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Automatica ◽  
2022 ◽  
Vol 137 ◽  
pp. 110093
Shengling Shi ◽  
Xiaodong Cheng ◽  
Paul M.J. Van den Hof

2022 ◽  
Vol 22 (1) ◽  
pp. 1-18
Chen Chen ◽  
Lei Liu ◽  
Shaohua Wan ◽  
Xiaozhe Hui ◽  
Qingqi Pei

As a key use case of Industry 4.0 and the Smart City, the Internet of Vehicles (IoV) provides an efficient way for city managers to regulate the traffic flow, improve the commuting performance, reduce the transportation facility cost, alleviate the traffic jam, and so on. In fact, the significant development of Internet of Vehicles has boosted the emergence of a variety of Industry 4.0 applications, e.g., smart logistics, intelligent transforation, and autonomous driving. The prerequisite of deploying these applications is the design of efficient data dissemination schemes by which the interactive information could be effectively exchanged. However, in Internet of Vehicles, an efficient data scheme should adapt to the high node movement and frequent network changing. To achieve the objective, the ability to predict short-term traffic is crucial for making optimal policy in advance. In this article, we propose a novel data dissemination scheme by exploring short-term traffic prediction for Industry 4.0 applications enabled in Internet of Vehicles. First, we present a three-tier network architecture with the aim to simply network management and reduce communication overheads. To capture dynamic network changing, a deep learning network is employed by the controller in this architecture to predict short-term traffic with the availability of enormous traffic data. Based on the traffic prediction, each road segment can be assigned a weight through the built two-dimensional delay model, enabling the controller to make routing decisions in advance. With the global weight information, the controller leverages the ant colony optimization algorithm to find the optimal routing path with minimum delay. Extensive simulations are carried out to demonstrate the accuracy of the traffic prediction model and the superiority of the proposed data dissemination scheme for Industry 4.0 applications.

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Mohammad Ali Torabandeh ◽  
Behrouz Dorri ◽  
Masood Rabieh ◽  
Ali Reza Motameni

Purpose This study aims to design a national innovation capability appraisal model. This would indicate Iran’s competitiveness situation among regional countries and suggest factors influencing Iran’s performance promotion. Design/methodology/approach The methodology included four sections: bibliometric analysis to discover intellectual evolution of innovation capability and related concepts; construction of a multi-division structure of national innovation capability according to the clusters extracted from bibliometric results, and experts’ opinions; creating dynamic network data envelope analysis (DEA) according to designed structure, and analysis of Iran’s performance among regional countries; identification and prioritization of the factors extracted from experts’ opinions that improve Iran’s performance in created network using Fuzzy decision-making trial and evaluation laboratory method. Findings The contemporary bibliometric analysis by its extracted clusters proved the necessity of a multi-division for measuring national innovation capability performance that each division and indicators of each step were designed according to clusters concepts. In designed structure, dynamic network DEA results revealed the weakness of Iran’s performance in the third division in the transformation of patents and high-tech imports to high-tech and creative exports, which led to proposing improving factors by getting experts’ opinions to enhance Iran’s performance in this division by prioritizing them. Research limitations/implications One of the limitations of this research was that the indicators used in three phases of national innovation capability in DEA were extracted only from the World Intellectual Property Organization database. Another limitation was the number of experts in focus group sessions because due to the difficulty of gathering them in one session, the researchers lost the participation of some of these recognized experts. Also, the research concentration was on the improvement of the third phase of national innovation capability, in which Iran’s performance was weak. Originality/value Creating a relationship between the divisions of dynamic network DEA, as a national innovation capability appraisal model, and the concepts of clusters extracted from reviewing the intellectual structure and evolution of innovation capability and related concepts.

