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Food environment research is increasingly gaining prominence in low- and middle-income countries (LMICs). However, in the absence of a systematic review of the literature, little is known about the emerging body of evidence from these settings. This systematic scoping review aims to address this gap. A systematic search of 6 databases was conducted in December 2017 and retrieved 920 records. In total, 70 peer-reviewed articles met the eligibility criteria and were included. Collectively, articles spanned 22 LMICs, including upper-middle-income countries (n = 49, 70%) and lower-middle-income countries (n = 18, 26%). No articles included low-income countries. Articles featured quantitative (n = 45, 64%), qualitative (n = 17, 24%), and mixed-method designs (n = 11, 8%). Studies analyzed the food environment at national, community, school, and household scales. Twenty-three articles (55%) assessed associations between food environment exposures and outcomes of interest, including diets (n = 14), nutrition status (n = 13), and health (n = 1). Food availability was associated with dietary outcomes at the community and school scales across multiple LMICs, although associations varied by vendor type. Evidence regarding associations between the food environment and nutrition and health outcomes was inconclusive. The paucity of evidence from high-quality studies is a severe limitation, highlighting the critical need for improved study designs and standardized methods and metrics. Future food environment research must address low-income and lower-middle-income countries, and include the full spectrum of dietary, nutrition, and health outcomes. Improving the quality of food environment research will be critical to the design of feasible, appropriate, and effective interventions to improve public health nutrition in LMICs.

Vitamin A deficiency is common among preschoolers in low-income settings and a serious public health concern due to its association to increased morbidity and mortality. The limited consumption of vitamin A-rich food is contributing to the problem. Many factors may influence children’s diet, including residential food environment, household wealth, and maternal education. However, very few studies in low-income settings have examined the relationship of these factors to children’s diet together. This study aimed to assess the importance of residential food availability of three plant-based groups of vitamin A-rich foods, household wealth, and maternal education for preschoolers’ consumption of plant-based vitamin A-rich foods in Addis Ababa. A multistage sampling procedure was used to enroll 5467 households with under-five children and 233 residential food environments with 2568 vendors. Data were analyzed using a multilevel binary logistic regression model. Overall, 36% (95% CI: 34.26, 36.95) of the study children reportedly consumed at least one plant-based vitamin A-rich food group in the 24-h dietary recall period. The odds of consuming any plant-based vitamin A-rich food were significantly higher among children whose mothers had a higher education level (AOR: 2.55; 95% CI: 2.01, 3.25), those living in the highest wealth quintile households (AOR: 2.37; 95% CI: 1.92, 2.93), and in residentials where vitamin A-rich fruits were available (AOR: 1.20; 95% CI: 1.02, 1.41). Further research in residential food environment is necessary to understand the purchasing habits, affordability, and desirability of plant-based vitamin A-rich foods to widen strategic options to improve its consumption among preschoolers in low-income and low-education communities.

The impact of incivility in terms of individual and team performance in clinical environments is increasingly acknowledged and supported by a growing evidence base. However, clinical environments are not just areas where patient care is delivered, they are also rich, key learning arenas for healthcare professionals. To date, the potential impact of incivility in clinical environments on healthcare professional learning and development has not been comprehensively explored. This article provides an overview of the physiological mechanisms that inhibit learning and memory recall in individuals experiencing or observing incivility and social stress. It establishes a clear need for focus on the impact of incivility on clinical learners and educators and further evidence for the need for clinical environments in which civility is firmly rooted into the pervading culture.

The adoption of the Circular Economy paradigm by industry leads to increased responsibility of manufacturing to ensure a holistic awareness of the environmental impact of its operations. In mitigating negative effects in the environment, current maintenance practice must be considered, not just for the reduction of its own direct impact but also for its potential contribution to a more sustainable lifecycle for the manufacturing operation, its products and related services. Focusing on the matching of digital technologies to maintenance practice in the automotive sector, this paper outlines a framework for organisations pursuing the integration of environmentally aware solutions in their production systems. This research acts as a primer for digital maintenance practice within the Circular Economy and the utilisation of Industry 4.0 technologies for this purpose.

