Okehampton Hospital

We present a genome assembly from a female specimen of Leptarthrus brevirostris (Slender-footed Robberfly; Arthropoda; Insecta; Diptera; Asilidae). The assembly contains two haplotypes with total lengths of 850.81 megabases and 851.46 megabases. Most of haplotype 1 (99.05%) is scaffolded into 6 chromosomal pseudomolecules. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 18.16 kilobases.

PurposeThe purpose of this study is to provide an insight into the role of predictive maintenance in industrial robots.Design/methodology/approachFollowing a short introduction, this first discusses the three main maintenance strategies used on industrial equipment. It then discusses the techniques presently used to maintain industrial robots. This is followed by examples of recent research and finally, conclusions are drawn.FindingsPredictive or condition-based maintenance involves conducting maintenance only when the failure of equipment or components is imminent. Benefits over reactive/run-to-failure and preventive/scheduled maintenance include a reduction of in-service failures and unscheduled downtime, pre-planning of maintenance and the replacement of only faulty components. Industrial robots are generally highly reliable, being mostly maintained by preventive/scheduled schemes as stipulated by the manufacturers. Faults and failures can occur and many robot manufacturers have developed software-based systems that augment scheduled maintenance and exploit IoT and cloud computing technology. These include modules that alert users about abnormalities and potential problems, allowing the implementation of preventive maintenance. More advanced technologies are under study by the academic community and have the potential to yield additional diagnostic functions, thereby facilitating enhanced preventive maintenance practices.Originality/valueThis provides details of the maintenance strategies used on industrial robots and the role played by, and developments in, predictive technologies.

PurposeThe purpose of this paper is to provide details of recent developments in agricultural robots with an emphasis of those that address labour shortages and environmental issues.Design/methodology/approachFollowing an introduction which highlights some of the challenges facing the agricultural industry, this discusses recent robotic agricultural vehicle developments and the enabling technologies. It then provides examples of terrestrial and airborne robots employed in precision agricultural practices. Finally, brief conclusions are drawn.FindingsTraditional, labour-intensive and environmentally harmful agricultural practices are not sustainable in the long term, and if food supply is to meet future demand, radical changes will be required. Exploiting recent advances in artificial intelligence (AI), agricultural equipment manufacturers are developing robotic vehicles in response to labour shortages. Precision agricultural practices will mitigate many of the detrimental environmental impacts and can also reduce the reliance on manpower. Weeding robots which reduce or eliminate the use of herbicides have been commercialised by a growing number of companies and again exploit AI techniques. Drones equipped with imaging device are playing an increasingly important role by characterising agricultural and crop conditions, thereby allowing highly targeted agrochemical application.Originality/valueThis illustrates how the agricultural industry is adopting robotic technology in response to the need to increased productivity while mitigating the problems of shortages of labour and environmental degradation.

My background is in nursing, midwifery, and acupuncture. In November of 2021, I came across a blog post about volunteering as an acupuncturist in a rehabilitation clinic for migrant refugees and asylum seekers on the island of Lesvos. With experience in the National Acupuncture Detoxification Association (NADA) protocol and trauma training provided by Acupuncturists Without Borders, I decided to apply to the nongovernmental organization Earth Medicine rehabilitation clinic. I stayed for 2 weeks in January 2022, and went again in September 2022 for 2 weeks, but that time, I was based inside the camp. On returning home from my first trip, and while giving a talk about Lesvos to our regional group, a fellow acupuncturist suggested that we could do something closer to home. Thus, we set up a project in our city, Exeter, in the United Kingdom. Thanks to a willing team of volunteers, asylum seekers and refugees are offered free acupuncture treatments weekly on Saturday mornings. This takes place in a community center in a group setting, using the NADA ear protocol, as well as other acupuncture points and occasional full-body treatments when the circumstances allow this. Although the work on Lesvos was hard, it was also very rewarding. Working there has had a profound effect on me and I plan to go back. At our local project, we receive very positive feedback from the people who come to us. Using acupuncture to address post-traumatic stress disorder is very worthwhile, and I encourage others to consider doing the same.

PurposeThis empirical research examined the factors and conditions that contribute to the success of international strategic learning alliances. The study aimed to provide organisations with evidence-based insights and recommendations that can help them to create more effective and sustainable partnerships and to leverage collaborative learning to drive innovation and growth. The examination is performed using game theory as a mathematical framework to analyse the interaction of the decision-makers, where one alliance's decision is contingent on the decision made by others in the partnership. There are 20 possible games out of 120 outcomes that can be grouped into four different types; each type has been divided into several categories.Design/methodology/approachThe research methodology included secondary and primary data collection using empirical data, the Delphi technique for obtaining qualitative data, a research questionnaire for collecting quantitative data and computer simulation (1,000 cases, network resources and cooperative game theory). The key variables collected and measured when analysing a strategic alliance were identified, grouped and mapped into the developed model.FindingsMost respondents ranked reputation and mutual benefits in Type 1 games relatively high, averaging 4.1 and 3.85 of a possible 5. That is significantly higher than net transfer benefits, ranked at 0.61. The a priori model demonstrate that Type 1 games are the most used in cooperative games and in-game distribution, 40% of all four types of games. This is also confirmed by the random landscape model, approximately 50%. The results of the empirical data in a combination of payoff characteristics for Type 1 games show that joint and reputation benefits are critical for the success of cooperation.Practical implicationsResearch on cross-border learning alliances has several implications. Managerial implications can help managers to understand the challenges and benefits of engaging in these activities. They can use this knowledge to develop strategies to improve the effectiveness of their cross-border learning alliances. Practical implications, the development of game theory and cross-border models can be applied in effective decision-making in a variety of complex contexts. Learning alliances have important policy implications, particularly in trade, investment and innovation. Policymakers must consider the potential benefits and risks of these collaborations and develop policies that encourage and support them while mitigating potential negative impacts.Originality/valueInternational learning alliances have become a popular strategy for firms seeking to gain access to new knowledge, capabilities and markets in foreign countries. The originality of this research lies in its ability to contribute to the understanding of the dynamics and outcomes of these complex relationships in a novel and meaningful way.

