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In this collection of short articles, we explored how a diverse group of theories, methodologies, and practices of spatial planning can help us unpack and better understand smart cities and sustainable development. Using the cases of Greater Manchester in the UK and Shenzhen in China, our emphasis was to identify innovative but actionable approaches of smart and sustainable planning for smart and equitable growth, lower carbon emissions, and environmental resilience to enhance the well-being of urban communities.

Bystanders Join in Cyberbullying on Social Networking Sites: The Deindividuation and Moral Disengagement PerspectivesCyberbullying on social networking sites escalates when bystanders join in the bullying. Bystanders’ joining-in behaviors reinforce the abuse, expose victims to a larger audience, and encourage further abuse by signaling their approval of the aggressive behavior. This study developed an integrative model that explains bystanders’ joining-in cyberbullying behaviors on SNSs to offer actionable insights into reducing such harmful behaviors. We tested the model using 1,179 responses using a scenario survey study. Our findings suggest that IT artifacts (including digital profile, search and privacy, relational ties, and network transparency) activated two key mechanisms that lead to cyberbullying joining-in behaviors: (i) the deindividuation experiences that attenuate self-identity and put salience on group/social identity, and (ii) the moral disengagement practices that permit the exercise of cognitive maneuvers to justify group-interested choices that do not align with social standard. The findings explain why people who do not know each other gang up to bully a target on social media. Platform owners who wish to discourage bystanders from joining in undesirable activities may consider regulating how users could share and access digital resources in a social network and should acknowledge the influence of social identity in igniting, driving, and prolonging harmful online group behaviors.Cyberbullying on social networking sites (SNSs) escalates when bystanders join in the bullying. Although researchers have recognized the harmful consequences of joining in cyberbullying behaviors, little is known about the role of information technology (IT) and its underlying mechanisms in fueling such negative group behavior on SNSs. To address this research gap, we develop and test an integrative model that explains bystanders’ joining-in cyberbullying behaviors on SNSs. Based on the theoretical premises of the social identity model of deindividuation effects (the SIDE model), we derive two deindividuation experiences enabled by SNSs, namely experienced anonymity and experienced social identity. We further use the social network research framework to gain insights into how IT features (i.e., digital profile, search and privacy, relational ties, and network transparency) enable these two deindividuation experiences. Considering the socially undesirable nature of joining-in behaviors, we integrate the SIDE model with moral disengagement theory to explain how deindividuation experiences allow bystanders to bypass their psychological discomfort when engaging in such behaviors through the practice of moral disengagement mechanisms. Our research model is tested using a scenario survey, with two samples recruited from Amazon Mechanical Turk and Facebook. Our results support the influences of IT-enabled deindividuation experiences on bystanders joining in cyberbullying and demonstrate the mediating effects of moral disengagement mechanisms in bridging the effects of deindividuation experiences on joining-in behaviors. For researchers, the integrative view offers a conceptual bridge connecting IT features, deindividuation, moral disengagement, and negative online group behaviors on SNSs. For practitioners, our findings provide platform owners and governmental agencies with directions on how to mitigate cyberbullying on SNSs and other forms of deviant and undesirable online group behaviors.

This paper examines how automation and digitalisation influence the way everyday scientific work practices are organised and conducted. Drawing on a practice-based study of the field of synthetic biology, the paper uses ethnographic, interview and survey data to offer a sociomaterial and relational perspective of technological change. As automation and digitalisation are deployed in research settings, our results show the emergence and persistence of what we call ‘mundane knowledge work’, including practices of checking, sharing and standardising data; and preparing, repairing and supervising laboratory robots. While these are subsidiary practices that are often invisible in comparison to scientific outputs used to measure performance, we find that mundane knowledge work constitutes a fundamental part of automated and digitalised biosciences, shaping scientists' working time and responsibilities. Contrary to expectations of the removal of such work by automation and digitalisation, we show that mundane work around data and robots persists through ‘amplification’ and ‘diversification’ processes. We argue that the persistence of mundane knowledge work suggests a digitalisation paradox in the context of everyday labour: while robotics and advanced data analytics aim at simplifying work processes, they also contribute to increasing their complexity in terms of number and diversity of tasks in creative, knowledge-intensive professions.

