There are only 20 amino acids and a few modifications of them found in nature. Yet these few building blocks can generate a huge diversity of chains of different composition and length whereupon life is based. It can be estimated that only a minority of this diversity has evolved into proteins encoded by the genomes. There might be very specific rules that govern peptide-mediated interactions during protein folding and protein-protein interactions, but these may be so complex that we do not know them yet.

Elements of Power Electronics features a unifying framework that includes the physical implications of circuit laws, switching circuit analysis, and the basis for converter operation and control. It discusses dc-dc, ac-dc, dc-ac, and ac-ac conversion tasks and principles of resonant converters and discontinuous converters. The text also addresses magnetic device design, thermal management and drivers for power semiconductors, control system aspects of converters, and both small-signal and geometric controls.

Based on artificially intelligent agents, learning and search theory, and bounded rationality, this chapter makes an effort to embed a sound theoretical foundation for the computational process approach and agent-based microsimulations. A pertinent new theory is proposed with experimental observations and estimations to demonstrate agents with systematic deviations from the rationality paradigm. Procedural and multidimensional decision-making are modelled. The numerical experiment highlights the capabilities of the proposed theory in estimating rich behavioural dynamics.

This book reveals the underlying mechanisms of complexity and stochastic evolutions of traffic flows. Using Eulerian and Lagrangian measurements, the authors propose lognormal headway/spacing/velocity distributions and subsequently develop a Markov car-following model to describe drivers’ random choices concerning headways/spacings, putting forward a stochastic fundamental diagram model for wide scattering flow-density points. In the context of highway onramp bottlenecks, the authors present a traffic flow breakdown probability model and spatial-temporal queuing model to improve the stability and reliability of road traffic flows. This book is intended for researchers and graduate students in the fields of transportation engineering and civil engineering.

This chapter develops a simulation-based optimization (SBO) framework by integrating metamodels with mesoscopic simulation-based dynamic traffic assignment models for large-scale network modeling problems. The adopted SBO approach reconstructs the response surface by only a few evaluations of the objective function and is capable of handling simulation noises. The main benefit in computational timesavings can be achieved by using metamodels to construct response surfaces for predicting optimal solutions. This chapter provides a macroscopic understanding of urban traffic dynamics by using both a simulation-based dynamic traffic assignment model and heterogeneous traffic detection data. The simulation is validated by a representation of macroscopic fundamental diagrams (MFDs) using fixed traffic flow detections and probe travel time measurements. The SBO approach is demonstrated in a real-world large-scale transportation network that consists of arterials and freeways.

Many on-demand service platforms use a fixed payout ratio (i.e., the percentage of the platform’s revenue that is paid to the providers) regardless of the customer demand and the number of participating providers that tend to vary over time. In this chapter, we examine the implications of time-based payout ratios. To do so, we first present a queueing model with endogenous supply (number of participating providers) and endogenous demand (customer request rate) to model this on-demand service platform. In our model, earnings-sensitive independent providers have heterogeneous reservation price (for work participation) to serve wait-time and price-sensitive customers with heterogeneous valuation of the service. As such, both the supply and demand are “endogenously” dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We use the steady state performance (associated with the M/M/1 queue) in equilibrium to characterize the optimal price, optimal wage and optimal payout ratio that maximize the profit of the platform. We find that it is optimal for the platform to offer time-based payout ratios by offering a higher payout ratio during peak hours and a lower payout ratio during non-peak hours.

Mesenchymal Stem Cells in Human Health and Diseases provides a contemporary overview of the fast-moving field of MSC biology, regenerative medicine and therapeutics. MSCs offer the potential to dramatically reduce human suffering from disease. Numerous MSC-based studies are ongoing each year, each offering hope for novel treatments in human disease. This book provides information on MSC application in well-studied human diseases and tissue repair/regeneration and recent advances in their research and treatment. These discoveries are placed within the structural context of tissue and developmental biology in sections dealing with recent advances in our understanding of MSC biology.

Research into stem cells started in the 1960s with experiments on spleen cultures. Evans and Kaufman made a breakthrough in mouse embryo culturing and embryonic stem cell extraction in 1981, followed by the work of Thomson in 1998 on the technique for extracting human embryonic stem cells. Since then, stem cell research has rapidly expanded as a therapeutic avenue for different diseases in humans. This book explains the basic developmental biology of stem cells including the development of stem cells during the implantation stage in utero to the regulation of stem cell division. Medical applications of stem cells in the therapy of diseases such as cancer, neurodegenerative diseases, and bone diseases are also explained in subsequent chapters. The book also explains the effect of parasitic cells on stem cell growth. Concepts in the book are explained in a simple clear manner, making this book an informative reference for non-experts, students and professionals in the field of biology and medicine.

In this study, we propose a digital twin pilot study for bridge monitoring and maintenance. In particular, an infrastructure management framework using UAV and surveillance cameras, and accelerometers-based digital twins is proposed to perform long-term and non-interruptive monitoring. Real-world monitoring data are obtained through an experimental test performed on the Juanhu bridge (Haning, Zhejiang, China). Traffic flow and accelerometer data of the tested bridge were measured. The digital twin model of the bridge is created as a real-time Finite Element model in OpenSees. The FE model geometry is produced using a 3D photogrammetric reconstruction, and its dynamic properties are updated based on Bayesian modal identification. The traffic flow information on the bridge is processed through computer vision techniques using the video footage from the UAV and surveillance cameras. The object detection algorithm YOLO and tracking algorithm DeepSORT are used to derive the time-space diagrams. These elements operate in tandem with the accelerometer data and the digital twin FE model to acquire a preliminary vehicle loading estimation. The results are presented in this study and showcase the feasibility of the proposed digital twin framework for bridge monitoring and maintenance.

Neural crest cells are a migratory cell population and can generate different types of cells/tissues during embryonic and adult stages of vertebrate development, including neurons, glia, connective tissue, bone, cartilage, and both endocrine and pigment cells. Many studies have suggested that neural crest-derived stem cell populations persist into adulthood and are valuable cell sources for tissue repair and various regenerative medicine strategies. In adults, neural crest stem cells can be isolated from different tissues such as the skin and hair follicle. Recent studies have reported that tooth and dental tissues are easily accessible and rich source for neural crest-derived ectomesenchymal stem cells that can be used for cell-based therapy and regenerative medicine. Since they are preserved in adult human individuals and have a common origin with the nervous system, dental neural crest-derived ectomesenchymal stem cells have been suggested as excellent candidates for generation of neural cells/tissues for cellular therapy and applications in neuroregenerative medicine, ischemic stroke, and spinal cord injury. Herein, we will outline recent advances on the sources and therapeutic applications of neural crest stem cells, particularly for regenerative medicine and nerve tissue regeneration by cell therapy. We will also review recent advances in using dental and non-dental neural crest stem cells in neural tissue repair and regeneration