Search Results (60)

Background/Objectives: Children with Autism Spectrum Disorder (ASD) often display heightened sensitivity to simple auditory stimuli, but have difficulty discriminating and integrating multiple phonological features (segmental: consonants and vowels; suprasegmental: lexical tones) at the syllable level, which negatively impacts their communication. This study aims to investigate the neural basis of segmental, suprasegmental and combinatorial speech processing challenges in Mandarin-speaking children with ASD compared with typically developing (TD) peers. Methods: Thirty children with ASD and thirty TD peers will complete a multi-feature oddball paradigm to elicit auditory ERP during passive listening. Stimuli include syllables with single (e.g., vowel only), dual (e.g., vowel + tone), and triple (consonant + vowel + tone) phonological deviations. Neural responses will be analyzed using temporal principal component analysis (t-PCA) to isolate overlapping ERP components (early/late MMN), and representational similarity analysis (RSA) to assess group differences in neural representational structure across feature conditions. Expected Outcomes: We adopt a dual-framework approach to hypothesis generation. First, from a theory-driven perspective, we integrate three complementary models, Enhanced Perceptual Functioning (EPF), Weak Central Coherence (WCC), and the Neural Complexity Hypothesis (NCH), to account for auditory processing in ASD. Specifically, we hypothesize that ASD children will show enhanced or intact neural discriminatory responses to isolated segmental deviations (e.g., vowel), but attenuated or delayed responses to suprasegmental (e.g., tone) and multi-feature deviants, with the most severe disruptions occurring in complex, multi-feature conditions. Second, from an empirically grounded, data-driven perspective, we derive our central hypothesis directly from the mismatch negativity (MMN) literature, which suggests reduced MMN amplitudes (with the exception of vowel deviants) and prolonged latencies accompanied by a diminished left-hemisphere advantage across all speech feature types in ASD, with the most pronounced effects in complex, multi-feature conditions. Significance: By testing alternative hypotheses and predictions, this exploratory study will clarify the extent to which speech processing differences in ASD reflect cognitive biases (local vs. global, per EPF/WCC/NCH) versus speech-specific neurophysiological disruptions. Findings will advance our understanding of the sensory and integrative mechanisms underlying communication difficulties in ASD, particularly in tonal language contexts, and may inform the development of linguistically tailored interventions. Full article

Background: Older adults often struggle to comprehend speech in noisy environments, a challenge influenced by declines in both auditory processing and cognitive functions. This study aimed to investigate how differences in speech-in-noise perception among individual with clinically normal hearing thresholds (ranging from normal to mild hearing loss in older adults) are related to neural speech tracking and cognitive function, particularly working memory. Method: Specifically, we examined delta (1–4 Hz) and theta (4–8 Hz) EEG oscillations during speech recognition tasks to determine their association with cognitive performance in older adults. EEG data were collected from 23 young adults (20–35 years) and 23 older adults (65–80 years). Cognitive assessments were administered to older adults, and both groups completed an EEG task involving speech recognition in Speech-Shaped Noise (SSN) at individualized noise levels based on their Sentence Recognition Scores (SRS). Results: The results showed that age significantly impacted hit rates and reaction times in noisy speech recognition tasks. Theta-band neural tracking was notably stronger in older adults, while delta-band tracking showed no age-related difference. Pearson’s correlations indicated significant associations between age-related cognitive decline, reduced hearing sensitivity, and Mini-Mental State Examination (MMSE) scores. Regression analyses showed that theta-band neural tracking at specific SRS levels significantly predicted word list recognition in the higher SRT group, while constructional recall was strongly predicted in the lower SRT group. Conclusions: These findings suggest that older adults may rely on theta-band neural tracking as a compensatory mechanism. However, regression results alone were not sufficient to fully explain how working memory affects neural tracking, and additional cognitive and linguistic factors should be considered in future studies. Furthermore, cognitive assessments were administered only to older adults, which limits the ability to determine whether group differences are driven by age, hearing, or cognitive status—a major limitation that should be addressed in future research. Full article

