Daffodil International University

Digital Transformation and Environmental Pillar of ESG ‐Based Performance Under Financing Constraints: The Mediating Role of Green Innovation in Chinese Listed Firms

ABSTRACT This study builds upon existing work that links digital transformation (DT), financing constraints (FC), green innovation (GI), and firms' environmental pillar of ESG‐based performance (SP(E)), and further examines whether DT supports SP(E) through GI under FC. Based on...

Understanding Hepatitis B–Related Knowledge, Attitudes, and Practices Among Nurses of a Selected Tertiary Hospital in Northwestern Bangladesh

ABSTRACT Background and Aims Hepatitis B virus (HBV) infection remains a global health concern, with nurses being particularly vulnerable to occupational exposure. In Bangladesh, however, there is limited understanding of the knowledge, attitudes, and practices (KAP) of nurses co...

Is AI adoption a pro-environmental choice? Integrating value-belief-norm theory and theory of planned behavior

Purpose Artificial intelligence (AI) could be essential to helping organizations improve efficiency and enable quick, accurate decision-making. This study investigates the adoption behavior of AI technology from an ecological perspective. Using the value-belief-norm (VBN) and the...

Evidence-based evaluation of berberine in neurodegenerative diseases: targeting multiple signaling pathways and modulating neuroinflammation, oxidative stress, and apoptosis

Neurodegenerative diseases (NDs), such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), are characterized by progressive neuronal loss, oxidative stress, mitochondrial dysfunction, and neuroinflammation. Novel neuroprotective drugs are urgently required since existing tr...

From tradition to smart agriculture: how value and technology readiness shape farmers’ adoption decisions

Purpose This study aims to investigate the slow adoption of smart farming technologies (SFTs) in developing regions, where farmers continue relying on traditional methods despite modernization policies. It examines how farmers’ value perceptions and technology readiness (TR) shap...

Productivity, institutional environments, and international contract success: asymmetric moderation evidence from Japanese construction firms

International projects are central to construction firms’ growth, yet whether firm productivity predicts international contract success and why productivity advantages translate differently across institutional settings remain underexplored. This study examines how firm productiv...

Influencer marketing and consumer engagement in shaping the relationship between pro-environmental behavior and sustainable consumption

To explore the relationship between pro-environmental behaviour and sustainable consumption and to assess the mediating effects of cognitive, emotional and behavioural engagement, as well as the moderating effect of influencer marketing, within the Stimulus-Organism-Response (S-O...

Toward Reproducible Local Evaluation of Prompt Injection in Open-Weight LLMs: Design and Threat Model

Open-weight language models are increasingly deployed in local and edge environments, yet their robustnessagainst prompt injection and system-prompt leakage remains poorly quantified under reproducible conditions.Existing large-scale benchmarks largely target hosted, API-served m...

Toward Reproducible Local Evaluation of Prompt Injection in Open-Weight LLMs: Design and Threat Model

Open-weight language models are increasingly deployed in local and edge environments, yet their robustnessagainst prompt injection and system-prompt leakage remains poorly quantified under reproducible conditions.Existing large-scale benchmarks largely target hosted, API-served m...

What survives? Semantic eligibility, distribution shift and metric interpretation in external validation of ADMET predictors

Machine-learning models for absorption, distribution, metabolism, excretion and toxicity (ADMET) are usually reported on benchmark splits drawn from the same curated collections used to train them. External validation is rarer, and when it is attempted, the assumption that a publ...

Developing environmental performance in the Bangladesh banking sector: role of fintech, climate finance and environmental awareness

This study aims to investigate the relationship between climate banking and the environmental performance of banks in Bangladesh, focusing on climate finance, environmental awareness, and the role of FinTech. The study used the partial least squares structural equation modeling (...

Sustainable Dyeing and Mordanting of Silk with a Binary Colorant from Agro-Waste Material

The use of agro-waste materials as an alternative to synthetic dyes has gained considerable interest in the development of sustainable textile coloration. This study investigates the utilization of binary colorants from agro-waste sources such as harmal seeds and thuja leaves for...

Design, RLC equivalent circuit modeling, and ML/DL-based performance prediction of a graphene MIMO antenna for 6G THz systems

Intense interest in ultra-high-speed, low-latency, and large-capacity wireless communication has accelerated the development of terahertz (THz) antenna systems for sixth-generation (6G) networks. This work presents a compact graphene-based 1 × 2 multiple-input, multiple-output (M...

Physicochemical properties, fatty acid composition, and trans fat content of unlabeled bakery products in Bangladesh: implications for food safety and regulation

The physicochemical characteristics and fatty acid composition of bakery products are key determinants of nutritional quality and stability. This study aimed to generate baseline data on unlabeled bakery products in Bangladesh by evaluating their physicochemical properties, fat c...

Triple band Yagi antenna design and performance prediction for next generation (6G) wireless applications using supervised regression models

This study presents a high-performance Yagi antenna designed for sub-terahertz (sub-THz) and terahertz (THz) wireless communication applications, addressing the growing demands of emerging technologies such as high-resolution imaging, short-range secure communication, sensing, sp...

A systematic review of machine learning and explainable artificial intelligence for electrocardiogram based cardiovascular disease prediction

Cardiovascular disease (CVD) are a leading cause of global morbidity and mortality, making early and accurate detection essential for improving patient outcomes. The electrocardiogram (ECG) is one of the most important diagnostic tools for identifying various cardiac abnormalitie...

Current cybersecurity threats to patient safety in the operating room: a review

Abstract Surgical, anesthetic, and intensive care practices now depend on a large ecosystem of wired and wireless devices, robotic consoles, imaging and laboratory systems, and cloud infrastructure: the Internet of Medical Things and the smart operating room, which extends care b...

Congestion Propagation Identification and Prediction Using Self Attention–Based Diffusion Convolutional Approach

Abstract Traffic congestion frequently propagates among the interconnected road networks over time, driven by spatial and temporal factors. Identifying and predicting these patterns is crucial for effective public transport management and urban planning. Existing systems often fa...

Detection of cardiovascular conditions using ECG image analysis: an evaluation of DenseNet121, InceptionV3, and a hybrid deep learning model

Cardiovascular diseases remain a leading cause of mortality worldwide, necessitating rapid and accurate diagnostic tools. Electrocardiogram (ECG) image analysis using deep learning offers a promising avenue for automated detection, yet model performance and generalizability requi...

Environmental Transparency Through Digital Transformation: Evidence on Carbon Disclosure Quality From China's Heavy‐Polluting Firms

ABSTRACT The rise of digital transformation (DT) has become an important driver of transparency in corporate environmental disclosure. Whether and how DT is related to the improvement of carbon information disclosure quality, particularly in heavily polluting firms that may have...