Purpose The purpose of this paper is to explore the role that computer vision can play within new industrial paradigms such as Industry 4.0 and in particular to support production line improvements to achieve flexible manufacturing. As Industry 4.0 requires “big data”, it is accepted that computer vision could be one of the tools for its capture and efficient analysis. RGB-D data gathered from real-time machine vision systems such as Kinect ® can be processed using computer vision techniques. Design/methodology/approach This research exploits RGB-D cameras such as Kinect® to investigate the feasibility of using computer vision techniques to track the progress of a manual assembly task on a production line. Several techniques to track the progress of a manual assembly task are presented. The use of CAD model files to track the manufacturing tasks is also outlined. Findings This research has found that RGB-D cameras can be suitable for object recognition within an industrial environment if a number of constraints are considered or different devices/techniques combined. Furthermore, through the use of a HMM inspired state-based workflow, the algorithm presented in this paper is computationally tractable. Originality/value Processing of data from robust and cheap real-time machine vision systems could bring increased understanding of production line features. In addition, new techniques that enable the progress tracking of manual assembly sequences may be defined through the further analysis of such visual data. The approaches explored within this paper make a contribution to the utilisation of visual information “big data” sets for more efficient and automated production.

This study aimed to determine if the Turner et al. (2018) framework allows researchers to identify and study relationships between food environments and individual food choice in diverse contexts and if updates to the framework are warranted. We mapped evidence from 15 drivers of food choice projects to the framework, using thematic analysis to identify common drivers within the food environment across countries and emergent characteristics not listed in the framework. The framework contained breadth and depth of content necessary to identify common drivers – prices and affordability, availability, and vendor and product properties. Insights regarding common drivers and emergent characteristics may inform iterative development of conceptual and empirical research and reinforce current strategies seeking to improve nutrition and health outcomes in LMICs through targeted policies and interventions.

Cyber–physical systems such as satellite telecommunications networks generate vast amounts of data and currently, very crude data processing is used to extract salient information. Only a small subset of data is used reactively by operators for troubleshooting and finding problems. Sometimes, problematic events in the network may go undetected for weeks before they are reported. This becomes even more challenging as the size of the network grows due to the continuous proliferation of Internet of Things type devices. To overcome these challenges, this research proposes a knowledge-based cognitive architecture supported by machine learning algorithms for monitoring satellite network traffic. The architecture is capable of supporting and augmenting infrastructure engineers in finding and understanding the causes of faults in network through the fusion of the results of machine learning models and rules derived from human domain experience. The system is characterised by (1) the flexibility to add new or extend existing machine learning algorithms to meet the user needs, (2) an enhanced pattern recognition and prediction through the support of machine learning algorithms and the expert knowledge on satellite infrastructure, (3) the ability to adapt to changing conditions of the satellite network, and (4) the ability to augment satellite engineers through interpretable results. An industrial real-life satellite case study is provided to demonstrate how the architecture could be used. A single blind experimental methodology was used to validate the results generated by our approach.

A new resource—DataJoint Elements—provides modular designs for assembling complete workflow solutions to organize data and computations for common neurophysiology experiments. The designs are derived from working solutions developed in leading research groups using the open-source DataJoint framework to integrate data collection and analysis in collaborative workflows.

This paper explores the notion of the modular building construction site as an applied instance of redistributed manufacturing, in so doing, this research seeks to reduce the environmental footprint of building sites, treating them as small digitally connected subunits. In seeking to provide a whole lifecycle appreciation of a construction project, it is noted that the presence of a framework to provide guidance on the consideration of Internet of Things (IoT) data streams and connected construction objects is currently lacking. This paper proposes use of embedded IoT enabled sensing technology within all stages of a modular building lifecycle. An expanded four-phase model of intelligent assets use in construction is proposed along with an outline of the required data flows between the stages of a given building’s entire lifecycle that need to be facilitated for a BIM (Buildings Information Modelling) representation to begin to describe a building project as a sustainable asset within the circular economy. This paper also describes the use of concrete as a modular sensing structure, proposing that health monitoring of the material in situ along with the recoding of environmental factors over time could help to extend the longevity of such structures.

