Advancements in the Additive Manufacturing of Magnesium and Aluminum Alloys through Laser-Based Approach.

Complex structures can now be manufactured easily utilizing AM technologies to meet the pre-requisite objectives such as reduced part numbers, greater functionality, and lightweight, among others. Polymers, metals, and ceramics are the few materials that can be used in AM technology, but metallic materials (Magnesium and Aluminum) are attracting more attention from the research and industrial point of view. Understanding the role processing parameters of laser-based additive manufacturing is critical to maximize the usage of material in forming the product geometry.

Adaptive Diagnosis of Lung Cancer by Deep Learning Classification Using Wilcoxon Gain and Generator.

Cancer is a complicated worldwide health issue with an increasing death rate in recent years. With the swift blooming of the high throughput technology and several machine learning methods that have unfolded in recent years, progress in cancer disease diagnosis has been made based on subset features, providing awareness of the efficient and precise disease diagnosis. Hence, progressive machine learning techniques that can, fortunately, differentiate lung cancer patients from healthy persons are of great concern.

Comprehensive characterization of natural cellulosic fiber from Coccinia grandis stem.

The anatomical, physico-chemical, mechanical, thermal and surface characteristics of Coccinia grandis fiber (CGF) were studied for a potential substitute to the harmful synthetic fibers. The anatomical analysis of Coccinia grandis stem reveals the presence of high strength xylem fibers. Polarized light microscopy and scanning electron microscopy of CGF shows a hierarchical cell structure composed of a primary and a secondary cell wall, cell lumen and the middle lamellae.