Networking Architecture and Key Technologies for Human Digital Twin in Personalized Healthcare: A Comprehensive Survey

Digital twin (DT), refers to a promising technique to digitally and accurately represent actual physical entities. One typical advantage of DT is that it can be used to not only virtually replicate a system's detailed operations but also analyze the current condition, predict future behaviour, and refine the control optimization. Although DT has been widely implemented in various fields, such as smart manufacturing and transportation, its conventional paradigm is limited to embody non-living entities, e.g., robots and vehicles. When adopted in human-centric systems, a novel concept, called human digital twin (HDT) has thus been proposed. Particularly, HDT allows in silico representation of individual human body with the ability to dynamically reflect molecular status, physiological status, emotional and psychological status, as well as lifestyle evolutions. These prompt the expected application of HDT in personalized healthcare (PH), which can facilitate remote monitoring, diagnosis, prescription, surgery and rehabilitation. However, despite the large potential, HDT faces substantial research challenges in different aspects, and becomes an increasingly popular topic recently. In this survey, with a specific focus on the networking architecture and key technologies for HDT in PH applications, we first discuss the differences between HDT and conventional DTs, followed by the universal framework and essential functions of HDT. We then analyze its design requirements and challenges in PH applications. After that, we provide an overview of the networking architecture of HDT, including data acquisition layer, data communication layer, computation layer, data management layer and data analysis and decision making layer. Besides reviewing the key technologies for implementing such networking architecture in detail, we conclude this survey by presenting future research directions of HDT

A Revolution of Personalized Healthcare: Enabling Human Digital Twin with Mobile AIGC

Mobile Artificial Intelligence-Generated Content (AIGC) technology refers to the adoption of AI algorithms deployed at mobile edge networks to automate the information creation process while fulfilling the requirements of end users. Mobile AIGC has recently attracted phenomenal attentions and can be a key enabling technology for an emerging application, called human digital twin (HDT). HDT empowered by the mobile AIGC is expected to revolutionize the personalized healthcare by generating rare disease data, modeling high-fidelity digital twin, building versatile testbeds, and providing 24/7 customized medical services. To promote the development of this new breed of paradigm, in this article, we propose a system architecture of mobile AIGC-driven HDT and highlight the corresponding design requirements and challenges. Moreover, we illustrate two use cases, i.e., mobile AIGC-driven HDT in customized surgery planning and personalized medication. In addition, we conduct an experimental study to prove the effectiveness of the proposed mobile AIGC-driven HDT solution, which shows a particular application in a virtual physical therapy teaching platform. Finally, we conclude this article by briefly discussing several open issues and future directions

Desorption of sulfamethoxazole from polyamide 6 microplastics: Environmental factors, simulated gastrointestinal fluids, and desorption mechanisms

Microplastics (MPs) can enrich pollutants after being released into the environment, and the contaminants-loaded MPs are usually ingested by organisms, resulting in a potential dual biotoxic effect. In this paper, the adsorption behavior of Sulfamethoxazole (SMX) on Polyamide 6 (PA6) MPs was systematically investigated and simulated by the kinetic and isotherm models. The effect of environmental conditions (pH, salinity) on the adsorption process was studied, and the desorption behavior of SMX-loaded PA6 MPs was focused on simulating the seawater, ultrapure water, gastric and intestinal fluids. We found that lower pH and solubilization of SMX by gastrointestinal components (bovine serum albumin (BSA), sodium taurocholate (NaT), and pepsin) can reduce the electrostatic interaction between the surface charge of PA6 MPs and SMX. The result will lead to an increase in the desorption capacity of SMX-loaded PA6 MPs in gastrointestinal fluids and therefore will provide a reasonable mechanism for the desorption of SMX-loaded PA6 MPs in the gastrointestinal fluids. This study will provide a theoretical reference for studying the desorption behavior of SMX-loaded PA6 MPs under gastrointestinal conditions.publishedVersio

Comparing the adsorption of methyl orange and malachite green on similar yet distinct polyamide microplastics: Uncovering hydrogen bond interactions

Microplastics (MPs) and dye pollutants are widespread in aquatic environments. Here, the adsorption characteristics of anionic dye methyl orange (MO) and cationic dye malachite green (MG) on polyamide 6 (PA6) and polyamide 66 (PA66) MPs were investigated, including kinetics, isotherm equilibrium and thermodynamics. The co-adsorption of MO and MG under different pH was also evaluated. The results reveal that the adsorption process of MO and MG is suitably expounded by a pseudo-second-order kinetic model. The process can be characterized by two stages: internal diffusion and external diffusion. The isothermal adsorption equilibrium of MO and MG can be effectively described using the Langmuir model, signifying monolayer adsorption. Furthermore, the thermodynamic results indicated that the adsorption was spontaneous with exothermic and endothermic properties, respectively. The results of binary systems reveal that MO dominates the adsorption at low pH (2–5), while MG dominates at high pH (8–10). Strong competitive adsorption was observed between MO and MG in neutral conditions (pH 6–8). The desorption experiments confirm that PA6 and PA66 could serve as potential carriers of MO and MG. The interaction between dyes and polyamide MPs is primarily mediated through hydrogen bonds and electrostatic attraction. The results reveal that PA6 formed more hydrogen bonds with the dyes, resulting in higher adsorption capacity than that of PA66. This difference can be attributed to the disparities in the synthesis process and polymerization method. Our study uncovered the adsorption mechanism of dye pollutants on PA6 and PA66, and provided a more comprehensive theoretical basis for the risk assessment concerning different types of polyamide MPs in aquatic environments.publishedVersio

