failures in the process of communication, mainly because of the differences in Korean and Vietnamese speaking norms, their limited Korean language skills, and the impact of their educational content. The experience of failure has led learners to emphasize the need for learning through experience and pragmatic education. Based on these findings, the study suggests the following implications for a more effective Korean language education for Vietnamese learners: Korean language education sites for Vietnamese language learners should consider the differences between the Korean and Vietnamese linguistic norms, and pragmatic learning and teaching by presenting the contexts and circumstances should be performed.
Child-directed speech, as a specialized form of speech directed toward young children, has been found across numerous languages around the world and has been suggested as a universal feature of human experience. However, variation in its implementation and the extent to which it is culturally supported has called its universality into question. Child-directed speech has also been posited to be associated with expression of positive affect or "happy talk." Here, we examined Canadian English-speaking adults' ability to discriminate child-directed from adult-directed speech samples from two dissimilar language/cultural communities; an urban Farsi-speaking population, and a rural, horticulturalist Tseltal Mayan speaking community. We also examined the relationship between participants' addressee classification and ratings of positive affect. Naive raters could successfully classify CDS in Farsi, but only trained raters were successful with the Tseltal Mayan sample. Associations with some affective ratings were found for the Farsi samples, but not reliably for happy speech. These findings point to a complex relationship between perception of affect and CDS, and context-specific effects on the ability to classify CDS across languages.
In this paper, we leverage pre-trained language models (PLMs) to precisely evaluate the semantics preservation of edition process on sentences. Our metric, Neighbor Distribution Divergence (NDD), evaluates the disturbance on predicted distribution of neighboring words from mask language model (MLM). NDD is capable of detecting precise changes in semantics which are easily ignored by text similarity. By exploiting the property of NDD, we implement a unsupervised and even training-free algorithm for extractive sentence compression. We show that our NDD-based algorithm outperforms previous perplexity-based unsupervised algorithm by a large margin. For further exploration on interpretability, we evaluate NDD by pruning on syntactic dependency treebanks and apply NDD for predicate detection as well.
Research has identified three different types of smiles – the reward, affiliation and dominance smile – which serve expressions of happiness, connectedness, and superiority, respectively. Examining their explicit and implicit evaluations by considering a perceivers’ level of social anxiety and psychopathy may enhance our understanding of these smiles’ theorised meanings, and their role in problematic social behaviour. Female participants (N=122) filled in questionnaires on social anxiety, psychopathic tendencies (i.e. the affective-interpersonal deficit and antisocial lifestyle) and callous–unemotional (CU) traits. In order to measure explicit and implicit evaluations of the three smiles, angry and neutral facial expressions, an Explicit Valence Rating Task and an Approach-Avoidance Task were administered. Results indicated that all smiles were explicitly evaluated as positive. No differences in implicit evaluations between the smile types were found. Social anxiety was not associated with either explicit or implicit smile evaluations. In contrast, CU-traits were negatively associated with explicit evaluations of reward and dominance smiles. These findings support the assumptions of non-biased explicit information processing in social anxiety, and flattened emotional sensitivity in CU-traits. The importance of a multimethod approach to enhance the understanding of the effects of smile types on perceivers is discussed.
The presence of a partner can attenuate physiological fear responses, a phenomenon known as social buffering. However, not all individuals are equally sociable. Here we investigated whether social buffering of fear is shaped by sensitivity to social anxiety (social concern) and whether these effects are different in females and males. We collected skin conductance responses (SCRs) and affect ratings of female and male participants when they experienced aversive and neutral sounds alone (alone treatment) or in the presence of an unknown person of the same gender (social treatment). Individual differences in social concern were assessed based on a well-established questionnaire. Our results showed that social concern had a stronger effect on social buffering in females than in males. The lower females scored on social concern, the stronger the SCRs reduction in the social compared to the alone treatment. The effect of social concern on social buffering of fear in females disappeared if participants were paired with a virtual agent instead of a real person. Together, these results showed that social buffering of human fear is shaped by gender and social concern. In females, the presence of virtual agents can buffer fear, irrespective of individual differences in social concern. These findings specify factors that shape the social modulation of human fear, and thus might be relevant for the treatment of anxiety disorders.
<strong>ACCEPTED ABSTRACT:</strong> <strong>Introduction:</strong> Studies consistently report that patients with schizophrenia exhibit qualitative abnormalities on language production tasks. These abnormalities are possibly associated with the severity of psychotic symptoms. Despite this, some studies have conflictingly suggested that patients with schizophrenia exhibit similar word frequency (WF) effects on lexical tasks compared to healthy subjects. Given that previous studies calculated WFs from language corpora, we aimed to investigate the relationship between WF and psychotic symptoms using a novel, simple method for calculating WF. <strong>Methods:</strong> Thirty-six patients with schizophrenia were included in the study. The severity of positive symptoms was measured using the Scale for the Assessment of Positive Symptoms (SAPS). One semantic and one letter fluency task were administered with the patients instructed to produce as many animal anmes and words beginning with the letter p in 60 s, respectively. Every response in the output was assigned (1) a corpus-based WF, extracted from the German-language lexical database dlexDB, and (2) a within-sample WF. The within-sample WF was calculated as the raw number of participants who produced the word. Spearman’s correlations were computed between the WF variables and symptoms. <strong>Results:</strong> Corpus-based WF exhibited skewed, kurtic, and/or non-normal distribution. Contrastingly, within-sample WF displayed normal, non-skewed, and non-kurtic distribution. There were no significant correlations between corpus-based WF and symptoms on both tasks. Conversely, within-sample WF on semantic fluency was significantly negatively and weakly correlated with the global SAPS score, as well as subscales measuring delusions and bizarre behavior. Further, within-sample WF on letter fluency was significantly positively and weakly correlated with the subscale measuring bizarre behavior of the SAPS scale. <strong>Conclusion:</strong> The differences in the data distribution patterns between corpus-based WF and within-sample WF indicate that different methodological frameworks may have better use of one or the other variable type. Further, significant correlations with positive symptoms were observed only for within-sample WF. It can be concluded that within-sample WF may be more appropriate for analyzing verbal fluency output in psychiatric research compared to corpus-based WF.
