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ChatGPT could allow students to plagiarize the content of their coursework with little risk of detection. Little is known about undergraduate willingness to use AI tools. In this study, psychology undergraduates (N = 160) from the United Kingdom, indicated their willingness to use, and history of using, ChatGPT to write university assignments. Almost a third (32%) indicated that they would use such tools; 15% indicated that they had used them already. Neither personality (conscientiousness, agreeableness, Machiavellianism, narcissism), academic performance, nor study skills self-efficacy could predict future use of AI tools. A novel Degree Apathy Scale was the only significant predictor. Willingness to use AI tools was greater when the risk of getting caught was low, and punishment was light, particularly for those high in degree apathy. Findings suggest that degree apathy is a key risk factor in academic misconduct. Wider research and pedagogical applications of degree apathy are discussed. • Thirty-two percent of students surveyed reported that they would use ChatGPT on future academic assignments. • Future use of AI tools was significantly predicted by a new Degree Apathy Scale. • Big Five and Dark Triad scores were not significant predictors, nor was previous academic performance. • Likelihood of cheating using ChatGPT was reduced with increasing risk of detection or severity of punishment. [ABSTRACT FROM AUTHOR]

Staphylococcus argenteus and Staphylococcus schweitzeri, previously known as divergent Staphylococcus aureus clonal lineages, have been recently established as novel, difficult-to-delimit, coagulase-positive species within the S. aureus complex. Methicillin-resistant strains of S. argenteus are known from Australia and the UK. Knowledge of their epidemiology, medical significance and transmission risk is limited and partly contradictory, hampering definitive recommendations. There is mounting evidence that the pathogenicity of S. argenteus is similar to that of 'classical' S. aureus , while as yet no S. schweitzeri infections have been reported. To provide decision support on whether and how to distinguish and report both species. PubMed, searched for S. argenteus and S. schweitzeri. This position paper reviews the main characteristics of both species and draws conclusions for microbiological diagnostics and surveillance as well as infection prevention and control measures. We propose not distinguishing within the S. aureus complex for routine reporting purposes until there is evidence that pathogenicity or clinical outcome differ markedly between the different species. Primarily for research purposes, suitably equipped laboratories are encouraged to differentiate between S. argenteus and S. schweitzeri. Caution is urged if these novel species are explicitly reported. In such cases, a specific comment should be added (i.e. 'member of the S.aureus complex') to prevent confusion with less- or non-pathogenic staphylococci. Prioritizing aspects of patient safety, methicillin-resistant isolates should be handled as recommended for methicillin-resistant Staphylococcus aureus (MRSA). In these cases, the clinician responsible should be directly contacted and informed by the diagnosing microbiological laboratory, as they would be for MRSA. Research is warranted to clarify the epidemiology, clinical impact and implications for infection control of such isolates. [ABSTRACT FROM AUTHOR]

The growing number of space debris is alarming as it threatens space-borne services. Hence, there is an increasing demand to remove space debris to ensure sustainability and protect valuable orbital assets. Over the past few years, the research community, agencies and industries have studied many passive and active debris removal methods. However, the current technology readiness for space debris removal is still low. This paper first presents a comparative study of various space debris removal technologies to address the knowledge gap and quantify the challenges. This paper reviews the current state-of-the-art space technologies relevant to Active Debris Removal (ADR) missions. Detailed trade-off analysis is then presented based on the Low Earth Orbit Pursuit for Active Removal of Debris (LEOPARD) Phase 0-A study; this study is part of the United Kingdom (UK) Space Agency's Active Debris Removal programme. The ADR mission scenario considered in this paper comprises a chaser spacecraft equipped with recommended technologies to capture non-cooperative targets safely. The final capture technology for the LEOPARD mission consists of an active robotic manipulator and a passive net capture mechanism. An analysis of the coupled-body dynamics of the chaser spacecraft carrying the robot manipulator and the targeted debris is carried out in simulation using SimscapeTM. The chaser spacecraft comprises Airbus's Versatile In-Space and Planetary Arm (VISPA) mounted on a base spacecraft from Surrey Satellite Technology Ltd. (SSTL); the targeted debris is SSTL's Tactical Operational Satellite (TOPSAT). The simulation results show dynamic changes in the chaser robot and the target satellite while performing non-cooperative capture. The simulation study accounted for various operational scenarios where the target is stationary or in motion. Further, for different modes of operation, the worst-case end-effector capture force limits were determined using open-loop control to execute a safe capture. Overall, the results presented in the paper advance the current state-of-the-art of robotic ADR and offer a significant leap in designing close-range motion and force control for stabilising the coupled multi-body system during capture and post-capture phases. In summary, this paper pinpoints the technological gaps, identifies barriers to realising ADR missions and offers solutions to catalyse technology maturity for protecting the space ecosystem. [ABSTRACT FROM AUTHOR]

Disposable paper cups comprise typical single-use plastic items, as they are lined internally with a thin plastic coating for waterproofing. They are consumed at a staggering rate worldwide, with the UK alone consuming around 7 million cups daily, thus annually producing around 30,000 tonnes of paper cup waste. Contrary to popular belief, less than 1 in 400 paper cups is currently recycled in the UK, which is in stark contrast to the waste hierarchy and the European Commission's ambitious Circular Economy Action Plan. Paper cups typically end up in landfill sites or even improperly disposed of, contributing to (micro)plastic waste and potentially polluting the world's oceans. The implications of the latter are not fully known yet and cannot be quantified by existing life cycle impact assessment methods. By employing the life cycle assessment methodology, UK's annual carbon footprint from paper cup consumption was found to be 75 kt of carbon dioxide equivalents, which is similar to that of manufacturing 11,500 mid-size passenger cars. Globally, their environmental footprint was found to be comparable to that of some 1.5 M average European inhabitants, indicating the nature and extent of the single-use plastics problem, which paper cups are just a typical example of. Paper cup recycling could reduce this environmental footprint by up to 40%, whereas switching to reusable cups appears to be more environmentally sustainable, achieving a threefold reduction in carbon emissions, which at global scale is more than twice Malta's annual carbon footprint. Results indicate that consumerism along with small daily choices, such as using reusable cups or bags instead of their disposable counterparts, could play a huge role in climate change. At policy level, no concrete measures to curb the superfluous consumption of paper cups, as well as of other single-use plastic items that are becoming increasingly ubiquitous, have materialised. Furthermore, it appears that decision- and policy-makers tend to step in to curtail wasteful and polluting practices only when environmental problems have started to generate widespread concern, instead of undertaking preventative policy measures. Image 1 • The environmental sustainability of disposable paper cups was examined. • 75 kt CO 2eq are emitted annually in the UK and 7.5 Mt CO 2eq globally. • Switching to reusable cups axes carbon emissions by threefold. • Robust LCIA methods should be introduced to account for (micro)plastic pollution. • Existing policy on single use plastics appears to be too little too late. [ABSTRACT FROM AUTHOR]

Liver transplantation (LT) for unresectable colorectal liver metastases (CRCLM) demonstrates good overall survival for selected patients in contemporary studies, with 5-year survival of 80%. A Fixed Term Working Group (FTWG), set up by NHS Blood and Transplant (NHSBT) Liver Advisory Group (LAG), advised whether CRCLM should be considered for LT in United Kingdom. Their recommendation was that LT may be undertaken for isolated and unresectable CRCLM using strict selection criteria as a national clinical service evaluation. Opinions were sought from colorectal cancer/LT patient representatives, experts in colorectal cancer surgery/oncology, LT surgery, hepatology, hepatobiliary radiology, pathology, and nuclear medicine, and appropriate patient selection criteria, referral and transplant listing pathways were identified. This paper summarises selection criteria for LT in United Kingdom for isolated and unresectable CRCLM patients, and highlights referral framework and pre-transplant assessment criteria. Finally, oncology-specific outcome measures to be utilised for assessing applicability of LT are described. This service evaluation represents a significant development for colorectal cancer patients in United Kingdom and a meaningful step forward in the field of transplant oncology. This paper details the protocol for the pilot study, scheduled to begin in the fourth quarter of 2022 in United Kingdom. [ABSTRACT FROM AUTHOR]

