The Accuracy of PUMA Questionnaire in Combination With Peak Expiratory Flow Rate to Identify At-risk, Undiagnosed COPD Patients.

INTRODUCTION: The English PUMA questionnaire emerges as an effective COPD case-finding tool. We aimed to use the PUMA questionnaire in combination with peak expiratory flow rate (PEFR) to improve case-finding efficacy in Chinese population. METHODS: This cross-sectional, observational study included two stages: translating English to Chinese PUMA (C-PUMA) questionnaire with linguistic validation and psychometric evaluation, followed by clinical validation. Eligible participants (with age ≥40 years, respiratory symptoms, smoking history ≥10 pack-years) were enrolled and subjected to three questionnaires (C-PUMA, COPD assessment test [CAT], and generic health survey [SF-12V2]), PEFR measurement, and confirmatory spirometry. The C-PUMA score and PEFR were incorporated into a PUMA-PEFR prediction model applying binary logistic regression coefficients to estimate the probability of COPD (PCOPD). RESULTS: C-PUMA was finalized through standard forward-backward translation processes and confirmation of good readability, comprehensibility, and reliability. In clinical validation, 240 participants completed the study. 78/240 (32.5%) were diagnosed with COPD. C-PUMA exhibited significant validity (correlated with CAT or physical component scores of SF-12V2, both P<0.05, respectively). PUMA-PEFR model had higher diagnostic accuracy than C-PUMA alone (area under ROC curve, 0.893 vs. 0.749, P<0.05). The best cutoff values of C-PUMA and PUMA-PEFR model (PCOPD) were ≥6 and ≥0.39, accounting for a sensitivity/specificity/numbers needed to screen of 77%/64%/3 and 79%/88%/2, respectively. C-PUMA ≥5 detected more underdiagnosed patients, up to 11.5% (vs. C-PUMA ≥6). CONCLUSION: C-PUMA is well-validated. The PUMA-PEFR model provides more accurate and cost-effective case-finding efficacy than C-PUMA alone in at-risk, undiagnosed COPD patients. These tools can be useful to detect COPD early.

The effects of family, culture and sex on linguistic development across 20 languages.

Languages vary in their complexity; caregivers vary in the way they structure their communicative interactions with children; and boys and girls can differ in their language skills. Using a multilevel modelling approach, we explored how these factors influence the path of language acquisition for young children growing up around the world (mean age 2-years 9-months; 56 girls). Across 43 different sites, we analysed 103 mother-child pairs who spoke 3,170,633 utterances, 16,209,659 morphemes, divided across 20 different languages: Afrikaans, Catalan, Cantonese, Danish, Dutch, English, Farsi, French, German, Hebrew, Icelandic, Irish, Italian, Japanese, Mandarin, Norwegian, Portuguese, Spanish, Swedish and Turkish. Using mean length of utterance (MLU) as a measure of language complexity and developmental skill, we found that variation in children's MLU was significantly explained by (a) between-language differences; namely the rate of child MLU growth was attuned to the complexity of their mother tongue, and (b) between-mother differences; namely mothers who used higher MLUs tended to have children with higher MLUs, regardless of which language they were learning and especially in the very young (<2.5 years-old). Controlling for family and language environment, we found no evidence of MLU sex differences in child speech nor in the speech addressed to boys and girls. By modelling language as a multilevel structure with cross-cultural variation, we were able to disentangle those factors that make children's pathway to language different and those that make it alike. RESEARCH HIGHLIGHTS: The speech of 103 mother-child pairs from 20 different languages showed large variation in the path of early language development. Language, family, but not the sex of the child, accounted for a significant proportion of individual differences in child speech, especially in the very young. The rate at which children learned language was attuned to the complexity of their mother tongue, with steeper trajectories for more complex language. Results demonstrate the relative influence of culture, family, and sex in shaping the path of language acquisition for different children.

Using language sample analyses across English dialects: A case-based approach for preschoolers.

