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A PCA-Enhanced t-SNE Plot and Its Application in Biological and Medical Research
Full text linkIn this paper, we apply a two-step dimension reduction method, PCA-t-SNE to a real gene expression dataset as case study. It turns out that the PCA-t-SNE can signigicantly improve the visualization and cluster separation of high-dimensional biological data. While t-SNE alone often fails to reveal clear cluster structures in complex datasets, our approach first applies Principal Component Analysis (PCA) to reduce noise and dimensionality, followed by t-SNE to condense the data into a two-dimensional space and then apply the k-means to clustering the two-dimensional data. We demonstrate that PCA-t-SNE produces more distinct and interpretable clusters compared to the standard t-SNE. Statistical validation via a projected F-test for MANOVA confirms that clusters derived from PCA-t-SNE exhibit significantly greater mean separation, with lower p-values, underscoring the enhanced discriminative power of the method. The proposed PCA-t-SNE plot proves particularly effective for nonlinear data where conventional t-SNE performs poorly, offering a robust visualization tool and supporting the utility of sequential dimension reduction in exploratory data analysis for biological and medical research.
Purpose: This study aims to evaluate the effect from a combination of the classical PCA and the modern t-SNE technique for dimension reduction in clustering of high-dimensional gene expression data from the aspects of both visualization and MANOVA.
Methods: This paper presents a combined approach to dimension reduction for high-dimensional gene expression data. The effect of the visual approach is re-enhanced by the classical MANOVA method for large sample sizes (n > p) and the newly developed MANOVA method for small sample sizes (n < p).
Results: The proposed PCA t-SNE approach significantly improves the pure t-SNE approach for the selected gene expression dataset in the sense of clearer classification of the data from both visual observation and statistical significance tests. This provides a pre-processing of high-dimensional gene expression data before implementing the nonlinear dimension reduction, making the t-SNE approach more effective.
Contribution: We carry out a successful application of the two-step dimension reduction method PCA-t-SNE to a real gene expression dataset as case study. The idea of the PCA-t-SNE approach to visualizing high-dimensional gene expression data, enhanced by the projection-type MANOVA tests, opens a new way to discrimination of complex high-dimensional with statistical significance in the case of high dimension with a small sample size (n < p). It enhances the clustering of those nonlinear-type of data where the pure t-SNE almost fails to discriminate the clusters, and provides insight into a two-step dimension reduction approach
Experiences and Challenges of Implementing the Individualized Education Plan (IEP) for Students with Learning and Intellectual Disabilities in Kuwait
Full text linkThis study explores the development and effectiveness of Individualized Education Programs (IEPs) in supporting students with special educational needs (SEN). Utilizing a descriptive-analytical approach, the research examines key factors influencing the implementation of IEPs, including teacher expertise, parental involvement, and institutional support. The study sample comprises special education teachers and school administrators, selected using a stratified sampling method to ensure diverse representation.
Findings indicate that while IEPs play a crucial role in enhancing student learning outcomes, challenges persist in adapting the curriculum, facilitating interdisciplinary collaboration, and assessing continuous progress. The study also reveals that teachers with specialized training in inclusive education demonstrate greater confidence in designing and executing IEPs, whereas limited parental engagement and administrative constraints hinder effective implementation.
The results underscore the need for comprehensive professional development programs, stronger family-school partnerships, and policy reforms to optimize IEP practices. These findings offer valuable insights for educators, policymakers, and stakeholders seeking to improve inclusive education strategies and individualized instructional planning
Lecturers’ Attitudes and Readiness toward Teaching Students with Intellectual Disabilities in Higher Education Institutions in Nigeria
Full text linkBackground: Inclusive education plays a vital role in promoting equitable learning opportunities, particularly for students with intellectual disabilities in higher education institutions. The attitudes and readiness of lecturers to adopt inclusive teaching practices are crucial to the successful implementation of inclusive policies and pedagogies. Guided by the Theory of Planned Behaviour (TPB), this study investigates how lecturers’ attitudes, perceived social expectations, and perceived behavioural control influence their readiness to teach students with intellectual disabilities in Nigerian higher education institutions.
Methods: The study adopted a descriptive survey design, involving 270 lecturers selected through accidental sampling from various higher education institutions across Nigeria. Data were collected using a structured questionnaire designed to assess lecturers' attitudes, institutional expectations, and perceived control over inclusive teaching practices. Descriptive statistics, such as the mean and standard deviation, were used to analyze the data, while independent t-tests were employed to test the hypotheses at a 0.05 level of significance.
Results: The findings revealed that lecturers demonstrate a moderate to high level of readiness to implement inclusive teaching. Respondents reported willingness to participate in training, adopt inclusive strategies, and manage mixed-ability classrooms. Attitudes toward inclusion were largely positive. However, challenges were noted in areas such as adapting instructional materials and using assistive technologies, indicating limitations in perceived behavioural control.
