Nano-biosorbents for Decontamination of Water, Air, and Soil Pollution explores the properties of nanobiosorbents and their applications in the removal of contaminants from the natural environment. The use of nanobiosorbents for environmental protection is a combinational approach that incorporates nanotechnology with naturally occurring biopolymers that form an amalgamation of nano-biopolymers used as sorbent materials in the removal of a variety of contaminants from wastewaters. This is an important reference source for materials scientists, bioscientists and environmental scientists who are looking to understand how nanobiosorbents are being used for a range of environmental applications.

Smart Polymer Nanocomposites: Design, Synthesis, Functionalization, Properties, and Applications brings together the latest research on synthetic methods and surface functionalization of polymers and polymer composites for advanced applications. Sections cover the basic principles of advanced polymer nanocomposites, including morphology, materials, characterization, and copolymerization, provide in-depth coverage of synthetic methods, facilitating the preparation of polymeric nanoparticles with the required properties, examine the morphologies of polymer nanocomposites and stimuli-responsive surfaces, and focus on cutting-edge approaches to tailoring polymeric nanocomposites according to the requirements. The book's final chapters focus on smart polymer nanocomposites for specific advanced applications, including high-temperature environments, bone tissue regeneration, biomedicine, wastewater treatment, dielectric and energy storage, chiral separation, food packaging, sensing, and drug delivery. This is a valuable resource for researchers and advanced students in polymer science, composite science, nanotechnology, and materials science, as well as those approaching the area from a range of other disciplines, including industry R&D.

Significant performance gains are achievable in wireless systems using a Multi-Input Multi-Output (MIMO) communication system employing multiple antennas.This architecture is suitable for higher data rate multimedia communications.One of the challenges in building a MIMO system is the tremendous processing power required at the receiver. MIMO Symbol detection involves detecting symbol from a complex signal at the receiver. Nature Inspired techniques for non-linear approximate MIMO detectors with a low complexity near-optimal performance is presented. The approach is particularly attractive as Swarm Intelligence (SI) is well suited for physically realizable, real- time applications, where low complexity and fast convergence is of absolute importance. Application of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms is studied. While an optimal Maximum Likelihood (ML) detection using an exhaustive search method is prohibitively complex, it is established that Swarm Intelligence optimized MIMO detection algorithms gives near-optimal Bit Error Rate (BER) performance, thereby reducing the ML computational complexity significantly