Multi-layer Framework Research Articles

From Anthropocene to Aerocene, through Biocene: Critical Reflections on the Future of Air Mobility

The paper illustrates a case study developed within the Rhode Island School of Design (RISD) for Hyundai Motor Company (Hyundai), focusing on the future of Urban Air Mobility (UAM). The interest in the topic of aerial transportation followed a recent partnership between Hyundai and Uber Inc., aiming to commercialise an electric flying taxi service in 2028 in the city of San Francisco. In response to the increasing need for sustainable options, this research project explores the risks, alternative trajectories, and socioeconomic and environmental implications for the future of UAM. The work is generated at the conjunction of the Anthropocene, Aerocene and Biocene, which, besides representing both the conceptual and operational context, provide the inspiration for a multilayered conceptual framework. The Anthropocene, characterising the human species, flows into critical practices; the Aerocene, as a future scenario, engages with speculations; and the Biocene, as a new environmental order, fosters a post-human-centred approach.

Epidemiological connectivity between humans and animals across an urban landscape.

Urbanization is predicted to be a key driver of disease emergence through human exposure to novel, animal-borne pathogens. However, while we suspect that urban landscapes are primed to expose people to novel animal-borne diseases, evidence for the mechanisms by which this occurs is lacking. To address this, we studied how bacterial genes are shared between wild animals, livestock, and humans (n = 1,428) across Nairobi, Kenya-one of the world's most rapidly developing cities. Applying a multilayer network framework, we show that low biodiversity (of both natural habitat and vertebrate wildlife communities), coupled with livestock management practices and more densely populated urban environments, promotes sharing of Escherichia coli-borne bacterial mobile genetic elements between animals and humans. These results provide empirical support for hypotheses linking resource provision, the biological simplification of urban landscapes, and human and livestock demography to urban dynamics of cross-species pathogen transmission at a landscape scale. Urban areas where high densities of people and livestock live in close association with synanthropes (species such as rodents that are more competent reservoirs for zoonotic pathogens) should be prioritized for disease surveillance and control.

Systemic risk propagation in the Eurozone: A multilayer network approach

In this paper, we study systemic risk propagation by exploring the dynamic mechanism of financial contagion among Eurozone countries. Using a multilayer information spillover network framework, we can consider the sovereign, banking and equity sectors’ risk spillover between countries simultaneously. This specification helps us to better identify the systemically important countries, i.e., the Eurozone financial stability. The findings emphasise the prominence of considering systemic risk propagation in a multilayer network structure. In fact, our empirical analysis suggests that considering intra-layer and inter-layer propagation is essential to gain a deeper insight into Eurozone systemic risk mechanisms.

Granular media deformation and fluid flow as overlapping, concurrent, coupled multilayered depth-averaged framework

A novel coupled depth-averaged formulation for the combination of multilayered fluid and monolayer granular flows as a set of interpenetrating continua has been developed in this study. Granular and fluid phases are coupled through an interaction force pair comprised of fluid stresses, and drag forces. Fluid phase is discretized in the vertical direction through a set N of virtual layer interfaces to obtain a variation of flow properties along depth. A novel algorithm for mass and momentum exchange between fluid layers for flow through and over porous media has been proposed. Eigenstructure analysis of the coupled system shows that the system may be discretized in N+1 separate yet coupled Riemann problems. An improved version of well-known HLL method is developed for solution of the model (Finite Volume Method) in a regular grid. The resistive source–sink terms are embedded implicitly within the interfacial flux. Based on the choices of state variables and layer-interface porosity, four variants of the coupled system are developed. A set of benchmark experimental test-cases and a representative test involving both rigid and deformable granular media has been simulated using the four variants to establish the robustness of the model and the coupling procedure.

Multi-Layered Filtration Framework for Efficient Detection of Network Attacks Using Machine Learning.

The advancements and reliance on digital data necessitates dependence on information technology. The growing amount of digital data and their availability over the Internet have given rise to the problem of information security. With the increase in connectivity among devices and networks, maintaining the information security of an asset has now become essential for an organization. Intrusion detection systems (IDS) are widely used in networks for protection against different network attacks. Several machine-learning-based techniques have been used among researchers for the implementation of anomaly-based IDS (AIDS). In the past, the focus primarily remained on the improvement of the accuracy of the system. Efficiency with respect to time is an important aspect of an IDS, which most of the research has thus far somewhat overlooked. For this purpose, we propose a multi-layered filtration framework (MLFF) for feature reduction using a statistical approach. The proposed framework helps reduce the detection time without affecting the accuracy. We use the CIC-IDS2017 dataset for experiments. The proposed framework contains three filters and is connected in sequential order. The accuracy, precision, recall and F1 score are calculated against the selected machine learning models. In addition, the training time and the detection time are also calculated because these parameters are considered important in measuring the performance of a detection system. Generally, decision tree models, random forest methods, and artificial neural networks show better results in the detection of network attacks with minimum detection time.