Graphene-related materials (GRMs) are subject to intensive investigations and considerable progress has been made in recent years in terms of safety assessment. However, limited information is available concerning the hazard potential of GRM-containing products such as graphene-reinforced composites. In the present study, we conducted a comprehensive investigation of the potential biological effects of particles released through an abrasion process from reduced graphene oxide (rGO)-reinforced composites of polyamide 6 (PA6), a widely used engineered thermoplastic polymer, in comparison to as-produced rGO. First, a panel of well-established in vitro models, representative of the immune system and possible target organs such as the lungs, the gut, and the skin, was applied. Limited responses to PA6-rGO exposure were found in the different in vitro models. Only as-produced rGO induced substantial adverse effects, in particular in macrophages. Since inhalation of airborne materials is a key occupational concern, we then sought to test whether the in vitro responses noted for these materials would translate into adverse effects in vivo. To this end, the response at 1, 7 and 28 days after a single pulmonary exposure was evaluated in mice. In agreement with the in vitro data, PA6-rGO induced a modest and transient pulmonary inflammation, resolved by day 28. In contrast, rGO induced a longer-lasting, albeit moderate inflammation that did not lead to tissue remodeling within 28 days. Taken together, the present study suggests a negligible impact on human health under acute exposure conditions of GRM fillers such as rGO when released from composites at doses expected at the workplace., This work was supported by the European Union (EU) 8th Framework Program for Research and Technological Development, Graphene Flagship project (H2020-FET- GrapheneCore2 - #785219 and H2020-FET- GrapheneCore3 - #881603). Part of this work was supported by the University of Trieste, the Agence Nationale de la Recherche (ANR) through the LabEx project Chemistry of Complex Systems (ANR-10-LABX- 0026_CSC), the Maria de Maeztu Units of Excellence Program from the Spanish State Research Agency – Grant No. MDM-2017-0720 and the Swiss National Science Foundation (Grant 310030_169207).

BackgroundCommunity health workers (CHWs) play a critical role in supporting health systems, and in improving accessibility to primary healthcare. In many settings CHW programmes do not have formalised employment models and face issues of high attrition and poor performance. This study aims to determine the employment preferences of CHWs in Malang district, Indonesia, to inform policy interventions.MethodsA discrete choice experiment was conducted with 471 CHWs across 28 villages. Attributes relevant to CHW employment were identified through a multistage process including literature review, focus group discussions and expert consultation. Respondents’ choices were analysed with a mixed multinomial logit model and latent class analyses.ResultsFive attributes were identified: (1) supervision; (2) training; (3) monthly financial benefit; (4) recognition; and (5) employment structure. The most important influence on choice of job was a low monthly financial benefit (US$~2) (β=0.53, 95% CI=0.43 to 0.63), followed by recognition in the form of a performance feedback report (β=0.13, 95% CI=0.07 to 0.20). A large monthly financial benefit (US$~20) was most unappealing to respondents (β=−0.13, 95% CI=−0.23 to −0.03). Latent class analysis identified two groups of CHWs who differed in their willingness to accept either job presented and preferences over specific attributes. Preferences diverged based on respondent characteristics including experience, hours’ worked per week and income.ConclusionCHWs in Malang district, Indonesia, favour a small monthly financial benefit which likely reflects the unique cultural values underpinning the programme and a desire for remuneration that is commensurate with the limited number of hours worked. CHWs also desire enhanced methods of performance feedback and greater structure around training and their rights and responsibilities. Fulfilling these conditions may become increasingly important should CHWs work longer hours.