• Systematic mass testing in closed settings provides information on infection rates. • Test positivity was 11.6%, with only one-quarter reporting symptoms. • The prison wing handling new admissions reported the second-lowest positivity rate. • Testing uptake was higher in residents than in staff members. • Mass testing is a valuable tool to bring outbreaks under control quickly. The aim of this paper was to describe the results of mass asymptomatic testing for COVID-19 in a male prison in England following the declaration of an outbreak. It provides novel data on the implementation of a mass testing regime within a prison during the pandemic. The paper is an observational evaluation of the mass testing conducted for 6 months following the declaration of a COVID-19 outbreak within a prison. It investigated the incidence of positive cases in both staff and residents using polymerase chain reaction testing. Data from October 2020 until March 2021 was included. A total of 2170 tests were performed by 851 residents and 182 staff members; uptake was 48.3% for people living in prison and 30.4% for staff. Overall test positivity was 11.6% (14.3% for residents, 3.0% for staff), with around one-quarter of these reporting symptoms. The prison wing handling new admissions reported the second-lowest positivity rate (9.4%) of the eight wings. Mass testing for COVID-19 over a short space of time can lead to rapid identification of additional cases, particularly asymptomatic cases. Testing that relies on residents and staff reporting symptoms will underestimate the true extent of transmission and will likely lead to a prolonged outbreak. [ABSTRACT FROM AUTHOR]

Numerous Artificial Intelligence (AI) solutions are available for achieving thermal comfort. They were either trained with limited datasets or using personalized training with limited field studies. This work assessed the model that used the ASHRAE multiple databases as the shallow supervised learning dataset for an Artificial Neural Network (ANN) based controller suitable for the residential dwellings' node. The learning accuracy can be increased to 96.1%. This paper presented the field studies to show the model performances for the common UK dwellings: the prior 1970s, the new, modular, refurbished, and the use of new materials to improve indoor thermal performance. The result shows that the model was able to perform in different environments and able to acknowledge adaptive human comfort. This was shown by the ability to represent 98.90% of the ASHRAE Standard 55 data, 6.06% improvement from the previous research. As a result, the broader comfort zone acknowledgement can lead to energy saving whilst maintaining comfort by the possibility of lowering the temperature set point. This study also proves that further energy savings can be acquired from the occupants' presence, scheduling, and activities. These factors can increase the comfort probability to more than 10%. [Display omitted] • This paper addresses the gap between the physiology and the psychology thermal comfort approach, dominated by AI solutions. • The work shows a wider comfort zone which has been identified to become progressively narrower over the past several decades. • The field studies represent major UK-dwelling cases that weren't addressed in the previous Artificial Intelligence approach. • The occupant presence and scheduling can contribute to more than a 10% increase in comfort which impacts energy saving. • This work highlights the possibility of achieving indoor thermal comfort with less energy for more sustainable dwellings. [ABSTRACT FROM AUTHOR]

Despite the transition towards a circular economy (CE) being a significant element in achieving the decarbonisation of the built environment, a clear and common pathway to applying CE principles to building design is still lacking in both industry practice and academia. The integration of Building Information Modelling (BIM) and Life Cycle Assessment (LCA) has the potential to enable the identification of feasible pathways to increase circularity. This study aims to investigate its practical use to facilitate the application of circular economy principles at the early stage of building design via using LCA-based BIM plugins. Within this aim, the paper centres on a co-production approach and presents a gap analysis by identifying gaps in knowledge and implementation as well as addressing the pressing needs of the current practice in the UK. A series of semi-structured interviews with expert practitioners in the field were conducted for data collection, contributing to the following phases of the co-production by allowing for an in-depth investigation and reflection of the practice. The findings have revealed that: (a) there is still an insufficient level of contextual awareness and readiness in the implementation of CE principles in the built environment and LCA understanding and (b) the adoption of BIM at the early stages of building design is still limited in the current practice; BIM models with sufficient level of data details and quality to enable circularity assessment are rarely produced. Thus, the paper highlights the need for enabling mechanisms, including the introduction of legislative instruments, the involvement and commitment of the industry and key stakeholders, the support for training and skills improvement, and the establishment of effective communication and implementation process management frameworks. Future research agenda points to the need of formulation of a BIM protocol to enable integration of BIM and LCA to promote CE principles in the building design process. [Display omitted] • Co-production is a promising approach to capture and respond to the industry needs. • Lack of seamless integration between BIM and LCA tools. • Insufficient understanding of how to apply CE principles in the building design. • Lack of systematic guidance and standardised process to implement BIM and LCA integration. • A tailored BIM protocol needed for applying LCA from a CE perspective in the building design. [ABSTRACT FROM AUTHOR]

Numerous Artificial Intelligence (AI) solutions are available for achieving thermal comfort. They were either trained with limited datasets or using personalized training with limited field studies. This work assessed the model that used the ASHRAE multiple databases as the shallow supervised learning dataset for an Artificial Neural Network (ANN) based controller suitable for the residential dwellings' node. The learning accuracy can be increased to 96.1%. This paper presented the field studies to show the model performances for the common UK dwellings: the prior 1970s, the new, modular, refurbished, and the use of new materials to improve indoor thermal performance. The result shows that the model was able to perform in different environments and able to acknowledge adaptive human comfort. This was shown by the ability to represent 98.90% of the ASHRAE Standard 55 data, 6.06% improvement from the previous research. As a result, the broader comfort zone acknowledgement can lead to energy saving whilst maintaining comfort by the possibility of lowering the temperature set point. This study also proves that further energy savings can be acquired from the occupants' presence, scheduling, and activities. These factors can increase the comfort probability to more than 10%. [Display omitted] • This paper addresses the gap between the physiology and the psychology thermal comfort approach, dominated by AI solutions. • The work shows a wider comfort zone which has been identified to become progressively narrower over the past several decades. • The field studies represent major UK-dwelling cases that weren't addressed in the previous Artificial Intelligence approach. • The occupant presence and scheduling can contribute to more than a 10% increase in comfort which impacts energy saving. • This work highlights the possibility of achieving indoor thermal comfort with less energy for more sustainable dwellings. [ABSTRACT FROM AUTHOR]

Do 'green' environmental concerns – such as about biodiversity, climate change, pollution – deter citizens from having children? This paper reports the first longitudinal evidence consistent with that increasingly discussed hypothesis. It follows through time a random sample of thousands of initially childless men and women in the UK. The paper shows that those individuals who are committed to a green lifestyle are found to be substantially less likely to go on later to have offspring. Probit and Weibull survival models are estimated. The results are robust to controlling for people's age, education, income, marital status, mental health, life satisfaction, optimism, and physical health. The paper's key estimated effect-size is substantial. A person entirely unconcerned about environmental behaviour is estimated to be just over 50% more likely to go on to have a child than a deeply committed environmentalist. • Will fertility decline because humans become so concerned about environmental damage? • Using UK data on thousands of randomly selected young adults, we provide the first longitudinal evidence that those who have environmental concerns and act in a 'green' way go on to have fewer children. • The estimated effect-size is large. [ABSTRACT FROM AUTHOR]

Police negotiators work in small units or teams. In a crisis negotiation, one of the team becomes the 'primary' negotiator and talks with the person in crisis. However, because the person in crisis may refuse to participate, and because several negotiators are co-present, there are multiple opportunities for negotiators to talk between themselves, 'behind-the-scenes'. We used conversation analysis to analyse these interstitial sequences in a corpus of audio-recorded UK suicide crisis negotiations. Our analysis focused on how negotiators talk about what, when, and how to communicate to people in crisis. We found that negotiators evaluated different communication technologies and modalities (e.g., telephone versus face-to-face) and physical locations (e.g., standing on the ground versus on a roof) in terms of their affordances for future interactions and impact on previous ones. Second, negotiators (re)formulated what and how to communicate with persons in crisis and evaluated hypothetical consequences. Third, they evaluated their progress in terms of specific (in)effective words and phrases. The analysis shows how negotiators, in contrast to individual post hoc reflection, come to share live scrutiny of their negotiation practice. Overall, the paper augments what we know about the low frequency but high-stakes activity of crisis negotiation. • The paper examines 'behind-the-scenes' communication between teams of crisis negotiators. • We analysed UK police negotiations with suicidal people in crisis. • Data were transcribed and analysed using conversation analysis. • Negotiators plan their ongoing communication in terms of precise words and phrases. • In contrast to individual post hoc reflection, negotiators evaluate practice in real time. [ABSTRACT FROM AUTHOR]

