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Sustainable Development Goals (SDGs) And Share Price : A Study of Malaysian Listed Companies
No full textSDGs have been integrated into corporate strategies and this trend is accompanied by action from the side of investors who increasingly look at sustainability as well as financial performance. The lack of clear disclosure rules in Malaysia makes it hard for investors to assess sustainability performance listed companies due to limited information.
The main objective of this study is to examine the correlation between SDGs and Malaysian companies' share price performance. Stakeholder theory suggests sustainability info boosts share prices by gaining trust
from stakeholders while Signalling theory suggests it shows a company’s long-term value, attracting investors. Through the analysis of panel data comprising at least 30 Bursa Malaysia-listed firms for the 2021–2023 period, secondary data from annual reports and sustainability disclosures were used. Multiple linear regression analysis was employed to evaluate
the influence of SDGs and control variables, including leverage, firm size, firm age, liquidity, and profitability, on share prices. The findings reveal
that while SDG disclosures are positively associated with share price, the relationship is statistically insignificant, suggesting limited influence on
market valuation. In contrast, profitability and firm age show significant positive effects on share price, while liquidity has a significant negative impact. These results indicate that traditional financial indicators continue to play a more critical role in influencing share prices than
sustainability disclosures
When islands collide : Divergence predicts outcomes of secondary contact during the fusion of Sulawesi’s paleo-archipelago
No full textDownloaded from https://www.pnas.org by Benjamin Karin on October 27, 2025 from IP address 136.152.214.5.
Speciation often results from the accumulation of reproductive isolation associated with lineage divergence, but secondary contact between diverged lineages can reshape the trajectory of speciation and reveal its underlying processes. The Indonesian island of Sulawesi is a tectonically complex island formed by the fusion of many paleo-islands, resulting in replicated cases of secondary contact among once-isolated lineages. Unlike secondary contact on continents where hybridization often results from unpredictable range shifts, Sulawesi’s fauna presents a replicated set of geologically constrained natural experiments to test how the magnitude of evolutionary divergence predicts outcomes of secondary contact and hybridization. Using thousands of genome-wide loci from Eutropis sun skinks spanning Wallace’s Line on Sulawesi and Borneo, we reconstructed a reticulate evolutionary history shaped by overwater dispersal, isolation, island fusion, hybridization, and character displacement. We delimited five distinct species (three undescribed) and uncovered multiple ancient hybridization events following island fusion leading to distinct outcomes. These outcomes—speciation reversal, parapatry, and sympatry putatively through reproductive character displacement—were associ- ated with increasing levels of prior divergence consistent with evolutionary theory. Sympatry, specifically, was preceded by substantial introgressive hybridization and body size divergence that likely confers reproductive incompatibility. Together, these results provide empirical support for divergence-dependent tipping points along the speciation continuum. The sun skink radiation also includes a rare instance of reverse colonization of Borneo across Wallace’s Line that established a narrowly divergent species with a uniquely intermediate body size absent from Sulawesi
Newspaper Coverage of Rabies in Malaysia: Persuasive Appeals and Health Belief Constructs
No full textRabies presents biosecurity concerns in Malaysia that was rabies-free for 20 years prior to 2017. This
study examines how Malaysian newspapers framed rabies outbreaks in 2017 and 2022, focussing on rhetorical
appeals and content in The Star (national) and Borneo Post (regional). A total of 89 articles were identified using
‘‘rabies’’, ‘‘dog’’ and ‘‘canine’’ as search terms. A time-series comparison revealed that media attention was driven
more by news value than by disease severity. When rabies re-emerged after two decades, emotional appeals and
severity was emphasised in the 63 news articles on rabies (20 BP, 43 TS). By 2022, only 26 news articles (13 BP, 13
TS) on rabies were identified despite more cases and deaths, and there was a shift towards logical appeals and the
content was mostly control measures. The cross-newspaper comparison further showed that The Star emphasised
susceptibility, warning readers of personal risk, while Borneo Post stressed severity but both newspapers
emphasised protective actions. The findings suggest that disease framing of rabies in newspapers should sustain
use of human stories to motivate preventive action after the initial shock of an infectious disease outbreak has
passed
Integrating the Protection Motivation Theory Scale Among Older Adults : Insights for Fall Prevention Behaviour
No full textThis commentary examines the application of the Protection Motivation Theory (PMT) scale to evaluate older adults' threat and coping appraisals, fear, and protective behaviours in reducing fall risks. The findings highlighted the impact of fear, threat and coping appraisals on older adults' intentions to adopt protection motivation to reduce fall risk. Mediating effects are found in coping appraisal for protective behaviour, fear for perceived cost, and threat appraisal for protection motivation. This study has also emphasised the implications of adopting the PMT scale among older adults in Sarawak, Malaysia
Development of Far-Source Earthquake Ground Motion Model Using Recurrent-Based Neural Network