This study compared language samples from typically developing 4-year-olds who spoke African American English (AAE), Jamaican English (JE), or Mainstream American English (MAE) to assess the value of using language sample analysis (LSA) measures for characterising language use across dialects of English. Specific LSA metrics included mean length of utterance (MLU) in morphemes and in words, the Index of Productive Syntax (IPSyn), Developmental Sentence Scoring (DSS) and measures of lexical diversity. Children demonstrated diverse linguistic patterns across dialects, but a Kruskal-Wallis H test did not reveal significant differences in scores obtained through LSA measures. Notably, the IPSyn captured morphosyntactic structures in each category across dialects where prior research has highlighted limitations. This preliminary study uses a case-based approach to illustrate the applicability of LSAs in describing linguistic variations across children who speak different dialects of English. Moreover, the findings from this study underscore the potential use of LSAs in describing linguistic patterns to support the characterisation of communication profiles for culturally and linguistically diverse children.

Exploring cross-linguistic differences in parental input and their associations with child expressive language in ASD: Bulgarian versus English comparison.

BACKGROUND: Parental input plays a central role in typical language acquisition and development. In autism spectrum disorder (ASD), characterized by social communicative and language difficulties, parental input presents an important avenue for investigation as a target for intervention. A rich body of literature has identified which aspects of grammatical complexity and lexical diversity are most associated with child language ability in both typical development and autism. Yet, the majority of these studies are conducted with English-speaking children, thus potentially overlooking nuances in parental input derived from cross-linguistic variation. AIMS: To examine the differences in verbal parental input to Bulgarian- and English-speaking children with ASD. To examine whether aspects of verbal parental input found to be concurrent predictors of English-speaking children's expressive language ability are also predictors of the expressive language of Bulgarian-speaking children with ASD. METHODS & PROCEDURES: We compared parental input to Bulgarian-speaking (N = 37; 2;7-9;10 years) and English-speaking (N = 37; 1;8-4;9 years) children with ASD matched on expressive language. Parent-child interactions were collected during free play with developmentally appropriate toys. These interactions were transcribed, and key measures of parental input were extracted. OUTCOMES & RESULTS: English-speaking parents produced more word tokens and word types than Bulgarian-speaking parents. However, Bulgarian parents produced more verbs in relation to nouns and used more statements and exclamations but asked fewer questions than English-speaking parents. In addition, child age and parents' use of questions were significant concurrent predictors of child expressive vocabulary. CONCLUSIONS & IMPLICATIONS: This is one of the first studies to conduct a cross-linguistic comparison of parental input in ASD. The differences found emphasize the need to further study parental input to Bulgarian children and adapt naturalistic parent-mediated interventions to the local language and its specific characteristics. WHAT THIS PAPER ADDS: What is already known on the subject A rich body of literature has identified the specific aspects of grammatical complexity, lexical diversity, and question-asking that are concurrently and longitudinally associated with the language ability of children with typical development and of children with ASD. Yet, the majority of these studies are conducted with English-speaking children. What this paper adds to the existing knowledge The present study finds that there are specific differences in verbal parental input to Bulgarian- and English-speaking children with autism in terms of lexical composition and question-asking. Bulgarian parents used more verbs than nouns, and the opposite pattern was found for English-speaking parents. In addition, Bulgarian parents asked fewer questions but used more statements and exclamations. Nevertheless, parental question use was significantly correlated with children's language ability across both groups, suggesting that question-asking should be further examined as a potential target for parent-mediated language interventions for Bulgarian children with autism. What are the potential or actual clinical implications of this work? Most language and social communication interventions for autism are designed and piloted with English-speaking children. These interventions are often simply translated and used in different countries, with different populations and in different contexts. However, considering that one of the defining characteristics of autism is language difficulty, more studies should examine (1) how these language difficulties manifest in languages other than English, and (2) what characterizes verbal parental input in these other contexts. Such research investigations should inform future language and social communication interventions. The present study emphasizes the cross-linguistic differences between Bulgarian- and English-speaking parents' verbal input to their children with autism.

Assessing GPT-4's Performance in Delivering Medical Advice: Comparative Analysis With Human Experts.