In an increasingly interconnected world, educational systems must meet the needs of diverse learners from varying cultural, linguistic, and socioeconomic backgrounds. This study aims to explore the principles and practices of designing inclusive digital learning environments tailored to global classrooms, where diversity in language, learning styles, accessibility, and technological resources presents unique challenges and opportunities. This study also explores how leveraging digital tools, artificial intelligence, and adaptive learning technologies can create environments that are responsive to individual learners’ needs and sensitive to cultural nuances. Research on inclusive instructional design was compiled, highlighting methods such as localized content adaptation, multi-language support, and flexible learning pathways. Furthermore, the role of collaborative learning platforms was assessed to foster a sense of community across geographic and cultural boundaries. Case studies were conducted from diverse educational perspectives to propose effective strategies for inclusive digital design, highlighting successful approaches and areas for improvement. Ultimately, a roadmap was constructed for educators, designers, and policymakers to create accessible and culturally aware digital learning spaces to support the academic and social development of all learners, regardless of their background. The results of this study underscore the importance of inclusivity in digital education, contributing to a more equitable and connected global learning landscape. Full article

Of the few studies that have investigated the linguistic development of heritage speakers (HSs) in the study abroad (SA) context, none have utilized on-line experiments, in spite of these tasks’ clear methodological benefits. In this study, therefore, we test HSs’ on-line sensitivity to lexically selected mood morphology in Spanish. Ten adult HSs completed a self-paced reading task at the beginning and end of a fifteen-week-long SA program in Spain. The task assessed both (a) whether HSs were sensitive to mood incongruencies (e.g., by slowing down after ungrammatical verbs) and (b) whether that (in)sensitivity was different with regular vs. irregular verbs. It was hypothesized that participants would be more sensitive to mood with irregular verbs and that their mood sensitivity would increase over the course of the semester abroad, but these hypotheses were only partially supported. Although HSs developed sensitivity to mood incongruencies with regular verbs over the course of the semester abroad, they showed the reverse pattern with irregular verbs, demonstrating sensitivity at Session 1 but not Session 2. Nonetheless, because participants’ reading times decreased sharply over the semester—and without any concomitant decrease in comprehension accuracy—we argue that SA immersion likely does facilitate morphosyntactic processing in the HL. Full article

Large-language-model (LLM) APIs demonstrate impressive reasoning capabilities, but their size, cost, and closed weights limit the deployment of knowledge-aware AI within biomedical research groups. At the other extreme, standard attention-based neural language models (SANLMs)—including encoder–decoder architectures such as Transformers, Gated Recurrent Units (GRUs), and Long Short-Term Memory (LSTM) networks—are computationally inexpensive. However, their capacity for semantic reasoning in noisy, open-vocabulary knowledge bases (KBs) remains unquantified. Therefore, we investigate whether compact SANLMs can (i) reason over hybrid OpenIE-derived KBs that integrate commonsense, general-purpose, and non-communicable-disease (NCD) literature; (ii) operate effectively on commodity GPUs; and (iii) exhibit semantic coherence as assessed through manual linguistic inspection. To this end, we constructed four training KBs by integrating ConceptNet (600k triples), a 39k-triple general-purpose OpenIE set, and an 18.6k-triple OpenNCDKB extracted from 1200 PubMed abstracts. Encoder–decoder GRU, LSTM, and Transformer models (1–2 blocks) were trained to predict the object phrase given the subject + predicate. Beyond token-level cross-entropy, we introduced the Meaning-based Selectional-Preference Test (MSPT): for each withheld triple, we masked the object, generated a candidate, and measured its surplus cosine similarity over a random baseline using word embeddings, with significance assessed via a one-sided t-test. Hyperparameter sensitivity (311 GRU/168 LSTM runs) was analyzed, and qualitative frame–role diagnostics completed the evaluation. Our results showed that all SANLMs learned effectively from the point of view of the cross entropy loss. In addition, our MSPT provided meaningful semantic insights: for the GRUs (256-dim, 2048-unit, 1-layer): mean similarity $\left({\mu }_{sts}\right)$ of 0.641 to the ground truth vs. 0.542 to the random baseline (gap 12.1%; $p<{10}^{-180}$). For the 1-block Transformer: ${\mu }_{sts}=0.551$ vs. $0.511$ (gap 4%; $p<{10}^{-25}$). While Transformers minimized loss and accuracy variance, GRUs captured finer selectional preferences. Both architectures trained within <24 GB GPU VRAM and produced linguistically acceptable, albeit over-generalized, biomedical assertions. Due to their observed performance, LSTM results were designated as baseline models for comparison. Therefore, properly tuned SANLMs can achieve statistically robust semantic reasoning over noisy, domain-specific KBs without reliance on massive LLMs. Their interpretability, minimal hardware footprint, and open weights promote equitable AI research, opening new avenues for automated NCD knowledge synthesis, surveillance, and decision support. Full article