FrameNet is a lexical semantic resource based on the linguistic theory of frame semantics. A number of framenet development strategies have been reported previously and all of them involve exploration of corpora and a fair amount of manual work. Despite previous efforts, there does not exist a well-thought-out automatic/semi-automatic methodology for frame construction. In this paper we propose a data-driven methodology for identification and semi-automatic construction of frames. As a proof of concept, we report on our initial attempts to build a widerscale framenet for the legal domain (LawFN) using the proposed methodology. The constructed frames are stored in a lexical database and together with the annotated example sentences they have been made available through a web interface.
Subject of the work: to find out how S. Maugham was able to use stylistic means in this story. Purpose of the work: to find out what stylistic means were used in this story. Relevance: Stylistics is the science that studies styles of speech and the use of linguistic means in them. This helps to make speech stylistically correct. And the correctness of speech is the basis of speech culture, that is, the ability to assimilate linguistic norms and use the expressive means of language. Stylistics also helps with the formation of skills in the coherent exposition of thoughts in oral and written form. Stylistics introduces the patterns of language use in different spheres of communication, their stylistic originality, and thereby enriches knowledge about the functional aspect of the language. Stylistics as a branch of linguistics is of great importance for the development and theory of language. Conclusion: The purpose of the work has been achieved. We found out what stylistic means were used. Предмет работы: выяснить каким образом С.Моэм смог использовать стилистические средства в этом рассказе. Цель работы: выяснить какие стилистические средства были использованы в этом рассказе. Актуальность: Стилистика - это наука, изучающая стили речи и использование в них языковых средств. Это помогает сделать речь стилистически правильной. А правильность речи - основа речевой культуры, то есть умение усваивать языковые нормы и пользоваться выразительными средствами языка. Стилистика также помогает в формировании навыков связного изложения мыслей в устной и письменной форме. Стилистика знакомит с закономерностями использования языка в разных сферах общения, их стилистической оригинальностью и тем самым обогащает знания о функциональной стороне языка. Стилистика как раздел языкознания имеет большое значение для развития и теории языка. Вывод: Цель работы была достигнута. Мы выяснили какие стилистические средства были использованы. Жұмыс тақырыбы: бұл әңгімеде С.Моэм стилистикалық құралдарды қалай қолдана білгенін білу. Жұмыстың мақсаты: бұл әңгімеде қандай стилистикалық құралдар қолданылғанын білу. Өзектілігі: Стилистика - сөйлеу мәнерлерін және оларда тілдік құралдарды қолдануды зерттейтін ғылым. Бұл сөйлеуді стилистикалық тұрғыдан дұрыс жасауға көмектеседі. Ал сөйлеудің дұрыстығы - сөйлеу мәдениетінің негізі, яғни тілдік нормаларды сіңіріп, тілдің экспрессивті құралдарын қолдана білу. Стилистика сонымен қатар ойды ауызша және жазбаша түрде үйлестіру дағдысын қалыптастыруға көмектеседі. Стилистика қарым-қатынастың әр түрлі салаларында тілдің қолданылу заңдылықтарын, олардың стилистикалық ерекшелігін енгізеді және сол арқылы тілдің функционалдық аспектісі туралы білімді байытады. Стилистика тіл білімінің бір саласы ретінде тілдің дамуы мен теориясы үшін үлкен маңызға ие. Қорытынды: Жұмыстың мақсаты орындалды. Біз қандай стилистикалық құралдар қолданылғанын білдік.
BACKGROUND: The affective states most strongly associated with nonsuicidal self-injury (NSSI) remain poorly understood, particularly among veterans. This study used ecological momentary assessment (EMA) to examine relationships between affect ratings and NSSI urges and behaviors among veterans with NSSI disorder. METHODS: Participants (N = 40) completed EMA entries via mobile phone for 28 days (3722 total entries). Entries included intensity ratings for five basic affective states, as well as NSSI urges and behaviors, during the past 4 hours. RESULTS: Bivariate analyses indicated that each affect variable was significantly associated with both NSSI urges and behaviors. Angry/hostile and sad were most strongly associated with both NSSI urges and behaviors. A multivariate regression revealed that angry/hostile, disgusted with self, and happy (inversely related) were contemporaneously (within the same period) associated with NSSI behaviors, whereas all five basic affective states were contemporaneously associated with NSSI urges. In a lagged model, angry/hostile and sad were associated with subsequent NSSI urges but not behaviors. CONCLUSIONS: Findings highlight the relevance of particular affective states to NSSI and the potential utility of targeting anger in treatments for NSSI among veterans. There is a need for future EMA research study to further investigate temporal relationships between these variables.
