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Background: Predicting fire behaviour is an ongoing challenge in temperate peatlands and heathlands, where live fuels can form the dominant fuel load for wildfire spread, and where spatial heterogeneity in fuel moisture is important but not typically represented in fuel models. Aims: We examine the impact of fuel moisture variation on simulated fire behaviour across a temperate peatland/heathland landscape. Methods: We collected field measurements of fuel moisture content in Calluna vulgaris shrub from 36 sites across the North Yorkshire Moors, United Kingdom. We used these to define fuel moisture inputs within existing shrubland fuel models to simulate fire behaviour in BehavePlus. Key results: Simulated rates of spread varied with fuel moisture content; average mean variance of 23–80% from the landscape average rate of spread. The driest sites had simulated rates of spread up to 135% above the landscape average and the wettest sites up to 86% below average. Fuel model selection dramatically impacted simulated rates of spread by a factor of five. Conclusions: We need to constrain the role of live fuel moisture within temperate fuel models to develop accurate fire behaviour predictions. Implications: Capturing cross-landscape heterogeneity in fire behaviour is important for safe and effective land and wildfire management decision-making. Predicted fire behaviour varies significantly when cross-landscape fuel moisture differences are included in simulations. In temperate fuels, where live fuel moisture is not well represented in models, this may create dangerous situations where fire behaviour is underpredicted during the typical spring fire season, which has implications for fire management decision-making. [ABSTRACT FROM AUTHOR]

A coordinated testing policy is an essential tool for responding to emerging epidemics, as was seen with COVID‐19. However, it is very difficult to agree on the best policy when there are multiple conflicting objectives. A key objective is minimizing cost, which is why pooled testing (a method that involves pooling samples taken from multiple individuals and analyzing this with a single diagnostic test) has been suggested. In this article, we present results from an extensive and realistic simulation study comparing testing policies based on individually testing subjects with symptoms (a policy resembling the UK strategy at the start of the COVID‐19 pandemic), individually testing subjects at random or pools of subjects randomly combined and tested. To compare these testing methods, a dynamic model compromised of a relationship network and an extended SEIR model is used. In contrast to most existing literature, testing capacity is considered as fixed and limited rather than unbounded. This article then explores the impact of the proportion of symptomatic infections on the expected performance of testing policies. Symptomatic testing performs better than pooled testing unless a low proportion of infections are symptomatic. Additionally, we include the novel feature for testing of non‐compliance and perform a sensitivity analysis for different compliance assumptions. Our results suggest for the pooled testing scheme to be superior to testing symptomatic people individually, only a small proportion of the population (>10%$$ >10\% $$) needs to not comply with the testing procedure. [ABSTRACT FROM AUTHOR]

Background: In this study we used Mendelian randomization (MR) to investigate the potential causal association of lipoprotein (a) [Lp(a)] levels with pulse wave velocity (PWV). Methods: Genetic variants associated with Lp(a) were retrieved from the UK Biobank GWAS (N = 290,497). A non‐ overlapping GWAS based on a European cohort (N = 7,000) was used to obtain genetic associations with PWV (outcome) and utilized two different measures for the same trait, brachial–ankle (baPWV) and carotid–femoral (cfPWV) PWV. We applied a two‐sample MR using the inverse variance weighting method (IVW) and a series of sensitivity analyses for 170 SNPs that were selected as instrumental variables (IVs). Results: Our analyses do not support a causal association between Lp(a) and PWV for neither measurement [βiwv(baPWV) = −.0005, p =.8 and βiwv(cfPWV) = −.006, p =.16]. The above findings were consistent across sensitivity analyses including weighted median, mode‐based estimation, MR‐Egger regression and MR‐PRESSO. Conclusion: We did not find evidence indicating that Lp(a) is causally associated with PWV, the gold standard marker of arterial stiffness. [ABSTRACT FROM AUTHOR]