Graphene has drawn a lot of interest in the material community due to unique physicochemical properties. Owing to a high surface area to volume ratio and free oxygen groups, the oxidized derivative, graphene oxide (GO) has promising potential as a drug delivery system. Here, the lung tolerability of two distinct GO varying in lateral dimensions is investigated, to reveal the most suitable candidate platform for pulmonary drug delivery. Following repeated chronic pulmonary exposure of mice to GO sheet suspensions, the innate and adaptive immune responses are studied. An acute and transient influx of neutrophils and eosinophils in the alveolar space, together with the replacement of alveolar macrophages by interstitial ones and a significant activation toward anti-inflammatory subsets, are found for both GO materials. Micrometric GO give rise to persistent multinucleated macrophages and granulomas. However, neither adaptive immune response nor lung tissue remodeling are induced after exposure to micrometric GO. Concurrently, milder effects and faster tissue recovery, both associated to a faster clearance from the respiratory tract, are found for nanometric GO, suggesting a greater lung tolerability. Taken together, these results highlight the importance of dimensions in the design of biocompatible 2D materials for pulmonary drug delivery system., A.F. and A.A would like to acknowledge studentships co-funded by the Lloyds Register Foundation funded International Consortium on Nanotechnology (LRF-ICON) and the UK Research and Innovation Engineering and Physical Sciences Research Council (UKRI-EPSRC) Centre for Doctoral Training programme Graphene NOWNANO (EP/L01548X/1). This work was also supported by the European Union (EU) 8th Framework Programme for Research and Technological Development, GrapheneFlagship project (H2020-FET-GrapheneCore2—#785219 and H2020-FET-GrapheneCore3—#881603). The authors also thank Dr. Adrian Esteban Arranz, Dr. Miguel Arellano, Irene Rebollido, and Angeliki Karakasidi for their contributions to the synthesis and characterization of the GO materials used in the present study. Matthew Drummond and Abbie Dodd are acknowledged for their contributions to the tissue collection. In addition, the authors would like to acknowledge the following groups at ICN2 (Catalan Institute of Nanoscience and Nanotechnology, Barcelona, Spain): Advanced Electronic Materials and Devices led by Prof. Jose Garrido for the AFM and Raman instrumentation and assistance, and Supramolecular NanoChemistry and Materials led by Prof. Daniel Maspoch for the UV–vis equipment and assistance. The ICN2 is funded by the CERCA programme, Generalitat de Catalunya, and is supported by the Severo Ochoa Centres of Excellence programme by the Spanish Research Agency (AEI, grant no. SEV-2017-0706).

This paper proposes a novel method for bridge inspection that essentially digitises bridges using LIDAR so that they can be later inspected in a virtual reality environment. The work uses conventional terrestrial LIDAR together with affordable virtual reality hardware and freely available software development kits originally intended for authoring computer games. The resulting VR app is evaluated for a case study involving a typical masonry bridge; comparing the proposed technique with traditional inspection methods. The new approach promises to be highly effective in terms of interpretation of results, accessibility to critical areas and safety of inspectors. The work represents an important step towards the creation of digital twins of important assets in the built environment. Recent bridge collapse incidents have affected local economies, traffic congestion, and in some extreme cases led to a loss of life. The work is timely as law making agencies are paying greater attention to structural rehabilitation. This paper will be of particular interest to bridge engineers, construction professionals and law makers; and could lead to future revisions of bridge inspection processes and standards.

The editorial provides a broad contextualization of recent and developing theoretical and empirical examinations of digital materiality in museums. This Special Issue includes seven papers, which cover a range of theorizations, issues and challenges that arise in the intersection of digital and materiality in museum and heritage contexts.

Purpose The advent of Industry 4.0 has engendered opportunities for a coalescence of digital technologies that collectively enable driverless vehicles to operate during the construction and use of a highway. Yet, hitherto scant research has been conducted to review these collective developments and/or sample construction practitioner opinion on them. This study aims to present a systematic review of extant literature on the application of driverless technologies in civil engineering and in particular, the highways infrastructure sector and offers insight into the limitations of associated barriers to full adoption, namely, current technological development processes, legal deficiencies and societal concerns. In so doing, this work presents a vignette of contemporary developments augmented by a critical analysis from practitioners’ perceptions. Design/methodology/approach A mixed philosophical methodological approach is adopted for this inductive research study. Interpretivism is used to critically analyse the literature and post-positivism to perform content analysis of the literature and synthesis of the discourse with practitioners. A total of 44 related papers published between 1998 and 2019 have been included in this study. Emergent themes identified from literature are then discussed in some further detail, namely, 1) automation and robotics; 2) case studies and simulations; and 3) safety and ergonomics). A focus group is then held with leading industrialists to discuss their experiences of advanced driverless technology applications in practice. Based upon a culmination of emergent evidence, a conceptual model of prevailing barriers is then developed to further elucidate upon the challenges facing the highways infrastructure sector. Findings Research into driverless technologies within the highways infrastructure sector has received relatively scant academic attention. Hitherto, most advancements made have stemmed from multidisciplinary teams consisting of engineering, information technology and social scientist researchers. There is insufficient supporting evidence of civil engineering and construction academics input into developments made – suggesting that prototype products often fail to adequately consider practical applications in the highways infrastructure sector at the design and use case stage. This view is substantiated by feedback from leading industry experts who participated in unstructured telephone interviews. Their feedback suggests that practical applications of products have been beset with problems, thus creating a perception that advanced technologies are largely “unusable” within the highways infrastructure sector and so are unsuitable for large-scale (and particularly bespoke) industrial applications. Originality/value This research critically synthesises the prevailing scientific discourse within extant literature on driverless technologies implemented but also garners practitioner feedback from leading UK industrialists on their applications in practice. Hitherto, this combined analysis approach has been rarely used in spite of it having significant advantages of tacit knowledge reflection on technologies used, where such can be used as a basis for further informed discourse and/or development. Moreover, this work culminates in a conceptual model that acts as a catalyst for future research investigations.