Online reviews are the newest method for patients to evaluate their providers. However, insufficient studies focus on the role of inherent physician characteristics, such as gender and years of experience, on patient satisfaction. We analyzed both quantitative and qualitative online reviews of 350 general dermatology providers at 121 Accreditation Council for Graduate Medical Education–accredited dermatology programs across the country to determine the effect of gender and years of experience. There were 38,008 online reviews of general dermatology providers. There was no significant difference in male and female overall ratings. Ratings were overall equally positive for both genders. Female providers were more likely to have positive written comments regarding time spent with patients (P = 0.027). New providers received highest overall, promptness, and time spent with patient ratings (P < 0.001). Medium experience providers received highest scores in bedside manner (P < 0.001), accurate diagnosis (P = 0.018), and ability to answer questions (P = 0.005). Advanced providers scored the lowest across all categories. In conclusion, gender did not significantly affect ratings, although females received more positive written comments on time spent with patients. Years of experience, however, is a significant factor in patient ratings, with new or medium experience providers scoring higher than advanced providers in every category. Online reviews are the newest method for patients to evaluate their providers. However, insufficient studies focus on the role of inherent physician characteristics, such as gender and years of experience, on patient satisfaction. We analyzed both quantitative and qualitative online reviews of 350 general dermatology providers at 121 Accreditation Council for Graduate Medical Education–accredited dermatology programs across the country to determine the effect of gender and years of experience. There were 38,008 online reviews of general dermatology providers. There was no significant difference in male and female overall ratings. Ratings were overall equally positive for both genders. Female providers were more likely to have positive written comments regarding time spent with patients (P = 0.027). New providers received highest overall, promptness, and time spent with patient ratings (P < 0.001). Medium experience providers received highest scores in bedside manner (P < 0.001), accurate diagnosis (P = 0.018), and ability to answer questions (P = 0.005). Advanced providers scored the lowest across all categories. In conclusion, gender did not significantly affect ratings, although females received more positive written comments on time spent with patients. Years of experience, however, is a significant factor in patient ratings, with new or medium experience providers scoring higher than advanced providers in every category.
In a 21st century dominated by VUCA environments (Volatile, Uncertain, Complex and Ambiguous) and in an increasingly diverse and global society, education should rethink how to meet the real needs of the citizens of the present and the future. Educational methods for language instruction have received assiduous attention from researchers, that may have overlooked educational ends, and that is to serve real life purposes. Learning a language is more than just acquiring knowledge about a new linguistic norm and its rules: it is above all, a vehicle for communication, an open channel to the world and a new scope with which new cultures are explored and different views and perspectives are discovered and shared. This paper aims at exploring task-based learning approach for language instruction and presenting a study on the benefits attributed to this approach, relating them to existing trends in current educational innovation. In doing so, a comparison between meaning-based learning and instruction-based learning is needed. Here we will review some of the most relevant theories and approaches to better understand task-based learning and explore its potential.
Abstract Listening to pleasurable music is known to engage the brain’s reward system. This has motivated many cognitive-behavioral interventions for healthy aging, but little is known about the effects of music-based intervention (MBI) on plasticity of the cognitive and reward systems. Here we show preliminary evidence that brain network connectivity can change after receptive MBI in cognitively unimpaired older adults. Using a combination of whole-brain regression, seed-based connectivity analysis, and representational similarity analysis (RSA), we examined fMRI responses during music listening in older adults before and after an eight-week personalized MBI. Participants rated self-selected and researcher-selected musical excerpts on liking and familiarity. Parametric effects of liking, familiarity, and selection showed simultaneous activation in auditory, reward, and default mode network (DMN) areas. Seed-based connectivity comparing pre- and post-intervention showed significant increase in functional connectivity between auditory regions and medial prefrontal cortex (mPFC); this auditory-mPFC connectivity was modulated by participant liking and familiarity ratings. RSA showed significant representations of selection and novelty at both time-points, and an increase in striatal representation of musical stimuli following intervention. Taken together, results show how regular music listening can provide an auditory channel towards the mPFC, thus offering a potential neural mechanism for MBI supporting healthy aging.
BACKGROUND: While romantic jealousy may help to maintain relationships, following partner infidelity and an irretrievable loss of trust it can also promote break-ups. The neuropeptide oxytocin can enhance the maintenance of social bonds and reduce couple conflict, although its influence on jealousy evoked by imagined or real infidelity is unclear. AIMS: This study aimed to investigate the effects of intranasal oxytocin (24 IU) on romantic jealousy in both males and females in imagined and real contexts. METHODS: Seventy heterosexual couples participated in this double-blind, placebo-controlled, between-subject design study. Jealousy was firstly quantified in the context of subjects imagining partner infidelity and secondly in a Cyberball game where their partner interacted preferentially with an opposite-sexed rival stranger to simulate partner exclusion, or rejected a neutral stranger but not the partner. RESULTS: Oxytocin primarily decreased jealousy and arousal ratings towards imagined emotional and sexual infidelity by a partner in both sexes. During the Cyberball game, while male and female subjects in both groups subsequently threw the ball least often to the rival stranger, under oxytocin they showed reduced romantic jealousy and arousal ratings for stranger players, particularly the rival one, and reported reduced negative and increased positive feelings while playing the game. CONCLUSIONS: Together, our results suggest that oxytocin can reduce the negative emotional impact of jealousy in established romantic partners evoked by imagined or real infidelity or exclusive social interactions with others. This provides further support for oxytocin promoting maintenance of relationships.
