Search Results (117)

Introduction: Due to the inherent difficulty in obtaining information using language-based questionnaires, research on the quality of life (QOL) for persons with aphasia (PWAs) is lacking. The purpose of this study was to investigate which factors have an impact on a PWA and to investigate the reliability of using proxy responses from either spouse/caregivers or speech-language pathologists (SLPs). Methods: A QOL scale was developed with 11 factors identified in the literature as having an impact on the QOL of PWAs. Data were collected through interviews with 31 PWAs and 26 spouse/caregivers recruited from a community aphasia therapy center. Thirty-six SLPs responded to an online survey. Results: Vocation was identified by PWAs as having the most impact on their QOL and family as having the least impact. Cronbach’s alpha and intraclass correlation coefficients (ICCs) showed decreased internal consistency and reliability across ratings and respondents. Conclusions: Overall results suggest that proxy responses may not accurately reflect the factors that impact the QOL of a PWA but that spouse/caregiver responses may be more representative than those of SLPs. Full article

Recovery from aphasia is a complex process involving restoring language ability to a level comparable to an individual’s pre-aphasia state. This recovery extends beyond linguistic functions such as improved quality of life and functional communication. Understanding language recovery in PWAs is a key area in aphasia research. Thus, the current study aimed to understand the pattern of language recovery in the acute and sub-acute stages of persons with aphasia (PWAs). A total of 11 PWAs aged between 40 and 80 were recruited. The study was conducted in two phases. In the acute stage (within one week post-stroke), participants were assessed using the Western Aphasia Battery-Kannada (WAB-K). In the sub-acute stage (between seven and fifteen days post-stroke), a similar test battery was repeated. The findings of the study showed auditory verbal comprehension scores were pronounced in the acute and sub-acute stages of recovery. Further, language quotient (LQ) scores were higher in the sub-acute stage compared to the acute stage, though these differences failed to evince statistical differences. Correlation analysis revealed strong positive correlations between LQ and spontaneous speech, repetition, and naming, with moderate correlations for auditory verbal comprehension. The study’s findings highlight the importance of targeted therapeutic interventions for PWAs, emphasizing an early focus on auditory verbal comprehension to enhance overall language recovery. Full article

Online education has become an important channel for extensive, inclusive and flexible learning experiences. However, significant gaps persist in providing truly accessible, personalized and adaptable e-learning environments, especially for students with disabilities, varied language backgrounds, or limited bandwidth. This paper presents AccessiLearnAI, an AI-driven platform, which converges accessibility-first design, multi-format content delivery, advanced personalization, and Progressive Web App (PWA) offline capabilities. Our solution is compliant with semantic HTML5 and ARIA standards, and incorporates features such as automatic alt-text generation for images using Large Language Models (LLMs), real-time functionality for summarization, translation, and text-to-speech capabilities. The platform, built on top of a modular MVC and microservices-based architecture, also integrates robust security, GDPR-aligned data protection, and a human-in-the-loop to ensure the accuracy and reliability of AI-generated outputs. Early evaluations indicate that AccessiLearnAI improves engagement and learning outcomes across multiple ranges of users, suggesting that responsible AI and universal design can successfully coexist to bring equity through digital education. Full article

Any failure in frontonasal development can lead to malformations at the middle facial region, such as frontonasal dysplasia, midfacial clefts, and hyper/hypotelorism. Various environmental factors influence morphogenesis through epigenetic regulations, including the action of noncoding microRNAs (miRNAs). However, it remains unclear how miRNAs are involved in the frontonasal development. In our analysis of publicly available miRNA-seq and RNA-seq datasets, we found that miR-28a-5p, miR-302a-3p, miR-302b-3p, and miR-302d-3p were differentially expressed in the frontonasal process during embryonic days 10.5 to 13.5 (E10.5–E13.5) in mice. Overexpression of these miRNAs led to a suppression of cell proliferation in cultured mouse embryonic frontonasal mesenchymal (MEFM) cells as well as in O9-1 cells, a cranial neural crest cell line. Through advanced bioinformatic analyses and miRNA-gene regulation assays, we identified that miR-28a-5p regulated a total of 25 genes, miR-302a-3p regulated 23 genes, miR-302b-3p regulated 22 genes, and miR-302d-3p regulated 20 genes. Notably, the expression of miR-302a/b/d-3p—unlike miR-28a-5p—was significantly upregulated by excessive exposure to all-trans retinoic acid (atRA) that induces craniofacial malformations. Inhibition of these miRNAs restored the reduced cell proliferation caused by atRA by normalizing the expression of target genes associated with frontonasal anomalies. Therefore, our findings suggest that miR-302a/b/d-3p plays a crucial role in the development of frontonasal malformations. Full article