Industry 4.0 technologies, process digitalisation and automation can be applied to support the formation of supply chain collaborations in manufacturing. Underpinned by information and communication technologies, collaborations of independent companies can dynamically pool production capacities and capabilities to jointly react to new business opportunities. These collaborations may involve a wide range of enterprises with different sizes and scope that individually would not be able to tender for such new business opportunities. To form these collaborative teams, assistive processes and technologies can underpin the effort towards exploring the tender requirements, unbundling the tender into smaller tasks and finding a suitable supplier for each task. In this paper, we present an approach and a tool to support decision making concerning forming supply chain collaborations in Industry 4.0. The approach proposed is unique in integrating industry domain ontologies, assistive human-computer interaction tools and multi-criteria decision support techniques to form team compositions speeding-up the collaboration process whilst maximising the chances of forming a viable team to fulfil the tender requirements. We also show evaluation results involving stakeholders from the supply chain function pointing to the effectiveness of the proposed solution, available online as a demo1.

Of the build out of humanity predicted up to the end of the century, a substantial portion will occur within informal urban settlements – areas characterised by poor access to infrastructure and services. There is a pressing need to better understand how and with what implications the growing proliferation of Internet of Things (IoT) technologies, as a component of smart urbanism, are being applied to address the challenges of these areas. The following paper addresses this research gap, showing how IoT technology is reconfiguring trust within water and energy infrastructures in Nairobi. We apply work on informal urban infrastructures and smart urbanism to three case studies, producing novel insights into how IoT technologies reconfigure connections between users, providers and infrastructures. This reconfiguration of trust smooths chronic infrastructural uncertainties and generates reliability within informal settlements and, in doing so, leads to increased personal economies. We conclude by considering how these examples provide insights into the implications of IoT for everyday urbanisms in informal settlements and how these insights relate to global smart city debates more widely.

Deeper City is the first major application of new thinking on ‘deeper complexity’, applied to grand challenges such as runaway urbanization, climate change, and rising inequality. The author provides a new framework for the collective intelligence – the capacity for learning and synergy – in many-layered cities, technologies, economies, ecologies and political systems.The key is in synergistic design thinking, to move beyond smart efficiency with ‘winner-takes-all’, towards wiser human systems where ‘winners-are-all’. 40 distinct pathways ‘from smart to wise’ are mapped in Deeper City and presented for strategic action, ranging from local neighbourhoods to global finance.As an atlas of the future, and resource library of pathway mappings, this book expands on the author’s previous work, City-Region 2020. From a decade of development and testing, Deeper City combines visual thinking with a narrative style and practical guidance. This book will be indispensable for those seeking a sustainable future - students, politicians, planners, systems designers, activists, engineers and researchers.

Understanding regional building energy patterns is the prerequisite to efficiently and effectively promote sustainable urban development. Previous studies have proposed various data-driven methods to investigate the relationship between building energy consumption and hundreds of potential influencing features. However, it is difficult to include all potential features in one single model since either some data could be unavailable or the model would be too complex. To identify the critical features, this study develops a data-driven random forest (RF) based framework with a dataset of Taipei City, consisting of 24,764 buildings in 881 city-blocks, to model the relationship between city-block-level building-oriented features and building energy consumption. The RF model is found to outperform other machine learning models including logistic regression, k-nearest neighborhood, support vector machine, and decision tree models in the predictive accuracy of the classification problem. Seven critical features related to the built year of buildings, building gross floor area, building density, and the ratio of commercial buildings in the block are identified from the 59 city-block-level building-oriented features. The developed framework could refine the features adopted in regional building energy models, and policymakers and city planners would get practical implications from the identified critical features.