Conclusions: The study affirms the relevance of the Theory of Planned Behaviour in explaining lecturers' readiness for inclusive teaching. Addressing capacity gaps through targeted training and institutional support is essential for advancing inclusive education and achieving Sustainable Development Goal 4
Translating from Igbo (Nigeria) – A Bumpy Journey
Full text linkLiteratures in African languages have remained largely untranslated and thus unknown outside their linguistic domain. This situation led the ELLAF http://ellaf.huma-num.fr/ team to start gathering oral and written texts and build an online encyclopaedia of literatures in African languages. Igbo language, one of the three major national Nigerian languages, is also one of the eleven African languages chosen for this project. Igbo rich oral and written literature remains largely unknown to this day, with only one translation into French, that of its first novel, Omenuko (1933). This article will present the difficulties and challenges experienced by the French translation of the Igbo text during this long period, from a first attempt in the 1990s unto its 2010 publication in Paris. It will equally contribute to the on-going reflection on challenges facing the translation and publication of literary texts in African languages
Reimagining Culture and Arts Education through the Integration of Artificial Intelligence and the Sixth Industrial Revolution: Demands, Challenges, and Future Implications
Full text linkThis scoping review explores the demands and integration of Artificial Intelligence (AI) and the Sixth Industrial Revolution (IR 6.0) in culture and arts education. It maps existing literature to understand how these technological advancements reshape educational practices, enhance creativity, and prepare learners for a rapidly evolving digital society. Anchored in Technological Determinism and Social Constructivism, the study investigates five key research questions on AI and IR 6.0 demands, integration challenges, alignment strategies, and educational implications. Findings highlight the transformative potential of AI in delivering personalized learning, fostering creativity, preserving cultural heritage, and facilitating immersive experiences through virtual and augmented reality. Likewise, IR 6.0 demands integration of digital tools, blended learning, interdisciplinary approaches, and sustainability. However, challenges such as resistance to change, limited expertise, unequal access to technology, and ethical concerns persist. The review underscores the need for proactive strategies including project-based learning, equitable access, ethical AI use, and continuous teacher training. It concludes that AI and IR 6.0, if harnessed responsibly, can enrich culture and arts education. Gaps in long-term impact studies, ethics, access, and student perceptions are identified, with recommendations for future research to foster inclusive, innovative, and future-ready educational practices
UK AI Governance at a Crossroads: Charting the Path Ahead
Full text linkGovernance of Artificial Intelligence (AI) in the UK remains in its formative stages, guided by the policy objective of a “proportionate and pro-innovation regulatory framework” as set out in the White Paper (DSIT, 2023). Consistent with this framing, the UK has adopted a cross-sectoral, principles-based approach that seeks to balance regulatory flexibility with innovation while addressing AI-related risks. Rather than enacting comprehensive AI-specific legislation, the government relies on sectoral regulators to implement overarching principles - safety, transparency, fairness, accountability and contestability - through existing legal and institutional frameworks (DSIT, 2023).This trajectory is reflected in key initiatives such as the National AI Strategy (DSIT, 2022a), the establishment of the AI Safety Institute, and the AI Opportunities Action Plan (DSIT, 2025), collectively signalling a decentralised and innovation-friendly governance model. Nevertheless, whether this regulator-led approach should be maintained or replaced by a more uniform, horizontal legislative framework remains an increasingly contested question.To address this issue, this paper examines how AI is currently regulated in three sectors - healthcare, education and legal services - and evaluates the extent to which cross-sectoral principles are being operationalised consistently and effectively. It contrasts these practices with the EU’s horizontal framework under the EU AI Act (European Parliament and Council, 2024). The analysis identifies persistent challenges, including regulatory fragmentation, inconsistent application of principles and uneven enforcement capacities. It concludes that the UK model’s long-term effectiveness depends on stronger central coordination, proposing minimum statutory duties for regulators, a lead coordinating authority and clearer accountability pathways across sectors
International Survey about Perceptions of Courts’ Role in Addressing Social Issues through Problem-Solving Courts
Full text linkPurpose of the study: Community sentiment is a collective group of attitudes toward an object–such as problem-solving courts–which could differ between populations. This study addresses community sentiment regarding whether the courts should address social problems and whether community sentiment differs based on the type of problem-solving court. It also investigates whether the perceived responsibility of courts to address social issues differs based on country (United States, Australia, and Canada) or individual differences, as well as whether group or individual differences are more predictive of support for problem-solving courts. Method: We surveyed citizens in the U.S., Australia, and Canada using an online survey. Results: We found that participants had positive community sentiment toward all four (drug, homelessness, mental health, tribal wellness/Aboriginal) problem-solving courts and community sentiment did not differ between countries. We also found that endorsement of therapeutic jurisprudence was the largest predictor for community sentiment toward all four courts. Conclusion: We found that sentiment was positive but similar in all countries. Individual differences (e.g., authoritarianism, support for justice principles, and attributions for crime) were stronger predictors than country of residence. This study can help encourage the creation of specialty courts to address social issues