Violence against people with albinism (PWAs) in Tanzania continues nearly two decades after mass media reported the first incidents in the mid-2000s. The violence is linked to organ trafficking for use in “magical rituals” that allegedly help politicians and businesspeople to succeed in their endeavors. Over time, as societal awareness grows, the attacks become increasingly clandestine and complex. PWAs themselves, the public, and gray literature frequently relate the violence to the increased political and economic activity and participation following Tanzania’s adoption of political and economic liberalization. However, scholarly research is either silent or mentions the occult practices only in passing. This paper, therefore, explores Tanzania’s institutional arrangements both driving the violence and crippling the efforts at promoting the rights and welfare of PWAs in the wake of increasing political and economic participation in the country. It discusses the ways in which violence against PWAs has evolved alongside political and economic dynamics from the time such incidents came to public attention until the present. I argue that the current approach, whereby advocacy about the rights of PWAs relies on appeasing the state, appears to perpetuate the very beliefs and practices driving the violence. The exploration makes use of first-hand experience through my participation in numerous formal and informal interactions with PWAs, internal and external meetings within the Tanzania Albinism Society (TAS), interviews, and gray literature on the subject. Full article

The contamination of paddy soils with arsenic (As) and cadmium (Cd), coupled with the depletion of soil organic carbon (SOC), poses significant threats to rice yields and quality. There is an urgent need to identify a suitable soil additive capable of achieving simultaneous heavy metal remediation and promotion of organic matter enrichment. The current study introduced two novel iron (Fe)/magnesium (Mg)-based bimetal-oxide-modified rice straw biochar (RSB), namely RSB-Fe/Mn and RSB-Fe/Mg. It evaluated their effectiveness in As/Cd immobilization and SOC preservation. An 8-week cultivation experiment was carried out in sequential drying–flooding moisture fluctuation conditions, with the soil pore water As/Cd (PWAs/Cd) and SOC fractions monitored. The mechanisms of As/Cd immobilization were investigated using Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and X-ray Photoelectron Spectroscopy (XPS) characterizations. Results revealed that PWAs and PWCd were reduced by up to 67.1% and 80.2% during the drying period and by 27.0% and 76.5% during the flooding period, respectively. Additionally, SOC content increased by 16.3% and 33.9% with RSB-Fe/Mn addition during the drying and flooding period, respectively, with an increase in the mineral-associated organic carbon (MAOC) fraction. The study proves that RSB-Fe/Mn and RSB-Fe/Mg are effective for soil As/Cd passivation and SOC stabilization, offering a promising solution to mitigate As and Cd pollution in paddy soils while maintaining soil quality. Full article

A novel scattering formalism, the multi-configuration Dirac–Fock partial wave analysis (MCDF-PWA), is presented in this study. This approach extends the conventional Dirac partial wave analysis by incorporating multiple atomic configurations of the target scatterer. The newly formulated methodology is employed to compute the cross-sections in elastic e-atom scattering. The analysis is performed for a few atomic targets like Mg, Ca, and Ba. Full article

The inherent flammability and toxic smoke emission of epoxy resins (EPs) pose significant challenges to their advanced engineering applications. To address this limitation, we developed a novel flame-retardant additive through the organic modification of layered double hydroxides (LDHs) using a ternary MgAlLa hydrotalcite structure intercalated with phosphotungstic acid (PWA). This innovative design established a synergistic mechanism by combining the catalytic carbonization effect of lanthanum with the radical scavenging capability of PWA. The optimized MgAlLa-PWA/EP composite demonstrated remarkable flame retardancy and smoke suppression improvements, exhibiting 77.9% and 62.4% reductions in the peak heat release rate (pHRR) and total heat release (THR), respectively, compared to pure EP. Particularly noteworthy was the 72.6% decrease in total smoke release (TSR), accompanied by a significant elevation of the limiting oxygen index (LOI) value to 26.8% and achievement of UL-94 V-0 rating. Microstructural analysis revealed that the modified composite formed a continuous and uniform layer with increased density during combustion, effectively inhibiting oxygen exchange, smoke diffusion, and heat transfer. This study provides a novel strategy for designing multi-element synergistic LDHs additive for high-efficiency flame retardancy and smoke suppression of EP. Full article