This paper explores distinct usages of the response particle right in American versus British English conversation. The analysis shows that, in American English, right conveys the speaker's knowing stance and, in certain environments, the speaker's claim of primary knowledge. In contrast, in British English, right registers provided information as previously unknown, informative, and relevant to the current speaker's ongoing project. The analysis draws on large corpora of audio- and video-recorded ordinary and institutional interactions in British and American English. We use the methodology of Conversation Analysis to examine sequential environments in which right is used, its interactional import, and prosodic realizations. • The response particle right is used differently in US versus UK English interaction. • In US English, right coneys a knowing stance and sometimes epistemic authority. • In UK English, right registers information as previously unknown but informative. • Implications of these findings are discussed. • The study employs Conversation Analysis to examine diverse data corpora. [ABSTRACT FROM AUTHOR]

This paper analyses the potential implications of the proposed European Union Deforestation Regulation (EUDR) and the recently adopted United Kingdom (UK) legislation on deforestation-free supply chains (henceforth 'the legislation') for different stakeholders in Brazil. These regulations intend to address global commodity-driven deforestation and forest degradation by ensuring that targeted commodities and products placed on (or exported from) markets are of minimal risk of being associated with - in the EU - deforestation and forest degradation or - in the UK - illegal deforestation. The paper examines potential compliance readiness in cattle, cocoa, coffee, palm oil, soybean and tropical timber supply chains in Brazil, indicating specific challenges that may arise. Through the construction of a "Compliance Likelihood Index", our research provides comparable indications to policymakers on sectors and stakeholders that may need stronger support to meet the requirements, in order to maintain Brazil's access to EU and UK markets. The paper indicates that coffee is the sector with the highest level of incentivization and smallest hurdles for compliance, while the cattle sector may face stronger challenges to rapidly adjust its production system towards a deforestation-free value chain and prove compliance. Results of our analysis also highlight the need for collaboration between the EU/UK and Brazil in order to promote alignment between domestic and demand-side legislations so that they are mutually reinforcing. Results of this exercise, which has a focus on the producer-country view of demand-side legislation, will contribute to discussions on the merits of different approaches to strengthen the governance of deforestation-risk commodity trade. [Display omitted] • Brazil's coffee sector may currently have the greatest likelihood of ready compliance. • Cattle may be the sector to which the regulations may pose the greatest challenges. • The EU and UK should focus on providing financial means and technical assistance for smallholders. • The EU and UK legislation will need to be accompanied by domestic policies and regulations in Brazil. [ABSTRACT FROM AUTHOR]

In this study, we examined two related aspects in pragmatic knowledge: namely, knowledge of the contexts in which certain linguistic forms are prototypically used (i.e. form-context mappings), and the indexical meanings which are produced when a form is used in a particular context. We employed one-to-one metapragmatic interviews with 30 L1 Korean speakers, 28 L2 Korean learners in the UK as well as eight group interviews with 26 of the learners. The interviews focused on the participants' understanding of the Korean first-person honorific pronoun ce in relation to its non-honorific equivalent na. The findings revealed that, while the learners' understanding of the contexts in which ce is normally used was fairly similar to L1 speakers, the indexical meanings that they associated with the form-context mappings differed saliently from that of L1 speakers. In addition, the learners struggled to align with the L1 speakers' meaning interpretations and made unsuccessful attempts to incorporate them into their existing indexical systems. The findings thus demonstrate that form-context mappings represent only one part of L2 learners' pragmatic competence. Future research and pedagogical efforts are encouraged to take into consideration the indexical meanings that underly language usage and help learners make more informed linguistic choices. • This paper examines two related aspects of pragmatics: form-context mappings and indexical meanings. • Second language learners had native-like understanding of the contexts in which a linguistic form is normally used. • However, they differed from the L1 speakers significantly in their interpretations of indexical meanings. [ABSTRACT FROM AUTHOR]

Over recent times there has been a rise in the number of objects placed into Earth orbit. With various countries licensing a number of large constellations, the orbital population is set to increase dramatically. A significant number of technical advances have facilitated this and, in the UK and elsewhere, this has been matched by the updating of legislation and an increased policy focus on the need for increased space surveillance and tracking. The rise of large constellations coupled with an increasing number of experimental techniques such as active debris removal or on-orbit servicing procedures means that establishing fault will be crucial if litigation is to be successful. In doing this, any legal proceedings will look at both norms of behaviour, deviation from which will point towards fault and the types and standard of evidence that will be required. This paper will outline these problems in detail. It will be proposed that what is required to map out the contours of liability are both codification of the norms for satellite operations and clarity on protocols for evidence gathering in cases where fault may be contested in orbital operations. This discussion will identify that a way in which this could be achieved is by the use of "space law games". These are simulations, similar to military war games, in which fictional scenarios could highlight some of the key legal issues that might need to be dealt with. The paper will outline some of the ways in which the law games might work and pose questions as to what data and other considerations will be needed to make such simulations meaningful. [ABSTRACT FROM AUTHOR]

Negative social and environmental consequences caused by corporate activities (e.g., workplace incidents, oil spills, and product-related accidents) can significantly affect the success and survival of a business. When there is bad news to report, how will companies handle the information disclosure? This paper examines discursive strategies UK and Chinese Fortune 500 companies used for communicating negative aspects in corporate social responsibility (CSR) reports. Based on 50 UK and 50 Chinese CSR reports, the study shows how companies legitimize the bad news via the strategies of Denial, Deflection, Mitigation and Admission. Two major differences were observed in the legitimation efforts made by Chinese and UK companies: i) almost all legitimation strategies were more frequently found in UK reports, and ii) UK reports mobilized a wider range of linguistic and rhetorical resources for realizing the strategies. The paper discusses the results by considering cultural, social, and organizational factors that may shape CSR discourse in the two countries. Findings add to the understanding of crisis communication and image repair strategies used by large corporations and the genre of CSR reporting in different cultures. • Legitimation strategies used by UK and Chinese companies were investigated. • 50 UK and 50 Chinese corporate social responsibility reports were analysed. • Chinese companies relied mainly on strategies of Deflection and Corrective Actions. • UK companies employed a wider range of linguistic and rhetorical tactics. • Findings reveal differences in the genre of CSR reporting in the two countries. [ABSTRACT FROM AUTHOR]

Meeting the goal of reaching zero emissions by 2050 requires profound changes in the production of bulk materials, cement and concrete. For construction sector, this transition is also dependent on the evolution of demand, stemming from changes in the population structure and practice in structural design. Many timelines have been produced suggesting pathways to zero emissions, but none have looked at the required investment level, or the feasibility of transition looking at the level of single plants being shut, transformed or built within a single country. In this paper, we have looked at transition pathways in the United Kingdom as a function of the available funding and the possible emergence of transformative technologies. We find that trade is a necessary component of the transition, allowing for continued construction while the production apparatus is upgraded. Our results further suggest that the current level of investment is consistent with today's carbon price but falls short of what is necessary to achieve net zero by 2050. Finally we find that pathways assuming that CCS will be available at scale are particularly susceptible to overshoot their emissions target if the technological deployment fails to materialise. This is because they combine heavy investments, immature technology and concentrated risk. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper aims to introduce an artificial intelligence approach to enhance short-term daily streamflow forecasts through the integration of machine learning (ML) techniques with meta -heuristic (MH) algorithms. To maximize performance, a comprehensive analysis involving the autocorrelation and partial autocorrelation functions of the observed streamflow was conducted to derive ten distinct input combinations, from which the most suitable set was selected for investigation. Subsequently, six distinct ML methods, namely, decision trees, support vector regression, long short-term memory, gated recurrent unit, multi-layer perceptron, and radial basis function (as the optimal input combination), were leveraged to predict one-day-ahead streamflow. The most promising outcomes from these six explored methods were synergistically amalgamated to enhance predictive precision. This amalgamation was then optimized by utilizing parameter values hyper-tuned by four different MH algorithms. The algorithms included the shuffled frog leaping algorithm, particle swarm optimization, ant colony optimization (ACO), and gray wolf optimization (GWO). In culmination, a case study centered around the "Wick" river in the UK was conducted to rigorously evaluate the performance of the proposed method, utilizing a range of statistical evaluation indices. The results underscored the efficacy of the proposed combined method in substantially refining streamflow predictions, exhibiting an impressive level of accuracy. Additionally, the outcomes emphasized that ACO and GWO stand out as the optimal algorithms for calibrating the parameters of the amalgamated model. For instance, the R2 values attained by the combined models optimized through the ACO and GWO algorithms were 0.69422 and 0.69444, respectively. These values notably surpass those observed in the initial models, substantiating the superiority of the applied optimization approaches. [ABSTRACT FROM AUTHOR]