All-Fabric Tactile Sensors Based on Sandwich Structure Design with Tunable Responsiveness.

Capacitance tactile sensors (TSs) based on electrode distance and contact area variations have been notably employed for various purposes due to their magnificent stress sensitivity. Nevertheless, developing TSs with tunable responsiveness in a broad pressure interval is crucial owing to the trade-off between sensitivity and linear identification range. Herein, a TS including Ag-coated Velcro and spacer fabric is constructed, where its sandwich framework provides a sizable expansion in compression deformation ability. In addition, a multilayered framework composed of the stacked TS from self-adhesive Velcro provides more contact area and significant deformation for stress distribution, further balancing the sensitivity, sensing range, and linearity for smart garment application. By utilizing the overlaid selection of multilayer structures, the all-textile TS demonstrates outstanding sensitivity with a one-layer structure (0.036 kPa-1) over a pressure range of 0.2-5 kPa and retains a sensitivity of 0.002 kPa-1 in a four-layer structure over a wide pressure range of 0.2-110 kPa, representing a significant improvement compared to previous results. The sensor possesses excellent performance in terms of response speed (104 ms), repeatability (10,000 cycles), and flexibility. In addition, its significant applications, involving human motion detection, pliable keyboards, and human-computer interface, are successfully shown. Based on the facile and scalable manufacturing approach, a suitable procedure is presented to construct next-generation wearable electronics.

Coping with informal fish vending constraints and resilience implications among urban-based women fish vendors in Dar es Salaam

The aim of this study is to examine threats related to informal fish vending business among urban-based women and to propose strategies for overcoming the threats. Specifically, the study ascertains the threats associated with the fishing business and strategies for coping and the capacity to cope. Based on the multi-layered social resilience framework, this study used a qualitative design and a sample size of 30 participants obtained both randomly and purposively. The findings revealed that threats experienced by the vendors include stigma, fish scarcity, higher fish prices, inadequate business capital, various forms of gender-related violence such as sexual harassment, lack of legal status, and various forms of crime including robbery, theft, and pickpocketing. Findings further indicated that vendors managed to develop both reactive and proactive strategies for coping with the threats. Reactive strategies include joining small self-helping groups popularly known as Village Community Banking (VICOBA) and soliciting family and relative support against insecurity threats. Proactive strategies include securing business financing from credible institutions, business diversification and adopting new kinds of business, business registration and licensing, searching for and participating in education and capacity-building programs, as well as business advocacy. It is recommended that government support, provision of education, and access to credit, should be considered in supporting women fish vendors to cope with the threats in their fishing business activities.

Spreading processes with mutations over multilayer networks

A key scientific challenge during the outbreak of novel infectious diseases is to predict how the course of the epidemic changes under countermeasures that limit interaction in the population. Most epidemiological models do not consider the role of mutations and heterogeneity in the type of contact events. However, pathogens have the capacity to mutate in response to changing environments, especially caused by the increase in population immunity to existing strains, and the emergence of new pathogen strains poses a continued threat to public health. Further, in the light of differing transmission risks in different congregate settings (e.g., schools and offices), different mitigation strategies may need to be adopted to control the spread of infection. We analyze a multilayer multistrain model by simultaneously accounting for i) pathways for mutations in the pathogen leading to the emergence of new pathogen strains, and ii) differing transmission risks in different settings, modeled as network layers. Assuming complete cross-immunity among strains, namely, recovery from any infection prevents infection with any other (an assumption that will need to be relaxed to deal with COVID-19 or influenza), we derive the key epidemiological parameters for the multilayer multistrain framework. We demonstrate that reductions to existing models that discount heterogeneity in either the strain or the network layers may lead to incorrect predictions. Our results highlight that the impact of imposing/lifting mitigation measures concerning different contact network layers (e.g., school closures or work-from-home policies) should be evaluated in connection with their effect on the likelihood of the emergence of new strains.