Background/Objectives: Noninvasive arrhythmic risk stratification in patients with ischemic heart disease is poor nowadays, and further investigations are needed. The most correct approach is based on the use of electrocardiogram (ECG) with the extraction of indices such as ECG alternans (ECGA). The aim of this study is to monitor the ECG evidence of ischemic coronary artery occlusion by the ECGA and to verify its ability to monitor the time course of balloon inflation, with the final goal of contributing to the exploration of the prognostic role of ECGA in ischemic heart disease. Methods: The ECGA amplitude and magnitude were computed by the correlation method (CM) on the STAFF III database, where ischemic coronary artery occlusion was induced in a controlled manner through coronary artery blockage by balloon inflation. ECGA computed during balloon inflation was also compared with periods before and after the inflation. Results: ECGA values became statistically higher during inflation than in the pre-inflation period and increased as inflation time increased, although not always in a statistically significant manner. ECGA went from values in the range 4–7 µV and 169–396 µV·beat before inflation to values in the range 5–9 µV and 208–573 µV·beat during 5 min of inflation (resulting statistically higher than before inflation), returning towards values in the range 4–8 µV and 182–360 µV·beat after inflation for amplitude and magnitude, respectively. Conclusions: CM-based ECGA detection was able to track the balloon inflation period. Our ECGA investigation represents a contribution in the field of research exploring its prognostic role as a noninvasive electrical risk index in ischemic heart disease. Full article

This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. A network of four piezoelectric wafer active sensors (PWAS) was installed on the tested plate to acquire impact signals. These signals consisted of reflection waves that provided valuable information about impact events. In this methodology, each of the received signals was divided into several equal segments. Then, a wavelet transform (WT)-based time-frequency analysis was used for processing each segment signal. The generated WT diagrams of these segments’ signals were cropped and resized using MATLAB code to be used as input image datasets to train, validate, and test the proposed CNN model. Two scenarios were adopted from PAWS transducers. First, two sensors were positioned in two corners of the plate, while, in the second scenario, four sensors were used to monitor and collect the signals. Eight datasets were collected and reshaped from these two scenarios. These datasets presented the signals of two, three, four, and five impacts. The model’s performance was evaluated using four metrics: confusion matrix, accuracy, precision, and F1 score. The proposed model demonstrated exceptional performance by accurately localizing all of the impact points of the first scenario and 99% of the second scenario. The main limitation of the proposed model is how to differentiate the data samples that have similar features. From our point of view, the similarity challenge arose from two factors: the segmentation interval and the impact distance. First, applying the segmenting procedure to the PWAS signals led to an increase in the number of data samples. The procedure segmented each PWAS signal to 30 samples with equal intervals, regardless of the features of the signal. Segmenting and transforming different PWAS signals into image-based data points led to data samples that had similar features. Second, some of the impacts had a close distance to the PWAS sensors, which resulted in similar segmented signals. Therefore, the second scenario was more challenging for the proposed model. Full article

The genome-wide association studies (GWAS) of lung disease and lung function indices suffer from challenges to be transformed into clinical interventions, due to a lack of knowledge on the molecular mechanism underlying the GWAS associations. A proteome-wide association study (PWAS) was first performed to identify candidate proteins by integrating two independent largest protein quantitative trait loci datasets of plasma proteins and four large-scale GWAS summary statistics of lung function indices (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC and peak expiratory flow (PEF)), followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, with a discovery dataset, we conducted Mendelian randomization (MR) and Bayesian colocalization analyses to select potentially causal proteins, followed by a replicated MR analysis with an independent dataset. Mediation analysis was also performed to explore the possible mediating role of these indices on the association between proteins and two common lung diseases (chronic obstructive pulmonary disease, COPD and Asthma). We finally prioritized the potential drug targets. A total of 210 protein–lung function index associations were identified by PWAS, and were significantly enriched in the pulmonary fibrosis and lung tissue repair. Subsequent MR and colocalization analysis identified 59 causal protein-index pairs, among which 42 pairs were replicated. Further mediation analysis identified 3 potential pathways from proteins to COPD or asthma mediated by FEV1/FVC. The mediated proportion ranges from 68.4% to 82.7%. Notably, 24 proteins were reported as druggable targets in Drug Gene Interaction Database, among which 8 were reported to interact with drugs, including FKBP4, GM2A, COL6A3, MAPK3, SERPING1, XPNPEP1, DNER, and FER. Our study identified the crucial plasma proteins causally associated with lung functions and highlighted potential mediating mechanism underlying the effect of proteins on common lung diseases. These findings may have an important insight into pathogenesis and possible future therapies of lung disorders. Full article

This study examines how gamification can improve the satisfaction level of foreign learners studying the Indonesian language using the innovative multiplatform application named Belajar Indo. In consideration of the Indonesian government’s heightened focus on language proficiency for foreign workers and students, this study examines the challenges encountered in Bahasa Indonesia for Foreign Speakers (BIPA) programs. Integrating gamified elements into a Progressive Web App (PWA) presents an engaging alternative to traditional learning resources, which frequently fall short in terms of interactivity and accessibility. Data gathered from surveys, online observation, and user engagement metrics indicate that gamification greatly improves learner motivation, resulting in a success rate of 93.51% and a Net Promoter Score (NPS) of 8.11. The findings demonstrate that gamification enhances language acquisition while simultaneously cultivating a greater enthusiasm for learning Indonesian, proving advantageous for both beginners and advanced learners. This study advances the domain of educational technology by presenting a model that integrates language acquisition with digital innovation, highlighting gamified learning as an effective instrument for foreign language education. Future recommendations involve fine-tuning user interface components to improve usability and maintain elevated engagement levels. Full article

