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Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities.

Fueled by pressing global climate concerns, the integration of large-scale renewable distributed generation sources, including distributed wind power and photovoltaics, along with electricity substitution loads into the distribution network has been accelerated to diminish carbon emissions. This shift introduces significant challenges and necessitates the advanced operation and control of distribution systems to accommodate these changes effectively. Against this backdrop, there is a growing expectation for an open and scalable central control mode, equipped with compatible interfaces, to offer a visionary development platform for the grid. This platform is anticipated to meet the evolving needs of future distribution system development, ensuring adaptability and forward compatibility. The aforementioned platform requires open, scalable, and interface-compatible models of key distribution network equipment as its foundation. To address the challenges presented, this paper proposes a data–physics-driven modeling approach for automating simulations in distribution systems. This method employs a simplified and standardized system of linear differential equations with undetermined coefficients to capture the common physical characteristics of specific device types. The models designed through this approach are notably open, allowing for real-time data to refine undetermined coefficients and accurately depict the dynamic behavior of equipment over various periods. Their scalability also stands out, rendering them apt for large-scale distribution network simulations. The paper elaborates on models for distributed photovoltaic, wind turbine, energy storage, and electric vehicle, and demonstrates their application within an IEEE-33 node distribution network topology built on Python.

This is one of the first books to provide a comprehensive description of OPNET IT Guru and Modeler software. The book explains how to use the software for simulating and modeling computer networks and includes laboratory projects that help readers learn different aspects of the software in a hands-on way. The authors illustrate how to develop and configure models for every layer of the TCP/IP reference model. They also offer extensive examples that show how to set up and configure many nontrivial features of OPNET software.

A Digital Twin (DT) is a set of computer-generated models that map a physical object into a virtual space. Both physical and virtual elements exchange information to monitor, simulate, predict, diagnose and control the state and behavior of the physical object within the virtual space. DTs supply a system with information and operating status, providing capabilities to create new business models. In this paper, we focus on the construction of DTs. More specifically, we focus on determining (methodologically) how to design, create and connect physical objects with their virtual counterpart. We explore the problem into several phases: from functional requirement selection and architecture planning to integration and verification of the final (digital) models. We address as well how physical components exchange real-time information with DTs, as well as experimental platforms to build DTs (including protocols and standards). We conclude with a discussion and open challenges.

Primary immunodeficiencies (PIDs) are a group of over 300 hereditary, heterogeneous, and mainly rare disorders that affect the immune system. Various aspects of immune system and PID proteins and genes have been investigated and facilitate systems biological studies of effects of PIDs on B cell physiology and response. We reconstructed a B cell network model based on data for the core B cell receptor activation and response processes and performed semi-quantitative dynamic simulations for normal and B cell PID failure modes. The results for several knockout simulations correspond to previously reported molecular studies and reveal novel mechanisms for PIDs. The simulations for CD21, CD40, LYN, MS4A1, ORAI1, PLCG2, PTPRC, and STIM1 indicated profound changes to major transcription factor signaling and to the network. Significant effects were observed also in the BCL10, BLNK, BTK, loss-of-function CARD11, IKKB, MALT1, and NEMO, simulations whereas only minor effects were detected for PIDs that are caused by constitutively active proteins (PI3K, gain-of-function CARD11, KRAS, and NFKBIA). This study revealed the underlying dynamics of PID diseases, confirms previous observations, and identifies novel candidates for PID diagnostics and therapy.

Sustaining economic activities while curbing the number of new coronavirus disease 2019 (COVID-19) cases until effective vaccines or treatments become available is a major public health and policy challenge. In this paper, we use agent-based simulations of a network-based susceptible−exposed−infectious−recovered (SEIR) model to investigate two network intervention strategies for mitigating the spread of transmission while maintaining economic activities. In the simulations, we assume that people engage in group activities in multiple sectors (e.g., going to work, going to a local grocery store), where they interact with others in the same group and potentially become infected. In the first strategy, each group is divided into two subgroups (e.g., a group of customers can only go to the grocery store in the morning, while another separate group of customers can only go in the afternoon). In the second strategy, we balance the number of group members across different groups within the same sector (e.g., every grocery store has the same number of customers). The simulation results show that the dividing groups strategy substantially reduces transmission, and the joint implementation of the two strategies could effectively bring the spread of transmission under control (i.e., effective reproduction number ≈ 1.0).