Mixed sediment beaches are globally commonplace, yet little is understood of the extent and behaviour of their nearshore zones, potentially underestimating total cross-shore change. This paper is the first study to investigate the lateral and vertical extent of the active zone of the gravel-rich mixed beach in Pevensey Bay, a study site on the South East UK coastline. Morphodynamic change in the nearshore zone was studied at a range of timescales (days, months, years) suggesting that the width of the active nearshore zone correlated with the magnitude of the peak morphological change, whilst the depth of closure was influenced by bed slope, grain size and local variation in wave conditions. A conceptual model detailing the physical parameters responsible for local variations in the depth of closure was used to help understand differences between the observed and predicted depths of closure. Finally, ongoing chronic loss of sediment from below Mean Sea Level (MSL) was examined, which was shown to be independent of the depth of closure, but closely linked to the wider geomorphic setting of the bay. • Comparison of observational and predicted depth of closure for a mixed sediment beach • Local variations in the observed depth of closure examined using a conceptual model • Magnitude of subtidal bed elevation change may be controlled by sediment availability. • Loss of nearshore sediments over time reflects the trend in upper beach steepening. [ABSTRACT FROM AUTHOR]

• Load-related and non-load related planning is integrated into a single methodology. • The concept of probabilistic asset health indices (HIs) is developed. • Averages and pdfs of asset virtual ages and HIs are calculated along system indices. • Asset in-service time is modelled via proportional hazard and Kijima 2 models. • Proposed methodology gives lower investments that the UK deterministic approach. In the last price control review, the UK regulator has specified a common set of "network output measures" that includes both system-wide and individual asset metrics. This paper introduces a two-stage framework for the replacement planning and develops the second – simulation stage. It consists of two Monte Carlo procedures, where the latter is based on the proposed probabilistic health index (HI) methodology and application of several types of asset interventions, such as minimal, minor and major repairs and replacement. The probabilistic HI model makes use of proportional hazard models and Kijima II virtual – age model. The outputs are system-wide and nodal reliability indices, as well as asset interventions and asset profiles. IEEE test network is used to test the probabilistic HI methodology, which is then compared to the deterministic HI method applied in the UK. [ABSTRACT FROM AUTHOR]

The modern electricity network is seeing a trend in the replacement of fossil fuel power plants with converter interfaced generation as worldwide efforts are made to combat climate change. New converter control structures such as grid-forming are seen as a key building block for maintaining the stability of the future power system. Moreover, wind power is the fastest growing renewable technology in the UK with ambitious targets set for installed capacity in the coming decade. While the benefits and drawbacks of the technology have been explored, little attention has been given to how many grid-forming converters will be needed to stabilise the modern network. Is there such a thing as too much grid-forming? This paper utilises an impedance-based windfarm model with the capability to include unique control systems on each turbine to present a small-signal based methodology for determining the penetration limits of grid-forming technology. Key stability and screening metrics are applied to identify the penetration that provides the strongest and most stable system. Three key points are specified: the critical, optimal and maximum penetrations. Moreover, findings suggest providing enhanced system strength via converters is only applicable to a certain extent where further interactions cause increased stability issues. • The balance between grid-following and forming is of key concern. • Grid-forming is useful but too much can cause poor system behaviour. • A novel technique utilising small-signal impedances is suggested for analysis. • Three key penetrations have been specified minimum, optimal and maximum. • System strength must be considered as a function of frequency. [ABSTRACT FROM AUTHOR]

Modern economies rely on economic growth for stability and prosperity. Further, periods of stagnation and recession are currently associated with poor health and wellbeing outcomes for citizens. However, 50 years of research indicates that this state of dependency is ecologically unsustainable. It is therefore critical that we better understand the growth dependency of our economies and welfare systems, and how to overcome it. In this paper we first offer a working definition of growth dependency, clarifying its core dimensions. Next, taking the UK's adult social care sector as a case study, we argue that growth dependencies emerge in the welfare state as a result of three distinct dynamics: 1) growth in manifest needs; 2) labour productivity growth; 3) the pursuit of economic rents. Lastly, we propose a novel, sector-led framework for identifying, analysing and transforming growth dependencies. We make the case that the growth dependency of the welfare state is not inevitable, but is instead the product of specific social, economic and structural factors that can be disrupted and transformed, if we can find the political will to do so. [ABSTRACT FROM AUTHOR]

[Display omitted] • In-train air quality in UK diesel trains tested for 13 different train classes. • Means were PM 10 : 8–52; PM 2.5 : 4–36; BC: 1–11; NO 2 : 28–201 (µg/m3); UFP: 225–9131 #/cm3. • Large in-train variability was observed and associated with multiple factors. • Trains under 10 years old had the lowest in-train PM concentrations. • UK diesel trains measured lower PM 2.5 and PNC than other transport modes. Concentrations of particulate matter (PM 10 , PM 2.5), ultrafine (UFP), particle number (PNC), black carbon (BC), nitrogen dioxide (NO 2) and nitrogen oxides (NO X) were measured in train carriages on diesel and bi-mode trains on inter-city and long-distance journeys in the United Kingdom (UK) using a high-quality mobile measurement system. Air quality on 15 different routes was measured using highly-time resolved data on a total of 119 journeys during three campaigns in winter 2020 and summer 2021; this included 13 different train classes. Each journey was sampled 4–10 times with approximatively 11,000 min of in-train concentrations in total. Mean-journey concentrations were 7.552 µg m−3 (PM 10); 3.936 µg m−3 (PM 2.5); 333–11,300 # cm−3 (PNC); 225–9,131 # cm−3 (UFP); 0.6–11 µg m−3 (BC); 28–201 µg m−3 (NO 2); and 130–3,456 µg m−3 (NO X). The impact of different factors on in-train concentrations was evaluated. The presence of tunnels was the factor with the largest impact on the in-train particle concentrations with enhancements by a factor of 40 greater than baseline for BC, and a factor 6 to 7 for PM and PNC. The engine fuel mode was the factor with the largest impact on NO 2 with enhancements of up to 14-times larger when the train run on diesel compared to the times running on electric on hybrid trains. Train classes with an age < 10 years observed the lowest in-train PM, BC and NO X concentrations reflecting improvements in aspects of rail technology in recent years. Air quality on UK diesel trains is higher than ambient concentrations but has lower PM 2.5 and PNC than most other transport modes, including subway systems, diesel and petrol cars. This paper adds significantly to the evidence on exposure to poor air quality in transport micro-environments and provides the industry and regulatory bodies with reference-grade measurements on which to establish in-train air quality guidelines. [ABSTRACT FROM AUTHOR]

In the era of Big Data, the Internet has become one of the main data sources: Data can be collected for relatively low costs and can be used for a wide range of purposes. To be able to timely support solid decisions in any field, it is essential to increase data production efficiency, data accuracy, and reliability. In this framework, our paper aims at identifying an optimized and flexible method to collect and, at the same time, geolocate social media information over a whole country. In particular, the target of this paper is to compare three alternative methods to collect data from the social media Twitter. This is achieved considering four main comparison criteria: Collection time, dataset size, pre-processing phase load, and geographic distribution. Our findings regarding Great Britain identify one of these methods as the best option, since it is able to collect both the highest number of tweets per hour and the highest percentage of unique tweets per hour. Furthermore, this method reduces the computational effort needed to pre-process the collected tweets (e.g., showing the lowest collection times and the lowest number of duplicates within the geographical areas) and enhances the territorial coverage (if compared to the population distribution). At the same time, the effort required to set up this method is feasible and less prone to the arbitrary decisions of the researcher. [ABSTRACT FROM AUTHOR]

