University of Strathclyde

With the increasing demands for unmanned aerial vehicle (UAV) based autonomous inspections in the oil and gas industry, one of the challenging issues for 3D UAV positioning has emerged due to the satellite signal blocking. Considering the existing characteristics of the ultrasonic based technique, such as the low cost, extremely lightweight and high positioning accuracy, it can be promising as the potential solution. Nevertheless, the low position update rate and vulnerable positioning performance to the changing environment still limit its applications on UAV. Therefore, in this article, an ultrasonic and inertial measurement unit (IMU) based localisation algorithm and low cost UAV autonomous inspection system are presented. With the incorporation of the IMU, the position update rate, accuracy and stability of the algorithm can all be significantly improved. This is done by the adaptively estimated noise covariance matrices through the proposed adaptive extended Kalman filter (AEKF) algorithm and the added weighting factors. Followed by, an additional virtual observation process is presented to overcome the unavailability of the observation information for further performance improvement. Finally, extensive numerical results and field tests demonstrate that the proposed algorithm and system can achieve the high update rate, reliable, accurate and precision UAV positioning in oil and gas pressure vessels and are feasible for the UAV autonomous inspection in these environments.

Spin-Vertical Cavity Surface Emitting Lasers (spin-VCSELs) are undergoing increasing research effort for new paradigms in high-speed optical communications and photon-enabled computing. To date research in spin-VCSELs has mostly focused on Quantum-Well (QW) devices. However, novel Quantum-Dot (QD) spin-VCSELs, offer enhanced parameter controls permitting the effective, dynamical and ultrafast manipulation of their light emission’s polarization. In the present contribution we investigate theoretically in detail the operation of QD spin-VCSELs subject to polarization modulation for their use as ultrafast light sources in optical communication systems. We reveal that QD spin-VCSELs outperform their QW counterparts in terms of modulation efficiency, yielding a nearly two- fold improvement. We also analyse the impact of key device parameters in QD spin-VCSELs (e.g. photon decay rate and intra-dot relaxation rate) on the large signal modulation performance with regard to simulated optical modulation amplitude and eye-diagram opening penalty. We show that in addition to exhibiting enhanced polarization modulation performance for data rates up to 250 Gb/s , QD spin-VCSELs enable operation in dual (ground and excited state) emission thus allowing future exciting routes for multiplexing of information in computing and processing applications.

When a complex cyber-physical infrastructure is attacked, operators need to isolate the attack location. Since sensors and actuators are physically intertwined in such structures, operators must be able to separate incoming status data to isolate the precise location of the cyberattack. We let several unsupervised algorithms compete and analyze the extent to which they can provide fast and efficient analysis in order to support operators with this task, using data from the Secure Water Treatment testbed (SWaT), an experimental infrastructure in Singapore that allows us to simulate the behavior of large infrastructure systems. We find that the k-Shape algorithm performs best. This result suggests that unsupervised algorithms can support human operators efficiently even in critical infrastructures with complex sensor data time series.

The mechanical properties of the materials are determined by the size and morphology of fine microscopic features. Quantitative microstructural analysis is a key factor to establish the correlation between the mechanical properties and the thermomechanical treatment under which material condition has been achieved. As such, microstructural analysis is a very important and complex task within the manufacturing sector. Published standards are used for metallographic analysis but typically involve extensive manual interpretation of grain boundaries, resulting in measurements that are slow to produce, difficult to repeat and highly subjective. Computer vision and the evolution of artificial intelligence in the past decade can offer solutions to such problems. Deep learning and digital image processing techniques allow digital microstructural analysis to be automated using a fast and repeatable method. This paper proposes a novel boundary class semantic segmentation approach (BCSS) to identify each phase of the microstructure and additionally estimate the location of the grain boundaries. The BCSS is then combined with more traditional segmentation techniques based on the Watershed Transform to improve the identification and measurement of each feature within the microstructure using a new, hybrid automated digital microstructure analysis approach. The new method is validated on a published dataset of two-phase titanium alloy microstructure pictures captured using a scanning electron microscope. Measurements match the level of accuracy of accepted manual standards, and the method is demonstrated to be more reliable than other automated approaches. The influence of the subjective nature of manual labelling, required to train the proposed network, is also evaluated.

In this paper, a new point process is introduced. It combines the nonhomogeneous Poisson process with the generalized Polya process (GPP) studied in recent literature. In reliability interpretation, each event (failure) from this process is minimally repaired with a given probability and GPP-repaired with the complementary probability. Characterization of the new process via the corresponding bivariate point process is presented. The mean numbers of events for marginal processes are obtained via the corresponding rates, which are used for considering an optimal replacement problem as an application.