IntroductionMyotonic dystrophies type 1 and 2 (DM1 and DM2) are progressive, inherited multisys- tem disorders characterized by muscle weakness, myotonia and life-threatening cardiac dysrythmias. Treatment of myotonia is important for quality of life, mobility, and functional independence. Mexiletine is a sodium channel blocker, which has so far been shown to be effective in myotonia management in non-dystrophic myotonias. However, cardiac side effects are reported. Its long-term safety and efficacy in DM1 has not been established.Methods25 patients with DM1 or DM2 have been treated with mexiletine in the NHNN cohort. Efficacy and tolerance was determined by patient report. PR interval, QRS duration and corrected QT interval (QTc) were noted.ResultsMean duration of treatment was 32.9 months. 21/25 patients reported efficacy, 3/25 partial efficacy, and 4/25 discontinued treatment due to gastrointestinal side effects.Mexiletine did not precipitate symptomatic arrhythmia in any patient. Paired assessment of ECG param- eters at baseline and at the highest treatment dose revealed no significant change in PR interval, QRS complex duration, or QTc.ConclusionsThis small retrospective analysis suggests long-term efficacy and cardiac safety of mexiletine for treatment of myotonia in patients with myotonic dystrophies.christinamousele92@gmail.com

Evidence supports Allport's (1954) contention that social contact reduces mental illness stigma and promotes symptom recognition. However, an important limitation of existing research is that it typically relies on relatively simplistic measures of contact (e.g., any contact, number of contacts). Here, we build on prior work by examining how contact with persons with mental illness within social networks shapes labeling processes and beliefs about the causes of mental illness. Using egocentric network methods and vignette data from the 2018 General Social Survey (N = 1173), findings reveal that connections to valued ties (e.g., friends, family) that disconfirm commonly held stereotypes about people with mental illness contribute to improved recognition of mental illness and reduce the likelihood of endorsing stigmatizing beliefs about causes of mental illness. By using network theory and methods, this research extends current understanding of the role of contact by revealing not only whether contact matters, but how it matters and under what circumstances it may reduce prejudice and discrimination attached to mental illness in contemporary society.

Studies using transcranial direct current stimulation (tDCS) typically incorporate a fade‐in, short‐stimulation, fade‐out sham (placebo) protocol, which is assumed to be indistinct from a 10–30 min active protocol on the scalp. However, many studies report that participants can dissociate active stimulation from sham, even during low‐intensity 1 mA currents. We recently identified differences in the perception of an active (10 min of 1 mA) and a sham (20 s of 1 mA) protocol that lasted for 5 min after the cessation of sham. In the present study we assessed whether delivery of a higher‐intensity 2 mA current would exacerbate these differences. Two protocols were delivered to 32 adults in a double‐blinded, within‐subjects design (active: 10 min of 2 mA, and sham: 20 s of 2 mA), with the anode over the left primary motor cortex and the cathode on the right forehead. Participants were asked “Is the stimulation on?” and “How sure are you?” at 30 s intervals during and after stimulation. The differences between active and sham were more consistent and sustained during 2 mA than during 1 mA. We then quantified how well participants were able to track the presence and absence of stimulation (i.e. their sensitivity) during the experiment using cross‐correlations. Current strength was a good classifier of sensitivity during active tDCS, but exhibited only moderate specificity during sham. The accuracy of the end‐of‐study guess was no better than chance at predicting sensitivity. Our results indicate that the traditional end‐of‐study guess poorly reflects the sensitivity of participants to stimulation, and may not be a valid method of assessing sham blinding., We quantified how well participants were able to track the presence and absence of a tDCS current (i.e. their sensitivity), using cross‐correlations. Current strength was a good classifier of sensitivity (higher for 2mA than 1mA), but the accuracy of their end‐of‐study guess was no better than chance at predicting sensitivity. The traditional end‐of‐study guess method poorly reflects the sensitivity of participants to stimulation, and may not be a valid method of assessing sham blinding.

Letter: Reply to Mendes LL, Pessoa MC, Duarte CM. Comments on the article: food environment research in low- and middle-income countries: a systematic scoping review. Adv Nutr 2020;11(4):1046–7.

