Research Title: The Difference Between Conventional and Simulation-based BLS Training on Nursing Students’ Knowledge Acquisition and Self-Efficacy in Jordan

Author: Ahmad Mohammad Hassan Al-bashaireh, Published Year: 2026

Al-Rafidain Journal of Medical Sciences, 10 (2)

Faculty: Nursing

Abstract: Background: Advanced technology in education and training is a challenging task that requires appropriate assessment of new, innovative methods. Objective: To evaluate the difference between conventional and simulation-based basic life support (BLS) training on nursing students’ knowledge acquisition and self-efficacy. Methods: A pretest-posttest quasi-experimental design was utilized. 87 nursing students (43 in the control and 44 in the intervention groups) were recruited. The data were analyzed using descriptive statistics, an independent-samples t-test, a paired-samples t-test, Spearman's correlation, ANCOVA, and a multiple linear regression. Results: Significant differences were reported in exam scores between the intervention control groups pre- and post-intervention. Post-intervention exam scores were statistically higher in the simulation group (difference= 2.8), with both groups achieving pass scores. Significant differences between the groups in the total self-efficacy scores for resuscitation were reported. ANCOVA results showed significant differences in exam scores between the two groups (p=0.013), and the intervention had a significantly positive effect on students’ knowledge (7% of the variance in exam scores) (η²=0.07). Conclusions: Students' BLS knowledge and self-efficacy significantly improved after training, regardless of the training method, although simulation-based training showed statistically significant improvement in BLS knowledge acquisition. The modest difference indicates limited educational significance, particularly in the context where conventional training already achieves the competency threshold. Educators and policymakers should consider including simulation-based BLS training in nursing education. However, traditional BLS training is still efficient in improving student knowledge and self-efficacy, especially in limited-resource countries.

Keywords: BLS; Cardiopulmonary resuscitation; Knowledge; Nursing students; Simulation training; Self-efficacy.

Research Title: Enabling digital service innovation in logistics and supply chains: a framework from an institutional perspective

Author: Mohammad Mahmoud AbdulMajeed Al-Nadi, Published Year: 2026

Business Process Management Journal,

Faculty: Business

Abstract: Purpose This study investigates the organisational and institutional factors that influence the successful implementation of digital service innovation (DSI) in logistics organisations and operations. Specifically, it seeks to develop an understanding of the mechanisms of how specific key enablers and barriers within Logistics and Supply Chain Management (L&SCM) organisations impact the success of DSI initiatives. Design/methodology/approach An inductive, theory-informed qualitative study using grounded-theory-inspired coding techniques was used to analyse how organisational factors influence DSI in L&SCM. Qualitative interviews were conducted to collect data from 25 participants. Iterative constant comparison was used to compare emerging codes to ensure high consistency in the analysis process. Then, a focus group workshop was used to facilitate a participatory analysis, which helped in an in-depth exploration of DSI in the logistics context. The focus group tool helped develop the framework by categorising the factors that emerged from the interview analysis into core themes based on the interplay between enablers and inhibitors. Findings A framework emerged for facilitating DSI in L&SCM operations, which consists of four interconnected core themes: Organisational Readiness, Technological Capability, Collaboration and Organisational Adaptability. These core themes work together to enable DSI, which is encased by certain enablers and inhibitors. This study shows that although resistance to change, legacy systems and financial constraints create significant barriers to the implementation of DSI in logistics organisations, key enablers such as leadership commitment, strong technological infrastructure, collaboration with external partners and active employee engagement play a crucial role in addressing these obstacles and driving successful digital innovation. Originality/value This study makes an original contribution by using an inductive, theory-informed qualitative study using grounded-theory-inspired coding techniques to explain unique institutional factors of DSI adoption in the logistics context. The study shows the dynamic interplay of organisational practices and dimensions of technological structures that influence DSI implementation through the involvement of industry professionals in the participatory analysis method. It presents a framework developed directly from the research data, offering a well-grounded perspective on what drives successful DSI implementation. It also shows interesting perceptions, not only for academics but also for industry professionals and managers who are trying to implement DSI successfully, by mitigating the challenges that logistics organisations can face.