Cryptocurrencies are here to Stay! Think you aren’t Vulnerable, Think Again
Full text linkCryptocurrencies are here to stay and represent a market capitalisation of approximately $3.57T. It has been reported that over 500 million people globally own cryptocurrencies. In this paper, I discuss the vulnerabilities identified with cryptocurrency ownership including who is vulnerable and then explore the role education plays. The study described involved 745 cryptocurrency owners (including 140 non-fungible token (NFT) owners) from Australia and explores the ways in which vulnerabilities play out for various demographics. The above-mentioned research revealed that almost everyone is vulnerable when it comes to cryptocurrency and/or NFT ownership and challenges who has previously been identified as experiencing financial vulnerabilities. Demographic characteristics associated with financial vulnerabilities often includes individuals with lower education levels who are living on low incomes, who identify as female and/or Indigenous and/or for whom English is a second language. It is often assumed that anyone else who does not meet the above-mentioned characteristics are assumed to be financially capable. However, with cryptocurrency ownership almost everyone is vulnerable. Education has a role to play to help combat the risks associated with cryptocurrency and/or NFT ownership. We need educators willing to teach about cryptocurrencies and NFT ownership, storage and tax implications
Assessing the Impact of Human and Technological Factors on Hospital Management Information System Utilization: A Case Study at Hospital X In Padang City Indonesia
Full text linkThis study examines the application of the HOT-Fit method, which evaluates the relationship between Human, Technology, and Net Benefit components within the Hospital Management Information System (HMIS) at Hospital X Padang. The Human component is assessed based on system usage and user satisfaction, while the Technology component is analyzed through information quality, service quality, and system quality. This study employs a quantitative crosssectional design, with the research population comprising all active users of the HMIS application at Hospital X Padang, including employees from various departments interacting with the system. The research aims to determine the extent to which the Human and Technology components influence the Net Benefit of the HMIS and to explore these relationships in greater depth. The findings reveal a significant relationship between the Human component and the Net Benefit, as well as between the Technology component and the Net Benefit of the HMIS. Among the factors examined, Technology emerges as the most dominant factor affecting the Net Benefit of the system. These results provide valuable insights for optimizing the implementation and impact of HMIS in healthcare settings
Effect of Online Learning on Mental Health and Academic Outcomes of Students with Intellectual Disabilities in Higher Education
Full text linkThe COVID-19 pandemic shift to online learning has raised concerns regarding students’ mental health and academic performance, particularly for students with intellectual disabilities.
Objective: This paper examines the effects of online learning on stress, anxiety, and social isolation and those factors on academic performance, Grade Point Average (GPA), and participation in online learning and engagement, particularly for students with intellectual disabilities (IDs).
Methods: The current study employed a quasi-experimental research design and targeted 500 participants, comprising both undergraduate and postgraduate students. Of these, 50 participants were identified as having intellectual disabilities (IDs) through self-reporting and institutional records. The remaining 450 participants were typically developing students selected through stratified random sampling to ensure proportional representation across academic levels and disciplines. The Perceived Stress Scale (PSS), Generalized Anxiety Disorder-7 (GAD-7), and UCLA Loneliness Scale were adopted from validated and widely used psychometric tools in mental health research. These instruments have been previously validated for reliability and applicability across diverse populations. Multiple linear regression and Pearson correlation coefficients (PPMC), which help identify associations and control for confounding factors, were used to examine the relationships and potential predictive effects between mental health variables and learning outcomes.
Pearson correlation coefficients were utilized to analyze the linear relationships between mental health variables (stress, anxiety, and social isolation) and academic performance (GPA). Additionally, multiple linear regression analysis was conducted to predict the impact of these mental health variables on academic performance while controlling for confounding factors such as age, gender, and degree level.
Results: Participants with IDs reported significantly higher levels of stress (PSS, M = 25.8), anxiety (GAD-7, M = 12.5), and social isolation (UCLA, M = 48.6) compared to the control group. Mental health variables had a significant negative relationship with GPA, with stress having a correlation coefficient of -0.51 and anxiety having a correlation coefficient of -0.48. In regression analysis, stress was found to have the largest effect on the outcome of GPA, seconded by anxiety and then social isolation.
Conclusion: A direct impact of mental health on learning is observed, particularly for students with IDs, implying the necessity of developing an individual mental health promotion program and ways of creating more effective online learning for students with IDs that help alleviate stress, anxiety, and isolation