Facial expressions are a rich information source from which observers infer the emotional states of others. Despite much understanding about the brain regions that represent facial expressions, we do not yet know how representations of these facial movements transform into judgments of emotions in the brain. We addressed this question in 5 participants who judged the emotion of individual face movements called Action Units (AUs) while we concurrently measured brain activity using magnetoencephalography (MEG). Stimuli were animations of 5 facial movements--Outer Brower Raiser (AU2), Nose Wrinkler (AU9), Lip Corner Puller (AU12), Chin Raiser (AU17), Lip Stretcher (AU20), each at 4 levels of intensity (%25 - %100). We instructed participants to rate each animation according to either its perceived valence (‘negative’, ‘neutral’ or ‘positive’) or arousal (‘low,’ ‘neutral’ or ‘high’). Tasks alternated between blocks of 40 trials (5 AUs X 4 intensity levels X 2 repetitions) and participants completed 4,000 ~ 6,000 trials in total. We averaged all ratings of each AU and intensity level per task for each participant. We show that the arousal ratings increased along AU intensity levels while valence ratings are consistent for each AU (e.g., Nose Wrinkler (AU9) as negative and Lip Corner Puller (AU12) as positive). Then, we calculated Mutual Information (MI, permutation test) between MEG recording and task ratings. The results revealed the spatial and temporal distribution of brain activities related to the specific valence and arousal. We found that the valence and arousal evoked similar representational peaks ~270ms and ~750 ms in the temporal lobes while a special peak from parietal lobes at 387ms for valence task that differentiated between the two inferences. Our results show where (in temporal lobes and parietal lobes) and when (at ~270ms, 380ms and 750 ms post stimulus) the brain processes dynamic AUs as meaningful affective signals.
The complete semantic representation of a Tibetan sentence is mainly determined by the addition of a specific functional word. The choice of Tibetan functional words is mainly influenced (both explicitly and implicitly) by the sequence of Tibetan suffixes. In this article, we propose an RNN-based Tibetan radical suffix unit (TRSU) to consider this relationship. Specifically, for the Tibetan radical suffix unit-explicit (TRSU-E) method, the fixed suffix in Tibetan is used to determine the virtual functional words. For the Tibetan radical suffix unit-implicit (TRSU-I) method, the decision is assisted by adding a specific suffix. To test the method, we design a standard Tibetan corpus, which consists of different genres. Our experimental results show that the complexity of our method is reduced by up to 22.2% relative to the best baseline. Furthermore, with the hidden semantic information and implicit suffix, TRSU-I outperforms TRSU-E by reducing the perplexity (PPL) by 3%. Moreover, good results are achieved on the English Penn Treebank data set.
While Out-of-distribution (OOD) detection has been well explored in computer\nvision, there have been relatively few prior attempts in OOD detection for NLP\nclassification. In this paper we argue that these prior attempts do not fully\naddress the OOD problem and may suffer from data leakage and poor calibration\nof the resulting models. We present PnPOOD, a data augmentation technique to\nperform OOD detection via out-of-domain sample generation using the recently\nproposed Plug and Play Language Model (Dathathri et al., 2020). Our method\ngenerates high quality discriminative samples close to the class boundaries,\nresulting in accurate OOD detection at test time. We demonstrate that our model\noutperforms prior models on OOD sample detection, and exhibits lower\ncalibration error on the 20 newsgroup text and Stanford Sentiment Treebank\ndataset (Lang, 1995; Socheret al., 2013). We further highlight an important\ndata leakage issue with datasets used in prior attempts at OOD detection, and\nshare results on a new dataset for OOD detection that does not suffer from the\nsame problem.\n
Binary Stanford Sentiment Treebank (SST2) is a binary version of SST and Movie Review dataset (the neutral class was removed), that is, the data was classified only into positive and negative classes. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_<k>.pkl: pandas DataFrame with k-cross validation partition
The research is focused on definitions of discourse relations, a topic that is currently little-studied. The paper gives a brief overview of existing solutions for discourse relations definitions: Rhetorical Structure Theory (RST), Segmented Discourse Representation Theory (SDRT), Penn Discourse Treebank (PDTB), and Cognitive approach to Coherence Relations. The author shows criteria used to define a discourse relation, or, in case of a narrower definition, a logical-semantic relation, in these approaches and outlines the shortcomings of the described definitions. The author also describes the principles used to build the classification and the definitions of logical-semantic relations (LSR) in the Supracorpora Database of connectives (SDB). The classification is based on four basic semantic operations upon which rests every LSR's definition: implication, location on the chronological scale, comparison, correlation between specific and general or an element and a set. The classification consistently distinguishes the levels at which the LSR can be established: propositional, illocutionary, and metalinguistic. Each LSR is defined on the basis of these two criteria. Thus, for example, for the LSR of alternative based on the comparison operation, one has the choice between the LSR of propositional, illocutionary and metalinguistic alternative (We will go to the mountains or to the sea vs. Put the gun away, or are you scared? vs. The symbol of the year or, simply speaking, cutie-pie). In case of LSRs based on implication or comparison, the polarity criterion is added, distinguishing whether the LSR is established between p and q or their negative correlates p and q are also to be taken into account in order to obtain a correct interpretation (cf. well-known descriptions of how the Russian conjunction no 'but' functions). In addition, semantic and pragmatic characteristics of the context are also considered in the classification. For example, in the case of the LSR of specification and generalization, the semantic correlation between p and q (together with their intensional and extensional interpretations) is taken heed of. Several definitions of LSR and corresponding examples are provided. Thus, the LSR of extensional specification is defined as follows: based on the operation of correlation between the general and the particular; established at the propositional level; X contains a generalized notion or state of things p; Y contains a more particular q-notion, limiting p-extensional. And the LSR of intensional specification is defined as follows: based on the operation of correlation between the general and the particular; established at the metalinguistic level; X contains a generalized concept or state of things p; Y contains a more particular q-notion, limiting p-intensional. The definitions used in the SDB definitions make it possible to evaluate, on the basis of the proposed criteria, the semantic closeness of relations and increase the level of consistency in the work of experts and annotators. That in turn increases the value of the annotated material, and therefore its reliability.