2022 ◽  
Vol 11 (1) ◽  
pp. 62
Zhenkai Yang ◽  
Yixin Hua ◽  
Yibing Cao ◽  
Xinke Zhao ◽  
Minjie Chen

As a new product of the Internet and big data era, migration data are of great significance for the revealing of the complex dynamic network patterns of urban agglomerations and for studying the relations between cities by using the “space of flows” model. Based on Baidu migration data of one week in 2021, this paper constructs a 30 × 30 rational data matrix for cities in Zhongyuan Urban Agglomeration and depicts the network pattern from static and dynamic perspectives by using social network analysis and dynamic network visualization. The results show that the network of Zhongyuan Urban Agglomeration is characterized by a circular structure with Zhengzhou as the center, a city belt around Zhengzhou as the connection, subcentral cities as the support and peripheral cities as the extension. Zhengzhou is the core city of the entire network, related to which the central and backbone networks divided in this paper account for nearly 40% of the total migration. Shangqiu, Luoyang, Zhoukou and Handan also play an important role in the structure of the migration network as subcentral cities. For a single city, the migration scale generally peaks on weekends and reaches its minimum during Tuesday to Thursday. Regarding the relations between cities, the migration variation can be divided into four types: peaking on Monday, peaking on weekends, bimodal and stable, and there are obvious phenomena of weekly commuting. In general, the links between cities outside Henan Province and other cities in the urban agglomeration are relatively weak, and the constraints of administrative regionalization on intercity migration are presumed to still exist. According to the results, the location advantage for multi-layer development and construction of Zhongyuan Urban Agglomeration should be made use of. In addition, the status as the core city and the radiation range should be strengthened, and the connections between the peripheral cities and the other cities should be improved, so as to promote the integrated and efficient development of the whole urban agglomeration.

Cancers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 359
Ângela Marques-Magalhães ◽  
Tânia Cruz ◽  
Ângela Margarida Costa ◽  
Diogo Estêvão ◽  
Elisabete Rios ◽  

More than a physical structure providing support to tissues, the extracellular matrix (ECM) is a complex and dynamic network of macromolecules that modulates the behavior of both cancer cells and associated stromal cells of the tumor microenvironment (TME). Over the last few years, several efforts have been made to develop new models that accurately mimic the interconnections within the TME and specifically the biomechanical and biomolecular complexity of the tumor ECM. Particularly in colorectal cancer, the ECM is highly remodeled and disorganized and constitutes a key component that affects cancer hallmarks, such as cell differentiation, proliferation, angiogenesis, invasion and metastasis. Therefore, several scaffolds produced from natural and/or synthetic polymers and ceramics have been used in 3D biomimetic strategies for colorectal cancer research. Nevertheless, decellularized ECM from colorectal tumors is a unique model that offers the maintenance of native ECM architecture and molecular composition. This review will focus on innovative and advanced 3D-based models of decellularized ECM as high-throughput strategies in colorectal cancer research that potentially fill some of the gaps between in vitro 2D and in vivo models. Our aim is to highlight the need for strategies that accurately mimic the TME for precision medicine and for studying the pathophysiology of the disease.

Maryam Gillani ◽  
Hafiz Adnan Niaz ◽  
Muhammad Umar Farooq ◽  
Ata Ullah

AbstractWe live in the era of Intelligent Transport Systems (ITS), which is an extension of Vehicular AdHoc Networks (VANETs). In VANETs, vehicles act as nodes connected with each other and sometimes with a public station. Vehicles continuously exchange and collect information to provide innovative transportation services; for example, traffic management, navigation, autonomous driving, and the generation of alerts. However, VANETs are extremely challenging for data collection, due to their high mobility and dynamic network topologies that cause frequent link disruptions and make path discovery difficult. In this survey, various state-of-the-art data collection protocols for VANETs are discussed, based on three broad categories, i.e., delay-tolerant, best-effort, and real-time protocols. A taxonomy is designed for data collection protocols for VANETs that is essential to add precision and ease of understandability. A detailed comparative analysis among various data collection protocols is provided to highlight their functionalities and features. Protocols are evaluated based on three parametric phases. First, protocols investigation based on six necessary parameters, including delivery and drop ratio, efficiency, and recovery strategy. Second, a 4-D functional framework is designed to fit most data collection protocols for quick classification and mobility model identification, thus eradicating the need to read extensive literature. In the last, in-depth categorical mapping is performed to deep dive for better and targeted interpretation. In addition, some open research challenges for ITS and VANETs are discussed to highlight research gaps. Our work can thus be employed as a quick guide for researchers to identify the technical relevance of data collection protocols of VANETs.