Keywords: Innovation, Service, Logistics, Supply chain, Framework

Research Title: Digitalisation of food supply chains: transformation factors for sustainable logistics in the digital era

Author: Mohammad Mahmoud AbdulMajeed Al-Nadi, Published Year: 2026

Journal of International Logistics and Trade ,

Faculty: Business

Abstract: Purpose This study aims to identify and explore the factors crucial in facilitating the digital transformation in food supply chains within the context of the food industry. Design/methodology/approach A qualitative study that depends on interviews with potential food supply chain players was used accompanied by a grounded theory methodology through an iterative process. Thirty-one interviews were conducted with food supply chain stakeholders: suppliers, logistics providers and retailers. NVivo programme was used for the analysis. Following this, a focus group workshop was conducted to categorise the themes into highly abstracted core factors. Findings The study identified six core factors that are vital for digital transformation: training, collaboration and communication, management support and commitment, security, data integration, and supply chain tracking and monitoring. These core factors are derived from workshop discussion, which highlight particularly the vital role of training, and management support and commitment. Each core factor consists of low-level themes; 12 low-level themes emerged from the analysis. These findings highlight the role of transformation factors in facilitating digitalisation in food supply chains. Originality/value This study presents a framework to help stakeholders overcome obstacles in digitising the food supply chain and improving efficiency and food security, particularly in developing countries. This research provides a framework of core factors accompanied by low-level themes that give detailed explanations of how organisations can leverage digital technologies to optimise their supply chains. The framework also establishes a reference point for future studies to add or refine these factors. As the industry continues to embrace digital transformation, it is crucial for stakeholders to carefully consider the opportunities and challenges that come with these technological advancements to fully leverage their benefits.

Keywords: Digitalisation, Food security, Supply chains, Logistics, Factors, Blockchain, Internet of things IoT, Cloud computing, Artificial intelligence AI, Cybersecurity

Research Title: نقد الشعر والشعراء في كتاب (الغصون اليانعة) لابن سعيد الأندلسي

Author: Omar Faris Yousif AlKafaween, Published Year: 2026

مجلة جامعة الشارقة للعلوم الإنسانية والاجتماعية, مجلد 23/ العدد 2

Faculty: Arts

Abstract: تناولت هذه الدراسة قضية نقد الشعر والشعراء في كتاب (الغصون اليانعة) لابن سعيد الأندلسي، الذي ترجم فيه لثمانية وعشرين شاعرًا مشرقيًّا ومغربيًّا، من الذين عاشوا في القرن السابع الهجري، وهدفت إلى رصد آرائه حول الشعراء وشعرهم ودراستها وتصنيفها، معتمدة المنهج الوصفي لدوره في هذا الرصد والتصنيف، وقدرته على محاورة تلك الملحوظات النقدية التي ذكرها مؤلف الكتاب، ووضعها تحت قضايا مستقلة عن بعضها، وخلصت إلى أن ابن سعيد قيّم الشعراء على أساس معايير محددة، تتمثل بالأدبية والشهرة والبراعة والفقه والفلسفة وغيرها، واستحسنها فيهم، وقيّم بعض أشعارهم من خلال معايير ترتبط بالمعاني والألفاظ والبلاغة، معتمدًا في ذلك على الانطباعية والذوق.

Keywords: ابن سعيد الأندلسي، الغصون اليانعة، النقد

Research Title: An AI-Driven Mathematical Framework for Optimizing Cloud Computing Adoption in Pharmaceutical Institutions

Author: Eman Fares Mousa Al-Mashagbah, Published Year: 2026

Applied Mathematics & Information Sciences, 6

Faculty: Information Technology

Abstract: Cloud computing solution has been in recent years incorporated in the e-business sectors i.e., the pharmaceutical industries as data storage and backup support, and also for numerous uses and purposes like collaboration with in-house research staff, support legal liability management audit, help business to grow etc. Furthermore, many of the successful applications of cloud computing in the business sector may not necessarily be replicated in the pharmaceutical industry because of various reasons. This research explores the influential factors of the extent to which pharmaceutical companies have adopted cloud computing, the existing cloudy issues, and how firms can go about undertaking such changes for purpose of combining it with performance improvement and competitive advantage. A model calling on data security, regulatory barriers, system compatibility, economic conservativeness, organizational conditions, moderation and management indicators is used for the analysis. This is because this framework interests’ ways of operations within an economic environment characterized by the given institutional boundary and attempts to capture the aspects of data values and technology limits. The study also establishes that even though cloud adoption offers great potential in improving accessibility to information, effective organizational outcomes, and innovative capacity, the major issue of concern remains in governance of data such as minimizing, regulatory issues that endanger pharmaceutical industry dimensions and promotion of change in the organization. The study further allows to understand the remedial measures that can be put in place to support decision-making processes among the management of the pharmaceutical organization and assess the importance of preparedness for cloud computing for meeting long-term goals of the organizations.

