The Internet-of-Things (IoT) revolution has triggered the need of massive connectivity for billions of devices requiring a system capacity which is far beyond the current network designs that can be supported. This emerging requirement has reshaped the society and industry in pursuing efficient communication paradigm. In particular, massive machine-type communications (mMTC) will be a prime driver for enabling the vision of scalable IoT with heterogeneous applications, where the massive access is of paramount importance. This book discusses important massive IoT scenarios and the key technical requirements of the corresponding massive access. We review the state-of-the-art IoT standards and mMTC solutions, and summarize the limitations of the existing schemes from the perspectives of the network architecture, random access procedure, and multiple access techniques. Here, we specify the massive access challenges and reveal that the facilitation of MTC invokes a dramatically different access scheme from current ones mainly designed for human-centric communications. Moreover, we propose several promising massive access solutions to overcome the limitations, where sufficient theoretical model and algorithm design guidance are provided. Besides, detailed simulation and engineering implementation methods are also included.
The book focuses on the advanced mmWave/Sub-terahertz ultra-massive MIMO wireless communications, which are regarded as a promising paradigm shift in future 5G beyond and even 6G. This is achieved by providing a comprehensive review of the rapidly developing field of massive MIMO communication, in-depth discussions on the impact of extremely large-scale antenna array, and detailed numerical simulation results on our proposed schemes. Several case studies are given after introducing basic communication system components, and the simulation codes are open sourced in our book, which shows the reproducibility of our models and methods and provides convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.
The advance of experimental technologies in biology, including complete genome sequencing and high density microarray, has enabled biologists to collect molecular biology data at an unprecedented pace and scale. However, due to the diverse types and enormous amount of data from these high-throughput experiments, more sophisticated computational methods are urgently needed to analyze them in order to reveal useful biological insight. In this dissertation work, we identified several critical challenges in modeling gene transcriptional regulatory networks, and developed machine learning based algorithms to address these challenges. First, we proposed a genome-wide cis-regulatory motif discovery approach by combining promoter sequences and gene co-expression networks to predict the cis-regulatory motif of each individual gene, thereby overcoming the disadvantages of current clustering based methods that often fail to provide gene- specific or species-specific predictions. Second, we developed a multi-instance-learning based method to model the physical interactions between transcription factors (TF) and DNA, which, by better handling of DNA sequence regional information, significantly outperformed traditional single-instance-learning based methods in predicting both in vivo and in vitro TF-DNA interactions. Finally, we proposed a novel TF-DNA interaction model by utilizing structural features with multi-instance learning, which further improved the accuracy of modeling in vitro TF-DNA interactions. This research clearly demonstrated the advantage of machine learning methods in modeling transcriptional regulatory networks, and revealed several promising new directions for future development of computational methods in this area.
The complexity of problem understanding biochemical and molecular basis of healthy life, and eagerness to find simple solution necessitate evolution of technology like mutagenesis. The chapters of this book contain experiences of scientists working in the area of mutagenesis. It describes suitable experimental models (microorganism, plants or animals) for testing spontaneous and induced mutations which are useful for basic and translational research. It includes methods towards gene targeting, developing disease and pest resistant plants, creating temperature sensitive molecular machines, understanding mitochondrial mutagenesis, detecting anti-mutagens, improving genetic insight into impaired immunity and disease. It also describes mutagenesis induced by DNA damage. It has also provided advantage of in vitro transcription and translation to yield proteins with point mutations, deletions or insertions for studying stability, DNA-protein or protein-protein interaction. Trust, it will serve readers as valuable integrated resources emphasizing methods of mutagenesis, and understanding mechanism of variable penetrance or expressivity of mutations.
I'm just helping the dead fulfill their last wish. I didn't mean to kiss you ..." After she finished speaking, she lowered her head and pressed her lips onto his. Suddenly, he opened his eyes. "You delivered yourself to me." In the blink of an eye, before the high difficulty quest was delivered to his doorstep, he had arrogantly said to her, "If the quest is completed, I'll reward her with marrying him. If she can't, then I'll punish her to marry him!" Hm? Was there something wrong with this operation? Mao Jingjing was stupefied...
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