There are approximately over 2.5 million bridges throughout the world, built towithstand massive forces and last for decades or centuries but very unlikely to last forever. According to a recent survey, there are more than 64,000 bridges in the US that have been declared as structurally deficient. Moreover, recent bridge collapse incidents in Italy, South Africa, United States and India have resulted in unplanned bridge closures affecting the economy of a state, traffic congestion, negative impact on day to day activities and in some extreme cases led to loss of life due to complete structural collapse. Therefore, law making agencies are pushed into paying greater attention to structural rehabilitation. Performanceevaluation of bridges includes visual inspection, destructive and non-destructive testing. It has been stated that “Regardless of the fact that many structure testing methods have so far been developed, visual inspection is likely to remain the most significant aid for bridge condition assessment, especially for smaller typical structures”. Results from inspection serve as a foundation for engineers to suggest if further testing (destructive or non-destructive) is required. However, precision and accuracy greatly vary with qualification, motivation andequipment of persons conducting these inspections. This paper emphasizes the use of modern day technology by presenting a workflow of bridge inspection namely, visual inspection to address limitations and difficulties faced by engineers in assessing performance of bridges. It involves the use of lidar to capture, on-site, an image of the structure with all its imperfections such as cracks, corrosion, spalling, signs of corrosion, seepage marks, weathering, segregation, honeycombing etc. The processed image is displayed in an immersive 3D virtual reality environment for assessment. Visual inspection through virtual reality (VR) promises to be a highly efficient and highly powerful inspection technique. Evaluation will become more reliable and accurate which will make engineers capable of effectively deciding the next step of rehabilitation. This technique is critically analyzed, interpreted and compared with traditional inspection methods to highlight the potentially improved efficiency of the proposed workflow. It is intended that the research findings will greatly contribute to the industrial development by raising standards and efficiency of bridge performance evaluation.

Background: Following an initial NHS Health Check appointment, the National Institute for Health and Care Excellence (NICE) suggest patients with QRISK2 scores of ≥ 10% should be offered advice on lifestyle and the risks and benefits of starting a statin. NICE recommend GPs should ascertain patients’ pre-existing knowledge of cardiovascular disease risk, explore health beliefs, assess readiness to change, offer support, and engage family members. Condensing this complex discussion into a short consultation may result in inadequate patient understanding of the benefits of preventive measures. An alternative approach is needed. We propose a digital adjunct giving patients the opportunity to interact with their health check results from home before returning to see their GP. Before embarking on funding applications we sought the views of patients and members of the public.\ud \ud Methods: We consulted the Primary Care Research in Manchester Engagement Resource (PRIMER), an established departmental Patient and Public Involvement (PPI) group (N=9) and then ran a workshop with 19 members of the public, co-facilitated by 4 members of PRIMER. Following a brief presentation on the background to the project, attendees were split into four groups and introduced to Ketso, a toolkit for creative engagement. Ketso was used to encourage group discussions regarding the project idea.\ud \ud Results: This PPI work improved the study design and proposed intervention. Discussions focussed on three themes: 1) positive feedback, 2) challenges and solutions, and 3) improvements/alternatives. Positive feedback included benefits to the NHS and patients. Challenges identified related to: 1) access, 2) data security, 3) engagement, and 4) negative consequences. Workshop members generated various solutions to these challenges and made additional suggestions for improvement relating to: 1) population (e.g. also including those with QRISK2 scores ≤ 10%), 2) duration (e.g. ongoing access to provide continued feedback), and 3) platform content (e.g. signposting to relevant services).\ud \ud Conclusions: This PPI work helped identify potential challenges and solutions not previously considered by the research team. Findings have informed the subsequent intervention design and strengthened the bid for funding. We aim to ensure ongoing patient and public involvement in all future stages.