Current OEM (Original Equipment Manufacturer) facilities tend to be highly integrated and are often situated on one site. While providing scale of production such centralisation may create barriers to the achievement of fully flexible, adaptable, and reconfigurable factories. The advent of Industry 4.0 opens up opportunities to address these barriers by decentralising information and decision-making in manufacturing systems through CPS (Cyber Physical Systems) use. This research presents a qualitative study that investigates the possibility of distributing information and decision-making logic into ‘smart workpieces’ which can actively participate in assembly operations. To validate the concept, a use-case demonstrator, corresponding to the assembly of a ‘flat-pack’ table, was explored. Assembly parts in the demonstrator, were equipped with computation, networking, and interaction capabilities. Ten participants were invited to evaluate the smart assembly method and compare its results to the traditional assembly method. The results showed that in its current configuration the smart assembly was slower. However, it made the assembly process more flexible, adaptable and reconfigurable.

I examine several recent interpretations of Cynic philosophy. Next, I offer my own reading, which draws on Schopenhauer’s Incongruity Theory of Humor, Aristotle’s account of the emotions in the Rhetoric, and the work of Theodor Adorno. I argue that Cynic humor is the deliberate exposure of incongruities between what a thing or state of affairs is supposed to be (either by nature or according to tradition) and what it in fact is, as evidenced by its present manifestation to our sense-perception and thought. Finally, I interpret the significance of this new reading: the exposure of incongruity aims to elicit a response of righteous indignation at the failure of phenomena to live up to our reasonable expectations. Cynic humor redeems the value of ‘wrong life’ by rendering its wrongness palpable and thus intolerable, by availing itself of reason’s inability to withstand flagrant contradictions.

Undergraduate and graduate education research has stratified study strategies from low-utility to high-utility with respect to durable learning. The purpose of this study was to determine the prevalence of these evidence-based learning strategies among surgery residents in preparation for the American Board of Surgery In-Training Examination (ABSITE).A 23-item survey was administered during individual interviews. It assessed whether they had a study plan, and the average length and frequency of their independent study, both during the year and the month prior to the ABSITE. Data were also collected on their primary resources and study strategies. Residents rated their usage of those strategies based on a 5-point Likert scale.Maine Medical Center, an academic tertiary care center located in Portland, ME.All residents in the Department of Surgery.Residents (n= 23) intensified their preparation for the ABSITE in the month prior to the exam compared to the remainder of the year, adopting study plans (87% vs 61%, p = 0.53) and increasing the time spent studying (median, 420 vs 120 minutes per week, p0.001). Primary resources used were textbooks (65%), ABSITE review books (26%) and online question banks (9%). All residents (100%) often or always used testing, but fewer residents often or always used spacing (24%), both considered high-utility strategies. Most residents (60%) often or always used highlighting, considered a low-utility strategy. There were no relationships between study strategies and ABSITE scores.All residents use self-testing as a study strategy. Most underuse spacing and overuse highlighting. Further research is needed to establish the relationship between these study strategies and ABSITE scores.

Fibre steering is involved in the development of non-conventional variable stiffness laminates (VSL) with curvilinear paths as well as in the lay-up of conventional laminates with complex shapes. Manufacturability is generally overlooked in design and, as a result, industrial applications do not take advantage of the potential of composite materials. This work develops a design for manufacturing (DFM) tool for the introduction in design of the manufacturing requirements and limitations derived from the fibre placement technology. This tool enables the automatic generation of continuous fibre paths for manufacturing. Results from its application to a plate with a central hole and an aircraft structure – a windshield front fairing – are presented, showing good correlation of resulting manufacturable paths to initial fibre trajectories. The effect of manufacturing constraints is assessed to elucidate the extent to which the structurally optimal design can be reached while conforming to existing manufacturing specifications.

Summary The National Institute for Health and Care Excellence published guidelines for managing early-onset neonatal infections in 2012. It recommended provision for reporting blood cultures (BCs) with growth detected or not detected at 36 h. To determine if this was followed, a telephone survey was conducted amongst lead biomedical scientists based at microbiology laboratories (N = 209) in the UK. Overall, 202/209 responded and 139/202 had on-site facilities for BCs. BC results with growth detected or not detected at 36 h were available out-of-hours in 36/139 (26.6%) and 66/139 (47.5%) neonatal units, respectively. Early discontinuation of antibiotics should lead to improved antibiotic stewardship.

