Marine-derived natural products are rich source of secondary metabolites with huge potentials including novel therapeutic agents. Marine algae are considered to be a good source of secondary metabolites with versatile bioactivities. During the last few decades, researches related to natural products obtained from brown algae have remarkably escalated as they contain active compounds with varied biologically activities like antimicrobial, anticancer, antioxidant, anti-inflammatory, antidiabetic, and antiparasitic properties. The main bioactive components such as phlorotannin, fucoxanthin, alginic acid, fucoidan, and laminarin have been briefly discussed here, together with their composition and biological activities. In this review, the biological function of extracts and the metabolites of brown algae as well as their pharmacological impacts with the description of the possible mechanism of their action are described and discussed. Also, this study is expected to examine the multifunctional properties of brown algae that facilitate natural algal products, including the ability to integrate these functional properties in a variety of applications.

The objective of this work is to find the influence of fiber content, stacking pattern, and their sequence on the mechanical properties of hybrid composites. Hybrid composites in four varieties with five laminae containing different stacking sequences of jute/madar/glass fibers were fabricated using hand-layup technique with glass fiber woven mats as their skin layers that just enclose bio-fibers oriented horizontally. The stacking sequences were GJMJG, GMJMG, GJGJG and GMGMG where G, J, and M represents glass fiber mats, jute, and madar fibers, respectively. The fibers in the core layer were oriented perpendicular to the enclosing adjacent plies and they may be jute/madar fibers depending on the stacking sequence. Load Vs deflection curves show that stress and strain were linear and all the samples fail abruptly except the sample that contains high proportion of madar fibers. Jute fiber layers imparted more strength and energy-absorbing capacity, whilst madar fiber layers imparted more strain and toughness to the composites. Studies showed that intercalation of glass fiber mats as the core and skin layers exhibited a significant effect on the mechanical properties of the composites than other samples. The morphology of the fractured samples exhibited compatibility between matrix and reinforcements.

Image fusion can be performed on images either in spatial domain or frequency domain methods. Frequency domain methods will be most preferred because these methods can improve the quality of edges in an image. In image fusion, the resultant fused images will be more informative than individual input images, thus more suitable for classification problems. Artificial intelligence (AI) algorithms play a significant role in improving patient’s treatment in the health care industry and thus improving personalized medicine. This research work analyses the role of image fusion in an improved brain tumour classification model, and this novel fusion-based cancer classification model can be used for personalized medicine more effectively. Image fusion can improve the quality of resultant images and thus improve the result of classifiers. Instead of using individual input images, the high-quality fused images will provide better classification results. Initially, the contrast limited adaptive histogram equalization technique preprocess input images such as MRI and SPECT images. Benign and malignant class brain tumor images are applied with discrete cosine transform-based fusion method to obtain fused images. AI algorithms such as support vector machine classifier, KNN classifier, and decision tree classifiers are tested with features obtained from fused images and compared with the result obtained from individual input images. Performances of classifiers are measured using the parameters accuracy, precision, recall, specificity, and 1 score. SVM classifier provided the maximum accuracy of 96.8%, precision of 95%, recall of 94%, specificity of 93%, 1 score of 91%, and performed better than KNN and decision tree classifiers when extracted features from fused images are used. The proposed method results are compared with existing methods and provide satisfactory results.

Increased environmental concerns and global warming have diverted effort all over the world to focus on renewable and sustainable resources for the next generation of composite products due to their recyclability, renewability, cost effectiveness, and satisfactory mechanical performance. Bio/natural fibers which are environment friendly materials employed as reinforcement have led to developing a biocomposite for reduction in greenhouse emission and carbon footprints. However, biofibers are also having some limitations that need to be addressed including poor compatibility between the reinforcing fiber matrices, high moisture absorption, swelling, poor chemical and fire resistance, and high dispersion of mechanical properties. A lot of research has been performed on physical and mechanical properties of natural fiber composite. Properties of such novel composite mainly depend on adhesion between fiber and matrices. Consequently, poor adhesion, high moisture absorption, and swelling lead to formation of crack in both the matrix and fiber. Therefore, numerous techniques have been tried till date to modify both fiber surfaces to enhance their adhesion and reduce their water absorption. This review article provides comprehensive information about effect of various surface modification techniques that include alkaline, silane, acetylation, permanganate, peroxide, benzoylation, acrylonitrile grafting, maleic anhydride grafted, acrylation, and isocyanate. In addition, the effects of cellulose, hemicellulose, lignin, and pectin of biofibers are also reported. This review concluded that chemical treatment of biofibers with 5% NaOH concentration improves the physical, mechanical, and thermal properties of the resulting composites compared to untreated fiber composites.

3D printing, also called additive manufacturing (AM), is a method of creating 3D solid parts from a digital document. By utilizing additive routes, the fabrication of 3D‐printed objects can be made. These layers can be viewed as a gently cut level cross‐area of the manifest object. 3D printing is somewhat in obstruction to subtractive manufacture, which is expelling/discharging out a touch of metal or plastic for the occurrence of a milling machine. 3D printing authorizes creating multifarious profiles employing fewer materials than conventional fabrication systems. This review article provides the general idea of 3D printing production techniques, materials used, and applications in the aircraft and automobile industry and biomedical fields.