Amman Arab University is a university in Amman, Jordan. It is mainly for graduate studies..
The development of sustainable, plant-derived antimicrobial polymeric biomaterials is increasingly important for managing infections associated with wound environments, particularly in the context of rising antimicrobial resistance. In this study, low-cost bacterial cellulose (BC) was produced using waste-derived fruit media and subsequently modified with Croton confertus leaf extract (CE) through an ex situ infusion process to obtain bioactive BC-CE composites. The physicochemical structure of the composites was characterized using FE-SEM and FTIR analyses, which confirmed successful incorporation of phytochemicals into the nanofibrillar cellulose matrix and demonstrated reduced porosity, enhanced hydrogen-bonding interactions, and improved microstructural stability. BC-CE films revealed better moisture-retention capabilities than pure BC, maintaining structural stability for repeated swelling/drying cycles. Antibacterial performance indicated clear inhibition zones (1.28 cm for Staphylococcus aureus and 1.11 cm for Escherichia coli) and substantial growth containment, with 46% and 36% reductions in bacterial proliferation, respectively. In vivo wound-healing experiments further demonstrated accelerated epithelial regeneration and reduced inflammation in BC-CE-treated wounds compared to BC control dressings. Collectively, these findings highlight the synergistic benefits of integrating plant-derived phytochemicals within a sustainable BC platform, providing a cost-effective and biocompatible polymeric biomaterial with promising potential for next-generation wound-care applications with antimicrobial functionality.
Griseofulvin, a common antifungal, suffers from poor solubility and skin penetration, limiting its topical efficacy. The main purpose of the study is to develop and characterize a griseofulvin-loaded transfersomal gel to enhance topical delivery and sustain antifungal activity. The transfersomes were prepared by thin-film hydration with varying ratios of lecithin and Tween 80 and evaluated for vesicle size, morphology, and entrapment efficiency (EE). The optimized formulation (GRF7) had the highest EE (98.02 ± 0.55
In this research work, the new subclass Upsilon=,a,L,m,phi(qe) of bi-univalent functions related to Fibonacci numbers Sigma is presented. Our primary contributions to this for functions in this particular subclass, the study entails placing restrictions on the absolute values of the second coefficient |a2| and the third coefficient |a3|. Furthermore, Fekete-Szeg & ouml; functional problems are solved by us. In addition, our analysis shows interesting results from the particular parameter values applied in our primary conclusions.
The growing importance of digital technologies in industrial environments has increased academic and managerial interest in understanding how Internet of Things (IoT) adoption can improve sustainability performance. Industrial firms are under rising pressure to enhance resource efficiency, reduce environmental impact, and support long-term sustainable operations. Despite the expanding relevance of IoT in industrial transformation, limited empirical research has examined its effect on sustainability performance through renewable energy and under the influence of green logistics capability. Grounded in the Resource-Based View, this study investigates the impact of IoT adoption on sustainability performance in the industrial sector, while examining the mediating role of renewable energy and the moderating role of green logistics capability. A quantitative approach was adopted, and data were collected from industrial firms using a structured questionnaire. Partial Least Squares Structural Equation Modeling was employed to test the proposed hypotheses. The findings reveal that IoT adoption has a significant positive effect on sustainability performance. Renewable energy was found to mediate this relationship, while green logistics capability strengthened the positive influence of IoT adoption on sustainability performance. The study contributes to the literature by presenting an integrated model that connects digital adoption, renewable energy, green logistics capability, and sustainability performance.
A hybrid parallel storage system is a system which has a hierarchy of storage; each is a primary or secondary storage device, which has significantly different rates of reading the data. The more one goes up the storage hierarchy, greater will be the speed of data access. Moving critical application data to higher levels can greatly lessen application I/O wait time. In general, it assists in cutting down the total time consumption of the app to finish a process. This study presents a prototype of a two-level parallel hybrid storage system with SSD and HDD. The proposed system uses data mining methods to systematically evaluate and classify the application data. While the application runs and requests data, the solution at the same time works to reactively predict what data will be useful next. Data blocks that are classified as high priority are automatically elevated to SSD within the same hybrid cloud storage disk group. With the help of simulation, the data migration strategy backed up by data mining will improve user productivity. The application execution time decreases significantly if any of the application's data access trace is particular and over 57.21% is used. New hybrid storage architectures paired with predictive data management help applications run faster than ever before.
