922017 research outputs found
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Quantifying the Impacts of Modelling Assumptions on Accuracy and Computational Efficiency for Integrated Water-Energy System Simulations Under Uncertain Climate
No full textJointly managing water and energy systems, rather than treating each system independently, is recognised as an approach that can lead to a more cost-effective and reliable supply, which is particularly critical in water-rich and developing countries. This has motivated the development of various integrated water-energy simulators, each one catering for specific modelling needs through the use of specific sets of modelling assumptions, e.g., representing water and energy with balance equations, or dedicated river flow and power network equations. In this context, it becomes critical to assess the effectiveness of different modelling assumptions to improve the design of water-energy simulators. In particular, it is important to develop a methodology that can identify, based on a systematic assessment process, the portfolios of modelling assumptions that better capture the uncertain future conditions in the water and energy sectors, e.g., climate-driven stresses and shocks such as water scarcity, temperature rise, etc. To address this challenge, this paper proposes a Mixed Integer Linear Programming (MILP) integrated water-energy system simulation methodology designed to adapt and quantify different modelling assumptions under various weather-related conditions (e.g., water scarcity and high temperatures). The models were developed to capture the characteristics of non-pressurised water systems (e.g., channels and rivers) and electricity systems. The methodology is used to investigate typical modelling assumptions (e.g., temporal resolutions and water and power system models) and novel approaches to model the impacts of high temperatures on generation capacity to capture the effects of extreme weather on power generation. The methodology is demonstrated on the Ghanaian integrated water-energy system. The results highlight the benefits in terms of computational costs and modelling accuracy, of the customisable simulation, and provide guidance to select adequate modelling assumptions
Energy consumption and performance optimisation of laser cleaning for coating removal
No full textSelective removal of coatings by lasers can facilitate the reuse of coated tools in a circular economy. In order to optimise and control the process, it is essential to study the impact of process input variables on process performance. In this paper, coating removal from tooling was carried out using a picosecond a pulsed fibre laser, in order to investigate the effects of laser pulse energy, pulse frequency, galvo scanning speed and scanning track stepover. A fractional factorial design of experiments and analysis of variance was used to optimise the process; considering cleaning rate, specific energy consumption and surface integrity as assessed by changes in surface roughness and composition of the tooling after laser cleaning. The results shows synergy between cleaning rate and specific energy with the laser pulse frequency and galvo scanning speed as the two most significant factors, while the laser pulse energy had the greatest contribution to changes in surface composition. Based on extensive experiments, the relationship between processing rate and system specific energy consumption was mathematically modelled. The paper contributes a new specific energy model for laser cleaning and provides a benchmark of the process energy requirements compared to other manufacturing processes. Additionally, the generic scientific learning from this is that the rate of energy input is a key tool for maximising cleaning rate and minimising specific energy requirements, while the intensity of energy applied, is a key metric that influences surface integrity. More complex factors, influence the surface integrity.</p
Clinical challenges associated with utility of neoadjuvant treatment in patients with pancreatic ductal adenocarcinoma
No full textPancreatic ductal adenocarcinoma (PDAC) is an increasingly common cancer with a persistently poor prognosis, and only approximately 20% of patients are clearly anatomically resectable at diagnosis. Historically, a paucity of effective therapy made it inappropriate to forego the traditional gold standard of upfront surgery in favour of neoadjuvant treatment; however, modern combination chemotherapy regimens have made neoadjuvant therapy increasingly viable. As its use has expanded, the rationale for neoadjuvant therapy has evolved from one of `downstaging` to one of early treatment of micro-metastases and selection of patients with favourable tumour biology for resection. Defining resectability in PDAC is problematic; multiple differing definitions exist. Multidisciplinary input, both in initial assessment of resectability and in supervision of multimodality therapy, is therefore advised. European and North American guidelines recommend the use of neoadjuvant chemotherapy in borderline resectable (BR)-PDAC. Similar regimens may be applied in locally advanced (LA)-PDAC with the aim of improving potential access to curative-intent resection, but appropriate patient selection is key due to significant rates of recurrence after excision of LA disease. Upfront surgery and adjuvant chemotherapy remain standard-of-care in clearly resectable PDAC, but multiple trials evaluating the use of neoadjuvant therapy in this and other localised settings are ongoing