Discrete-Event Simulation (DES) is commonly used for the simulation of manufacturing systems. In many practical cases, DES practitioners have to make simplifications or to use the software in an unconventional or convoluted fashion to meet their needs. Petri nets enable the development of transparent models which conciseness are a synonym of increased flexibility and control for designers. Furthermore, Petri nets take advantage of a solid mathematical ground and constitute a simple language. However, Petri nets lack the software capabilities to realise their full potential. This study investigates the suitability and relevance of Discrete-Event Simulation (DES) software for Petri net modelling in the context of manufacturing systems. A framework is developed for the modelling of different classes of Petri nets on DES. Analytical models of asynchronous flow lines are developed. Initial results show that the analytical models are without closed-form solution and the explosion of the state space is observed, justifying the use of computational methods and simulation for the analysis of manufacturing systems. This study shows that the gain in flexibility provided by Petri nets provides a new insight into the effects of stochasticity on setup and failure times in manufacturing systems.

International audience; Multiple recent global nutrition initiatives have recommended actions to transform food systems to improve food environments and food choice. This study aimed to identify actions recommended by these initiatives and understand their similarities and differences. Twelve global nutrition initiatives were reviewed, collectively spanning 13 action themes and accompanying strategies. Action themes were analyzed according to primary focus on either food environments and their food system drivers or food choice. Representation of the 13 actions varied across initiatives. Some actions overlapped; others were infrequently represented. Strategies targeting food environments and their food system drivers were more frequently recommended than strategies targeting food choice for 11 of the 13 action themes. Although these global initiatives share a mission to improve nutrition through food systems and food environments, less attention has been allocated to individual food choice and sustainability.

This study investigates consumer experiences of food environments and food acquisition practices during the Covid-19 pandemic. Our rapid assessment online survey featured a convenience sample of 2015 individuals from 119 countries, spanning Western Europe, North America, Latin America, Asia-Pacific, and Africa. Data collection took place in April 2020 during the second month of the pandemic. Participants were recruited via existing networks of the United Nations System Standing Committee on Nutrition, through social media, and by snowballing. The majority of participants were female (71.9%), from low- and middle-income countries (51.0%), and working in nutrition or healthcare (39.3%). Qualitative thematic analysis and descriptive statistics reveal a series of common global experiences related to food availability and accessibility, food prices and affordability, food acquisition practices, and food preparation and consumption. The importance of community food participation, food sharing, and resource allocation are highlighted, along with increasing awareness of healthy diets and food waste. We identify ten synergistic policy entry points to: 1) build resilient and equitable food environments resistant to stresses and shocks; 2) harness positive dietary-related behaviors manifested during the pandemic; and, 3) mitigate the projected nutrition crisis and promote sustainable healthy diets for all.

In conversation with trauma specialist Bessel van der Kolk, this paper poses three questions for a theology of spiritual care. What does current thinking in trauma studies say about trauma and the human person? What does current thinking about trauma mean for the way we understand spirit and spirituality? What does this mean for the way spiritual care practitioners offer spiritual care to people living with trauma-related disorders? Taking seriously the advances in neuroscience that Van der Kolk applies to trauma studies, the paper proposes that spiritual care must understand spirit as a physiological reality and therefore welcome the whole human organism into the spiritual care space with kenotic humility. The conclusions of the paper are situated within the context of the theological conversation that follows the work of Friedrich Schleiermacher. It provides a critique of the recent definition of spirituality reported by Christina Puchalski, et al. [2014. “Improving the Spiritual Dimension of Whole Pers...

Summary Background Bronchiolitis is the most common reason for hospitalization in young children. In addition to respiratory syncytial virus (RSV), other viruses have been increasingly implicated. Guidance on testing has also changed. Aims To compare clinicopathological outcomes in young children admitted with bronchiolitis due to RSV in comparison with rhinovirus (RV), and identify associated risk/epidemiological factors. Methods Children aged less than two years admitted to hospital with a clinical diagnosis of bronchiolitis with positive results for either RSV or RV were included in this study. Polymerase-chain-reaction-negative cases using an extended respiratory virus panel served as a control group. Retrospective data were collected on sex, risk factors, respiratory support, intravenous fluids and antibiotics. Outcomes such as length of stay (LOS) and need for transfer to the high-dependency unit/paediatric intensive care unit were included. Findings Two hundred and twenty-seven out of 437 nasopharyngeal aspirate samples were positive for either RSV (N = 162) or RV (N = 65). The median age of cases was three months and 75% had at least one risk factor. Risk factors were higher in the RV group (P = 0.004). RV accounted for the majority of cases outside the RSV season (P