Metrology provides the underpinning science that supports the practical use of testing standards; ensuring that different users, be it academia, government or industry, develop a common language regarding the capabilities of many materials sectors. For the hardmetal community, after a century of fundamental and effective applications, it isn't surprising that there are already a considerable number of formal International Standards. For example, ISO and ASTM are well known [1], and over time these have evolved, with international consensus, from metrological studies. Currently important properties of hardmetals such as Stiffness, Density, Hardness, Toughness, Abrasion Resistance, Macroscopic Strength and Phase and Magnetic properties are comprehensively supported by these international standards. However, there are other testing strategies where improved knowledge could contribute to enhanced carbide functionality. These might include high resolution microscopy, indentation strength measurements, micro-tribology, thermal fatigue testing and modelling in all its diverse approaches which are not yet addressed through standards, though they often feature strongly in published academic papers. The hardmetal research community is international, diverse and productive in addressing these many facets and frequently embed metrological studies that are relevant to the practical characterisation of hardmetals. In the UK the Materials Group at the National Physical Laboratory, NPL, has a prime remit to focus on metrology and our contribution to the WC-Co 100 year anniversary publication provides some specifics of typical metrological issues that need further attention before addressing the formal stage of standardisation. In this celebratory paper we have chosen examples of recent metrological activities that fall under this remit and which have only partly been contributed to the scientific published domain. These five examples are High Hardness measurements, Dislocation Analysis, Micro-Tribology, Nanoindentation and Structural Characterisation. • Issues associated with high hardness metrologies. • Assessment of dislocations in WC using slip trace analysis. • Micro-tribology as a metrology tool for hardmetal wear. • Nanoindentation of WC crystals at ambient and high temperatures. • WC grain size issues using EBSD, especially in large data files. [ABSTRACT FROM AUTHOR]

Zero‑carbon electricity is a pre-requisite for decarbonisation of the wider economy and many scenarios envisage rapid expansion of renewables. IEA estimates a need to double the annual rate of investment to 2030. A rapid transition to low carbon electricity creates a risk to investors because projects being financed now will generate their revenue in a zero‑carbon electricity system for which there is no track record of price formation. Although the cost of renewable power has fallen greatly, future revenues from renewables are still affected by market price risks that are often outside the control of generators. If risks are difficult to quantify, they may be mis-priced, leading to inefficient premiums being added to the cost of capital, which could increase the overall cost of the transition. In this context many countries around the world provide support for low carbon energy, such as the UK Contracts for Difference. In this paper we investigate exposure to price risk caused by uncertainty over the mix of technologies used to achieve decarbonisation, which we term 'transition risk', and how this varies under different technology mixes, and for different policy regimes. We show that exposing investors to transition risk could increase the cost of delivering the renewables needed for a zero‑carbon electricity system by around 25% or £7bn/year compared to policy options that reduce exposure to wholesale market price risk. The paper concludes that as long as transition risks remain high, de-risking policy mechanisms can help to minimise the overall cost of achieving net-zero. • We characterise the current stage of the low-carbon transition as a 'build phase', requiring large volumes of investment • Uncertainty over the final physical state of the decarbonised system causes significant financial risk to investors • 'Contracts for difference' (CfDs) help to manage this 'transition risk' and reduce the cost of capital for projects • Exposing projects fully to transition risk could increase costs by a third, and raise the cost of transition by £7bn per year [ABSTRACT FROM AUTHOR]

• A net-zero DN model composed of solely non-dispatchable DGs and BESSs has been considered to tackle severe windstorms. • The proposed framework is particularly effective in DNs with high shares of converter-based DGs. • The proposed three-stage resilience assessment can provide up to 25 percent load shedding reduction. • A detailed spatiotemporal representation of the DN was implemented to accurately estimate the status of the grid. Increasing incidences of extreme weather events pose significant challenges to the electrical grids in terms of the ability to withstand those high-impact eventualities. This paper proposes a resilience assessment framework for net-zero active distribution networks (ADNs) to tackle the impacts of extreme windstorms where only renewable energy resources (RESs) and battery energy storage systems (BESSs) are considered. To accurately capture the influence of windstorms on the grid, a detailed spatiotemporal representation of grid system assets and their exposure to the wind has been implemented. The suggested day-ahead resilience assessment is based on a three-stage approach. The first stage computes the probabilities of failure of each line and determines the most vulnerable ones. The second stage obtains the optimal grid configuration based on the outcomes of the first stage given the available non-dispatchable RESs and commits the available resources in each island to minimize the loss of load during the windstorm. If such a value is still larger than zero after the second stage, a novel voltage regulation scheme is applied in the third stage, taking advantage of the RESs and BESSs in each island. The proposed resilience assessment has been evaluated using the IEEE 33-bus test system with the meteorological data retrieved from an actual windstorm event occurred in the UK on the 20th of February. The outcomes of this paper underscore that a significant reduction in load shedding during such extreme events can be achieved, thus having a notable enhancement to the overall resilience of the system. Finally, the performance of this approach is compared with other resilience-oriented methods for windstorms, where the benefits of using the scheme reported in this paper are highlighted and quantified. [ABSTRACT FROM AUTHOR]

The heat released from the disposal of High-Heat-Generating Waste (HHGW) in a Geological Disposal Facility (GDF) will result in an increase in temperature, and therefore thermal expansion of both the engineering materials and surrounding rocks. The changes to the stress state arising from the thermal expansion of these materials, restrained by the surrounding rock mass, could affect several of the Thermal, Hydraulic, and Mechanical (THM) processes that operate after closure of a GDF. In this paper a methodology is described which suggests how the influence of thermal stress on fracture aperture around a GDF can be evaluated. A set of calculations on an illustrative Discrete Fracture Network (DFN) are reported. These calculations estimate the responses of the fractures to changes in rock stress, considering changes in fracture aperture and the resultant changes to effective intrinsic permeability. • This paper provides a methodology to describe the influence of thermal stress on fracture aperture. • It uses a, realistic, but illustrative 3D fracture network involving several million finite elements. • Fracture apertures were found to be reduced in a region around and beneath the GDF due to compressive stresses. • The maximum decrease in fracture apertures in the vicinity of the GDF was by a factor of about 2. • The changes in fracture aperture led to a modified effective permeability of the rock mass. [ABSTRACT FROM AUTHOR]

• All-Terrain Vehicles (ATVs) are linked to farming fatalities and injuries every year. However, despite evidence that wearing a helmet reduces the risk of serious injury, few farmers wear them. • This study assessed farmer attitudes to ATV helmets using the Michie COM-B model. • Participants reported a range of barriers to helmet wearing including the perception that helmets could interfere with work activities, social stigma and perceived exemption from harm. • Key interventions are suggested using the Michie behaviour change wheel, including modelling, raising awareness and training. All-Terrain Vehicles (ATV) are a popular piece of farming machinery but are linked to many fatalities and injuries every year. Despite evidence that ATV helmets reduce the risk of serious or fatal injury, research suggests that few farmers wear them. The aim of this study was to explore farmer attitudes toward ATV helmets, using the COM-B model as a framework to identify key barriers and enablers of helmet use and suggest potential interventions to increase helmet use in agriculture. Methods : A mixed-methods online survey featuring quantitative and qualitative questions was used to explore key attitudinal factors relevant to farmer helmet wearing. A total of 211 UK and Irish farmers were recruited, including farm owners, managers, workers, and contractors. Results : Personal exemption from risk, emotional benefits, cognitive barriers, and guideline prompts were all found to be significant predictors of farmer helmet wearing. Key categories within the qualitative data indicated that helmet properties, risk perception, farming culture, and the farming environment could all function as barriers to helmet wearing. Suggested enablers of helmet use included increasing helmet availability and enhancing awareness of the consequences of ATV accidents. Conclusions : The key barriers and enablers presented within this paper highlight the relevance of capability (helmet design, time pressure), opportunity (social norms), and motivation (perceived control of risk) when considering farmer helmet wearing behaviors. In order to encourage farmers to wear helmets it will be necessary to design specific interventions using the behavior change wheel. Practical applications : Key interventions to prompt helmet use include the inclusion of more cues to prompt helmet wearing (e.g., stickers on the ATV), enhanced training and education, and modelling (e.g., key farming figures shown to wear helmets in the media). [ABSTRACT FROM AUTHOR]

