A Journey From Neural Networks to Deep Networks

The chapter is about deep learning fundaments and its recent trends. The chapter mentions many advanced applications and deep learning models and networks to easily solve those applications in a very smart way. Discussion of some techniques for computer vision problem and how to solve with deep learning approach are included. After taking fundamental knowledge of the background theory, one can create or solve applications. The current state-of-the-art of deep learning for education, healthcare, agriculture, industrial, organizations, and research and development applications are very fast growing. The chapter is about types of learning in a deep learning approach, what kind of data set one can be required, and what kind of hardware facility is required for the particular complex problem. For unsupervised learning problems, Deep learning algorithms have been designed, but in the same way Deep learning is also solving the supervised learning problems for a wide variety of tasks.

The Development of Biomimetic Aligned Skeletal Muscles in a Fully 3D Printed Microfluidic Device

Human skeletal muscles are characterized by a unique aligned microstructure of myotubes which is important for their function as well as for their homeostasis. Thus, the recapitulation of the aligned microstructure of skeletal muscles is crucial for the construction of an advanced biomimetic model aimed at drug development applications. Here, we have developed a 3D printed micropatterned microfluid device (3D-PMMD) through the employment of a fused deposition modeling (FDM)-based 3D printer and clear filaments made of biocompatible polyethylene terephthalate glycol (PETG). We could fabricate micropatterns through the adjustment of the printing deposition heights of PETG filaments, leading to the generation of aligned half-cylinder-shaped micropatterns in a dimension range from 100 µm to 400 µm in width and from 60 µm to 150 µm in height, respectively. Moreover, we could grow and expand C2C12 mouse myoblast cells on 3D-PMMD where cells could differentiate into aligned bundles of myotubes with respect to the dimension of each micropattern. Furthermore, our platform was applicable with the electrical pulses stimulus (EPS) modality where we noticed an improvement in myotubes maturation under the EPS conditions, indicating the potential use of the 3D-PMMD for biological experiments as well as for myogenic drug development applications in the future.

Graphene-based biosensors for disease theranostics: Development, applications, and recent advancements

Graphene, owing to its unique chemical structure and extraordinary chemical, electrical, thermal, optical, and mechanical properties, has opened up a new vista of applications, specifically as novel sensing platforms. The last decade has seen an extensive exploration of graphene and graphene-based materials either alone or modified with nanoparticles and polymers for the fabrication of nanoscale biosensors. These biosensors displayed excellent conductivity, high sensitivity, and selectivity, good accuracy, and precision, rapid detection with low detection limits as well as long-term stability. The unmatched properties of graphene and graphene-based materials have been applied for the detection of a number of chemical and biological molecules successfully for the diagnosis of a variety of diseases, pathogens, and biomarkers of the diseases. This review is aimed to cover the fabrication methods, functionalization techniques, and biomedical applications along with the recent advancements in the field of development of graphene-based biosensors. Recent clinical trials and patents as well as market trends and opportunities associated with graphene-based biosensors are also summarized. The application of graphene-based biosensors in the detection of SARS-CoV-2 causing COVID-19 is also reviewed.

Artificial Intelligence and Business Leadership Development: Applications and Solutions

Artificial intelligence (AI) is the promise of today and future businesses. Any leadership development model that ignores AI could miss out on modern business tools, technology, and resources. Though evaluations in developing business leaders present a positive relationship between AI and leadership development (Husain, 2017; Reese, 2018; Hosanagar, 2019), not many studies have been conducted in these areas. With Roomba Robots listening to social media and iRobot’s identifying customers and reaching out to them through private channels (Carr, 2011), a question arises: will AI be required to use business leadership practices in solving applicable challenges, or it will just be a marketing tool? Leadem (2017) quoted Colin Angle, iRobot’s founder, and CEO in an Entrepreneur Magazine, “I have been able to remain CEO, not because of the fact I was CEO yesterday, but because I've worked very hard to listen, learn and evolve in the seat." Developing business leaders could be rooted in AI knowledge, applicability, challenges, and solutions while paying attention to the three keywords of listening, learning, and evolving in leadership.

Fandom, Place Protection, and Urban Planning: Two Sporting Case Studies

This study explores the intersections between the study of sport and the study of the city through the extension of sport history to themes traditionally explored by geography—notably urban planning scholars. Its focus is two case studies related to urban planning decisions in early millennial Sydney, Australia. Through an examination of public submissions in response to building development applications made by two community-owned professional sports organizations competing in the National Rugby League, the study explores how modern sporting fandom complicates ideas about place and locality through forms of delocalization and glocalization. The authors conclude that when exploring the phenomenon of place protection, the built environment is not necessarily the primary factor informing a sense of place attachment in an urban environment.