The Internet of Things (IoT) is a global network of interconnected computing, sensing, and networking devices that can exchange data and information via various network protocols. It can connect numerous smart devices thanks to recent advances in wired, wireless, and hybrid technologies. Lightweight IoT protocols can compensate for IoT devices with restricted hardware characteristics in terms of storage, Central Processing Unit (CPU), energy, etc. Hence, it is critical to identify the optimal communication protocol for system architects. This necessitates an evaluation of next-generation networks with improved characteristics for connectivity. This paper highlights significant wireless and wired IoT technologies and their applications, offering a new categorization for conventional IoT network protocols. It provides an in-depth analysis of IoT communication protocols with detailed technical information about their stacks, limitations, and applications. The study further compares industrial IoT-compliant devices and software simulation tools. Finally, the study provides a summary of the current challenges, along with a broad overview of the future directions to tackle the challenges, in the next IoT generation. This study aims to provide a comprehensive primer on IoT concepts, protocols, and future insights that academics and professionals can use in various contexts.

Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists, computational and system biologists This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC). The book is organized into four parts that deliver materials in a way equally attractive for a reader with training in computation or biology. Each of these sections, authored by well-known researchers and experienced practitioners, provides the relevant materials for the interested readers. The first part of this book contains an introductory background to the field. The second part presents the EC approaches for analysis and reconstruction of GRN from gene expression data. The third part of this book covers the contemporary advancements in the automatic construction of gene regulatory and reaction networks and gives direction and guidelines for future research. Finally, the last part of this book focuses on applications of GRNs with EC in other fields, such as design, engineering and robotics. • Provides a reference for current and future research in gene regulatory networks (GRN) using evolutionary computation (EC) • Covers sub-domains of GRN research using EC, such as expression profile analysis, reverse engineering, GRN evolution, applications • Contains useful contents for courses in gene regulatory networks, systems biology, computational biology, and synthetic biology • Delivers state-of-the-art research in genetic algorithms, genetic programming, and swarm intelligence Evolutionary Computation in Gene Regulatory Network Research is a reference for researchers and professionals in computer science, systems biology, and bioinformatics, as well as upper undergraduate, graduate, and postgraduate students. Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Toyko, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the journal of Genetic Programming and Evolvable Machines. Nasimul Noman is a lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012 he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.

The quantum internet is envisioned as the ultimate stage of the quantum revolution, which surpasses its classical counterpart in various aspects, such as the efficiency of data transmission, the security of network services, and the capability of information processing. Given its disruptive impact on the national security and the digital economy, a global race to build scalable quantum networks has already begun. With the joint effort of national governments, industrial participants, and research institutes, the development of quantum networks has advanced rapidly in recent years, bringing the first primitive quantum networks within reach. In this work, we aim to provide an up-to-date review of the field of quantum networks from both theoretical and experimental perspectives, contributing to a better understanding of the building blocks required for the establishment of a global quantum internet. We also introduce a newly developed quantum network toolkit to facilitate the exploration and evaluation of innovative ideas. Particularly, it provides dual quantum computing engines, supporting simulations in both the quantum circuit and measurement-based models. It also includes a compilation scheme for mapping quantum network protocols onto quantum circuits, enabling their emulations on real-world quantum hardware devices. We showcase the power of this toolkit with several featured demonstrations, including a simulation of the Micius quantum satellite experiment, a testing of a four-layer quantum network architecture with resource management, and a quantum emulation of the CHSH game. We hope this work can give a better understanding of the state-of-the-art development of quantum networks and provide the necessary tools to make further contributions along the way.

In this paper, the effect of channel conditions on the global behavior of a wireless Visible Light Communications (VLC) optical network are studied. It presents a system-level simulator that considers jointly a channel propagation model and the MAC mechanisms to have a realistic description of the network, even in situations where the emitted signal is heavily affected by reflections in any close surface or obstacle. The resulting platform also accurately evaluates both Line-Of-Sight (LOS) and Non-LOS (NLOS) contributions on each node and enables the effective use of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) schemes as defined by IEEE 802.15.7r1 standard, as well as allows a correct evaluation of lifelike problems such as the effect of hidden nodes. This work shows the necessity of accurately modeling VLC MAC layer performances, taking also into account the physical nature of visible light propagation in indoor scenarios.