Month: January 2025

Becoming bilingual (or not): A look into the public’s intersecting orientations towards Bilingual 2030 in multilingual Taiwan

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Abstract

The Bilingual 2030 policy in Taiwan has attracted both support and criticism since it was introduced in 2018. Those who embrace the policy consider it an opportunity for Taiwan to become more globally connected, while those who are skeptical question whether the policy could actually lead Taiwan to a better place in the longer run—not just linguistically, but also socially, economically, and politically. Driven by this concern, this paper seeks to systematically examine the public’s response towards Bilingual 2030—through the analysis of opinion pieces and polls collected between 2019 and 2022, in addition to a series of comments gathered from a policy petition filed in 2023. With Ruiz’s (NABE J 8:15–34, 1984) theory as a guiding framework, this paper shows that the public’s language orientations are relational, intersecting, and multilayered, implicated in wider language power dynamics. In particular, the findings unveil a disconnect between what is projected and what is received, moving from an English-as-resource focus to a more dynamic discussion of resource, right, and problem orientations associated with different languages in Taiwan. While there is ample discussion around the economic benefits of English, issues related to national identity and de/colonization are also very much alive and kicking in interpretations of the policy. The main argument of this paper is that the “bilingual” label in policy discourse needs to be taken more critically and in ways that address the language concerns of the people. The paper ends with some suggestions to advance the vision of enhancing multilingual Taiwan.

Facilitators and barriers affecting the implementation of e-health for chronic respiratory diseases in remote settings: a qualitative evidence synthesis

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Abstract

Background

Chronic respiratory diseases are important causes of disability and mortality globally. Their incidence may be higher in remote locations where healthcare is limited and risk factors, such as smoking and indoor air pollution, are more prevalent. E-health could overcome some healthcare access obstacles in remote locations, but its utilisation has been limited. An improved understanding of barriers and facilitators to the implementation of e-health in remote locations could aid enhanced application of these approaches.

Methods

We performed a qualitative evidence synthesis to explore factors affecting the successful implementation of e-health interventions in remote locations for patients with chronic respiratory diseases. We searched PubMed, CINAHL, Embase, Web of Science and PsycINFO databases for qualitative and mixed-methods studies. Studies were assessed by two researchers, and 41 studies were included in the synthesis. Quality was assessed via the CASP-tool. Findings were coded with Atlas.ti software and categorised based on an adapted Digital Health Equity Framework.

Results

Nineteen themes were identified across five levels (individual, interpersonal, community, society and technology), with associated facilitators and barriers for implementation. An important facilitator of e-health was its role as a tool to overcome obstacles of distance and to increase access to care and patients’ self-efficacy. Potential barriers included the reduction of in-person interactions and an increased burden of work for healthcare providers. Good quality, usability, adaptability and efficacy of e-health interventions were important for implementation to be successful, as were adaptation to the local setting — including culture and language —and involvement of relevant stakeholders throughout the process.

Conclusions

Several factors affecting the implementation of e-health in remote and rural locations for patients with chronic respiratory disease were identified. Intervention objectives, target population, geographical location, local culture, and available resources should be carefully considered when designing an e-health intervention. These findings can be used to inform the successful design and implementation of future e-health interventions.

The paradox of ontological security in far-right narratives and the securitization of identified alterities: the cases of Spain and Italy

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Abstract

Nationalistic far-right discourse promises to restore and defend the nation against identified alterities, which they blame for a supposed lost “national authenticity.” An analysis of the paradoxical claims of the Italian and Spanish far-right parties in 2022 and 2023 examines how discourses of ontological insecurities are presented as threats posed by alterities to national majorities. The article claims that sometimes these discourses are mixed with securitization moves, but at times there is evident separation between the two processes. Among what the far-right identifies as alterities, political and cultural adversaries are blamed for national ontological insecurity: the US liberal system, religious minorities, the EU, and migration. The findings illustrate that the far-right uses a catch-all strategy on all these themes through the usage of paradoxical claims in their discourse. Through the analysis, it becomes evident that the scapegoating of alterities is crucial to identify when ontological insecurity is indeed connected to the spiraling of the securitization process and particularly to how it allows the far-right to prosper.