• Improved PPP is used in kinematic model for oscillating displacement monitoring. • The improved PPP has better convergence performance with high cut off angle. • Better accuracy can be achieved by ZWD augmented PPP in kinematic model. This paper developed the tropospheric correction augmented PPP for the purpose of bridge displacement monitoring. ZWD is estimated from undifferenced observations collected by UK CORS, and further applied to augment PPP client for displacement at the bridge surveying points. Coordinate time series obtained by GPS DD are treated as the true bridge displacement, which is used to assess the standard and CORS ZWD augmented PPP solutions obtained by varying cutoff angles. The experimental results reveal that the displacement precision of standard PPP severely depends on the satellite geometry. Meanwhile, the CORS ZWD augmented PPP results are less affected. The RMSE of improved PPP time series in the vertical component drops by 12%, 49% and 66% for the 5°, 10° and 15° cutoff angle cases, respectively. CORS ZWD augmented PPP can improve the monitoring precision and eliminate irregular displacement time series due to poor satellite geometry. [ABSTRACT FROM AUTHOR]

This paper shows how existing methods of time series analysis and modeling can be exploited in novel ways to monitor and forecast the COVID-19 epidemic. In the past, epidemics have been monitored by various statistical and model metrics, such as evaluation of the effective reproduction number, R (t). However, R (t) can be difficult and time consuming to compute. This paper suggests two relatively simple data-based metrics that could be used in conjunction with R (t) estimation and provide rapid indicators of how the epidemic's dynamic behavior is progressing. The new metrics are the epidemic rate of change (RC) and a related state-dependent response rate parameter (RP), recursive estimates of which are obtained from dynamic harmonic and dynamic linear regression (DHR and DLR) algorithms. Their effectiveness is illustrated by the analysis of COVID-19 data in the UK and Italy. The paper also shows how similar methodology, combined with the refined instrumental variable method for estimating hybrid Box–Jenkins models of linear dynamic systems (RIVC), can be used to relate the daily death numbers in the Italian and UK epidemics and then provide 15-day-ahead forecasts of the UK daily death numbers. The same approach can be used to model and forecast the UK epidemic based on the daily number of COVID-19 patients in UK hospitals. Finally, the paper speculates on how the state-dependent parameter (SDP) modeling procedures may provide data-based insight into a nonlinear differential equation model for epidemics such as COVID-19. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused huge and disruptive technological changes in the healthcare sector, transforming the way businesses and societies function. To respond to the global health crisis, there have been numerous innovation projects in the healthcare sector, including the fast design and manufacturing of personal protective equipment (PPE) and medical devices, and testing, treatment, and vaccine technologies. Many of these innovative activities happen beyond organizational boundaries with collaboration and open innovation. In this paper, we review the current literature on open innovation strategy during the pandemic and adopt the co-evolution view of business ecosystems to address the context of change. Based on a detailed exploration of the COVID-19-related technologies in the UK and global healthcare sectors, we identify the key emerging themes of open innovation in crisis. Further discussions are conducted in relation to each theme. Our results and analysis can help provide policy recommendations for the healthcare sector, businesses, and society to recover from the crisis. [ABSTRACT FROM AUTHOR]

Several studies have demonstrated the capability of data-driven modelling based on on-site measurements to characterise the thermal performance of building envelopes. Currently, such methods include steady-state and dynamic heating experiments and have mainly been applied to scale models and unoccupied test buildings. Nonetheless, it is proposed to upscale these concepts to characterise the thermal performance of in-use buildings based on on-board monitoring (OBM) devices which gather long-term operational data (e.g., room temperatures, gas and electricity consumption...). It remains, however, to be proven whether in-use data could be a cost-effective, practical and reliable alternative for the dedicated tests whose more intrusive measurements require on-site inspections. Furthermore, it is presently unclear what the optimal experimental design of the OBM would be and which data analysis methods would be adequate. This paper presents a first step in bridging this knowledge gap, by using on-board monitoring data to characterise the overall heat loss coefficient (HLC) [W/K] of an occupied, well-insulated single-family house in the UK. With the aid of a detailed building physical framework and specifically selected data subsets a sensitivity analysis is carried out to analyse the impact of the measurement set-up, the duration of the measurement campaign and the applied data analysis method. Although the exact HLC of the building is unknown and no absolute errors could hence be calculated, this paper provides a new understanding of the decisions that have to be made during the process from design of experiment to data analysis. It is demonstrated that such judgements can lead to differences in the mean HLC estimate of up to 89.5%. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between people's feelings about dirt, and an apparent reduction in the lifetime of vacuum cleaners. The short life-spans of vacuum cleaners is a significant environmental issue. In addition to the waste generated, they have an impact on climate change: vacuum cleaners account for the second largest embodied greenhouse gas emissions of electrical goods in the UK after televisions, largely because of their high sales volumes. Drawing from qualitative and quantitative research undertaken for the UK Department for Environment, Food & Rural Affairs (Defra), the paper demonstrates that one motivation for vacuum cleaner replacement is the increased enjoyment from dirt removal that a new vacuum cleaner may provide. The paper also shows that premature disposal can occur once a product becomes dirty and visually damaged, and whilst functional, is perceived to be less effective. Solutions to premature disposal were explored through the co-creation of design concepts and design features were tested via an online survey. Vacuum cleaner users were clustered into four cleaner types; Spartan, Minimal, Caring and Manic. Overall, respondents reported that improving the ease of maintaining vacuum cleaners would be the most effective way to help them to increase their vacuum cleaner's longevity. Across all cleaner types maintenance levels were low, although Caring and Manic cleaners were significantly more likely to undertake such tasks. Motivations for disposal were similar across cleaner types and we found no evidence that Caring and Manic cleaners disposed of their machines earlier because they were 'worn out.' We discovered that Caring and Manic cleaners spend the most on their vacuum cleaners, vacuum more often and are the most likely to replace their machine after the shortest period. Those willing to do 'a lot more' to help the environment were significantly more likely to want to 'keep the floors in my home spotlessly clean' and significantly more likely to indicate that they preferred their vacuum cleaner to look new. Consequently, the paper proposes that design interventions to increase vacuum longevity should be targeted toward Caring and Manic cleaners and concludes with key design recommendations for these two cleaner types. [ABSTRACT FROM AUTHOR]

The UK is facing tremendous challenges in tackling food waste diversion from landfill. Whilst much effort has been made to prevent food waste, there is still a lack of attention and strategic approach in dealing with resource recovery and valorisation of food waste. This paper presents a systematic framework for sustainable organic waste management and valorisation in the UK through (i) review of current policy framework; (ii) analysis of resource recovery potential from food waste at national, community and organisational levels; (iii) proposition of alternative waste management strategies; and (iv) examination of challenges and opportunities with respect to economic, environment and social dimensions of sustainability of waste management strategies. The paper explores valorisation of source-segregated food waste and mixed waste from the supermarket and households into electricity and transportation fuels, through partially and completely decentralised configurations using anaerobic digestion and gasification technologies. This study demonstrates a potential for reducing the cost of electricity and greenhouse gas emissions of one supermarket store by 12% when adopting partially decentralised food waste anaerobic digestion strategy, and full substitution of fossil fuel based electricity with net surplus renewable electricity generation through complete decentralisation of mixed waste gasification. Therefore, a more integrated, circular and advanced technological approach in waste management should be undertaken as it can lead to a wider range of socio-economic and environmental advantages to the local community, highly essential in the UK. Image 1 • Valorisation of waste closer to the source promotes resource circularity. • A synergistic approach is robust in addressing challenges in waste management. • Technology and configuration determine the viability of valorisation strategies. • Decentralised waste management enhances community participation. • A supportive fiscal incentive scheme promotes uptake of waste valorisation. [ABSTRACT FROM AUTHOR]

Maritime transport is an indispensable element of the global logistics network. Most maritime loading-unloading operations are supported by quay cranes, making their availability and condition critical to port operations. This work identifies discordant trends arising during the vibration-based condition monitoring of these quay cranes in one of the busiest container ports in the United Kingdom. This work proposes an unsupervised and constrained discord detection approach for irregular but near real-time time series data obtained from multi-modal IoT-based condition monitoring sensors installed on these cranes and transmitted over a 5G network. Due to the live nature of the seaport's operations, the development of controlled anomaly signatures for a baseline reference was not possible. To address the challenges of incomplete asset health information, irregular and batched time-series sensor data, massive data volumes, and the lack of the assets' vibration signature baselines, this paper proposes an unsupervised, robust, and fast discord detection mechanism that can rapidly highlight discordant time-series chunks in the received vibration data at a central server. A Support Vector Machine based One-Class Classifier (OCC-SVM) is used to identify the discordant vibration signatures in the time series data. During the development of this approach, the timestamped data chunks from the add-on IoT-based vibration sensors were clustered into two weight classes (loaded and unloaded) based on the crane's default Programmable Logic Controller (PLC) sensors. The efficacy of this method is checked against the crane maintenance logs and data from a separate crane's vibration and PLC data. Further, a method for generating synthetic noise-embedded vibration signatures to test the effectiveness of the discord detection method has been devised. Finally, the practicality of the proposed OCC-SVM approach for discord detection was inspected in a constrained environment setting. [ABSTRACT FROM AUTHOR]