The capacity for induced pluripotent stem (iPS) cells to be differentiated into a wide range of neural cell types makes them an attractive donor source for autologous neural transplantation therapies aimed at brain repair. Translation to the in vivo setting has been difficult, however, with mixed results in a wide variety of preclinical models of brain injury and limited information on the basic in vivo properties of neural grafts generated from human iPS cells. Here we have generated a human iPS cell line constitutively expressing green fluorescent protein as a basis to identify and characterize grafts resulting from transplantation of neural progenitors into the adult rat brain. The results show that the grafts contain a mix of neural cell types, at various stages of differentiation, including neurons that establish extensive patterns of axonal growth and progressively develop functional properties over the course of 1 year after implantation. These findings form an important basis for the design and interpretation of preclinical studies using human stem cells for functional circuit re-construction in animal models of brain injury.

The development agenda over the next 15 years will be framed by the Sustainable Development Goals (SDGs), of which more than half relate either directly or indirectly to the agricultural sector, highlighting its importance in economic growth and development of low- and middle-income countries (LMICs) (FAO 2015). It is therefore imperative that agricultural systems are better understood, so that they may be strengthened and optimised to deliver outcomes in line with the SDGs. The interface between agriculture, nutrition and health is particularly multifaceted and complex, and the development of successful strategies will require an integrated and multi-sectoral approach (Dorward and Dangour 2012; Jones and Ejeta 2016).\ud \ud ‘Agri-health’ is an evolving paradigm seeking to unify research approaches and methodologies between agriculture and health. Research within the field encapsulates a broad range of disciplines, locations and actors, and aligns these into a common research agenda. In doing so, agri-health aims to transcend barriers imposed by the longstanding institutional and disciplinary silos. Much progress has been made in recent years in this regard (Harris et al. 2013; Kanter et al. 2014; Picchioni et al. 2015). However, more coordinated efforts are required to generate consensus and target strategic priorities amongst the many existing information gaps (Webb and Kennedy 2014). Understanding the linkages between complex issues such as globalisation, climate change, food systems, and evolving burdens of malnutrition is central to agri-health research.\ud \ud The Leverhulme Centre for Integrative Research on Agriculture and Health (LCIRAH) was created in 2010 with a key focus on agri-health interdisciplinary research. LCIRAH includes experts from across the member colleges of the University of London: the London School of Hygiene and Tropical Medicine (LSHTM), the School of Oriental and African Studies (SOAS), and the Royal Veterinary College (RVC).\ud \ud The Agriculture, Nutrition and Health Academy (ANH Academy), was established in 2015 as a platform to facilitate learning, knowledge sharing, capacity building and collaborative partnerships among the growing global community of researchers, practitioners and policy makers working within agri-health. It was developed with support from the Innovative Metrics and Methods for Agriculture and Nutrition Actions (IMMANA) research programme,Footnote1 led by LCIRAH and Tufts University, in partnership with the CGIAR Programme on Agriculture for Nutrition and Health (A4NH). Within this scope, the ANH Academy hosts an annual ANH Academy Week, building on the legacy of five agri-health research conferences organised by LCIRAH; as well as events and activities coordinated under the CGIAR A4NH.\ud \ud The inaugural ANH Academy Week took place in Addis Ababa, Ethiopia, in June 2016 and included two days of interactive ‘learning labs’ (training sessions on skills and methods across a broad range of disciplines in agri-health), followed by a three-day research conference. The conference included a mix of abstract-driven sessions, round table discussions, and keynote speeches from across the spectrum of agriculture, nutrition and health disciplines, and a wide range of countries.\ud \ud Hawkes et al. (2012) developed a conceptual framework (Fig. 2, hereafter referred to as the Framework), outlining the key pathways through which agriculture may affect nutritional status in Low and Middle Income Countries (LMICs), as well as broader drivers of these pathways. Drawing on this Framework, this paper aims to provide an analytical synthesis of the ANH Academy week by mapping the research and debates presented during the conference.