This creative-critical article explores intersections of video game environments and lyric modes as the basis for theorising a poetics of ‘lyric solarity’ in exemplary works by contemporary poets. Lyric solarity is a poetics in which solar imaginaries are linguistically mediated and refracted through the close rhythms, affects, sensoria and arts of noticing found within everyday life. Drawing from Dominic Boyer, Imre Szemam and Rhys Williams’ recent work on solarity from the field of petrocultures and the energy humanities, I consider the oil spill aesthetics and solar accumulation of Nintendo’s 2002 platform game, Super Mario Sunshine, as the basis for reading tensions of solar totality, infrastructure, singularity and agency in works by Dom Hale, Sean Bonney, Verity Spott, Anne Lesley Selcer and Ed Luker. This article is a speculative exegesis on the critical, ethical and ecological affordances of lyric solarity, which I examine in dialogue with what Reza Negarestani calls ‘the blobjective earth […] nurtured by petropolitics’. While the blobjective offers a limited and often apocalyptic vision of resource conflict, I take up Dominic Boyer and Timothy Morton’s notion of ‘hyposubjectivity’ to show how lyric solarity might offer an expanded and radical horizon for ecological thought. I argue that the infrastructures and relational architectures of lyric solarity, as a continuum of affects, aesthetics and political possibilities, may think beyond the thought-regimes of petro-modernity and towards alternative kinds of postcapitalist and queer desire, play, temporal orientation and abundance.

A numerical simulation method based on CFD has been established to simulate the fully coupled motion for an attenuator-type wave energy converter (WEC). Based on this method, a detailed parametric analysis has been conducted to investigate the design of the rafts. The effects of different parameters (wave parameters, structural parameters and PTO parameters) on the hydrodynamic characteristics of the attenuator-type WEC were studied in detail. The results show that in terms of wave parameters, there is an optimal wave period, which makes the relative pitching angle amplitude of the WEC reach the maximum, and the increase of wave height is conducive to the relative pitching angle amplitude of wave energy. Under different wave conditions, the relative pitch angle of the parallelogram raft device is the maximum. In terms of structural parameters, the parallelogram attenuator-type device has the optimal values in different relative directions, different distances and different apex angle, which makes the relative motion amplitude of the device reach the maximum, and the spacing and the apex angle have influence on the motion frequency of the device, while the relative direction has almost no influence on it. In terms of PTO parameters, there is an optimal damping coefficient, which makes the power generation efficiency of the WEC reach the maximum. The research results provide a valuable reference for future research and design of the attenuator-type WEC.

Ultrasound tongue imaging is becoming popular as a tool for both phonetic research and biofeedback for treating speech sound disorders. Despite this, it has not yet been adopted into cleft palate ± cleft lip care. This paper explores why this might be the case by highlighting recent research in this area and exploring the advantages and disadvantages of using ultrasound in cleft palate ± cleft lip care. Research suggests that technological advances have largely overcome some of the difficulties of employing ultrasound with this population and we predict a future increase in the clinical application of the tool.

While discourse about the Sustainable Development Goals (SDGs) has primarily focused on ‘whether the goals’ are achieved, there remains limited understanding of how developed countries organize their monitoring and evaluation (M&E) systems, which play a crucial role in tracking progress towards the SDGs. In this contribution, we unpack the M&E frameworks of Belgium, the Netherlands and the United Kingdom. To do so, we have devised an analytical heuristic that combines insights from the literature on policy performance measurement and measurement infrastructures with the more specific literature on SDG governance. Through document analysis and elite interviews conducted in 2021, our findings highlight similarity in underdeveloped M&E frameworks, rather than significant variation across the three case studies. The results do not suggest a linkage between SDG performance and the development of M&E frameworks.

This editorial highlights concerns with current Drug Laws in Pakistan, specifically regarding the purchasing of antibiotics without prescriptions, and its implications for antimicrobial resistance (AMR). The primary focus was on addressing the concerns related to the list of antimicrobial drugs outlined in Schedule D of the Punjab Drug Sale Rules. The authors emphasize the necessity of updating this list not only in Punjab but also in other provinces. The authors also advocate for implementing restrictions on the sale of these antibiotics without prescriptions, particularly for reserve group antibiotics. They stress the importance of improving appropriate dispensing practices, educating healthcare professionals, and aligning with the WHO's AWaRe guidance to combat rising AMR rates in Pakistan and similar settings. This comprehensive approach is essential to address the complex challenges posed by AMR effectively.

Traditional radar sensors used for surveillance rely on monostatic radar principles. However, recently the use of remote radio frequency telescopes as bistatic receivers represents an interesting way to reuse existing facilities while providing additional information to improve tracking accuracy. In this paper we study the benefits of using such a system for the task of manoeuvre detection in satellites in LEO and MEO. We investigate the conditions in which a multistatic radar is advantageous for this purpose, and show concrete results based on simulated data. Moreover, we propose novel manoeuvre detection methods, and compare their accuracy to methods found in the literature. A more general way of assessing the accuracy of these manoeuvre detection methods is also proposed, with the aim of taking into account that the parameters of the manoeuvre that actually takes place also have an effect on the accuracy. These can be split into optimal control based methods, and statistical methods. We found the addition of multistatic radar to allow considerable improvement in the accuracy of the manoeuvre detection process, an improvement that is shown to be greater the greater the baseline, i.e., the distance of the receiver to the transmitter. Furthermore, the manoeuvre detection methods that accurately model the uncertainty in the measurements were found to be the most accurate.