Recognising linguistic diversity as a person’s characteristic is arguably central to their multilingual identity and is important as an equity issue. Different indicators suggest that students with migrant backgrounds, whose linguistic diversity is often not reflected in European education systems, tend to underperform compared to their peers without migrant backgrounds. There is a dire need, therefore, to alleviate the educational inequalities that negatively affect some of the most plurilingual students in European school systems. This can be carried out by revisiting assessment tools. Developing assessments to make children’s full linguistic and cultural repertoire visible, and what they can do with it, is one way that potential inequalities in school systems and assessment practices can be addressed so that cultural and linguistic responsiveness of assessments and practices can be improved. This paper explores the concept of discontinuities or mismatches between the assessment of plurilingual children’s linguistic practices in one primary school in Catalonia and their actual linguistic realities, including heritage languages. It asks: (1) What are the children’s linguistic profiles? (2) What mismatches and/or educational inequalities do they experience? and (3) How does the co-creation and use of a rubric assessing plurilingual and intercultural competence attempt to mitigate these mismatches and inequalities? Mismatches are identified using a context- and participant-relevant reflection tool, based on 18 reflective questions related to aspects of social justice. Results highlight that mismatches exist between children’s plurilingual and intercultural knowledge and skills compared to the school, education system, curriculum, and wider regional and European policy. These mismatches highlight two plurilingual visions for language education. The paper highlights how language assessment tools and practices can be made more culturally and linguistically fair for plurilingual children with migration backgrounds. Full article

Objectives: The cultural and linguistic adaptation of the Boston Carpal Tunnel Questionnaire (BCTQ) to Polish and the assessment of its psychometric properties among patients undergoing extracorporeal shock wave therapy (ESWT). Methods: This was a cross-sectional study with repeated measures during retest examinations. Subjects from an outpatient rehabilitation center in Poland (n = 103) with mild to moderate carpal tunnel syndrome (CTS) were evaluated three times. Test 1 and test 3 (after a series of four treatments using EWST) included the following: completing the BCTQ, QuickDASH, and SF-36 questionnaires, the VAS pain scale, performing the Tinel–Hoffmann and Phalen tests, and an assessment of grip strength. Test 2 (test–retest BCTQ) was performed two to seven days after test 1. Results: The Polish version of the BCTQ demonstrated a high internal consistency, with a Cronbach’s alpha of 0.861 for the Symptom Severity Scale (SSS) and 0.924 for the Functional Status Scale (FSS). It also showed excellent test–retest reliability, with Intraclass Correlation Coefficients (ICCs) of 0.941 for the SSS and 0.925 for the FSS. The Standard Error of Measurement (SEM) was 0.16 for the SSS and 0.21 for the FSS, while the Minimal Detectable Change (MDC) was 0.43 and 0.59, respectively. It has a high construct validity as 80% of the a priori adopted hypotheses were confirmed. The mean decrease after ESWT on the SSS was 1.04 points, and on the FSS was 0.77 points. The ES value for the SSS scale was 1.62 and for FSS 0.99, and the SRM was 1.35 for the SSS, and 1.01 for the FSS, which proves a higher sensitivity to changes in the BCTQ-PL. Conclusions: The BCTQ-PL is a valid and reliable tool for assessing CTS-related symptoms and functional status in Polish-speaking patients. Full article

Natural disasters and emergencies continue to increase in frequency and severity worldwide, necessitating robust emergency management (EM) systems and evaluation methodologies. This study addresses critical gaps in current emergency response capacity (ERC) evaluation frameworks by developing a comprehensive quantitative decision-making model to assess ERC more effectively. This research constructs a systematic ERC assessment framework based on the four phases of the disaster management cycle (DMC): prevention, preparedness, response, and recovery. The methodology employs multi-criteria decision analysis to evaluate ERC using three distinct information representation environments: intuitionistic fuzzy (IF) sets, linguistic variables (LV), and a novel mixed IF-LV environment. For each environment, we derive appropriate aggregation operators, weight determination methods, and information fusion mechanisms. The proposed model was empirically validated through a case application to emergency plan selection in Shenzhen, China. A statistical analysis of results demonstrates high consistency across all three decision environments (IF, LV, and mixed IF-LV), confirming the model’s robustness and reliability. A sensitivity analysis of key parameters further validates the model’s stability. Results indicate that the proposed decision-making approach provides significant value for EM by enabling more objective, comprehensive, and flexible ERC assessment. The indicator system and evaluation methodology offer decision-makers (DMs) tools to quantitatively analyze ERC using various information expressions, accommodating both subjective judgments and objective metrics. This framework represents an important advancement in emergency preparedness assessment, supporting more informed decision-making in emergency planning and response capabilities. Full article