Keywords: Cloud computing adoption, pharmaceutical institutions, Digital transformation, Regulatory compliance Strategic decision-making.

Research Title: WHOLE EXOME SEQUENCING IDENTIFIES CANDIDATE VARIANTS IN JORDANIAN PATIENTS WITH INBORN ERRORS OF IMMUNITY

Author: Marwan Abu-Halaweh, Published Year: 2026

36th ANNUAL CONFERENCE OF THE AUSTRALASIAN SOCIETY OF CLINICAL IMMUNOLOGY AND ALLERGY (ASCIA), Te Pae Christchurch Convention Centre, New Zealand

Faculty: Science

Abstract: Background Inborn errors of immunity (IEI) refer to a diverse group of more than 480 disorders affecting the immune system. These conditions can lead to serious health challenges, including recurrent infections, autoimmune diseases, and even cancer. Although IEI are considered rare worldwide, they occur more frequently in Jordan, largely due to the high rate of consanguineous (within-family) marriages. Because these disorders are complex and vary widely, advances in genomic technologies have become essential for identifying the underlying genetic causes and improving diagnosis. Thus, rapid and accurate identification of the underlying genetic variants and affected immunological pathways is necessary, as it allows timely treatment to prevent life-threatening infections and irreversible organ damage. In this context, next generation sequencing (NGS), specifically whole exome sequencing (WES), has revolutionized the diagnosis of genetic diseases. It offers a powerful and increasingly cost effective tool for uncovering the genetic basis of these conditions, enabling earlier intervention and more personalized patient care. Methods In this study, we applied WES in patients from eight families of Jordan descent. The validation and segregation of the identified variants were performed by Sanger Sequencing. Results Homozygous candidate variants that may be relevant for the patients phenotype include one in GPSM1 (c.1283C>A, stop gained; p.Ser428Ter) and another in IFIH1 (c.2891G>A; p.Cys964Tyr). In addition, a CTC/CT frameshift mutation (L/X) was detected in GPSM1 in patient PID 32, and a TCTGGTCTT in frame insertion (p.V42VWSF) in IL17RC in patient PID 35. IL21R (c.563del, p.Leu188Argfs*43) have been identified. Another 2 samples show heterozygous candidate variants relevant to the patient phenotypes in UNG (c.262C>T, p.Arg88Cys) and COL4A1 (c.2705C>G, p.Pro902Arg), as well as variant in BLNK c.677+1G>A, p.? Conclusion Our findings indicate that WES is a useful approach for the identification of pathogenic variants associated with PIDs. More studies are still necessary to confirm the genotype-phenotype correlation at the functional level.

Keywords: WHOLE EXOME SEQUENCING, VARIANTS, INBORN ERRORS OF IMMUNITY, Jordanian, Immunity

Research Title: Protecting Cloud Computing from Various Attacks Using Deep Learning Algorithms

Author: Fadi Mohammad Al-Shimat, Published Year: 2026

IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT 2026), Amman

Faculty: Information Technology

Abstract: This study takes a close look on how well deep learning models can find cyber threats in Cloud Based Intrusion Detection Systems. Increasing amounts of organizations are using cloud services, and as this number grows many organizations need an effective and resilient way to identify intrusions when cyber threats continue to grow in number and sophistication. Our research is a crucial part of ongoing research into this field by analyzing how good different deep learning models are at detecting and classifying cyber-attacks that occur in a cloud based environment. We applied a number of different performance measurements (accuracy, recall, precision, F1 score, confusion matrix), to several different types of deep learning models (CNN, Long Short Term Memory LSTM) in order to determine how applicable they are to real world intrusion detection systems. We utilized the NSL-KDD dataset, and found that LSTM achieved the highest performance, while still having a solid balance between both accuracy and precision/recall. Our results demonstrate the enormous promise of ensemble and gradient boosting techniques in helping to increase the detection capabilities of cloud based IDSs. Our results illustrate the importance of deep learning in increasing the reliability, robustness, and efficiency of intrusion detection systems used in cloud environments, and ultimately contributes significantly to the security of our digital ecosystems.