Background: Accurate medical advice is paramount in ensuring optimal patient care, and misinformation can lead to misguided decisions with potentially detrimental health outcomes. The emergence of large language models (LLMs) such as OpenAI's GPT-4 has spurred interest in their potential health care applications, particularly in automated medical consultation. Yet, rigorous investigations comparing their performance to human experts remain sparse. Objective: This study aims to compare the medical accuracy of GPT-4 with human experts in providing medical advice using real-world user-generated queries, with a specific focus on cardiology. It also sought to analyze the performance of GPT-4 and human experts in specific question categories, including drug or medication information and preliminary diagnoses. Methods: We collected 251 pairs of cardiology-specific questions from general users and answers from human experts via an internet portal. GPT-4 was tasked with generating responses to the same questions. Three independent cardiologists (SL, JHK, and JJC) evaluated the answers provided by both human experts and GPT-4. Using a computer interface, each evaluator compared the pairs and determined which answer was superior, and they quantitatively measured the clarity and complexity of the questions as well as the accuracy and appropriateness of the responses, applying a 3-tiered grading scale (low, medium, and high). Furthermore, a linguistic analysis was conducted to compare the length and vocabulary diversity of the responses using word count and type-token ratio. Results: GPT-4 and human experts displayed comparable efficacy in medical accuracy ("GPT-4 is better" at 132/251, 52.6% vs "Human expert is better" at 119/251, 47.4%). In accuracy level categorization, humans had more high-accuracy responses than GPT-4 (50/237, 21.1% vs 30/238, 12.6%) but also a greater proportion of low-accuracy responses (11/237, 4.6% vs 1/238, 0.4%; P=.001). GPT-4 responses were generally longer and used a less diverse vocabulary than those of human experts, potentially enhancing their comprehensibility for general users (sentence count: mean 10.9, SD 4.2 vs mean 5.9, SD 3.7; P<.001; type-token ratio: mean 0.69, SD 0.07 vs mean 0.79, SD 0.09; P<.001). Nevertheless, human experts outperformed GPT-4 in specific question categories, notably those related to drug or medication information and preliminary diagnoses. These findings highlight the limitations of GPT-4 in providing advice based on clinical experience. Conclusions: GPT-4 has shown promising potential in automated medical consultation, with comparable medical accuracy to human experts. However, challenges remain particularly in the realm of nuanced clinical judgment. Future improvements in LLMs may require the integration of specific clinical reasoning pathways and regulatory oversight for safe use. Further research is needed to understand the full potential of LLMs across various medical specialties and conditions.

Optimizing bioremediation techniques for soil decontamination in a linguistic intuitionistic fuzzy framework.

Bioremediation techniques, which harness the metabolic activities of microorganisms, offer sustainable and environmentally friendly approaches to contaminated soil remediation. These methods involve the introduction of specialized microbial consortiums to facilitate the degradation of pollutants, contribute to soil restoration, and mitigate environmental hazards. When selecting the most effective bioremediation technique for soil decontamination, precise and dependable decision-making methods are critical. This research endeavors to tackle the aforementioned concern by utilizing the tool of aggregation operators in the framework of the Linguistic Intuitionistic Fuzzy (LIF) environment. Linguistic Intuitionistic Fuzzy Sets (LIFSs) provide a robust framework for representing and managing uncertainties associated with linguistic expressions and intuitionistic assessments. Aggregation operators enrich the decision-making process by efficiently handling the intrinsic uncertainties, preferences, and priorities of MADM problems; as a consequence, the decisions produced are more reliable and precise. In this research, we utilize this concept to devise innovative aggregation operators, namely the linguistic intuitionistic fuzzy Dombi weighted averaging operator (LIFDWA) and the linguistic intuitionistic fuzzy Dombi weighted geometric operator (LIFDWG). We also demonstrate the critical structural properties of these operators. Additionally, we formulate novel score and accuracy functions for multiple attribute decision-making (MADM) problems within LIF knowledge. Furthermore, we develop an algorithm to confront the complexities associated with ambiguous data in solving decision-making problems in the LIF Dombi aggregation environment. To underscore the efficacy and superiority of our proposed methodologies, we adeptly apply these techniques to address the MADM problem concerning the optimal selection of a bioremediation technique for soil decontamination. Moreover, we present a comparative evaluation to delineate the authenticity and practical applicability of the recently introduced approaches relative to previously formulated techniques.

An approach designed to fail deaf children and their parents and how to change it.

The matter of raising and educating deaf children has been caught up in percepts of development that are persistently inaccurate and at odds with scientific research. These percepts have negatively impacted the health and quality of life of deaf children and deaf people in general. The all too prevalent advice is to raise the child strictly orally and wait to see what happens. Only when the child is seriously behind is a completely accessible language - a sign language - introduced, and that is far too late for protecting cognitive health. The medical profession, along with others, needs to offer parents better advice and better supports so that neither the children nor their parents wait and watch as the oral-only method fails. All must take responsible action to assure an approach that succeeds.

Association of Language Preference with Therapeutic Care for Hospitalized COVID-19 Patients.