To address the challenges of assessing information security risks in smart energy systems, this study proposes a multi-attribute decision support method based on interval type-2 fuzzy numbers (IT2TrFN). First, expert questionnaires were designed to gather insights from eight specialists in the fields of smart energy and safety engineering. Linguistic terms associated with IT2TrFN were employed to evaluate indicators, converting expert judgments into fuzzy numerical values while ensuring data reliability through consistency measurements. Subsequently, a decision hierarchy structure and an expert weight allocation model were developed. By utilizing the score and accuracy functions of IT2TrFN, the study determined positive and negative ideal solutions to rank and prioritize the evaluation criteria. Key influencing factors identified include the rate of excessive initial investment, regulatory stringency, information security standards, environmental pollution pressure, and incident response timeliness. The overall risk index was calculated as 0.5839, indicating a moderate level of information security risk in the evaluated region. To validate the robustness of the model, sensitivity analyses were conducted by varying IT2FWA (Weighted aggregated operator) and IT2FGA (Weighted geometric operator) operator selections and adjusting weight coefficients. The results reveal that key indicators exhibit high risk under different scenarios. This method provides an innovative tool for the scientific evaluation of information security risks in smart energy systems, laying a solid theoretical foundation for broader regional applications and the expansion of assessment criteria. Full article

Background/Objectives: The “Palliative Care and Rapid Emergency Screening Tool” (P-CaRES) is used to identify patients with palliative needs in the emergency department. This study aims to translate, adapt, and validate the P-CaRES tool for the German healthcare context. Methods: This is a monocentric, non-interventional, retrospective study conducted in the emergency department of the University Hospital Essen, Germany. After a structured translation process, the tool’s face and content validity were evaluated using questionnaires completed by healthcare workers. Construct validity was established by comparing the results with the German-validated Supportive and Palliative Care Indicators Tool (SPICT). A palliative care physician blinded to the tool, independently assessed the screened patients, and made recommendations on the appropriateness of palliative care referrals. Results: Two hundred eighty-nine emergency department visits were examined. In addition, a total of 26 healthcare professionals were surveyed. 258 screenings were conducted, with P-CaRES identifying 50 positive cases (19.4%). Agreement between SPICT and P-CaRES was 88.4% (kappa: 0.67, 95% confidence interval (CI): [0.56, 0.78]), showing 64.7% sensitivity and 96.8% specificity. Expert comparison yielded 85.5% agreement (kappa: 0.54, 95% CI: [0.41, 0.68]), with 64.0% sensitivity and 90.8% specificity. Face and content validity showed strong agreement regarding the tool’s design, including its comprehensibility, applicability, ease of use, and precision, as well as its usefulness in referring patients to a specialized palliative care team. Conclusions: The study successfully validated a cultural and linguistic equivalent German version of the P-CaRES tool. Further research is necessary to assess the tool’s effectiveness in clinical practice. Full article

Children learn linguistic structures from the input they receive. Their learning may depend on several factors such as children’s sensitivity to structure in the input, prior language experience, and the consistency of linguistic structures in the input. In this study, we investigated how inconsistent input (i.e., substitution errors) in an artificial language affects 7 to 11-year-old Dutch-speaking children’s learning of words and rules. Using a cross-situational statistical learning task (CSL task), we assessed children’s learning of label–referent pairs (word learning) and their generalization of two morphophonological rules. Eighty-nine children were randomly allocated to three input conditions: a fully consistent input condition (n = 31), a 12.5% inconsistent input condition (n = 32), and a 25% inconsistent input condition (n = 26). In the inconsistent input conditions, children were exposed to substitution errors, respectively, 12.5% and 25% of the time. We found evidence that substitution errors in children’s language input hindered their cross-situational statistical language learning. While we have evidence that children learned the words in our artificial language, we have no evidence that children—regardless of input condition—detected the morphophonological rules. This study eventually may inform us on how differences in the quality of children’s language environments (arising from, e.g., speaker variability and language proficiency) affect their language learning. Full article