Temperature has a significant impact on the operational lifetime of electronic components, as excessive heat can lead to accelerated degradation and ultimately failure. In safety-critical applications, it is important that real-time monitoring is employed to reduce the risk of system failures and maintain the safety, reliability, and integrity of the connected systems. In the case of printed circuit boards (PCBs), it is often not feasible to install enough sensors to adequately cover all of the temperature sensitive components. In this study, we present a novel method for the temperature monitoring of PCBs using ultrasonic guided waves and machine learning techniques. Our approach utilizes a small number of low-cost, unobtrusive piezoelectric wafer active sensors (PWAS) sensors for propagating ultrasonic guided waves across a PCB. Through interaction with board features, the temperature of components can be predicted using multi-output regression algorithms. Our technique has been applied to three different PCBs, each with five hotspot positions, achieving an RMSE of <3.5 °C and $R^2$ > 0.95 in all three cases. Full article

Background/Objectives: A pilot study was conducted to investigate the effect of four weeks of creatine monohydrate (CrM) on vascular endothelial function in older adults. Methods: In a double-blind, randomized crossover trial, twelve sedentary, healthy older adults were allocated to either the CrM or placebo (PL) group for four weeks, at a dose of 4 × 5 g/day for 5 days, followed by 1 × 5 g/day for 23 days. Macrovascular function (flow-mediated dilation [FMD%], normalized FMD%, brachial-ankle pulse wave velocity [baPWV], pulse wave analysis [PWA]), microvascular function (microvascular reperfusion rate [% StO₂/sec]), and biomarkers of vascular function (tetrahydrobiopterin [BH₄], malondialdehyde [MDA], oxidized low-density lipoprotein [oxLDL], glucose, lipids) were assessed pre- and post-supplementation with a four-week washout period. Results: CrM significantly increased FMD% (pre-CrM, 7.68 ± 2.25%; post-CrM, 8.9 ± 1.99%; p < 0.005), and normalized FMD% (pre-CrM, 2.57 × 10⁻⁴ ± 1.03 × 10⁻⁴%/AUC_SR; post-CrM, 3.42 × 10⁻⁴ ± 1.69 × 10⁻⁴%/AUC_SR; p < 0.05), compared to PL. Microvascular reperfusion rates increased following CrM (pre-CrM, 2.29 ± 1.42%/sec; post-CrM, 3.71 ± 1.44%/sec; p < 0.05), with no change following PL. A significant reduction in fasting glucose (pre-CrM, 103.64 ± 6.28; post-CrM, 99 ± 4.9 mg/dL; p < 0.05) and triglycerides (pre-CrM, 99.82 ± 35.35; post-CrM, 83.82 ± 37.65 mg/dL; p < 0.05) was observed following CrM. No significant differences were observed for any other outcome. Conclusions: These pilot data indicate that four weeks of CrM supplementation resulted in favorable effects on several indices of vascular function in older adults. Full article

Guided ultrasonic wave (GUW) analysis is a well-investigated method for structural health monitoring (SHM) applications. For plate-like structures, the pitch-catch technique is a popular choice since it offers the possibility to investigate a large area with a small number of sensors. This method requires a large amount of data to be analyzed to detect and localize damage, with the consequence that, besides the presence of damage, environmental influences like temperature and load will also change the GUW signals. In addition, the location, size, and type of the damage will result in different changes in the GUW signals. Data-driven methods require sufficient data and therefore require data augmentation. In order to get closer to this goal, this study aims to demonstrate the conversion of GUW signals measured with an air-coupled measurement system (ACMS) into signals measured with piezoelectric wafer active sensors (PWAS). This would allow the fast measurement of GUW data with ACMS at different positions of a plate-like specimen and translate it to a surface-bonded PWAS signal without the time-consuming process of transducer mounting. In this study, it is assumed that the measurement methods are not independent of each other when they are measured at the same position. To obtain the transform function from ACMS to PWAS, GUW signals were measured both with ACMS and PWAS for different positions of artificial damage. Since both signal classes are physically dependent, it should be possible to determine the transform function with machine learning (ML) methods. As input, the ACMS time-dependent signal or signal features are used, while the PWAS signals serve as labels for the training process. We are evaluating different ML-based transform model architectures with respect to their suitability for signal or signal feature transformation, e.g., ANN, CNN, and LSTM-based networks, with a particular focus on autoencoders. Full article