Experimental investigation on the fatigue crack growth behaviour of Q420C
No full textThe lack of test data on the fatigue crack growth behaviour of Q420C steel affects its application in the field of wind power engineering. To fill this gap, this paper carried out an experimental study and theoretical analysis of the fatigue crack propagation behaviour of Q420C steel under constant amplitude. Six compact tension specimens were separately tested under six loading conditions comprising two maximum loads (𝐹𝑚𝑎𝑥=8 𝑘𝑁 𝑜𝑟 10 𝑘𝑁) and three load ratios (𝑅=0.1,0.3,𝑜𝑟 0.5). The Back-Face Strain method was used to calculate the crack length, and a complete cycle of strain values was recorded for every 1 mm of crack extension. The crack growth rate and crack opening load were calculated according to the ASTM E647-15. The test results show that for the two crack growth rate calculation methods given by the ASTM E647-15, the secant method provides large discrete results, while the incremental polynomial method can obtain a relatively smooth rate curve. In addition, for the incremental polynomial method, the normalisation of the number of cycles in the ASTM E647-15 should not be used to achieve acceptable results. The rate curves of Q420C steel show a clear load ratio effect, for the same stress intensity factor range Δ𝐾, the higher the load ratio, the faster the crack grows. Quantitative analysis of the effect of load ratios has shown that two-parameter models based on 'unified theory', such as Walker’s model, can accurately describe the effect of load ratios. However, the theory of plasticity-induced crack closure cannot account for the effect of load ratios, as the crack opening load 𝐹𝑜𝑝 is less than the minimum load 𝐹𝑚𝑖𝑛 for load ratios greater than 0.1. Finally, a comparison is carried out against the predictions by BS7910; results verify the applicability of BS7910 to Q420C steel material and demonstrate the different degrees of conservatism of all recommended design curves in BS7910
Risk Assessment of Cascading Failures in Power Systems with Increasing Wind Penetration
No full textThe ever-growing penetration of renewable based gen-eration is leading to significant increases in the risk of cascading failures in low-inertia, and interconnection-rich, power systems. This paper proposes a framework for quantifying the risk of cas-cading failures in renewable-rich power systems with fast fre-quency response (FFR) services. This is achieved by developing a novel time-based dynamic model of cascading failures to capture the transient behaviours of the system response and quantify the risk of blackout. This dynamic cascading failure model is comple-mented by unit commitment for representative dispatch and in-cludes the provision of FFR. The proposed framework is illus-trated using a modified version of the Illinois 200-bus synthetic system. As key outputs, the results emphasize the importance of accurate modelling of ancillary services associated with fre-quency regulation in cascading failure analysis, and indicate that increased wind penetration can lead to a higher probability of power outages. Adopting FFR services can help to mitigate the cascading risk but may introduce rotor angle instability issues
Prognostic impact of late gadolinium enhancement at the right ventricular insertion points in non-ischemic dilated cardiomyopathy.
No full textAimsTo evaluate the baseline characteristics and the prognostic implications associated with late gadolinium enhancement limited to the right ventricular insertion points (IP-LGE) or present at both the right ventricular insertion points and the left ventricle (IP&LV-LGE) in non-ischemic dilated cardiomyopathy (DCM). Methods and results Retrospective observational multicenter cohort study including 1165 consecutive patients with DCM evaluated by cardiac magnetic resonance. The primary endpoint included appropriate defibrillator therapies, sustained ventricular tachycardia, resuscitated cardiac arrest or sudden death. The secondary outcome encompassed heart failure hospitalizations, heart transplant, left ventricular assist device implantation and end-stage heart failure death. IP-LGE was found in 72 patients (6%), who had clinical characteristics closer to LGE- than to LGE+ patients. During follow-up (median 36 months), none of the IP-LGE patients experienced the primary endpoint. The cumulative incidence of the primary endpoint was similar between IP-LGE and LGE- patients (p=1) while IP-LGE had significantly lower cumulative incidence as compared to LGE+ patients (p<0.001). As compared to IP-LGE patients, the cumulative incidence of the secondary endpoint was similar in LGE- cases (p=0.86) but tended to be higher in LGE+ patients (p=0.06). Both clinical characteristics and outcomes were similar between IP&LV-LGE patients and the rest of LGE+ cases. ConclusionsIn a large cohort of DCM patients, IP-LGE was associated with similar outcome as compared to LGE- patients and with significant lower risk of ventricular arrhythmias and sudden death as compared to LGE+ cases. Patients with IP&LV-LGE had clinical characteristics and outcomes similar to the rest of LGE+ cases