Supplier selection in the shipbuilding industry is a typical multicriteria group decision-making (MCGDM) problem, often characterized by significant uncertainty and fuzziness. To address this issue effectively, this paper proposes a novel integrated approach for supplier selection in shipbuilding enterprises by combining intuitionistic fuzzy sets (IFSs) with the weighted aggregated sum product assessment (WASPAS) method. The proposed method utilizes IFS operators alongside an innovative process for evaluating indicator weights. Initially, an intuitionistic fuzzy number approach is employed to obtain indicator data, which effectively captures the uncertainty of linguistic variables and ensures accurate reflection of real-world conditions. Subsequently, the indicator weights are evaluated by integrating subjective weights, derived through the best–worst method, with objective weights, calculated using an entropy-based approach, resulting in more balanced and realistic weight assignments. Subsequently, the WASPAS method is used to prioritize alternative suppliers, and a shipbuilding enterprise in Shanghai is taken as an example to verify the effectiveness of the model. In addition, to evaluate the stability of the proposed method, sensitivity analyses were performed for varying attribute values. The results demonstrate that the combination of subjective and objective weights enhances the stability of the method under varying attribute weights. Finally, a comparison with various existing methods based on intuitionistic fuzzy information proves that the proposed method exhibits certain advantages in solving the MCGDM problem under uncertain environments. Full article

Background/Objectives: Health-related quality of life has come to the forefront of the process of treatment. As a non-quantitative value, it requires the use of specialized tools to be measured. Despite the availability of general HRQoL assessment tools in Polish, a specific instrument for children with gastrointestinal (GI) disorders has not been developed. This study aims to describe the linguistic validity and reliability of the Polish version of the PedsQL™ Gastrointestinal Symptoms Module, which measured health-related quality of life (HRQoL) in children with gastrointestinal (GI) disorders. Methods: The PedsQL™ module, originally in English, was translated according to a structured process. Professional medical translators conducted the translations, and cognitive debriefing was performed with 35 respondents. Field testing involved 371 completed questionnaires (203 adults and 168 children). Results: Internal consistency was assessed using Cronbach’s alpha, with values generally exceeding 0.8 indicating high reliability. Conclusions: The final Polish version of the PedsQL™ GI Symptoms Module exhibits strong linguistic and content validity, making it suitable for both clinical trials and routine practice. Its use enables a comprehensive, culturally sensitive assessment of HRQoL in pediatric patients with GI disorders, thereby supporting individualized patient care and enhancing the physician–patient communication that is essential for effective treatment. Full article

Within the realm of graphic design sustainability, selecting appropriate solutions has become a crucial strategic decision for organizations aiming to optimize their operations. This paper presents a novel hybrid multi-criteria decision-making (MCDM) approach, integrating a fuzzy analytical hierarchy process (FAHP) and fuzzy measurement alternatives and ranking according to compromise solution (FMARCOS). Evaluation criteria for graphic design sustainability are determined through consultation with experts, with their judgments expressed using linguistic terms based on fuzzy numbers. Criteria weights are calculated using FAHP, and the ranking and selection of the optimal potential solution are determined using FMARCOS. Subsequently, sensitivity analysis of the criteria weights is conducted to validate the results. Findings indicate that the integrated FAHP and FMARCOS model provides a robust and adaptable assessment framework for graphic design sustainability, enabling companies to navigate complexities strategically and effectively. The key contribution of this research is its emphasis on a systematic and objective model, offering practical insights relevant to the industry. It also serves as a valuable benchmark for future research in similar fields. Full article

Decision makers (DMs) are often viewed as autonomous in the majority of multicriteria group decision making (MCGDM) situations, and their psychological behaviors are seldom taken into account. Once more, we are unable to prevent both positive and negative flows of varying alternative preferences due to the nature of attributes or criteria in complicated decision-making problems. However, DMs’ perspectives are likely to affect one another in complicated MCGDM issues, and they frequently use subjective limited rationality while making decisions. The multicriteria quantum decision theory-based group decision making integrating the TODIM-PROMETHEE II strategy under linguistic Z-numbers (LZNs) is designed to overcome the aforementioned problems. In our established technique, the PROMETHEE II controls the positive and negative flows of distinct alternative preferences, the TODIM method manages the experts’ personal regrets over a criterion, and the quantum probability theory (QPT) addresses human cognition and behavior. Because LZNs can convey linguistic judgment and trustworthiness, we provide expert LZNs for their viewpoints in this work. We determine the criterion weights for each expert after first obtaining their respective expert weights. Second, to represent the limited rational behaviors of the DMs, the TODIM-PROMETHEE II approach is introduced. It is employed to determine each alternative’s dominance in both positive and negative flows. Third, a framework for quantum possibilistic aggregation is developed to investigate the effects of interference between the views of DMs. The views of DMs are seen in this procedure as synchronously occurring wave functions that affect the overall outcome by interfering with one another. The model’s efficacy is then assessed by a selection of renewable energy case studies, sensitive analysis, comparative analysis, and debate. Full article