No full textCountries having low to medium seismicity experience rare large, far-distance earthquakes. The development of its ground motion model is difficult due to data scarcity. Thus, the applicability of the LSTM recurrent neural network is explored, due to its ability to predict sequential data. Earthquakes from databases are collected with magnitudes larger than 6.5 Mw and distances between 200 and 500 km. The network is constructed with five input data, two LSTM layers, and 23 sequential outputs. The results show that the network underestimates the amplification at lower periods while predicting larger motions at higher periods, typical for far-source earthquakes
Innovative Strategies for Teaching Integers: A Systematic Literature Review
No full textThe instruction of integer has been one of the difficult mathematics education topics because of the current misconceptions and teaching gaps. This is a systematic literature review of research trends, pedagogical strategies, impact, limitations, and future directions of teaching integer operations that includes studies published after 2015. Twenty-one peer-reviewed articles were analysed with the help of the PRISMA model, and the usage of various innovative approaches, such as manipulative-based, contextual, model-based, technology-enhanced, and student-centred, was identified. These results prove that the number lines, manipulatives, and virtual tools are effective strategies to promote the conceptual learning and interest among students. Real life analogies and cultural elements provided contextual approaches that helped learners make learning relatable and the use of embodied learning and problem-posing activities enabled flexibility in reasoning. But problems like excessive use of tools, low sample sizes, little attention to multiplication and division, and teacher knowledge gaps were detected. Also, the ability to get students out of concrete thinking to abstract thinking is a critical challenge. This review highlights that there is a need to fill these gaps in future research that covers wider populations, longitudinal research, and teacher professional development. These points are consistent with the priorities of global education reform, which provides practical advice to educators, curriculum developers and policymakers on how to enhance the teaching of integers and help students develop mathematically
Revolutionizing banking services with ChatGPT: an integrated framework for user adoption
No full textThis study aims to understand the implementation of artificial intelligence (AI)-enabled technology in banking from a user perspective. For this purpose, we examine customer intention to adopt ChatGPT (Generative Pretrained Transformer) in performing banking services. To assess the study objectives, this research integrates two well-established technology models, namely, the Task-Technology Fit (TTF) Model and the Technol‑ogy Acceptance Model (TAM). This study employed a quantitative research approach
and utilized a survey-based questionnaire to collect primary data from banking customers. We analyzed a total of 424 valid responses via the partial least squares structural equation modeling (PLS-SEM) approach for the results and estimations. The results of this study indicate that the TTF and TAM have a positive and significant effect on customers’ intention to adopt ChatGPT in banking services. Additionally, this research revealed that ChatGPT knowledge plays a significant role as a modera‑tor in predicting user intentions toward ChatGPT adoption. Our findings provide
unique insights into the contemporary concept of AI-enabled technology adoption in the banking sector. This study highlights various aspects of the theoretical and man‑
agerial implications for managers and academicians. Theoretically, this study provides an in-depth analysis by integrating the TTF with an extended TAM. Practically, the find‑ings of this study enhance strategic planning and informed decisions in the bank‑ing sector regarding the use of ChatGPT. This study also assumes that this is the first
attempt in the Pakistani banking sector to analyze customer intentions to adopt ChatGPT in their banking transactions. Finally, our study limitations provide a discussion forum for subsequent studies that adapt or imitate our methodology in other demographics or countries. This will encourage the development of AI technologies in financial companies
EXPLORING CUSTOMER SATISFACTION IN HOTEL RESTAURANTS: THE ROLE OF PERCEIVED VALUE AND THE MODERATING EFFECT OF COVID-19 FEAR
No full textThis study examined how perceived value dimensions (physical environment, trust, corporate reputation, and price) influence customer satisfaction in hotel restaurants in Kuching, Malaysia. This study also explored the moderating role of COVID-19 fear on these relationships. Using data from 285 structured questionnaire responses, the findings reveal that all value dimensions are positively associated with customer satisfaction. Additionally, it was suggested
that COVID-19 fear is positively related to customer satisfaction and significantly moderates the effects of the physical environment and corporate reputation, but not trust or price, on satisfaction. This research integrates
perceived value theory with the Stimulus–Organism–Response (S-O-R) model to provide new insights into customer behaviour in the post-pandemic hospitality context. The results offer actionable implications for hotel
restaurant managers seeking to rebuild consumer trust, optimise service value, and adapt to customers’ heightened health and safety concerns in the wake of COVID-19
A Systematic Literature Review of Explainable Risk Assessment Models for Bronchial Asthma
No full textBackground:
The reduced quality and risks to life brought on by Bronchial Asthma (BA) have heightened the need for trustworthy risk assessment solutions with deliberate interpretability and transparency. Improper management of BA such as ignoring
symptoms, improper inhaler technique or recent admissions to the ICU puts a patient at a higher risk of future asthma exacerbations, complications or even death. This paper details a systematic literature review on recent literature to identify and analyse current Explainable Artificial Intelligence (XAI) risk assessment models used in
Bronchial Asthma or the assessment of risk in healthcare using XAI.