INTRODUCTION: There is a paucity of research investigating disparities in utilization of inpatient therapeutics for COVID-19 by language preference. The primary aim of this study was to assess if the likelihood of treatment with novel COVID-19 therapies differed for patients using a language other than English (LOE) relative to English-speaking patients. METHODS: This was a retrospective observational cohort study of COVID-19 patients hospitalized between March 1, 2020, and June 30, 2022, across 11 hospitals within a single not-for-profit health system. Multivariable relative risks were estimated for the impact of preferred language on the receipt of novel COVID-19 therapies: baricitinib, remdesivir, tocilizumab, and convalescent plasma. RESULTS: This study included 12,510 hospitalized adults with English as the most common preferred language (92.3%) followed by Spanish (3.1%), Somali (1.3%), Russian (0.9%), and Hmong (0.6%). Spanish speakers were more likely to receive any of the novel COVID-19 therapies compared to English speakers (RR 1.45; CI 1.32-1.59). Estimates for Hmong, Somali, Russian, and Other language groups were not statistically significant and closer to the null (aRR range, 0.89-1.12). CONCLUSION: Linguistic patterns in health outcomes expose inherent heterogeneity within racial and ethnic groups. Our study found that Spanish speakers were nearly 1.5 times more likely to receive any of the four novel inpatient COVID-19 therapeutics in comparison to English speakers. Future research is needed to explore the reasons for the heterogeneous findings including temporal influence, cultural factors, informed consent comprehension, and therapeutic hesitancy in all groups.

News Media Framing of Suicide Circumstances and Gender: Mixed Methods Analysis.

BACKGROUND: Suicide is a leading cause of death worldwide. Journalistic reporting guidelines were created to curb the impact of unsafe reporting; however, how suicide is framed in news reports may differ by important characteristics such as the circumstances and the decedent's gender. OBJECTIVE: This study aimed to examine the degree to which news media reports of suicides are framed using stigmatized or glorified language and differences in such framing by gender and circumstance of suicide. METHODS: We analyzed 200 news articles regarding suicides and applied the validated Stigma of Suicide Scale to identify stigmatized and glorified language. We assessed linguistic similarity with 2 widely used metrics, cosine similarity and mutual information scores, using a machine learning-based large language model. RESULTS: News reports of male suicides were framed more similarly to stigmatizing (P<.001) and glorifying (P=.005) language than reports of female suicides. Considering the circumstances of suicide, mutual information scores indicated that differences in the use of stigmatizing or glorifying language by gender were most pronounced for articles attributing legal (0.155), relationship (0.268), or mental health problems (0.251) as the cause. CONCLUSIONS: Linguistic differences, by gender, in stigmatizing or glorifying language when reporting suicide may exacerbate suicide disparities.

ArzEn-MultiGenre: An aligned parallel dataset of Egyptian Arabic song lyrics, novels, and subtitles, with English translations.

ArzEn-MultiGenre is a parallel dataset of Egyptian Arabic song lyrics, novels, and TV show subtitles that are manually translated and aligned with their English counterparts. The dataset contains 25,557 segment pairs that can be used to benchmark new machine translation models, fine-tune large language models in few-shot settings, and adapt commercial machine translation applications such as Google Translate. Additionally, the dataset is a valuable resource for research in various disciplines, including translation studies, cross-linguistic analysis, and lexical semantics. The dataset can also serve pedagogical purposes by training translation students and aid professional translators as a translation memory. The contributions are twofold: first, the dataset features textual genres not found in existing parallel Egyptian Arabic and English datasets, and second, it is a gold-standard dataset that has been translated and aligned by human experts.

Linguistic isolation correlates with length of stay and mortality for pediatric oncology patients in California.