In the process of implementing circular economy within the built environment, quantifying progress and performance towards this effort has posed a substantial challenge. In response, this paper reviews the current state of building-specific circularity indicators, creates a taxonomy, and integrates them within the Royal Institute of British Architects (RIBA) Plan of Work, a commonly employed framework within the UK's built environment. Through a systematic literature review considering both academic and grey literature, 32 building circularity indicators, developed by academia, consulting agencies, and governments, are identified. The first contribution of this study is the creation of a taxonomy of building circularity indicators, which classifies the identified indicators into 8 categories, such as basic characteristics of indicators, circularity level, and sustainability pillars. The second contribution of this study is the alignment of circularity within the stages of Plan of Work framework. It is revealed that the framework does not currently incorporate circularity, resulting in the proposal of a new Stage 8: End of Life to encompass demolition, disassembly, and deconstruction activities. Alignment of the taxonomy to Plan of Work framework provides a guide in utilization of building circularity indicators throughout the process of designing, constructing and operating building projects. • Building-specific circularity indicators are reviewed for the built environment. • A taxonomy of 32 building circularity indicators is created across eight categories. • A new Stage 8: End of Life is proposed for RIBA framework to enhance circularity. • The circularity indicators are integrated with the RIBA Plan of Work framework. • A traffic light approach is employed to guide the use of circularity indicators. [ABSTRACT FROM AUTHOR]

Energy poverty is driven by four factors: poverty; high energy prices; energy-inefficiency; and specific household characteristics. Increasingly refined definitions of energy poverty (and/or vulnerability) identify types or locations of households most likely to be suffering it. But there is also a place for a different approach, considering poverty reduction directly, as poverty is a necessary component within all energy poverty definitions. This paper investigates how high the UK's top marginal tax rates would need to be, to provide funds to lift low-income UK households above the poverty threshold as defined by the low-income-high-cost (LIHC) and 10% energy poverty indicators. It finds that the increased top tax rates would still be in line with those of other European OECD countries. Using recent and new research on income elasticities of CO2 emissions, it then estimates the net direct effects on CO2 emissions of this redistribution. For both scenarios the most likely effect is a small reduction in net CO2 emissions. Further, indirect downward pressures on CO2 emissions due to reduced income among the highest earners are likely to lead to yet more favourable outcomes for net CO2 emission reduction. [ABSTRACT FROM AUTHOR]

Tree populations worldwide are facing an unprecedented threat from a variety of tree diseases and invasive pests. Their spread, exacerbated by increasing globalisation and climate change, has an enormous environmental, economic and social impact. Computational individual-based models are a popular tool for describing and forecasting the spread of tree diseases due to their flexibility and ability to reveal collective behaviours. In this paper we present a versatile individual-based model with a Gaussian infectivity kernel to describe the spread of a generic tree disease through a synthetic treescape. We then explore several methods of calculating the basic reproduction number R 0 , a characteristic measurement of disease infectivity, defining the expected number of new infections resulting from one newly infected individual throughout their infectious period. It is a useful comparative summary parameter of a disease and can be used to explore the threshold dynamics of epidemics through mathematical models. We demonstrate several methods of estimating R 0 through the individual-based model, including contact tracing, inferring the Kermack–McKendrick SIR model parameters using the linear noise approximation, and an analytical approximation. As an illustrative example, we then use the model and each of the methods to calculate estimates of R 0 for the ash dieback epidemic in the UK. • Computational individual-based models can simulate the spread of plant disease. • Disease progression can be summarised by the epidemiological parameter R 0. • R 0 can be calculated from an individual-based model in several ways. • Methods include: analytic expressions, parameter inference, and contact-tracing. • Each has (dis)advantages — the best choice will vary depending on requirements. [ABSTRACT FROM AUTHOR]

High-frequency financial data is more difficult to predict than low-frequency data because it possesses nonlinearity, nonstationarity, higher volatility, and long memory and is frequently accompanied by the jump phenomena. In this paper, the nonparametric regression (NR) model based on kernel function is used to fit the nonlinear relationship between the nonstationary series Y t and its lagging series to model the trend of high frequency financial time series. Furthermore, the deep learning LSTM (long short-term memory) model is applied to capture the high volatility and frequent jumps of high frequency financial data and to improve the forecasting accuracy of the residual series. The results demonstrate that the hybrid NR and LSTM model has greatly improved the forecasting accuracy in several evaluation criteria. In comparison to NR, support vector machine (SVM), LSTM, ARIMA and NR-SVM models, the mean absolute error (MAE) of NR-LSTM has reduced by 89.78%, 97.85%, 86.48%, 32.47% and 89%, respectively. In addition, we have constructed the trading strategy for the Shanghai-Shenzhen 300 index by using the NR-LSTM model. The NR-LSTM model can continue to provide good returns even during a bear market, which can serve as a guide for investors. Furthermore, the NR-LSTM model also exhibits the best forecasting effect when we model the high-frequency data of Ping An bank in China, the FTSE 100 index in the UK, and the S&P 500 index in the US. [ABSTRACT FROM AUTHOR]

State-estimation plays a vital role to monitor, observe and understand the combined heat and electric network. In this paper, a hybrid framework is presented to accurately estimate the system states of electric distribution network and heat network, using the limited non-redundant measurements obtained from supervisory control and data acquisition and advanced metering infrastructure systems. The presented hybrid framework involves two steps, namely, the state-forecasting and the state-estimation. The state-forecasting uses a deep neural network to forecast the system states at every fifteen minutes interval, while these forecasted states are further used by the hybrid estimator, which uses a robust extended Kalman filter to estimate the system states with help of both datasets corresponding to supervisory control and data acquisition and advanced metering infrastructure systems, at hourly interval. The proposed framework does not completely rely on the system model at different instants. The effectiveness of the method is validated through thorough comparisons with simulation studies carried out using the Barry Island test system, United Kingdom. Satisfactory performance is observed even with the presence of bad data in the measurements. • A framework to estimate states of electric and heat networks with SCADA and AMI data • A method of forecasting the CHEN states using only a limited SCADA dataset • A robust Kalman filter for accurate estimation under gross errors in data. • Test results that validate the method on Barry Island CHEN system. • Comparative results over the state-of-art WLS and ANN based estimators. [ABSTRACT FROM AUTHOR]

• An innovative dew point cooling system was designed, constructed, installed and real live tested in live data centre. • The system can provide continuously stable cooling air and maintain the required temperature and humidity in data centre. • The average COP of 29.7 was achieved during the testing period. • 90 % energy saving can be achieved for data centre cooling. • Suitability, stability and reliability of the system used in data centre environment were proved. This paper presents the development and application of a super performance dew point cooling technology for data centres. The novel super performance dew point cooler showed considerably improved energy saving and carbon reduction for data centre cooling. The innovations of this technology are built upon a series of technological breakthroughs including, a novel hybrid flat/corrugated heat and mass exchanging sheets, an innovative highly water absorptive and diffusive wet-material for the sheets which enable an intermittent water supply with well-tuned water pressure and flow rate, and the optimised fan configurations. Following a list of fundamental research including theoretical, numerical and lab experimental testing of a small scale prototype system, a specialist 100 kW rated data centre dew point cooling system was dedicated designed, constructed, installed and real life tested in an operational live data centre environment, i.e., Maritime Data Centre at Hull (UK) to investigate its dynamic performance, suitability and stability for application in operational data centre environment conditions. During the testing period, the system showed its reliability and capability to remove a tremendous amount of heat dissipated from the IT equipment and maintain an adequate space temperature in the operational live data centre. The dynamic data collection and analysis during the continuous testing and monitoring period showed the average COP of 29.7 with the maximum COP of 48.3. Compared to the existing traditional vapor compression air conditioning system in the data centre, the energy saving using the super performance dew point cooling system is around 90 %. The work presented in this paper include detailed innovation aspects of the technology and the system operation, as well as the established bridging knowledges, methodology and technical procedure for bringing this new technology into real life operation which involve in data centre survey, optimum design and modularization of the specialist cooling system for data centre application, proven system installation, operating method and cooling air management for data centre as well as the assurance of the continuous sufficient cooling supply to the data centre. [ABSTRACT FROM AUTHOR]