In recent years, a step change has been seen in the rate of adoption of Industry 4.0 technologies by manufacturers and industrial organizations alike. This article discusses the current state of the art in the adoption of Industry 4.0 technologies within the construction industry. Increasing complexity in onsite construction projects coupled with the need for higher productivity is leading to increased interest in the potential use of Industry 4.0 technologies. This article discusses the relevance of the following key Industry 4.0 technologies to construction: data analytics and artificial intelligence, robotics and automation, building information management, sensors and wearables, digital twin, and industrial connectivity. Industrial connectivity is a key aspect as it ensures that all Industry 4.0 technologies are interconnected allowing the full benefits to be realized. This article also presents a research agenda for the adoption of Industry 4.0 technologies within the construction sector, a three-phase use of intelligent assets from the point of manufacture up to after build, and a four-staged R&D process for the implementation of smart wearables in a digital enhanced construction site.

The changing nature of manufacturing, in recent years, is evident in industry’s willingness to adopt network connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision making systems. While e-maintenance practice provides a framework for internet connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of a comprehensive framework for its processing, analysis and use should be a valuable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data and the provision of comprehensive framework for its processing analysis and use, allowing future systems to enable ‘Human in the loop’ interactions.

The emergence of new technologies such as the Internet of Things, big data, and advanced robotics, together with risks such as climate change, rising labour costs, and a fluctuating economy, are challenging the current UK manufacturing model. In this paper, business models for re-distributed manufacture (RdM) are developed using anIDEF (Icam DEFinition for Function Modelling) description to serve as a guide for the implementation of the RdM concept in the consumer goods industry. This paper explores the viability of a re-distributed business model for manufacturers employing new manufacturing technologies such as additive manufacturing or three-dimensional (3D) printing, as part of a sustainable and circular production and consumption system. An As-Is value chain model is presented alongside the proposed new business model for a sustainable re-distributed manufacturing system. Both are illustrated via a case study drawn from the shoe manufacturing industry. The case study shows that there is a need for robust facilities in close proximity to the customer. These facilities are store fronts which can also manufacture, remanufacture, and provide services. The reduction in transportation and increase in customer involvement throughout the process are the main benefits that would accrue if a re-distributed model is implemented in the given industry.

Silica fouling during groundwater reverse osmosis (RO) treatment can have a significant impact on filtration performance. To better understand this phenomenon, the equilibrium kinetics of amorphous colloidal silica were studied at conditions relevant to RO of silica-rich alkaline groundwater. The impact of particle size was investigated using synthetic monodisperse silica nanoparticles. Bench scale experiments were conducted by monitoring dissolved silica concentration of aqueous suspensions of colloids of 100 and 300 nm diameter and pH 8.5 to 9.5. The equilibrium data was determined from existing established rate law equations. This study concluded that surface energy has a major impact on silica dissolution rate constant, particularly for colloidal silica. Observations of Ostwald ripening in bidisperse silica dispersions further confirmed these results, which indicate that dissolution and redeposition is responsible for the problematic silica fouling behaviour during RO treatment. 2D modelling based on inferred equilibrium data allows visualization of scale layer growth in agreement with cross-sectional scanning electron micrographs of autopsied membranes.

Enteroviral meningitis in infants and children commonly leads to hospital admission. Diagnosing viral meningitis can be difficult clinically. We examined the usefulness of enteroviral polymerase chain reaction (PCR) testing using cerebrospinal fluid (CSF) samples on clinical practice by comparing positive enteroviral CSF PCR cases (n = 39/136) to negative controls using both clinical outcomes and laboratory parameters. A positive result correlated with a reduced admission to high dependency unit, reduced the duration of antibiotics and a shorter length of stay (P .05). Adjusted CSF white cell count 5/μL correlated with positive PCR (P .05) but would have missed 32% of cases of enteroviral meningitis. Following these findings, an algorithm for the management of suspected viral meningitis has been introduced.