Competition adsorption of malachite green and rhodamine B on polyethylene and polyvinyl chloride microplastics in aqueous environment

Microplastics (MPs) will cause compound pollution by combining with organic pollutants in the aqueous environment. It is important for environmental protection to study the adsorption mechanism of different MPs for pollutants. In this study, the adsorption behaviors of malachite green (MG) and rhodamine B (RhB) on polyethylene (PE) and polyvinyl chloride (PVC) were studied in single systems and binary systems, separately. The results show that in single system, the adsorptions of between MPs for pollutants (MG and RhB) are more consistent with the pseudo-second-order kinetics and Freundlich isotherm model, the adsorption capacity of both MPs for MG is greater than that of RhB. The adsorption capacities of MG and RhB were 7.68 mg/g and 2.83 mg/g for PVC, 4.52 mg/g and 1.27 mg/g for PE. In the binary system, there exist competitive adsorption between MG and RhB on MPs. And the adsorption capacities of PVC for the two dyes are stronger than those of PE. This is attributed to the strong halogen-hydrogen bond between the two dyes and PVC, and the larger specific surface area of PVC. This study revealed the interaction and competitive adsorption mechanism between binary dyes and MPs, which is of great significance for understanding the interactions between dyes and MPs in the multi-component systems.publishedVersio

Edge-Cloud Collaboration for Industrial IoT: An Online Approach

In this chapter, we take the Industrial Internet of Things (IIoT) as the background for studying the energy-saving resource management framework to control the cloud center (CC), edge server (ES), and terminal equipment in a closed loop. In this framework, industrial sensors collect data and transmit it to the ES for aggregation. These data form computing tasks for data analysis. Our goal is to minimize the energy consumption of the whole system while ensuring satisfied data processing accuracy and service delay of all IIoT tasks. We formulate the ES preprocessing mode selection, sensor sampling rate adaptation, and edge cloud computing and communication resource allocation as a joint optimization problem. Due to the random arrival of data and time-varying channel conditions, we introduce an online dynamic algorithm with low complexity, which efficiently solves the problem

Discovery of Potential piRNAs from Next Generation Sequences of the Sexually Mature Porcine Testes

Piwi- interacting RNAs (piRNAs), a new class of small RNAs discovered from mammalian testes, are involved in transcriptional silencing of retrotransposons and other genetic elements in germ line cells. In order to identify a full transcriptome set of piRNAs expressed in the sexually mature porcine testes, small RNA fractions were extracted and were subjected to a Solexa deep sequencing. We cloned 6,913,561 clean reads of Sus Scrofa small RNAs (18–30 nt) and performed functional characterization. Sus Scrofa small RNAs showed a bimodal length distribution with two peaks at 21 nt and 29 nt. Then from 938,328 deep-sequenced small RNAs (26–30 nt), 375,195 piRNAs were identified by a k-mer scheme and 326 piRNAs were identified by homology searches. All piRNAs predicted by the k-mer scheme were then mapped to swine genome by Short Oligonucleotide Analysis Package (SOAP), and 81.61% of all uniquely mapping piRNAs (197,673) were located to 1124 defined genomic regions (5.85 Mb). Within these regions, 536 and 501 piRNA clusters generally distributed across only minus or plus genomic strand, 48 piRNA clusters distributed on two strands but in a divergent manner, and 39 piRNA clusters distributed on two strands in an overlapping manner. Furthermore, expression pattern of 7 piRNAs identified by homology searches showed 5 piRNAs displayed a ubiquitous expression pattern, although 2 piRNAs were specifically expressed in the testes. Overall, our results provide new information of porcine piRNAs and their specific expression pattern in porcine testes suggests that piRNAs have a role in regulating spermatogenesis

Market-driven spectrum sharing in cognitive radio

This brief focuses on the current research on mechanism design for dynamic spectrum sharing in cognitive radio (CR) networks. Along with a review of CR architectures and characteristics, this brief presents the motivations, significances and unique challenges of implementing algorithmic mechanism design for encouraging both primary spectrum owners and secondary spectrum users to participate in dynamic spectrum sharing. The brief then focuses on recent advances in mechanism design in CR networks. With an emphasis on dealing with the uncertain spectrum availabilities, mechanisms based on spectrum recall, two-stage spectrum sharing and online spectrum allocation are introduced with the support of theoretic analyses and numerical illustrations. The brief concludes with a discussion of potential research directions and interests, which will motivate further studies on mechanism design for wireless communications. This brief is concise and approachable for researchers, professionals and advanced-level students in wireless communications and networks