Methods: A systematic review of English literatures was conducted through Science Direct, Association for Computing Machinery (ACM) Digital Library, Springer, PubMed, and Scopus from January 1, 2019 until October 26, 2023. All studies that
incorporated Explainable Artificial Intelligence or Risk Assessment Models for Bronchial Asthma or Health were included for this review. A combination and permutation of the following search terms was used: Explainable Artificial
Intelligence, Risk Assessment, Risk Assessment Model, Asthma, and Health.
Results: A total of 43 literatures were included after screening through 689 literatures
combined from the specified sources, with duplicates and materials not meeting the inclusion criteria removed. Among them, five of the literatures conducted research on asthma, while seven conducted research on lung related diseases using explainable machine learning or deep learning techniques. The model that had better performance when compared to the other models in the 12 most relevant literature out of the 43
was Extreme Gradient Boosting (XGBoost), with it having better performance two out of the three times it was compared to other models. The most common output was risk prediction with 36 literatures, followed by diagnosis with seven literatures and classification with one.
Conclusions: Explainable Artificial Intelligence has been used within the domain of asthma for diagnosis or prediction of future hospital visits, however there is a scarcity for studies on explainable predictive models for asthma exacerbation risks. Research on XAI within this domain has the potential to contribute towards explainability in
asthma risk prediction
Impact of anemia on clinical profile, treatment patterns and outcomes in heart failure: a retrospective cohort study
No full textBackground: Heart failure (HF) is a complex clinical syndrome associated with significant morbidity and mortality worldwide. Anemia are common comorbidities in HF patients and associated with poorer functional capacity and worse clinical outcomes. Despite advancements in HF therapies, the coexistence of anemia presents unique challenges in optimizing treatment. Current evidence highlights
the need for a better understanding of the baseline characteristics, treatment patterns, and outcomes in HF patients stratified by anemia status. Identifying
these differences may provide insights into the pathophysiology of HF and inform strategies for improving outcomes in this vulnerable population.
Objective: This study seeks to bridge this knowledge gap by comparing baseline demographics, treatment regimens, and clinical outcomes between HF patients with anemia and those without anaemia.
Methods: This retrospective cohort study analyzed 525 HF patients treated across 10 hospitals from January 2021 to June 2023. In this study, anemia is defined using hemoglobin (Hb) thresholds set by the World Health Organization (WHO):
men: Hb < 13 g/dL and women: Hb < 12 g/dL. Patients were divided into anemia (n=146, 27.8%) and non-anemia (n=379, 72.2%) groups based on hemoglobin levels. Baseline demographics, comorbidities, medication regimens, New York Heart Association (NYHA) functional class, and Ejection fraction (EF) were compared.
GDMT prescription and outcomes, including HF hospitalization, mortality, and a composite endpoint at 6 months, were assessed.
Results: Patients with anemia were older (60.7±14.3 vs. 54.5±13.6 years, p<0.001) and more frequently female (52.7% vs. 14%, p<0.001). Comorbidities, including diabetes mellitus (49.3% vs. 37.2%, p=0.009) and chronic kidney disease (41.1% vs. 23.7%, p<0.001), were more prevalent in the anemia group. The use of renin-angiotensin-aldosterone system inhibitors (RAAS) was significantly lower
in patients with anemia, even during follow-ups at 3 months (75.4% vs. 88.9%, p<0.001) and 6 months (79.4 % vs. 90.4%, p<0.001). Patients with anemia had worse functional status, with a higher proportion in NYHA Class 3 and 4 prior to the
clinic visit (42.4% vs. 24.9%, p=0.012) and at 6 months (9% vs. 2.2%, p=0.007).
EF was comparable at baseline between the two groups and improved similarly over time. Clinical outcomes revealed higher HF hospitalization rates in the anemia group
at 6 months (13% vs. 5.8%, p=0.006), though mortality (11.1% vs. 6.8%, p=0.112) and composite outcomes (20.5% vs. 14.8%, p=0.109) did not significantly differ.
Conclusion: HF patients with anemia exhibit a distinct clinical profile, with higher comorbidity burdens, worse functional status, and poorer treatment prescription
over time. These factors contribute to higher HF hospitalization rates and emphasize the need for tailored interventions to address the unique challenges faced by this
subgroup