Non-invasive electrical stimulation methods are often used in experimental settings to investigate the possible modulation of antinociceptive mechanisms. Studies using transcranial direct current stimulation (tDCS) typically incorporate a fade-in, short-stimulation, fade-out sham (placebo) protocol, which is assumed to be indistinct from a 10-30min active protocol on the scalp. However, many studies report that participants can dissociate active stimulation from sham, even during low-intensity 1mA currents. In the present study we assessed whether delivery of a high-intensity 2mA current would exacerbate differences in the perception of active and sham protocols. Two protocols were delivered to 32 healthy, pain-free adults in a double-blinded, within-subjects design (active: 10min of 2mA, and sham: 20s of 2mA), with the anode over the left primary motor cortex and the cathode on the right forehead. Participants were asked “Is the stimulation on?” and “How sure are you?” at 30s intervals during and after stimulation. The differences between active and sham were more consistent and sustained during 2mA than during 1mA. We then quantified how well participants were able to track the presence and absence of stimulation (i.e. their sensitivity) during the experiment using cross-correlations. A good classifier of sensitivity during active tDCS was current strength, but exhibited only moderate specificity during sham. The accuracy of the end-of-study guess was no better than chance at predicting sensitivity. Our results from this methodological approach indicate that the traditional end-of-study guess poorly reflects the sensitivity of participants to stimulation, and may not be a valid method of assessing sham blinding. Further research should be carried out into inter-individual responses to sham-blinding and assessment methods in pain studies and the broader neurostimulation field. Wellcome Trust.

The minimization of energy, waste, and emissions in operations are the foremost sustainability goals in industry. The shift from a linear product lifecycle to a circular one is required, along with increased energy efficiency and reduced resource use, to achieve these goals. This paper examines how the use of Re-Distributed Manufacturing (RdM) and a Product-Service System (PSS) approach, while leveraging the latest digital manufacturing technologies, enables the shift to this new economic model. A case study illustrates this new approach and relates it to the shoe manufacturing industry. The ShoeLab case study includes an outline of the business model options supporting this new approach to sustainable production highlighting the circularity that may be achieved in employing RdM and the latest digital manufacturing technologies in the form of 3-D printing. The research conducted indicates that using IDEF0 modelling could help to realize the full potential of RdM such as the manufacturing and transport of products involving less material, energy and waste.

This article explores Theodor W. Adorno's “central concept” of the Bann, generally translated as “spell” and understood as a suggestive, if vague, metaphor. Through etymological analysis and investigation into Adorno's use of it in several key texts, especially Negative Dialectics, an essential polysemy is revealed as necessary to an understanding of this most elusive of Adornian expressions. Explication of this polysemy establishes its relevancy for a deeper comprehension of Adorno's philosophical magnum opus and the Bann as a nonidentical conceptual formulation of the problematic project of identifying thinking.

The accessibility of legal documents to the different actors of the judicial system needs to be ensured for the implementation of a strong international rule of law. The gap of such accessibility is being addressed by the Jus Mundi multilingual search-engine for International Law. The data updated on this platform is qualified by skilled lawyers. However, the interconnection of references within such documents, is a key feature for lawyers since, a major part of the legal research is analysing such citations to support their arguments. The process of interconnecting such references can prove to be expensive as well as time-consuming, if completed manually. Hence, the purpose of this research is to automatically extract such legal citations within international law, using Natural Language Processing (NLP), enabling the interconnectivity of documents on Jus Mundi. This study also discusses and addresses research gaps within this subject, especially in the domain specific to International Law. The method followed to achieve the automation is building an adaptable model through Regular-Expression based annotation language named JAPE (Java Annotation Patterns Engine). This set of automatically extracted links are then to be integrated with the search engine, having direct implication in the enablement of smoother navigation, making the law more accessible. This research also contributes to the state of the art bringing closer the eventual use of NLP in applications used to interact with International Law documents.

Low fruit and vegetable consumption is a key contributor to all forms of malnutrition. This qualitative study examined the perceptions of people living in peri-urban villages of Hyderabad, India, to characterise the sources of fruit and vegetables, the fruit and vegetable environment, and to inform future interventions to increase fruit and vegetable consumption. Health and food quality were primarily seen through a food safety lens and negative aspects were frequently attributed to increased pesticide use. Availability, price and affordability of fresh fruit and vegetables were important drivers of their acquisition and consumption. Promoting communal gardens may increase the availability of affordable fruit and vegetables, as would promoting cold storage facilities. Financial incentives would likely be effective in increasing consumption of fruit and vegetables.