2022 ◽  
Vol 0 (0) ◽  
Robert Daugs

Abstract English modal enclitics (’d and ’ll) are typically conceived of as colloquial pronunciation variants that are semantically identical to their respective full forms (would and will). Although this conception has already been challenged by Nesselhauf, Nadja. 2014. From contraction to construction? The recent life of ’ll. In Marianne Hundt (ed.), Late modern English syntax, 77–89. Cambridge: Cambridge University Press and Daugs, Robert. 2021. Contractions, constructions and constructional change: Investigating the constructionhood of English modal contractions from a diachronic perspective. In Martin Hilpert, Bert Cappelle & Ilse Depraetere (eds.), Modality and diachronic construction grammar, 12–52. Amsterdam: John Benjamins, who argue for the constructional status of both enclitics, the present study proposes a refinement according to which the differences between enclitics and full forms can be pinpointed to specific co-occurrence patterns. Rather than rashly postulating a general ’d-construction or an ’ll-construction, the data indicate that lower-level instances, like I’d V, we’ll V, or it would V, are very much capable of capturing the meaning differences between enclitics and full forms without recourse to higher, more abstract level. This is achieved by assessing the changes in the associative links these patterns entertain in a data-driven, bottom-up fashion. By utilizing the COHA and a variety of quantitative methods, it can be shown that, although enclitic patterns become more frequent and more varied, they remain overall still more restricted than the full forms, which promotes the emergence of ‘new’ symbolic associations. The results are integrated into current research in Diachronic Construction Grammar (Hilpert, Martin. 2013. Constructional change in English: Developments in allomorphy, word formation, and syntax. Cambridge: Cambridge University Press, Hilpert, Martin. 2021. Ten lectures in diachronic construction grammar. Leiden: Brill) and dynamic, network-oriented models of language (Schmid, Hans-Jörg. 2020. The dynamics of the linguistic system: Usage, conventionalization, and entrenchment. Oxford: Oxford University Press).

Maria Veronica Lipreri ◽  
Nicola Baldini ◽  
Gabriela Graziani ◽  
Sofia Avnet

As life expectancy increases, the population experiences progressive ageing. Ageing, in turn, is connected to an increase in bone-related diseases (i.e., osteoporosis and increased risk of fractures). Hence, the search for new approaches to study the occurrence of bone-related diseases and to develop new drugs for their prevention and treatment becomes more pressing. However, to date, a reliable in vitro model that can fully recapitulate the characteristics of bone tissue, either in physiological or altered conditions, is not available. Indeed, current methods for modelling normal and pathological bone are poor predictors of treatment outcomes in humans, as they fail to mimic the in vivo cellular microenvironment and tissue complexity. Bone, in fact, is a dynamic network including differently specialized cells and the extracellular matrix, constantly subjected to external and internal stimuli. To this regard, perfused vascularized models are a novel field of investigation that can offer a new technological approach to overcome the limitations of traditional cell culture methods. It allows the combination of perfusion, mechanical and biochemical stimuli, biological cues, biomaterials (mimicking the extracellular matrix of bone), and multiple cell types. This review will discuss macro, milli, and microscale perfused devices designed to model bone structure and microenvironment, focusing on the role of perfusion and encompassing different degrees of complexity. These devices are a very first, though promising, step for the development of 3D in vitro platforms for preclinical screening of novel anabolic or anti-catabolic therapeutic approaches to improve bone health.

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