OBJECTIVE: To evaluate social drivers of health and how they impact pediatric oncology patients' clinical outcomes during pediatric intensive care unit (PICU) admission via correlation with patient ZIP codes. METHODS: Demographic, clinical, and outcome variables from Virtual Pediatric Systems®, LLC for oncology patients (2009-2021) in California PICUs (excluding postoperative) using 3-digit ZIP Codes with social drivers of health variables linguistic isolation, poverty, race/ethnicity, and education abstracted from American Community Survey data for 3-digit ZIP Codes using the Environmental Protection Agency's EJScreen tool. Outcomes of length of stay (LOS), mortality, acuity scores, were compared with social variables. RESULTS: Positive correlation between mortality and minority racial groups (Hispanic/Latino) across ZIP Codes (correlation coefficients of 0.45 (95% CI: 0.22-0.64, p < 0.001) in 2017, 0.50 (95% CI: 0.27-0.68, p < 0.001) in 2018, 0.33 (95% CI: 0.07-0.54, p = 0.013) in 2020, and 0.32 (95% CI: 0.06-0.53, p = 0.018) in 2021). Median PICU length of stay significantly correlated with linguistic isolation (coefficient of 0.42 (95% CI: 0.18-0.61, p = 0.001) in 2021 versus -0.41 (95% CI: -0.61 to -0.16, p = 0.002) in 2019), which included PRISMIII (n = 7417). Mixed effects logistic regression model for other constant variables (PRISMIII, cancer type, race/ethnicity, year), random effect of patient, linguistic isolation (percentage as a continuous value) was significantly associated (95% CI: 1.01-1.06; p = 0.02) with mortality; (OR = 1.03). CONCLUSIONS: Linguistic isolation was correlated with LOS and mortality, however variable year to year.

Growth language mindset and willingness to communicate: Contributions of linguistic risk taking and learning experience.

As various contextual and individual difference factors determine how and when mindsets may influence learning outcomes, burgeoning L2 research has recently addressed the role of growth language mindset (GLM) in different learning outcomes such as L2 Willingness to Communicate (WTC). Since little is known about the underlying mechanism through which GLM may contribute to WTC, a highly desirable goal of L2 education and an important criterion for assessing its efficiency and success, the present study addresses this gap by investigating the possible mediating and moderating roles of linguistic risk taking and L2 learning experience, respectively. The participants were 392 Iranian L2 students chosen by multi-stage cluster sampling. Findings showed that GLM predicted WTC directly and positively, and their association was mediated and moderated by linguistic risk taking (an important affective factor) and L2 learning experience (an essential motivational factor), respectively. Suggestions for future studies and implications for promoting learners' GLM, linguistic risk taking, and L2 learning experience are presented.

Parental linguistic content and distancing predict beliefs about emotion and child emotion regulation.

ABSTRACTEmploying a constructionist framework of emotion, this study examines whether parental language during emotion belief discussions predicts parents' self-reported beliefs about emotion and child emotion regulation (ER). 102 parents of children ages 8 through 12 participated in focus groups about emotion beliefs, and nine months later, completed questionnaires on their emotion beliefs and child ER. Focus group content was analyzed for positive and negative emotion talk, cognitive process talk, and an established linguistic marker of psychological distancing. Parents' positive emotion talk and parental linguistic distancing when discussing their child's (but not their own) emotion experiences positively predicted beliefs about children's emotional capabilities. Finally, negative emotion talk negatively predicted parental beliefs about children's capacity to control their own emotions and the value of anger expression as well as child ER. Current findings contribute to our understanding of how parental communication patterns about emotions may influence emotion beliefs and child emotion development.

Translation and linguistic validation of 24 PROMIS item banks into French.

PURPOSE: The Patient-Reported Outcome Measurement Information System (PROMIS®) was developed to provide reliable, valid, and normed item banks to measure health. The item banks provide standardized scores on a common metric allowing for individualized, brief assessment (computerized adaptive tests), short forms (e.g. heart failure specific), or profile assessments (e.g. PROMIS-29). The objective of this study was to translate and linguistically validate 24 PROMIS adult item banks into French and highlight cultural nuances arising during the translation process. METHODS: We used the FACIT translation methodology. Forward translation into French by two native French-speaking translators was followed by reconciliation by a third native French-speaking translator. A native English-speaking translator fluent in French then completed a back translation of the reconciled version from French into English. Three independent reviews by bilingual translators were completed to assess the clarity and consistency of terminology and equivalency across the English source and French translations. Reconciled versions were evaluated in cognitive interviews for conceptual and linguistic equivalence. RESULTS: Twenty-four adult item banks were translated: 12 mental health, 10 physical health, and two social health. Interview data revealed that 577 items of the 590 items translated required no revisions. Conceptual and linguistic differences were evident for 11 items that required iterations to improve conceptual equivalence and two items were revised to accurately reflect the English source. CONCLUSION: French translations of 24 item banks were created for routine clinical use and research. Initial translation supported conceptual equivalence and comprehensibility. Next steps will include validation of the item banks.