The saltmarsh carbon storage potential is a key topic in blue carbon research and climate policy. Ecosystem service valuations provide valuable information to policymakers for habitat management and climate change mitigation policies. Yet, only few saltmarsh valuation studies have included the carbon storage service in the UK context. This paper investigates how the public values saltmarsh ecosystem services, focussing on the carbon storage service. We used a choice experiment to elicit the willingness to pay (WTP) of a representative sample of the Scottish public to support interventions that would maintain or improve the provision of these services. Furthermore, we tested the effect of information on individuals' preferences and WTP with a split sample approach where one group received a treatment in the form of additional information. We found that (i) all attributes had a significant influence on individuals' choices; (ii) both groups had, on average, a positive marginal WTP for all presented ecosystem services; (iii) the treated sample had, on average, no significantly different marginal WTP for carbon storage than the control group. This paper adds to the limited literature on the saltmarsh carbon storage ecosystem service and demonstrates a developed nation's public's openness to nature-based climate change mitigation solutions. [Display omitted] • The Scottish public on average prefers saltmarsh management over the status quo. • Providing additional information reduced heterogeneity in WTP for carbon storage. • Most respondents preferred an improvement of all saltmarsh ecosystem services. • Therefore management should focus on both climate change mitigation and adaptation. [ABSTRACT FROM AUTHOR]

• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

Main road widening can reduce the clearance of the low-level underpass road, restricting the passage of vehicles and leading to collisions with structures. Therefore, checking the clearance of the underpass road effectively should be considered at the design stage. This paper describes a digital twin approach for checking the clearance of underpass roads in highway widening projects using online map data. The underpass road digital twin and BIM model of the newly widened road based on the existing main road digital twin are created to assist the clearance check and redesign. The proposed method presented a cost-effective clearance check for underpass roads in road widening design without field surveys and was successfully implemented in an underpass road in the UK. In future research, more digital twin methods for overpasses, bridges, tunnels, and traffic safety facilities should be employed comprehensively to assist more road widening applications. • A novel approach is presented to check the underpass road clearance in the road widening project. • A method for building road digital twins from online map data is proposed. • A systematic method for road widening based on the digital twin is proposed. • According to the clearance check, the underpass road can be redesigned to increase the insufficient clearance. [ABSTRACT FROM AUTHOR]

Many higher education institutions have started to develop academic curricula, research capacity and outreach activities related to circular economy. However, little is known yet on how to apply circular economy thinking to sustainable campus management. In an attempt to address this gap, this paper proposes a methodological framework and guidance to help universities develop a circular economy strategy aimed at improving resource efficiency and environmental sustainability of their campus operations. The approach is compatible with sustainability management frameworks as it follows the well-known iterative process of planning, doing, checking and improving. The framework involves three main steps: analysis of current situation with respect to circular economy within the organisation; stakeholder engagement to get a buy-in and inform the development of a circular economy strategy; and implementation of the strategy following the guidelines provided within the framework. Application of the framework is illustrated through a case of the University of Manchester, demonstrating how circular economy principles can be used to benchmark existing sustainability policies and action plans. The paper also shows how engaging key stakeholders can be used to identify challenges and opportunities for embedding circular economy thinking into the university's sustainability management systems. The proposed framework and the guidelines for implementation of circular economy thinking are generic and can be applied by any institution across the higher education sector. Image 1 • There is a lack of knowledge on how to implement circular economy in universities. • A simple but powerful framework is proposed to guide institutions in that process. • Application of the framework is illustrated through a real case of a large UK university. • Challenges and opportunities for CE are discussed based on stakeholder interviews. • Guidelines are provided for the development and implementation of a CE strategy. [ABSTRACT FROM AUTHOR]

• Drain water heat recovery potential of commercial kitchens is examined. • Financially feasible potential in the hospitality sector in the UK is 1.24 TWh / yr. • This can be achieved at 2.94 p £/ kg Ce saved , over a 10-year lifetime. • This leads to 344 k tons Ce / yr reduced emissions. • 160 GWh (a reduction of 44 k tons Ce / yr) remains commercially unexploitable. In order to meet ambitious greenhouse gas reduction targets, the reduction of fuel consumption in the heating sector is necessary. This paper assesses the impact of introducing direct drain water heat recovery systems in commercial kitchens in the UK, based on a commercially available heat exchangers. The recoverable heat from these kitchens was estimated using Monte Carlo simulation, sector consumption data, and data measured in the field. A financial criterion, the Net Present Value calculated over 10 years, was used to estimate feasibility threshold values for the kitchen water consumption, varying with the heating fuel used in each premises. This analysis resulted in a total financially feasible potential for drain water heat recovery in the hospitality and food service sector in the UK of approximately 1.24 TWh / yr , leading to a reduction in GHG emissions of 344 k tons Ce / yr. This could be achieved at a cost of approximately 2.94 p £/ kg Ce saved , over a 10-year lifetime, which was several orders of magnitude smaller than traditional renewable heat sources such as heat pumps. Commercially available drain water heat recovery systems could, when installed, exploit around 88% of current potential in drain water heat in commercial kitchens (1.40 TWh / yr) in a manner that is financially profitable. However, this paper assumes the availability of a 2 m vertical drop in the kitchen drain, required to install the heat exchanger, and thus achieve optimal effectiveness. In case this head is not available, the heat recovery potential would be untapped, as in approximately 160 GWh , in kitchens where the hot water consumption is too small for financial profitability. This corresponds to a reduction in GHG emissions of 44 k tons Ce / yr and leaves a gap in the market for inexpensive DWHR devices, which could exploit this potential at lower efficiencies. [ABSTRACT FROM AUTHOR]

• This study estimates the effect of education on trust with a RD design. • Education and trust are positively and significantly correlated. • The OLS estimates may suffer from omitted variable bias. • RD estimates imply the effects of education on trust may be small. • We need to interpret the relationship between education and trust with caution. Although many studies document that education and trust are positively correlated, few studies examine whether this correlation represents a causal effect. This paper fills in the gap with data from the British Social Attitudes Survey. Firstly, using the OLS method, this paper finds that education and the three measures of trust—trust in people, trust in politicians, and trust in government—are all positively and significantly correlated. Secondly, to examine whether this correlation represents a causal effect, this paper exploits exogenous variation in educational attainment induced by the compulsory schooling reform in 1972. The regression discontinuity estimates suggest that the effects of education on the three measures of trust are all small and statistically insignificant. The findings imply that the OLS estimates may suffer from omitted variable bias and the effects of education on trust may be small. [ABSTRACT FROM AUTHOR]

Abstract Regenerative eco-innovation , demanding radical and architectural change to restore, renew and revitalise the natural system, is arguably the most important type of eco-innovation to address the pressing challenges of sustainable development. The aim of this paper is to explore the role of the regulatory framework and wider contextual conditions in facilitating or hindering regenerative eco-innovations. This is especially relevant for the built environment, a sector that is highly regulated and where rates of innovation are typically slow. We combined a review of relevant archival material with an interview programme involving key stakeholders from the UK's built environment sector. We contribute to the literature by extending and elaborating our understanding of regenerative eco-innovation in two ways. First, we extend the literature on regulation and eco-innovation by exploring what constitutes high quality regulation in the context of regenerative development. Second, we elaborate on how regenerative eco-innovations are facilitated or hindered by wider contextual conditions. Our paper also has practical utility. More understanding of how effective regulation can support regenerative eco-innovations, and of how the wider contextual conditions facilitate or hinder regenerative eco-innovations, allows industry and government to respond better to the urgent global challenge of closing material cycles. Highlights • Explores the influence of regulation and wider contextual conditions on regenerative eco-innovation • Focuses on a case study of extracted materials in the UK built environment sector • Extends and elaborates our understanding of regenerative eco-innovation in two ways: • what constitutes high quality regulation in the context of regenerative development • how the regulatory roots of regenerative eco-innovation are affected by wider contextual conditions [ABSTRACT FROM AUTHOR]