While educators may be well positioned to support unaccompanied immigrant youth, there is limited interdisciplinary research focused on understanding the complexity of youth’s experiences in US schools. The purpose of this qualitative, interview-based study was to better understand how youth’s transnational experiences pre-, during, and post-migration affected their school-based experiences, and to explore how schools supported them. Participants included ten unaccompanied immigrant youths from Central America and six key informants who worked with youth in a professional capacity. Findings indicate that youth experienced multiple challenges including stressful and traumatic events, barriers to mental health and legal services, and unfamiliar cultural and linguistic norms that sometimes were not recognized or understood by their teachers and schools. The youth also brought important resources, such as high expectations and aspirations and strong connections to family and community. School-based experiences that built from youth’s resources and motivations (e.g., through school-community partnerships and responsive classroom practices) had the potential to enhance belonging, community connections, and wellness. More interdisciplinary research is needed to develop and support school-based practices and partnerships in consultation with youth that build from knowledge of their particular resources and challenges.
Dictionary-based methods in sentiment analysis have received scholarly attention recently, the most comprehensive examples of which can be found in English.However, many other languages lack polarity dictionaries, or the existing ones are small in size as in the case of Senti-TurkNet, the first and only polarity dictionary in Turkish.Thus, this study aims to extend the content of SentiTurkNet by comparing the two available WordNets in Turkish, namely KeNet and TR-wordnet of BalkaNet.To this end, a current Turkish polarity dictionary has been created relying on 76,825 synsets matching KeNet, where each synset has been annotated with three polarity labels, which are positive, negative and neutral.Meanwhile, the comparison of KeNet and TR-wordnet of BalkaNet has revealed their weaknesses such as the repetition of the same senses, lack of necessary merges of the items belonging to the same synset and the presence of redundant narrower versions of synsets, which are discussed in light of their potential to the improvement of the current lexical databases of Turkish.
The paper investigates „Sprachliche Verrohung“ (linguistic neglection/brutalization), a term that has been recently and often used within the German mass media. It seems, however, that there is no common understanding of what „Sprachliche Verrohung“ is. To obtain a definition, a thinkaloud study was conducted: 40 participants judged relevant linguistic examples by verbalizing aloud their thoughts and ideas. The obtained think-aloud protocols are analysed and the following definition is derived: Expressions of „Sprachliche Verrohung“ are in conflict with the linguistic norm and speakers uses them despite their knowledge of this conflict.
Abstract In this paper we introduce an extended version of the Vedic Treebank ( vtb, Hellwig et al. 2020) which comes along with revisited and extended annotation guidelines. In order to assess the quality of our annotations as well as the usability and limits of the guidelines we performed an inter-annotator agreement test. The results show that agreement between annotators is hampered by various factors, most prominently by insufficient understanding of the content because of the cultural and temporal gap and incomplete knowledge of Vedic grammar. An in-depth discussion of disagreeing annotations demonstrates that the setup of the workflow, too, has a major influence on inter-annotator agreement. We suggest some measures that can help increase the transparency and annotation consistency according to current knowledge of the language when annotating Vedic Sanskrit, or ancient language varieties in general.
Abstract The lexicon of emotion words is fundamental to interpersonal communication. To examine how emotion word acquisition interacts with societal context, the present study investigated emotion word development in three groups of child Korean users aged 4–13 years: those who use Korean primarily outside the home as a majority language (MajKCs) or inside the home as a minority language (MinKCs), and those who use Korean both inside and outside the home (KCs). These groups, along with a group of L1 Korean adults, rated the emotional valence of 61 Korean emotion words varying in frequency, valence, and age of acquisition. Results showed KCs, MajKCs, and MinKCs all converging toward adult-like valence ratings by ages 11–13 years; unlike KCs and MajKCs, however, MinKCs did not show age-graded development and continued to diverge from adults in emotion word knowledge by these later ages. These findings support the view that societal context plays a major role in emotion word development, offering one reason for the intergenerational communication difficulties reported by immigrant families.