Homo-humanitarianism: queering the Afghan crisis and evacuations

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Abstract

Upon the international community’s exit from Afghanistan in August 2021, the West made Afghanistan into a crisis, covering up its decades of violence while dehumanizing Afghans. Afghanistan was constructed as a site of oppression and homophobia, allowing the West to situate itself once again as not only ‘civilized’ but ‘queerly civilized’. From the United States to Canada, France and Ireland, saving the ‘at risk’ Afghan queers, trans and women became an international humanitarian responsibility. How and why did queer and trans Afghans all a sudden become “at risk” and “in need of saving” individuals? How did the Western governments and humanitarian regimes politicize queer and trans Afghan lives and “savings”? Based on a de/colonial ethnography of the Afghan evacuations at the moment of humanitarian exit, this article introduces the concept of ‘homo-humanitarianism’ through which the West so-called saved queer and trans Afghans upon/post its abrupt withdrawal while constructing Afghanistan as a site of perpetual violence and Afghans as homophobic.

Transboundary Water Resources in the South Caucasus

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Abstract

The South Caucasus region possesses the ramified network of ground and underground water systems. All water bodies in this region, particularly rivers and groundwater resources, are mostly transboundary. This is not only a challenge for the regional countries, but also new opportunities for cooperation. The political conflicts that occur in the region from time to time and also persistent deficit of finance are the major obstacles for strengthening the transboundary cooperation. However, the ecological situation still remains acceptable for creating the impulse for development of the transboundary water cooperation.

Correlation between different boundaries used in upper airway assessment

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Abstract

Background

The aim of this study was to evaluate the correlation of the volume and minimum axial area (MAA) measurements between different upper and lower boundaries used for oropharyngeal airway assessment.

Methods

Cone Beam Computed Tomography (CBCT) scans of 49 subjects taken for pre-orthognathic surgical planning were obtained retrospectively from the archives (n = 49; 32 females, 17 males; mean age = 20.9 ± 5.22). Volume and MAA of the oropharyngeal airway were measured in 32 different airway segmentations created with four different upper and eight different lower boundaries using the Dolphin3D (Dolphin Imaging & Management Solutions, Chatsworth, California, ABD) software. All measurements were performed by the same examiner and were repeated 2 weeks apart. The correlation between the measurements was evaluated with the Pearson correlation test. Intra-observer reliability was calculated with the intra-class correlation coefficient.

Results

Volume and MAA showed excellent intra-observer reliability (0.997 and 0.999 intraclass correlation coefficients, respectively) and a high level of positive correlation (r = 0.896–0.999, and r = 0.859-1.00, respectively) for all the measurements.

Conclusions

All measurements between different lower and upper boundaries showed a high correlation. It was found that the lower and upper limits assessed in this study can be used safely in future upper airway studies according to the study design.

Magnetic resonance imaging quantification of left ventricular mechanical dispersion and scar heterogeneity optimize risk stratification after myocardial infarction

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Abstract

Background

Left ventricular (LV) myocardial contraction patterns can be assessed using LV mechanical dispersion (LVMD), a parameter closely associated with electrical activation patterns. Despite its potential clinical significance, limited research has been conducted on LVMD following myocardial infarction (MI). This study aims to evaluate the predictive value of cardiac magnetic resonance (CMR)-derived LVMD for adverse clinical outcomes and to explore its correlation with myocardial scar heterogeneity.

Methods

We enrolled 181 post-MI patients (median age: 55.7 years; 76.8% male) who underwent CMR examinations. LVMD was calculated using the CMR-feature tracking (CMR-FT) technique, defined as the standard deviation (SD) of the time from the R-wave peak to the negative strain peak across 16 myocardial segments. Entropy was quantified using an algorithm implemented with a generic Python package. The primary composite endpoints included sudden cardiac death (SCD), sustained ventricular arrhythmias (VA), and new-onset heart failure (HF).

Results

Over a median follow-up of 31 months, LVMD and border zone (BZ) entropy demonstrated relatively high accuracy for predicting the primary composite endpoints, with area under the curve (AUC) values of 0.825 and 0.771, respectively. Patients with LVMD above the cut-off value (86.955 ms) were significantly more likely to experience the primary composite endpoints compared to those with lower LVMD values (p < 0.001). Multivariable analysis identified LVMD as an independent predictor of the primary composite endpoints after adjusting for entropy parameters, strain, and left ventricular ejection fraction (LVEF) (hazard ratio [HR]: 1.014; 95% confidence interval [CI]: 1.003–1.024; p = 0.010). A combined prediction model incorporating LVMD, BZ entropy, and LVEF achieved the highest predictive accuracy, with an AUC of 0.871 for the primary composite endpoints. Spearman rank correlation analysis revealed significant linear correlations between LVMD and entropy parameters (p < 0.001 for all).