A complex systems framework for examining the impact of school-based professional learning initiatives: emerging agentic practices in a collaborative curriculum redesign

ABSTRACTIt is difficult to identify direct causal relationships between school-based professional learning initiatives and changes in the participating teachers’ competencies or their students’ learning outcomes. This paper contributes a novel approach to examining the impact of such school-based professional learning by integrating the constructs of complex systems and agentic practice into how the processes in curriculum re-design contribute to professional learning outcomes. The paper first presents an integrated multilayered conceptual framework that combines perspectives on complex systems and agentic practices. Next, it outlines the main levels and aspects of the complex system that need to be considered when examining school-based professional learning initiatives. Then, using a case from a multi-school professional development initiative illustrates how this framework was applied to examine the impact of a professional learning initiative focused on a collaborative science curriculum redesign to support English Language Learners (ELLs). Analysing the agentic practices that emerged within and across different complex system levels provides a comprehensive insight into how the system, constraints or amplifies particular practices.

A verification-oriented and part-focused assembly monitoring system based on multi-layered digital twin

In line with the human centricity characteristics of the emerging Industry 5.0 paradigm, manual assembly has long been an indispensable element of the small-batch and customized products. Nevertheless, the flexibility of manual operations is prone to assembly errors caused by human uncertainties. Since the newly assembled part directly determines the quality of products, the part-focused verification method has been widely adopted for manual assembly assistance. However, a part is partial to the whole assembly and occluded by other parts, which makes verification difficult. By leveraging the digital twin (DT) technology, one can construct a physical twin (PT) scene to represent the on-site assembly and a DT scene to represent the assembly’s theoretical status in real time. Only if the part is assembled correctly, the newly assembled part can be mapped to the corresponding DT part model. Otherwise, the difference between the PT and the DT part can indicate a potential assembly error. Based on this idea, this paper proposes a verification-oriented and part-focused monitoring system based on multi-layered digital twin for manual assembly assistance. A multi-layered DT framework is constructed to build the geometric and logical connection between the physical and digital space. With the synchronization of DT, the newly assembled part and its corresponding template are generated using a point cloud reservation algorithm, and a two-direction matching algorithm is adapted to evaluate whether the newly assembled part is in the expected position for verification. The proposed monitoring system only requires one shot of the assembly scene in movable view for verification, which meets the flexible requirement for manual assistance in human-centric assembly. The experimental result shows that the proposed monitoring system can detect potential part errors and track assembly process information after manual assembly work, which is significant for human-centric intelligent manufacturing system development.

Workplace inclusion: A scoping review of the qualitative literature.

An inclusive workplace culture supports and values the individual and collective work processes of workers from diverse backgrounds. The reality or perception of inclusion or exclusion at work can influence the social functioning, health, and well-being of workers. However, we lack knowledge about the concepts relevant to inclusion at the workplace. Furthermore, research is needed to better understand the drivers and obstacles to workplace inclusion to better promote participation in working life. This scoping review of the qualitative literature identifies the barriers to and facilitators of workplace inclusion. Systematic searches of five databases were conducted from 2000 to January 2020. Pairs of reviewers independently screened and reviewed all citations and full-text articles. We used Arksey and O'Malley's scoping review framework which advances through five stages. Barriers and facilitators of workplace inclusion were categorized relative to a multi-layered conceptualization of workplace inclusion and grouped by theme. Studies were described and thematic results totaled and communicated with evidence tables and conceptual maps. Thirty-nine qualitative studies met our inclusion criteria. All five domains of the multi-layered framework were represented by the reported shared experiences of study participants. Organizational level factors, especially attitudinal barriers were the most reported barriers to workplace inclusion. Facilitators of workplace inclusion focused on employer level factors and most often cited the role of inclusive leadership and support. Workplace inclusion requires consideration of societal, organizational, employer, and interpersonal level factors in addition to individual worker characteristics.

Evaluating the Potential of MAMCA as a Framework for Stakeholder Engagement during the Setup of Energy Communities

The current energy transition is characterized by a high level of consumer and prosumer involvement. Energy communities (ECs) are instruments that fit into this trend, as they organize the collective and mainly citizen-driven exchange of clean energy. Most stakeholder engagement research for ECs focuses on one aspect such as awareness raising or deployment acceptance. Hitherto, no specific research has been conducted on a participatory approach that can be applied throughout all the phases of an EC setup and for different purposes. In our study, we determine how the Multi-Actor Multi-Criteria analysis (MAMCA) methodology can be used as an engagement tool for this purpose. By linking potential engagement goals and their connected tools and techniques to the corresponding MAMCA step, we have created a multi-layered practical framework that can be used by all types of EC initiators for stakeholder engagement throughout the setup of a new EC. As this practical tool stimulates solutions that cater better to stakeholder needs, it can contribute to smoother deployment and an associated increase in ECs in the general system. A theoretical evaluation and a performed case study demonstrate the utility of the methodology that is developed in this paper.