PurposeThis paper aims to illustrate the growing role of drones in applications involving physical tasks.Design/methodology/approachFollowing a short introduction, this first provides a brief introduction to drone technology. It then describes and discusses products and applications involving physical tasks in agricultural and forestry, maritime rescue, firefighting and product delivery. Finally, brief conclusions are drawn.FindingsExcluding military applications, drones were initially used primarily for image acquisition. Numerous different designs have since been developed with greatly varying wing configurations, payloads, flight duration, power sources and other features which are increasingly being used to conduct physical tasks. In the applications considered here drones are applying agrochemicals and dispersing crop and tree seeds; saving lives by deploying lifeboats and buoyancy aids; extinguishing fires in high-rise buildings and forests; and delivering groceries, food, mail, medicines and humanitarian aid, often in and to remote locations.Originality/valueThis study provides a detailed insight into selection of applications in which drones conduct physical tasks.

PurposeThis paper aims to illustrate the growing role of machine learning techniques in robotics.Design/methodology/approachFollowing an introduction which includes a brief historical perspective, this paper provides a short introduction to machine learning techniques. It then provides examples of robotic machine learning applications in agriculture, waste management, warehouse automation and exoskeletons. This is followed by a short consideration of applications in future generations of self-driving vehicles. Finally, brief conclusions are drawn.FindingsMachine learning is a branch of artificial intelligence and the topic of extensive academic study. Recent years have seen machine learning techniques being applied successfully to a diversity of robotic systems, most of which involve machine vision. They have imparted these with a range of unique or greatly improved operational capabilities, allowing them to satisfy all manner of new applications.Originality/valueThis provides a detailed insight into how machine learning is being applied to robotics.

PurposeThis paper aims to trace the technological and commercial developments in robotics over the last 50 years, from 1973, the year in which this journal was founded, to the present day.Design/methodology/approachFollowing an introduction, this identifies key robot developments on a decade-by-decade basis and considers research, products, applications and corporate activity and also highlights many of the enabling technologies. Brief conclusions are draw.FindingsThe robot industry has changed beyond all recognition during the last half century. Enabled by developments in microelectronics, computing, sensors, imaging technologies, data communication and power sources, today robots satisfy a multitude of applications and play a role in almost every sphere of human activity.Originality/valueThis provides a detailed review of robotic developments during the last 50 years.

Abstract We document the implementation of the Common Representative Intermediates Mechanism version 2, reduction 5 into the United Kingdom Chemistry and Aerosol model (UKCA) version 10.9. The mechanism is merged with the stratospheric chemistry already used by the StratTrop mechanism, as used in UKCA and the UK Earth System Model, to create a new CRI‐Strat mechanism. CRI‐Strat simulates a more comprehensive treatment of non‐methane volatile organic compounds (NMVOCs) and provides traceability with the Master Chemical Mechanism. In total, CRI‐Strat simulates the chemistry of 233 species competing in 613 reactions (compared to 87 species and 305 reactions in the existing StratTrop mechanism). However, while more than twice as complex than StratTrop, the new mechanism is only 75% more computationally expensive. CRI‐Strat is evaluated against an array of in situ and remote sensing observations and simulations using the StratTrop mechanism in the UKCA model. It is found to increase production of ozone near the surface, leading to higher ozone concentrations compared to surface observations. However, ozone loss is also greater in CRI‐Strat, leading to less ozone away from emission sources and a similar tropospheric ozone burden compared to StratTrop. CRI‐Strat also produces more carbon monoxide than StratTrop, particularly downwind of biogenic VOC emission sources, but has lower burdens of nitrogen oxides as more is converted into reservoir species. The changes to tropospheric ozone and nitrogen budgets are sensitive to the treatment of NMVOC emissions, highlighting the need to reduce uncertainty in these emissions to improve representation of tropospheric chemical composition.

Purpose This paper aims to provide an insight into the future for disaster relief (DR) and search and rescue (SAR) robots by considering research activities which seek to address real-world applications and by identifying key user requirements and development priorities. Design/methodology/approach Following a short introduction, this first provides a brief overview of the use of robots in DR and SAR and gives examples of organisations promoting their use. This is followed by details of development programmes aimed at meeting users’ requirements. Specific needs are identified and considered in detail and were derived from both the literature and through discussions with users. This paper concludes with a tabulated summary of key development priorities. Findings This study shows that several collaborative research programmes aim to address real DR and SAR applications, with robots being tested in simulated disaster scenarios. A number of key user requirements and development priorities are identified for aerial, ground and marine robots. Originality/value By identifying a number of specific requirements, this paper will assist in focussing research and development activities towards real users’ needs.