The influence of social support, financial status and lifestyle on the disparity between inflammation and disability in rheumatoid arthritis
No full textObjectives: To investigate how social support, financial status and lifestyle influence the development of excess disability in rheumatoid arthritis (RA).Methods: Data came from the Étude et Suivi des Polyarthrites Indifférenciées Récentes (ESPOIR) cohort study of people with RA. A previous analysis identified groups with similar inflammation trajectories but markedly different disability over 10 years; those in the higher disability trajectory groups were defined as having “excess disability”. Participants self-reported data on contextual factors (social support, financial situation, lifestyle) and completed patient reported outcome measures (PROMs; pain, fatigue, anxiety, depression) at baseline. The direct effect of the contextual factors on excess disability and the effect mediated by PROMs was assessed using structural equation models. Findings were validated within two independent datasets (Norfolk Arthritis Register [NOAR], Early Rheumatoid Arthritis Network [ERAN]).Results: Of 538 included ESPOIR participants (mean age [standard deviation (SD)]: 48.3 [12.2] years, 79.2% women), 200 (37.2%) were in the excess disability group. Less social support (β 0.17 [95% CI 0.08, 0.26]), worse financial situation (β 0.24 [95% CI 0.14, 0.34]), less exercise (β 0.17 [95% CI 0.09, 0.25]) and less education (β 0.15 [95% CI 0.06, 0.23]) were associated with excess disability group membership; smoking, alcohol consumption and body mass index were not. Fatigue and depression mediated a small proportion of these effects. Similar results were seen in NOAR and ERAN. Conclusions: Greater emphasis is needed on the economic and social context of people with RA at presentation; these factors might influence disability over the following decade. <br/
Physical activity, sedentary time and breast cancer risk: A Mendelian randomization study
No full textObjectives: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomization (MR) assesses causality by simulating randomized trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.Methods: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130,957 European-ancestry women (69,838 invasive cases), and published UK Biobank data (n=91,105-377,234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.Results: Greater genetically-predicted overall activity was associated with lower breast cancer risk, overall (OR=0.59; 95%CI 0.42-0.83 per-standard deviation [SD; ~8 milligravities acceleration]) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95%CI 0.45-0.87, ≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95%CI 1.07-2.92 per-SD [~7% time spent sedentary]), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger). Conclusion: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.<br/
Implications of the changes to patient online records access in English primary care
No full textNHS England have announced that patients in England registered for online services such as the NHS App will soon be able to see all new entries in their primary care record by default. This includes free text, hospital letters, test results, and new data added to the detailed coded record. Despite documented benefits of online records access for patients, primary care staff have raised concerns which can be grouped into issues around: 1) workload, 2) safeguarding, 3) patient confusion or distress, and 4) health inequities. This editorial examines each of these in turn, and considers what the future might hold for patient online records access.<br/
Comparison of biomedical relationship extraction methods and models for knowledge graph creation
No full textBiomedical research is growing at such an exponential pace that scientists, researchers, and practitioners are no more able to cope with the amount of published literature in the domain. The knowledge presented in the literature needs to be systematized in such a way that claims and hypotheses can be easily found, accessed, and validated. Knowledge graphs can provide such a framework for semantic knowledge representation from literature. However, in order to build a knowledge graph, it is necessary to extract knowledge as relationships between biomedical entities and normalize both entities and relationship types. In this paper, we present and compare a few rule-based and machine learning-based (Naive Bayes, Random Forests as examples of traditional machine learning methods and DistilBERT, PubMedBERT, T5, and SciFive-based models as examples of modern deep learning transformers) methods for scalable relationship extraction from biomedical literature, and for the integration into the knowledge graphs. We examine how resilient are these various methods to unbalanced and fairly small datasets. Our experiments show that transformer-based models handle well both small (due to pre-training on a large dataset) and unbalanced datasets. The best performing model was the PubMedBERT-based model fine-tuned on balanced data, with a reported F1-score of 0.92. The distilBERT-based model followed with an F1-score of 0.89, performing faster and with lower resource requirements. BERT-based models performed better than T5-based generative models