An App-Based Physical Activity Intervention in Community-Dwelling Chinese-, Tagalog-, and Vietnamese-Speaking Americans: Single-Arm Intervention Study.

BACKGROUND: Physical inactivity is associated with adverse health outcomes among Asian Americans, who exhibit the least adherence to physical activity guidelines compared with other racial and ethnic groups. Mobile app-based interventions are a promising approach to promote healthy behaviors. However, there is a lack of app-based interventions focused on improving physical activity among Asian Americans whose primary language is not English. OBJECTIVE: This pilot study aimed to assess the feasibility and acceptability of a 5-week intervention using a culturally and linguistically adapted, evidence-based mobile phone app with an accelerometer program, to promote physical activity among Chinese-, Tagalog-, or Vietnamese-speaking Americans. METHODS: Participants were recruited through collaborations with community-based organizations. The intervention was adapted from a 12-month physical activity randomized controlled trial involving the app and accelerometer for English-speaking adults. Sociodemographic characteristics, lifestyle factors, and physical measurements were collected at the baseline visit. A 7-day run-in period was conducted to screen for the participants who could wear a Fitbit One (Fitbit LLC) accelerometer and complete the app's daily step diary. During the 4-week intervention period, participants wore the accelerometer and reported their daily steps in the app. Participants also received daily messages to reinforce key contents taught during an in-person educational session, remind them to input steps, and provide tailored feedback. Feasibility measures were the percentage of eligible participants completing the run-in period and the percentage of participants who used the app diary for at least 5 out of 7 days during the intervention period. We conducted poststudy participant interviews to explore overall intervention acceptability. RESULTS: A total of 19 participants were enrolled at the beginning of the study with a mean age of 47 (SD 13.3; range 29-70) years, and 58% (n=11) of them were female. Of the participants, 26% (n=5) were Chinese, 32% (n=6) were Vietnamese, and 42% (n=8) were Filipino. All participants met the run-in criteria to proceed with the intervention. Adherence to the app diary ranged from 74% (n=14) in week 2 to 95% (n=18) in week 4. The daily average steps per week from accelerometers increased each week from 8451 (SD 3378) steps during the run-in period to 10,930 (SD 4213) steps in week 4. Participants reported positive experiences including an increased motivation to walk and the enjoyment of being able to monitor their physical activity. CONCLUSIONS: This is the first pilot study of a multicomponent intervention and evidence-based mobile phone app to promote physical activity among Asian Americans who use apps in traditional Chinese, Tagalog, or Vietnamese, which demonstrated high feasibility and acceptability. Future work focused on multilingual mobile apps to address disparities in physical inactivity among Asian Americans should be considered.

Towards AI-Driven Healthcare: Systematic Optimization, Linguistic Analysis, and Clinicians' Evaluation of Large Language Models for Smoking Cessation Interventions.

Creating intervention messages for smoking cessation is a labor-intensive process. Advances in Large Language Models (LLMs) offer a promising alternative for automated message generation. Two critical questions remain: 1) How to optimize LLMs to mimic human expert writing, and 2) Do LLM-generated messages meet clinical standards? We systematically examined the message generation and evaluation processes through three studies investigating prompt engineering (Study 1), decoding optimization (Study 2), and expert review (Study 3). We employed computational linguistic analysis in LLM assessment and established a comprehensive evaluation framework, incorporating automated metrics, linguistic attributes, and expert evaluations. Certified tobacco treatment specialists assessed the quality, accuracy, credibility, and persuasiveness of LLM-generated messages, using expert-written messages as the benchmark. Results indicate that larger LLMs, including ChatGPT, OPT-13B, and OPT-30B, can effectively emulate expert writing to generate well-written, accurate, and persuasive messages, thereby demonstrating the capability of LLMs in augmenting clinical practices of smoking cessation interventions.

Cognitive vs. Linguistic Training in Children with Developmental Language Disorder: Exploring Their Effectiveness on Verbal Short-Term Memory and Verbal Working Memory.