From a simplified analysis of adaptive methods, we derive AvaGrad, a new optimizer which outperforms SGD on vision tasks when its adaptability is properly tuned. We observe that the power of our method is partially explained by a decoupling of learning rate and adaptability, greatly simplifying hyperparameter search. In light of this observation, we demonstrate that, against conventional wisdom, Adam can also outperform SGD on vision tasks, as long as the coupling between its learning rate and adaptability is taken into account. In practice, AvaGrad matches the best results, as measured by generalization accuracy, delivered by any existing optimizer (SGD or adaptive) across image classification (CIFAR, ImageNet) and character-level language modelling (Penn Treebank) tasks. When training GANs, AvaGrad improves upon existing optimizers. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>
Time perception is not veridical, but, rather, it is susceptible to environmental context, like the intrinsic dynamics of moving stimuli. The direction of motion has been reported to affect time perception such that the movement of objects toward an observer is perceived as longer in duration than that of objects away from the observer. This looming-motion-induced time dilation has been explained in terms of an arousal-based or an attentional mechanism (or a combination of both). The current study was interested in which of these two explanations represents a more viable mechanism. With this aim, we investigated how the looming/receding temporal asymmetry is modulated by the emotional contents of stimuli. In two experiments, participants were shown face images expressing three emotions (angry, happy, and neutral) for one of seven target durations (400-1000ms) and performed a temporal bisection task by judging each presentation duration as “short” or “long”. In Experiment 1, the face images were shown in a constant-sized, stationary position. In Experiment 2, the images were expanding (looming) or contracting (receding) in size. In Experiment 1, we found no influence of facial emotion in perceived duration. In Experiment 2, however, looming stimuli were perceived as longer in duration than receding ones, replicating previous findings of the looming-induced time dilation using naturalistic human-face stimuli. More importantly, in Experiment 2 we found an interaction effect between arousal rating of faces and motion direction: The looming/receding asymmetry was pronounced when the arousal of the presented images was rated low, but this asymmetry diminished when arousal was high. These results suggest that (1) affective characteristics of looming stimuli can modulate temporal processing and more specifically, (2) the looming/receding asymmetry is reduced when arousing facial expressions enhance attentional engagement to receding stimuli, supporting the attentional mechanism of the looming-induced time dilation.
Background: Limited research has investigated whether replacing psychiatric diagnosis with psychological formulation-based approaches has implications for lay attitudes to mental health. The present study investigates experimentally whether presenting psychosis in terms of a schizophrenia diagnosis vs. formulation narrative affects stigma and treatment attitudes in the general public.Method: The study employed a between-groups experimental vignette design, with data collected online. 351 participants (64.1% female, aged 18–66, ) read a vignette about a person experiencing psychosis, defined with either a diagnosis of schizophrenia or a narrative-based formulation. Participants completed a battery of scales measuring their attitudes to the vignette character (social distance, attribution, recommended treatment options, mental help-seeking attitudes).Results: Desired social distance was significantly greater in participants exposed to the diagnostic label of schizophrenia. The schizophrenia label led participants to rate medical care as significantly more helpful relative to the formulation condition but did not affect ratings of specialist or community care or mental help-seeking attitudes.Conclusions: These findings suggest that a psychological formulation approach may slightly lessen stigma-related attitudes, relative to traditional diagnostic systems. Popularisation of formulation models need not compromise general orientations to help-seeking or perceived helpfulness of specialist care but may lead to less medicalised treatment preferences.
OBJECTIVE: To evaluate remote testing as a tool for measuring emotional responses to non-speech sounds. DESIGN: Participants self-reported their hearing status and rated valence and arousal in response to non-speech sounds on an Internet crowdsourcing platform. These ratings were compared to data obtained in a laboratory setting with participants who had confirmed normal or impaired hearing. STUDY SAMPLE: Adults with normal and impaired hearing. RESULTS: In both settings, participants with hearing loss rated pleasant sounds as less pleasant than did their peers with normal hearing. The difference in valence ratings between groups was generally smaller when measured in the remote setting than in the laboratory setting. This difference was the result of participants with normal hearing rating sounds as less extreme (less pleasant, less unpleasant) in the remote setting than did their peers in the laboratory setting, whereas no such difference was noted for participants with hearing loss. Ratings of arousal were similar from participants with normal and impaired hearing; the similarity persisted in both settings. CONCLUSIONS: In both test settings, participants with hearing loss rated pleasant sounds as less pleasant than did their normal hearing counterparts. Future work is warranted to explain the ratings of participants with normal hearing.
OBJECTIVES: Age differences in affective experience across adulthood are widely documented. According to the circumplex model of affect consists of 2 aspects-valence (positive vs negative) and arousal (low activation vs high activation). Prior research on age differences has primarily focused on the valence aspect. However, little is known about age differences in daily affect of high and low arousal. METHOD: The present study examined age differences in daily dynamics (i.e., mean levels, variability, and inertia) of negative affect (NA) and positive affect (PA) of high and low arousal in a sample of 492 adults aged 21-91. Participants completed daily affect ratings for 21 consecutive days. RESULTS: Age was negatively and linearly related to mean levels of both high-arousal and low-arousal NA. Both high-arousal and low-arousal PA mean levels showed increases after middle age. Further, age was related to lower variability in both NA and PA regardless of arousal. Additionally, high-arousal NA inertia showed a linear decrease with age, whereas low-arousal PA inertia showed an inverted-U pattern with age. After controlling for mean levels of affect, the associations between age and affect variability remained significant, whereas the associations between age and affect inertia did not. DISCUSSION: The affective profile of older age is characterized by lower mean levels of NA, higher mean levels of PA, lower affect variability, and less persistence in high-arousal NA and low-arousal PA in daily life. Our results contribute to a nuanced understanding of which affective processes improve with age and which do not.
In this study, the affective explicit and implicit attitudes toward electric and gasoline cars are investigated. One hundred sixty-five participants (103 cisgender women, 62 cisgender men) completed an explicit and implicit affective rating task toward pictures of electric and gasoline cars, measurements of sustainability, future and past behaviors, and mindfulness. The results showed a positive emotional attitude for the electric cars compared with the gasoline cars only for the explicit rating but not for the implicit one. Furthermore, factors that correlated to the attitudes were investigated: explicit ratings in car owners correlated with age, degree, sustainability in general, and the expressed intention to purchase an electric car in the future. Implicit attitudes in car owners correlated with the overall score of mindfulness and the dimension of "non-reactivity." For the non-car owners, explicit attitudes correlated with the expressed intention to purchase an electric car in the future and the mindfulness dimension of "describing". In this group, the implicit attitude correlated negatively with the mindfulness intention of acting with awareness. This indicates that several different factors should be considered in the development of promotion campaigns for the advantage of sustainable mobility behavior.
