Hydroxyapatite-cellulose (HAp-cellulose) composites blend the bioactivity of HAp with the flexibility and biodegradability of cellulose, offering promise in biomedical and industrial fields. In healthcare, they aid bone regeneration, drug delivery, and tissue engineering due to their biocompatibility and porosity. Industrially, they excel in water purification and eco-friendly catalysis. With advancements in 3D printing and electrospinning, these composites enable custom implants and multifunctional scaffolds. Despite challenges in optimizing properties and scalability, future research targets hybrid materials, better fabrication, and regulatory compliance. Their role in smart therapies and environmental cleanup supports global sustainability and circular economy goals. This review summarizes key developments.
Rosa damascena essential oil (EO) of Kelaat M’gouna region was investigated for volatile composition, antioxidant activity, and antibacterial activity in this study. The EO yield was 0.05%, and gas chromatography-tandem mass spectrometry (GC/MS-MS) identified 57 compounds that represented over 99.95% of the total EO composition. Antioxidant activity was determined by DPPH, ABTS, and FRAP assays, showing good free radical scavenging activity as evidenced by an IC50 value of 454.68±10 μg/mL. Antibacterial activity was assessed through agar diffusion test, measurement of inhibition zone, and testing of minimum bactericidal concentration (MBC) and minimum inhibitory concentration (MIC). Gram-negative bacteria were less sensitive, with an inhibition zone of 9.83 to 11.67 mm, while Gram-positive bacteria were more sensitive, with an inhibition zone of 15.67 to 15.83 mm. The oil was found to possess antibacterial activity against Staphylococcus aureus , Micrococcus luteus , and Bacillus subtilis with MBC values of 400, 600, and 1000 μg/mL, and MIC values of 65, 62.5, and 125 μg/mL, respectively. These findings indicate the potential of Rosa damascena EO as a natural antimicrobial and antioxidant agent for application in the cosmetic and food industries. The results further suggest that incorporation of this oil with antibiotics could reduce the amount needed to treat nosocomial infections, perhaps limiting toxicity and treatment cost. Further studies are needed to comprehensively determine its therapeutic application.
Photovoltaic (PV) systems have become a significant role player in the energy transition. However, they are subject to various external environmental factors, whether during manufacturing, installation, or throughout their lifetime. They need efficient, fast, and intelligent inspection, especially when it comes to large-scale farms. In this sense, the combination of UAV imagery with deep learning (DL) techniques will allow quality control while improving the performance of PV systems and minimizing operation and maintenance costs. The main objective of our study is to propose a deep-learning approach based on the concatenation of two DL models to automate the process of detecting and classifying PV panel anomalies from aerial Infrared thermal images. The proposed concatenation is based on the transfer learning of two CNN architectures, namely VGG19 and DenseNet201. We adopt the ‘CAVIAR’ strategy, which involves training several models in parallel and then selecting the most effective and best-performing one. We applied our approach to a set of images of real solar farms, including 20,000 images with six (06) classes of anomalies. The results show that the proposed concatenation-based model obtained the best accuracy by extracting features from two robust deep networks. The solution was able to predict the presence of anomalies with an F1 score of 86
The technological quality and potential utilization of wood from individual Eucalyptus clones under Moroccan plantation conditions remain uncertain, particularly for clone 699 at the age and under the plantation conditions investigated in this study. This study aimed to evaluate the physical and mechanical properties of wood from a nine-year-old Eucalyptus camaldulensis clonal plantation (clone 699) in Morocco and to provide evidence on its potential for alternative wood uses. Ten logs from ten different trees were collected and processed into standardized test specimens. Physical characterization included moisture content, basic density, radial, tangential and volumetric shrinkage, and shrinkage anisotropy, while mechanical characterization included dynamic and static modulus of elasticity, bending strength, compression strength, and axial tensile strength. The studied wood showed high basic density (668kg/m³), medium volumetric shrinkage (14,53%), and normal shrinkage anisotropy (2,40), while its mechanical properties were generally in the low-to-intermediate range compared with previously reported Eucalyptus materials. Overall, the physical and mechanical characterization provides evidence on the technological quality of nine-year-old clone 699 under the studied plantation conditions and contributes to reducing uncertainty regarding its potential utilization beyond its traditional applications.
Climate extremes and their trends in several parts of the world have exacerbated the biophysical susceptibility of agrosystems in semiarid regions. In the Sahel region, this is reflected in a gradual deterioration in the climatic resilience of agrosystems and their ecosystem productivity, with potential losses in cereal yields of up to 27