Strain‐Invariant, Highly Water Stable All‐Organic Soft Conductors Based on Ultralight Multi‐Layered Foam‐Like Framework Structures (Adv. Funct. Mater. 21/2023)

Soft Electronics Conventional soft conductors are characterized by a large change in conductance upon mechanical deformation. In article number 2212688, Fabian Schütt, Stefan Schröder, and co-workers, combine thin film deposition technologies in a three-dimensional fashion, resulting in multi-layered and ultra-lightweight foam-like framework structures based on poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate), coated with a polytetrafluoroethylene. These all-organic soft conductors show strain-invariant conductance over a large strain range, super elastic deformation and water stability.

Eviction-Related Threats and Coping Mechanisms among Women Street Food Vendors in Dar es Salaam, Tanzania

The purpose of this study was to investigate eviction-related threats and coping mechanisms among women street food vendors in Ubungo Municipality, Dar es Salaam, Tanzania. A cross-sectional research design was used and a questionnaire was administered to a random sample of 60 women. According to the findings, eviction-related threats included a decrease in the number of customers, the lack of specific location for food vending activities, an increase in the cost of doing business and the congestion of street food vendors in one location. Women coped with such evictions by maintaining the price but reducing the share of food, measuring food according to the client’s financial ability, practicing good customer service, borrowing money from financial institutions and striving to expand customers’ base. Other reported strategies include preparing enough food for the day and explaining to customers why food prices have risen. In harmony with the Multi-layered social resilience framework, respondents managed to demonstrate reactive capacities in dealing with such eviction-related threats. In order to cope with the threats more proactively, awareness campaigns are needed to educate women street food vendors on the need of conducting their enterprises in authorized locations in order to avoid further evictions. Similarly, women street vendors should be empowered to seek assistance from both local and national government authorities at various levels, participate in decision-making processes and create institutions that can defend and foster their well-being in the face of future crises.

Key physical topology features for optical backbone networks via a multilayer correlation analysis

A communication network is a multilayer network comprising various layered technologies, and the underlying physical topology is an important aspect that determines the upper bound of overall system performance, including total communication capacity, cost, and robustness. We expect that understanding the impact of the physical topology on system performance will lead to better optical communication network design in the future, and we thus focus on clarifying the relationship between physical topology features and system performance. There have been various studies on the relationship between topology features and overall network performance. For example, the average number of hops and the cluster coefficient are well known to change network properties in complex networks. From the perspective of optical communication networks, it is known that the algebraic connectivity and average path length are related to total network capacity, and these findings have been applied in physical topology design models. On the other hand, there have been no quantitative comparisons among various topology features, and the comprehensiveness of the population from which these features are extracted is insufficient. Hence, we have developed a multilayer (physical topology and layer 1) correlation analysis framework that enables a quantitative comparison of topology features. We use this framework to numerically examine the relationships between physical topology features and the total communication capacity, cost, and robustness of optical communication networks, including graph features (especially graph spectra) that have not been investigated. The results show that the Laplacian spectral radius and geodesic distance Laplacian spectral radius are strongly related to system performance, in addition to the conventional average number of hops, cluster coefficient, algebraic connectivity, and average path length. We confirm that these correlations hold for the different network sizes and spatial nonuniformity of real optical backbone networks in different countries and regions. The results show that the average path length and cluster coefficient, or the Laplacian spectral radius and geodesic distance Laplacian spectral radius, are important guidelines for physical topology design of real optical backbone networks.

The D-model for GDP nowcasting

The paper provides a disaggregated mixed-frequency framework for the estimation of GDP. The GDP is disaggregated into components that can be forecasted based on information available at higher sampling frequency, i.e., monthly, weekly, or daily. The model framework is applied for Greek GDP nowcasting. The results provide evidence that the more accurate nowcasting estimations require (i) the disaggregation of GDP, (ii) the use of a multilayer mixed-frequency framework, and (iii) the inclusion of financial information on a daily frequency. The simulation study provides evidence in favor of the disaggregation into components despite the inclusion of multiple sources of forecast errors.