The present study explores comparatively the effectiveness of a cognitive (verbal short-term memory (vSTM), verbal working memory (vWM)) and of a linguistic training (10-week duration each) in the diffusion of gains in cognitive abilities (vSTM and vWM) of in school-aged Greek-speaking children with developmental language disorder (DLD). To this purpose, two computerized training programs i.e., a linguistic and a cognitive one, were developed and applied to three groups (A, B, and C) of children with DLD (N = 49, in total). There were three assessments with two vSTM tasks (non-word repetition and forward digit span) and a vWM task (backward digit span): pre-therapeutically (time 1), where no significant between-group differences were found, post-therapeutically I (time 2), and post-therapeutically II (time 3) and two training phases. In phase Ι, group A received meta-syntactic training, whereas group B vSTM/vWM training and group C received no training. In phase ΙΙ, a reversal of treatment was performed for groups A and B: group A received vSTM/vWM while group B meta-syntactic training. Again, group C received no training. Overall, the results indicated a significant performance improvement for the treatment groups and revealed beneficial far-transfer effects as language therapy can affect vSTM and vWM in addition to direct and near transfer effects. In addition, the intervention type order affected performance as follows: first, better performance on the vSTM task (non-word repetition) was shown when the linguistic treatment was delivered first; second, better performance on the vWM in Time 2 and Time 3 was shown by group B, for which the cognitive treatment was delivered first. Concluding, not only intervention type but also intervention type order can affect performance in DLD.

The consistent fuzzy suitability assessment of forest land resources with multi-source heterogeneous data.

In view of the suitability assessment of forest land resources, a consistent fuzzy assessment method with heterogeneous information is proposed. Firstly, some formulas for transforming large-scale real data and interval data into fuzzy numbers are provided. To derive the unified representation of multi-granularity linguistic assessment information, a fuzzy quantitative transformation for multi-granularity uncertain linguistic information is proposed. The proofs of the desirable properties and some normalized formulas for the trapezoidal fuzzy numbers are presented simultaneously. Next, the objective weight of each assessment indicator is further determined by calculating the Jaccard-Cosine similarity between the trapezoidal fuzzy numbers. Moreover, the trapezoidal fuzzy numbers corresponding to the comprehensive assessment values of each alternative are obtained. The alternatives are effectively ranked according to the distance from the centroid of the trapezoidal fuzzy number to the origin. Finally, based on the proposed consistent fuzzy assessment method, the suitability assessment of forest land resources is achieved under a multi-source heterogeneous data setting.

Native language advantage in electrical brain responses to speech sound changes in passive and active listening condition.

It is not clear whether the brain can detect changes in native and non-native speech sounds in both unattended and attended conditions, but this information would be important to understand the nature of potential native language advantage in speech perception. We recorded event-related potentials (ERPs) for changes in duration and in Chinese lexical tone in a repeated vowel /a/ in native speakers of Finnish and Chinese in passive and active listening conditions. ERP amplitudes reflecting deviance detection (mismatch negativity; MMN and N2b) and attentional shifts towards changes in speech sounds (P3a and P3b) were investigated. In the passive listening condition, duration changes elicited increased amplitude in the MMN latency window for both standard and deviant sounds in the Finnish speakers compared to the Chinese speakers, but no group differences were observed for P3a. In passive listening to lexical tones, P3a was increased in amplitude for both standard and deviant stimuli in Chinese speakers compared to Finnish speakers, but the groups did not differ in MMN. In active listening, both tone and duration changes elicited N2b and P3b, but the groups differed only in pattern of results for the deviant type. The results thus suggest an overall increased sensitivity to native speech sounds, especially in passive listening, while the mechanisms of change detection and attentional shifting seem to work well for both native and non-native speech sounds in the attentive mode.

Multiple evolutionary pressures shape identical consonant avoidance in the world's languages.

Languages disfavor word forms containing sequences of similar or identical consonants, due to the biomechanical and cognitive difficulties posed by patterns of this sort. However, the specific evolutionary processes responsible for this phenomenon are not fully understood. Words containing sequences of identical consonants may be more likely to arise than those without; processes of word form mutation may be more likely to remove than create sequences of identical consonants in word forms; finally, words containing identical consonants may die out more frequently than those without. Phylogenetic analyses of the evolution of homologous word forms indicate that words with identical consonants arise less frequently than those without. However, words with identical consonants do not die out more frequently than those without. Further analyses reveal that forms with identical consonants are replaced in basic meaning functions more frequently than words without. Taken together, results suggest that the underrepresentation of sequences of identical consonants is overwhelmingly a by-product of constraints on word form coinage, though processes related to word usage also serve to ensure that such patterns are infrequent in more salient vocabulary items. These findings clarify aspects of processes of lexical evolution and competition that take place during language change, optimizing communicative systems.