Conclusions

Myocardial heterogeneity, as assessed by LVMD and BZ entropy, represents reliable and reproducible parameters reflecting cardiac remodeling following MI. LVMD has independent prognostic value, and the combination of LVMD and BZ entropy with the guideline-recommended LVEF as a unified model enhances the accuracy of forecasting the risk of primary combined endpoints in patients after MI.

Comparison between relining of ill-fitted maxillary complete denture versus CAD/CAM milling of new one regarding patient satisfaction, denture retention and adaptation

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Abstract

Purpose

This study aimed to compare different treatment modalities to correct ill-fitted maxillary complete denture either by the conventional relining method or by scanning the relining impression and digitally construct a new denture regarding patient satisfaction, denture retention, and adaptation.

Materials and methods

Twelve edentulous patients suffering from loose maxillary complete dentures were selected, dentures’ borders and fitting surfaces were prepared, and relining impressions were taken, the impressions were scanned and the STL files were used for CAD/CAM milling ( computer aided designing/ computer aided manufacturing) of new maxillary dentures (Group A), then the relining impression went through the conventional laboratory steps to fabricate (Group B) maxillary dentures. Both groups were evaluated regarding patient satisfaction by a specially designed questionnaire, retention values were measured by a digital force gauge at denture insertion appointment and two weeks later, geomagic software was used to evaluate dentures adaptation to oral tissues.

Results

Both groups (A and B) were completely satisfied with their dentures except regarding esthetics, all group A and 50% of group B were satisfied. Both groups showed a statistically significant increase in retention values at the two-week follow-up period compared to those at denture insertion time, with higher values were for group B. Finally, the relined dentures showed better oral tissue adaptation than digitally constructed dentures.

Conclusion

Relined maxillary dentures showed better retention, esthetics, and denture adaptation with lower cost than digitally constructed maxillary dentures which showed acceptable retention and adaptation, with better time and data saving.

Trial registration

Clinical trials number: NCT06366321. With registration date on ClinicalTrials.gov public website: 13/ 4/ 2024.

Detecting and assessing weak adhesion in structural single lap joints using a machine learning pipeline with lamb waves data

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Abstract

Adhesive joints are widely used in industries such as aerospace and automotive due to their lightweight and high mechanical performance. However, weak adhesion remains a significant issue affecting the structural integrity of these joints. Current detection methods of weak adhesion rely on destructive testing, which limits the widespread use of adhesive primary structures. This study proposes a novel nondestructive testing (NDT) technique to detect, evaluate the intensity, and localize weak adhesion in single lap joints (SLJs) using lamb waves (LWs) and machine learning (ML). The aim is to develop a ML-based pipeline capable of identifying weak adhesion with high accuracy and sensitivity, based on data from simulated and experimental SLJ samples. The proposed technique integrates LW data with convolutional neural networks (CNNs) in a ML pipeline for weak adhesion detection in SLJs. The use of a large simulated dataset combined with transfer learning allows for effective adaptation to experimental conditions, improving both the detection and localization of damage. This approach offers a significant advancement over traditional destructive testing techniques. The pipeline begins with the generation of simulated LW time-series data for SLJs with varying adhesion levels, damage locations, and sizes. After preprocessing, the data are input into a CNN, which is initially trained on synthetic data. Transfer learning is employed to fine-tune the model using a small experimental dataset. The final trained model is then applied to detect weak adhesion, estimate its intensity, and localize the damage. The proposed pipeline demonstrated high performance in both simulated and experimental datasets: regarding detection, the algorithm achieved over 95.3% accuracy in identifying damage from simulated data and near 100% detection of damaged cases in experimental data; for intensity estimation, the algorithm showed an average loss of approximately 45 MPa for weak adhesion intensity in experimental validation, with an average error of about 140 MPa and a best-case error of just near 3.6 MPa; in terms of localization, the average localization error was approximately 8 mm in the synthetic validation dataset; with respect to flexibility, the methodology is adaptable to different damage characteristics, such as existence, intensity, and localization, without requiring substantial modifications. Summing up, this study presents a novel NDT approach using ML and LW data that significantly improves the detection, evaluation, and localization of weak adhesion in adhesive joints. Its high accuracy and adaptability have the potential to enhance structural health monitoring, ensuring the safety and durability of bonded structures in critical industries.