Keywords: Cloud Computing, Cyber Attack, Deep Learning, Intrusion Detection System

Research Title: Arabic Vishing Detection Model Using Random Forest

Author: Ahmad Abedel- elah Mahmoud Momani, Published Year: 2026

The 2nd IEEE 2026 International Conference on Cybersecurity and AI-Based Systems (Cyber-AI 2026) , Bucharest, Romania

Faculty: Information Technology

Abstract: Voice phishing (vishing) is a form of social engineering attack that relies on voice communication to deceive individuals and obtain sensitive information, including bank credentials, authentication codes, and personal data. These attacks typically involve impersonating trusted entities, which increases their effectiveness, particularly in real-time interactions. Although vishing has been studied in several contexts, limited attention has been given to Arabic-language scenarios. This is mainly due to the lack of publicly available datasets, the variability of Arabic dialects, and the difficulty of combining speech processing with text-based analysis within a single framework. In this work, we propose a context-aware Arabic vishing detection framework that integrates automatic speech recognition, machine translation, natural language processing, semantic feature extraction, and machine learning classification. The system converts speech into text using Whisper, followed by translation into English, and uses Word2Vec to capture semantic relationships in the extracted text. A Random Forest classifier is then used to perform the final classification. The proposed approach was evaluated on a translated version of the KorCCVi-v2 dataset, achieving an accuracy of 99.77%. The results indicate that the combination of speech and text processing can support the effective detection of vishing attempts in Arabic environments. However, several challenges remain, including translation noise, dataset bias, and the need for validation under real-world conditions.

Keywords: Vishing, Voice Phishing, Arabic NLP, Whisper, Random Forest, Machine Learning, Cybersecurity, Word2Vec

Research Title: Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet and brain health: a systematic review

Author: Fuad Abdul Rahman Taha Abdulla, Published Year: 2026

Nutritional Neuroscience, 29 (7)

Faculty: Allied Medical Sciences

Abstract: ABSTRACT Introduction: By 2050, the global population aged 60+ is expected to reach two billion. As the population ages, the prevalence of neurodegenerative disorders will increase, while depression and anxiety will continue to be major causes of disability. A diet rich in antioxidants can positively impact cognitive function and protect against psychological disorders. Objective: to summarize the evidence of the impact of the MIND diet in reducing risks or slowing neurodegenerative and psychological diseases. Methodology: The data were collected by searching electronic databases, including PubMed and Science Direct, until September 2023. The search terms included ‘Alzheimer’s, Anxiety, Brain Health, Cognitive Decline, Dementia, Depression, Parkinson’s, MIND diet, and psychological disorders.’ Peer-reviewed studies conducted on individuals aged 18 or older were included. 135 papers were identified and reviewed. 26 full-text, relevant original articles were included. Results: The study analyzed a sample of 37 to 16,058 participants, ages 20–97. Among the identified studies, 6 RCTs, 11 cross-sectional studies, and 9 longitudinal studies were analyzed. The results indicate that adherence to the MIND diet slows cognitive decline and positively influences cognitive function and verbal memory in later life, reducing the risk of developing Parkinsonism, non-motor symptoms, depressive symptoms, and lowering stress levels. Conclusion: Our systematic review implies that the MIND diet can enhance cognitive health and is highly beneficial for mitigating risks of dementia, physiological diseases, anxiety, and depression due to its superior antioxidant and anti-inflammatory activities. However, further research is required to evaluate its long-term effects on health.

Keywords: Alzheimer’s disease, anxiety, brain health, cognitive decline, depression, mental, obesity, psychological disorders

Research Title: Computational Molecular Docking and Molecular Dynamics Simulations of Potential Inhibitors from Cistus incanus (Cistaceae) Against Ebola Virus

Author: Wafa Moh'd Khair Hourani, Published Year: 2026

Faculty: Pharmacy

Abstract: Background/Objectives: Until now, there have been no suitable medicines to treat infections caused by the Ebola virus. Cistus incanus, a traditional medicinal plant, contains several phytocompounds exhibiting antioxidant and anti-inflammatory properties. Methods: In this research, the molecular level interactions of the phytocompounds of Cistus incanus were investigated for their antiviral potential against the active site of VP40 protein of Ebola virus using in silico molecular docking. Further, the potential compounds were assessed for their stability in the protein using molecular dynamics (MD) simulations. Results: Methyl gallate, catechin, and quercetin showed excellent docking scores of −9.8, −8.8, and −7.7 kcal/mol, respectively, and favorable interactions with the target protein. These complexes showed good stability over the 100 ns MD simulation time. In addition, the phytocompounds displayed favorable pharmacokinetics and drug-like properties. Conclusions: Our study offers the antiviral potential of phytocompounds (methyl gallate, catechin, and quercetin) of Cistus incanus, suggesting their suitability as lead candidates for the treatment of Ebola viral infection.

Keywords: Cistus incanus; Ebola virus; molecular docking; molecular dynamics simulation; pharmacokinetics; VP40 protein