People use their previous experience to predict present affective events. Since we live in ever-changing environments, affective predictions must generalize from past contexts (from which they are implicitly learned) to new, potentially ambiguous contexts. This study investigated how past (un)certain relationships influence subjective experience following new ambiguous cues, and whether past relationships can be learned implicitly. Two S1-S2 paradigms were employed as learning and test phases in two experiments. S1s were colored circles, S2s negative or neutral affective pictures. Participants (N = 121, 116) were assigned to the certain (CG) or uncertain group (UG), and they were presented with 100% (CG) or 50% (UG) S1-S2 congruency during an uninstructed (Experiment 1) or implicit (Experiment 2) learning phase. During the test phase both groups were presented with a new 75% S1-S2 paradigm, and ambiguous (Experiment 1) or unambiguous (Experiment 2) S1s. Participants were asked to rate the expected valence of upcoming S2s (expectancy ratings), or their experienced valence and arousal (valence and arousal ratings). In Experiment 1 ambiguous cues elicited less negative expectancy ratings, and less unpleasant valence ratings, independently from prior experience. In Experiment 2, participants in the CG reported more negative expectancy ratings after the S1s previously paired with negative stimuli. Overall, we found that in the presence of ambiguous cues subjective affective experience is dampened, and we confirmed that people are able to infer probabilistic relationships from the environment (and to use them later) at an implicit level.
STUDY OBJECTIVES: Sleep plays a pivotal role in the off-line processing of emotional memory. However, much remains unknown for its immediate vs. long-term influences. We employed behavioral and electrophysiological measures to investigate the short- and long-term impacts of sleep vs. sleep deprivation on emotional memory. METHODS: Fifty-nine participants incidentally learned 60 negative and 60 neutral pictures in the evening and were randomly assigned to either sleep or sleep deprivation conditions. We measured memory recognition and subjective affective ratings in 12- and 60-h post-encoding tests, with EEGs in the delayed test. RESULTS: In a 12-h post-encoding test, compared to sleep deprivation, sleep equally preserved both negative and neutral memory, and their affective tones. In the 60-h post-encoding test, negative and neutral memories declined significantly in the sleep group, with attenuated emotional responses to negative memories over time. Furthermore, two groups showed spatial-temporally distinguishable ERPs at the delayed test: while both groups showed the old-new frontal negativity (300-500 ms, FN400), sleep-deprived participants additionally showed an old-new parietal, Late Positive Component effect (600-1000 ms, LPC). Multivariate whole-brain ERPs analyses further suggested that sleep prioritized neural representation of emotion over memory processing, while they were less distinguishable in the sleep deprivation group. CONCLUSIONS: These data suggested that sleep's impact on emotional memory and affective responses is time-dependent: sleep preserved memories and affective tones in the short term, while ameliorating affective tones in the long term. Univariate and multivariate EEG analyses revealed different neurocognitive processing of remote, emotional memories between sleep and sleep deprivation groups.
Recurrent neural networks are efficient ways of training language models, and various RNN networks have been proposed to improve performance. However, with the increase of network scales, the overfitting problem becomes more urgent. In this paper, we propose a framework-G2Basy-to speed up the training process and ease the overfitting problem. Instead of using predefined hyperparameters, we devise a gradient increasing and decreasing technique that changes the parameters training batch size and input dropout simultaneously by a user-defined step size. Together with a pretrained word embedding initialization procedure and the introduction of different optimizers at different learning rates, our framework speeds up the training process dramatically and improves performance compared with a benchmark model of the same scale. For the word embedding initialization, we propose the concept of "artificial features" to describe the characteristics of the obtained word embeddings. We experiment on two of the most often used corpora-the Penn Treebank and WikiText-2 datasets-and both outperform the benchmark results and show potential towards further improvement. Furthermore, our framework shows better results with the larger and more complicated WikiText-2 corpus than with the Penn Treebank. Compared with other state-of-the-art results, we achieve comparable results with network scales hundreds of times smaller and within fewer training epochs.
While some heritage languages enjoy large numbers of speakers and vibrant communities, centuries-old and ongoing sociohistorical and sociolinguistic oppression has resulted in the extreme endangerment of many Indigenous languages. To counter this linguistic and cultural loss, a growing number of communities have engaged in language revitalization efforts that are tied to broader objectives of ethnic reclamation and cultural resistance, aiming not only to maintain but also to strengthen what has been lost. Heritage language revitalization is a long-term project that demands change and engagement across many aspects of community life, work that is ripe with tensions and contradictions. This chapter considers three recurrent questions in heritage language revitalization: what efforts should be prioritized in language revitalization, who should take responsibility in revitalizing a language, and how should revitalization efforts navigate the perceived need to establish linguistic norms and standards while concomitantly supporting linguistic diversity. To date, these questions have been described as tensions or problems that reveal conflicting priorities, often the result of historical inequalities, and that frequently hinder language revitalization efforts. Rather than framing these questions as problems, the present chapter considers how communities have responded to these challenges to create new opportunities for collaboration and new approaches that embrace ambiguity and pluralism.