Gender equality approaches in water, sanitation, and hygiene programs: Towards gender-transformative practice

The recent (re-)emergence of gender-transformative approaches in the development sector has focused on transforming the gender norms, dynamics, and structures which perpetuate inequalities. Yet, the application of gender-transformative approaches within water, sanitation, and hygiene (WASH) programing remains nascent as compared with other sectors. Adopting a feminist sensemaking approach drawing on literature and practice, this inquiry sought to document and critically reflect on the conceptualization and innovation of gender-transformative thinking in the Australian Government's Water for Women Fund. Through three sensemaking workshops and associated analysis, participants developed a conceptual framework and set of illustrative case examples to support WASH practitioners to integrate strengthened gender-transformative practice. The multi-layered framework contains varied entry points to support multi-disciplinary WASH teams integrating gender equality, as skills and resources permit. Initiatives can be categorized as insensitive, sensitive, responsive or transformative, and prompted by five common motivators (welfare, efficiency, equity, empowerment, and transformative requality). The framework has at its foundation two diverging tendencies: toward instrumental gender potential and toward transformative gender potential. The article draws on historical and recent WASH literature to illustrate the conceptual framework in relation to: (i) community mobilization, (ii) governance, service provision, and oversight, and (iii) enterprise development. The illustrative examples provide practical guidance for WASH practitioners integrating gendered thinking into programs, projects, and policies. We offer a working definition for gender-transformative WASH and reflect on how the acknowledgment, consideration, and transformation of gender inequalities can lead to simultaneously strengthened WASH outcomes and improved gender equality.

Performance assessment of a communication infrastructure with redundant topology: A complex network approach

The physical assets within a critical infrastructure system are pivotal to its efficient performance and protection and that of other dependent systems. This is particularly the case for communication systems where network protection strategies usually involve asset redundancy. Although such redundancy is well-modelled in the literature, there is a gap in knowledge from a network science perspective in terms of its implications for network modelling and performance assessment. This paper presents a multilayer complex network framework that takes into account the heterogeneity of the redundant infrastructure for realistic network modelling and further analysis, a step change from using a single network model. Key performance indicators (KPIs) for communication networks (i.e., latency and jitter, bandwidth and throughput, queue depth and packet drops) are redefined to evaluate key important features of a long-haul backbone network such as network capacity and average use. In addition, these KPIs are adapted to deal with the aforementioned redundancy and so inform network managers with values defined over a model closer to the real system. The paper analyses the use case of a nationwide core and metro network infrastructure of one of the main UK internet service providers. The results of the analysis of KPIs showcase the advantage of the proposed multilayer complex network framework over the traditional single network model. Critical network elements within different dimensions of a communication network are identified based on their performance for prioritising network management measures.

MLStock: Multi-layer model for sentiment analysis based stock price prediction

In this paper, we address the task of predicting stock prices using the market sentiments extracted from Twitter. We propose MLStock, a multi-layer framework that models the market sentiment with the stock layer, the sector layer, and the market layer using the Gated Recurrent Unit (GRU), and use the sentiment to make directional prediction on stock price. Existing methods consider stocks individually, and might miss the signals in the current market sector which will affect the stock later. In contrast, our model summa-rizes the sector and market states through individual states and shows an improvement over traditional machine learning methods.

Multilayer brain network modeling and dynamic analysis of juvenile myoclonic epilepsy.

Objective: It is indisputable that the functional connectivity of the brain network in juvenile myoclonic epilepsy (JME) patients is abnormal. As a mathematical extension of the traditional network model, the multilayer network can fully capture the fluctuations of brain imaging data with time, and capture subtle abnormal dynamic changes. This study assumed that the dynamic structure of JME patients is abnormal and used the multilayer network framework to analyze the change brain community structure in JME patients from the perspective of dynamic analysis. Methods: First, functional magnetic resonance imaging (fMRI) data were obtained from 35 JME patients and 34 healthy control subjects. In addition, the communities of the two groups were explored with the help of a multilayer network model and a multilayer community detection algorithm. Finally, differences were described by metrics that are specific to the multilayer network. Results: Compared with healthy controls, JME patients had a significantly lower modularity degree of the brain network. Furthermore, from the level of the functional network, the integration of the default mode network (DMN) and visual network (VN) in JME patients showed a significantly higher trend, and the flexibility of the attention network (AN) also increased significantly. At the node level, the integration of seven nodes of the DMN was significantly increased, the integration of five nodes of the VN was significantly increased, and the flexibility of three nodes of the AN was significantly increased. Moreover, through division of the core-peripheral system, we found that the left insula and left cuneus were core regions specific to the JME group, while most of the peripheral systems specific to the JME group were distributed in the prefrontal cortex and hippocampus. Finally, we found that the flexibility of the opercular part of the inferior frontal gyrus was significantly correlated with the severity of JME symptoms. Conclusion: Our findings indicate that the dynamic community structure of JME patients is indeed abnormal. These results provide a new perspective for the study of dynamic changes in communities in JME patients.