Transportation is one of the main contributors to greenhouse gas emissions. Climate regulations on transportation are often a mix of sector-specific regulations and economy-wide measures (such as emission pricing). In this paper we consider how different and partly overlapping climate regulations interact and what are the effects on economic welfare, abatement costs and emissions? Our focus is on Norway, a nation where high taxation of conventional fossil-fuelled cars has paved the floor for another pillar of climate policies: promotion of electric vehicles (EVs) in private transport. Our contribution to the literature is two-fold. First, we analyse the costs and impacts of the partly overlapping climate regulations in transportation—the cap on domestic non-ETS emissions and the goal of all new cars for private households being EVs—focussing on the outcome in 2030. Second, we respond to a gap in the literature through a methodological development in economy-wide computable general equilibrium (CGE) approaches for climate policy by introducing EV technologies as an explicit transport equipment choice for private households. We find that, for the case of Norway, combining a specific EV target with policy to cap emissions through a uniform carbon price more than doubles the welfare costs.

Purpose This survey study aimed to establish current clinical practices of German-speaking speech-language pathologists (SLPs) regarding their assessment and treatment of communication disorders in children with neurological conditions, with a particular focus on the management of childhood dysarthria. Method A 23-question cross-sectional online survey was disseminated to practicing SLPs in Germany, Austria, and Switzerland via relevant professional bodies. SLPs were invited to provide information on their current assessment and treatment practices. Demographic data including case load and clinical settings were also gathered to contextualize practices. Results One hundred two SLPs responded to the survey, of which 68 valid responses were analyzed. German-speaking SLPs comprehensively assess and treat various aspects of overall communication, language, and swallowing functions in children with neurological conditions. Speech motor aspects did not represent a main intervention focus. In cases where the dysarthric component was targeted, specific approaches for childhood dysarthria were rarely used. Instead, SLPs reported using approaches developed for speech disorders other than dysarthria. Conclusions German-speaking SLPs working with children with neurological conditions use various assessment and treatment methods to support children's communication. However, dysarthria-specific approaches were not an established part of clinical practice. Results of the survey highlight the need for access to relevant developments in German and for evaluation of current curricula for speech-language pathology students and continuing education opportunities for practicing clinicians.

Minimally repaired items are considered. In practice, minimal repair can be unsuccessful, and in this case, it should be repeated. The Polya‐Aeppli process, which is a generalization of the Poisson process is used in the article for the corresponding modeling. Some properties, useful for optimal maintenance, are derived. An important generalization to the case when the probability of the unsuccessful attempt is time‐dependent is described. An application of the derived results to obtaining the optimal time of replacement for a system with multiattempt minimal repairs is discussed. The study is illustrated by detailed numerical examples.

Adipocyte dysfunction is a crucial driver of insulin resistance and type 2 diabetes. We identified EH domain-containing protein 2 (EHD2) as one of the most highly upregulated genes at the early stage of adipose tissue expansion. EHD2 is a dynamin-related ATPase influencing several cellular processes, including membrane recycling, caveolae dynamics and lipid metabolism. Here, we investigated the role of EHD2 in adipocyte insulin signalling and glucose transport. Using C57BL6/N EHD2 knockout mice under short-term high-fat diet conditions and 3T3-L1 adipocytes we demonstrate that EHD2 deficiency is associated with deterioration of insulin signal transduction and impaired insulin-stimulated GLUT4 translocation. Furthermore, we show that lack of EHD2 is linked with altered plasma membrane lipid and protein composition, reduced insulin receptor expression, and diminished insulin-dependent SNARE protein complex formation. In conclusion, these data highlight the importance of EHD2 for the integrity of the plasma membrane milieu, insulin receptor stability, and downstream insulin receptor signalling events, involved in glucose uptake and ultimately underscore its role in insulin resistance and obesity.

Disrespectful behaviour in the healthcare environment affects clinical learning, impacts those receiving such behaviour and adversely affects patient outcomes. Mandated ‘diversity training’ has minimal impact and, if poorly done, can worsen toxic work environments. Our study aimed to develop a simulation-based active bystander training (ABT) session for medical students and to evaluate the impact of this training. Method Sessions comprised short recap of students’ learning to date; prerecorded video vignettes; a card game and immersive simulation. Advocacy with inquiry debrief, facilitated by faculty with equality, diversity and inclusivity expertise followed each scenario. Students completed a validated questionnaire developed for this study, preintervention and postintervention. Results Sixty-six medical students from three teaching hospitals attended seven 3-hour sessions. The average number of students attending each session was 9 (range 7–12). The questionnaire was completed with matched pairs of preintervention and postintervention scores on a Likert scale by 58 (88%) students. There were significant deficits (p<0.001) in students’ self-rated knowledge with a mean preintervention score of 38.2 (SD 5.9) out of a maximum score of 55. This compared with postintervention score of 49.1 (SD 4.8). The mean increase in total score postintervention was 11.0 (95% C.I 9.4 to 12.5; p<0.001). Conclusion We found significant deficits in medical students’ self-rated knowledge of recognising disrespectful behaviour at work. Simulation in ABT was effective in reversing this. This is a timely study given the new responsibilities placed on doctors by the General Medical Council to act when witnessing discriminatory behaviour or harassment at work.