A 3D multi-scale cellular automata finite element (CAFE) framework for modelling fracture in heterogeneous materials is described. The framework is implemented in a hybrid MPI/Fortran coarray code for efficient parallel execution on HPC platforms. Two open source BSD licensed libraries developed by the authors in modern Fortran were used: CGPACK, implementing cellular automata (CA) using Fortran coarrays, and ParaFEM, implementing finite elements (FE) using MPI. The framework implements a two-way concurrent hierarchical information exchange between the structural level (FE) and the microstructure (CA). MPI to coarrays interface and data structures are described. The CAFE framework is used to predict transgranular cleavage propagation in a polycrystalline iron round bar under tension. Novel results enabled by this CAFE framework include simulation of progressive cleavage propagation through individual grains and across grain boundaries, and emergence of a macro-crack from merging of cracks on preferentially oriented cleavage planes in individual crystals. Nearly ideal strong scaling up to at least tens of thousands of cores was demonstrated by CGPACK and by ParaFEM in isolation in prior work on Cray XE6. Cray XC30 and XC40 platforms and CrayPAT profiling were used in this work. Initially the strong scaling limit of hybrid CGPACK/ParaFEM CAFE model was 2000 cores. After replacing all-to-all communication patterns with the nearest neighbour algorithms the strong scaling limit on Cray XC30 was increased to 7000 cores. TAU profiling on non-Cray systems identified deficiencies in Intel Fortran 16 optimisation of remote coarray operations. Finally, coarray synchronisation challenges and opportunities for thread parallelisation in CA are discussed.

Objectives: As electronic mental health records become more widely available, several approaches have been suggested to automatically extract information from free-text narrative aiming to support epidemiological research and clinical decision-making. In this paper we explore extraction of explicit mentions of symptom severity from initial psychiatric evaluation records. We use the data provided by the 2016 CGES N-GRID NLP Shared Task Track 2, which contains 541 records manually annotated for symptom severity according to the Research Domain Criteria (RDoC). Methods: We designed and implemented three automatic methods: a knowledge-driven approach relying on local lexicalized rules based on common syntactic patterns in text suggesting positive valence symptoms; a machine learning method using a neural network; and a hybrid approach combining the first two methods with a neural network. Results: The results on an unseen evaluation set of 216 psychiatric evaluation records showed a performance of 80.1% for the rule-based method, 73.3% for the machine-learning approach and 72.0% for the hybrid one. Conclusions: While more work is needed to improve the accuracy, the results are encouraging and indicate that automated text mining methods can be used to classify mental health symptom severity from free text psychiatric notes to support epidemiological and clinical research.

We examine the relationship between information and communication technology for development (ICT4D) and local historically embedded institutions. We argue that, to understand the process of implementing IT artifacts, one needs to consider not only technical feasibility and economic viability but also institutional permissibility. We present a novel theoretical framework based on dialectics and institutional theory and apply it to a case study that contributes adialectics-centered framework illustrated with empirical data from the informal sector in Latin America. The analysis demonstrates the institutionalization of IT artifacts as a conflicted and contested process and that historical institutionsmay enable some forms of institutionalization while resisting others contrary to social norms. We examine the emergence of contradictions, active praxis, and the resulting outcomes before concluding that, for IT artifacts to contribute todevelopment, one must emphasize the embedded institutional arrangements and contestation that historically embedded institutions present. We conclude the paper by discussing the theoretical and practical implications.

This paper describes a multi-scale fracture framework, for modelling dynamic fracture in polycrystalline materials. The motivation behind developing such an application is to provide a high delity tool to model and capture dynamic structural deformations, at the macro scale, undergoing fracture at the micro-scale. The application links two highly scalable applications ParaFEM and CASUP, that model continuum using the finite element method and fracture using cellular automata respectively. Linking the two is done through a initial coupling step assigning the cellular automata to appropriate finite elements. Each time step the application passes data between the two packages, a stress tensor from ParaFEM to CASUP and a damage variable from CASUP to ParaFEM. If the maximum resolved normal stress on any cleavage plane exceeds fracture stress, crack propagation is induced through the material in the cellular automata, and the damage variable changes appropriately, updating the macro properties of the structure, modelled using finite elements. An example test case is shown, considering the degradation of a structure using material with differing critical stresses. The case showed materials undergoing permanent damage without failure and complete failure. Finally the parallel scalability of the application was explored and found to scale to 1000's of cores. Improved fidelity from coupling multiple scales in simulations has a wide range of applications in energy, aerospace and naval industries.