BACKGROUND: Youth with anxiety disorders struggle with managing emotions relative to peers, but the neural basis of this difference has not been examined. METHODS: = 13.6; range = 8-17) with (n = 37) and without (n = 24) anxiety disorders completed a cognitive reappraisal task while undergoing functional magnetic resonance imaging. Emotional reactivity and regulation, functional activation, and beta-series connectivity were compared across groups. RESULTS: Groups did not differ on emotional reactivity or regulation. However, fronto-limbic activation after viewing aversive imagery with and without regulation, as well as affect ratings without regulation, were higher for anxious youth. Neither group demonstrated age-related changes in regulation, though anxious youth became less reactive with age. Stronger amygdala-ventromedial prefrontal cortex connectivity related to greater anxiety in control youth, but less anxiety in anxious youth. CONCLUSION: Anxious youth regulated when instructed, but regulation ability did not relate to age. Viewing aversive imagery related to heightened fronto-limbic activation even after reappraisal. Emotion dysregulation in youth anxiety disorders may stem from heightened emotionality and potent bottom-up neurobiological responses to aversive stimuli. Findings suggest the importance of treatments focused on both reducing initial emotional reactivity and bolstering regulatory capacity.
Reproduction of knowledge, especially tacit knowledge can be expensive during a pandemic. One of the most common causes is the reduced information accessibility during the translation process. Having the ability to assess the linguistic complexity of any given contents could potentially improve knowledge reproduction. Authors conduct two cross-linguistic studies on the World Health Organization (WHO)'s emergency learning platform to assess the linguistic complexity of two online courses in 10 languages. Morpho-syntactically annotated treebanks, unannotated materials from Wikipedia and language-specific corpora are set as control groups. Preliminary findings reveal a clear reduced complexity of learning contents in the most candidate languages while retaining the maximum amount of information. Creating a baseline study on low-resourced languages on the learning genre could be potentially useful for measuring impact of normative products at country and local level.
Emotion processing abnormalities and sleep pathology are central to the phenomenology of paediatric posttraumatic stress disorder, and sleep disturbance has been linked to the development, maintenance and severity of the disorder. Given emerging evidence indicating a role for sleep in emotional brain function, it has been proposed that dysfunctional processing of emotional experiences during sleep may play a significant role in affective disorders, including posttraumatic stress disorder. Here we sought to examine the relationship between sleep and emotion processing in typically developing youth, and youth with a diagnosis of posttraumatic stress disorder. We use high-density electroencephalogram to compare baseline sleep with sleep following performance on a task designed to assess both memory for and reactivity to negative and neutral imagery in 10 youths with posttraumatic stress disorder, and 10 age- and sex-matched non-traumatized typically developing youths. Subjective ratings of arousal to negative imagery (ΔArousal = post-sleep minus pre-sleep arousal ratings) remain unchanged in youth with posttraumatic stress disorder following sleep (mean increase 0.15, CI -0.28 to +0.58), but decreased in TD youth (mean decrease -1.0, 95% CI -1.44 to -0.58). ΔArousal, or affective habituation, was negatively correlated with global change in slow-wave activity power (ρ = -0.58, p =.008). When considered topographically, the correlation between Δslow-wave activity power and affective habituation was most significant in a frontal cluster of 27 electrodes (Spearman, ρ = -0.51, p =.021). Our results highlight the importance of slow-wave sleep for adaptive emotional processing in youth, and have implications for symptom persistence in paediatric posttraumatic stress disorder. Impairments in slow-wave activity may represent a modifiable risk factor in paediatric posttraumatic stress disorder.
Postpartum Depression (PPD) is the most common non-obstetric complications associated with childbearing, but currently has poor diagnostic regimes. Sensory symptoms of PPD are understudied, particularly with regard to the sense of olfaction. The present study addresses this research gap by assessing differences in olfactory abilities between 39 depressed mothers, who were within the perinatal period (i.e., during pregnancy and up to 1-year post pregnancy) and assessed with Edinburgh Postnatal Depression Scale, and their case-matched healthy volunteers. The assessments include two olfactory testing sessions conducted 4-weeks apart, each comprising a standard odour detection threshold test (i.e., Snap & Sniff Olfactory Test System), and intensity and valence ratings for 3 "pleasant" and 3 "unpleasant" odorants. The results revealed no difference between patients (M = 5.6; SE = 0.3) and control group (M = 5.7; SE = 0.4) in terms of olfactory detection threshold. However, the patients group perceived the 3 "unpleasant" odours as significantly less pleasant (p < 0.05), and 2 odorants (1 "pleasant" and 1 "unpleasant") as less intense. Additionally, these results did not appear to be significantly interacted with the individual's perinatal stage. The present study is the first to evaluate associations between olfactory function and PPD. Findings from the study suggest that, while PPD has little effect on the early stages of olfactory processing, these conditions may have stronger influence on higher-order olfactory perception, including both hedonic and intensity perception. These novel findings add knowledge to sensory symptoms of PPD.
The problems inherent in efforts to create large lexical databases by mapping machine-readable dictionaries onto each other are illustrated through an attempt to merge manually two short entries (whistle and whistler) from two monolingual English collegiate-style dictionaries. In view of the complexities revealed by this operation for the human mind, let alone the machine, we suggest that if lexical databases are to be created by automatic or semi-automatic means, it is essential to design the complete database first, following the demands of the language as identified by theoretical linguistic research, and only then to attempt to map the contents of any machine-readable dictionary into this ‘ideal’ database. We exemplify part of the suggested template lexical entry for verbs of sound, including whistle. 1