Background: Cutaneous melanoma (CM) of the skin stands as the leading cause of mortality among skin cancer-related deaths. Despite the successes achieved with novel therapies such as immunotherapy and targeted therapy, their efficacy remains limited, necessitating further exploration of new treatment modalities. The gut microbiota and CM may be linked, as indicated by a growing body of preclinical and observational research. Nevertheless, the exact correlation between the intestinal microbiota and CM remains to be determined. Therefore, this study aims to assess the potential causal relationship between the gut microbiota and CM. Methods: The study utilized exposure data obtained from the MiBioGen consortium's microbiome GWAS, which included a total of 18,340 samples gathered from 24 population-based cohorts. Data at the summary level for CM were acquired from the UK Biobank investigation. The main analytical strategy utilized in this research was the inverse variance weighted (IVW) technique, supported by quality assurance measures like the weighted median model, MR-Egger, simple model, and weighted model approaches. The Cochran's Q test was used to evaluate heterogeneity. To ascertain potential pleiotropy, we employed both the MR-Egger regression and the MR-PRESSO test. Sensitivity analysis was conducted using the leave-one-out method. Results: The study found that the class Bacteroidia (OR = 0.997, 95% CI: 0.995-0.999, p = 0.027), genus Parabacteroides (OR = 0.997, 95% CI: 0.994-0.999, p = 0.037), order Bacteroidales (OR = 0.997, 95% CI: 0.995-0.999, p = 0.027), and genus Veillonella (OR = 0.998, 95% CI: 0.996-0.999, p = 0.046) have protective effects on CM. On the order hand, the genus Blautia (OR = 1.003, 95% CI: 1-1.006, p = 0.001) and phylum Cyanobacteria (OR = 1.002, 95% CI: 1-1.004, p = 0.04) are identified as risk factors for CM. Conclusion: We comprehensively assessed the potential causal relationship between the gut microbiota and CM and identified associations between six gut microbiota and CM. Among these, four gut microbiota were identified as protective factors for CM, while two gut microbiota were identified as risk factors for CM. This study effectively established a causal relationship between the gut microbiota and CM, thereby providing valuable insights into the mechanistic pathways through which the microbiota impacts the progression of CM. [ABSTRACT FROM AUTHOR]

Background: While a few case-control studies indicated a possible correlation of IgG N-glycosylation patterns with pancreatitis, their restricted sample sizes and methodologies prevented conclusive insights into causality or distinguishing traits across pancreatitis types. Method: We conducted a two-sample Mendelian Randomization (MR) analysis to investigate the causal relationship between 77 IgG N-glycosylation traits and various types of pancreatitis, including acute pancreatitis (AP), chronic pancreatitis (CP), alcohol acute pancreatitis (AAP), and alcohol chronic pancreatitis (ACP). This analysis utilized summary-level data from genomewide association studies (GWAS), employing methods such as IVW, MR-Egger, and weighted median. To ensure the robustness of our findings, several sensitivity analyses, including Cochran's Q statistic, leave-one-out, MR-Egger intercept, and MR-PRESSO global test were conducted. Result: Our study uncovered the causal relationship between specific IgG Nglycosylation traits and various types of pancreatitis. Notably, an increase in genetically predicted IGP7 levels was associated with a decreased risk of developing AP. For CP, our data suggested a protective effect associated with higher levels of both IGP7 and IGP31, contrasting with increased levels of IGP27 and IGP65, which were linked to a heightened risk. Moreover, in the case of AAP, elevated IGP31 levels were causatively associated with a lower incidence, while higher IGP26 levels correlated with an increased risk for ACP. Conclusion: This study establishes causal relationship between specific IgG N-glycosylation patterns and varying risks of different pancreatitis forms, underscoring their potential as predictive biomarkers. These findings necessitate further exploration into the underlying mechanisms, promising to inform more personalized diagnostic and therapeutic strategies in pancreatitis management. [ABSTRACT FROM AUTHOR]

This article examines associations between precarious contract types and a range of self‐reported health measures for the UK. We focus on zero hours contracts (ZHCs), an extreme form of precarious employment that has grown rapidly in the UK over the last decade, and on mental health. We demonstrate that workers employed on ZHCs are more likely to report a long‐term health condition than workers employed on other types of contract, with the main driver being that they are almost twice as likely to report mental ill health. These associations survive conditioning on an extensive set of observable individual, job and contextual characteristics, and are robust to sensitivity analysis designed to explore the likely extent of bias due to unobserved confounders. We discuss potential explanations for these associations, from sorting of workers with poor health into ZHC employment to detrimental effects of ZHC employment on health, drawing on additional instrumental variables estimates to do so. Finally, we discuss potential policy implications. [ABSTRACT FROM AUTHOR]

A substantial number of dwellings in the UK have poor building fabric, leading to higher carbon emissions, fuel expenses, and the risk of cold homes. To tackle these challenges, domestic energy efficiency policies are being implemented. One effective approach is the use of energy models, which enable sensitivity analysis to provide valuable insights for policymakers. This study employed dynamic thermal simulation models for 32 housing archetypes representative of solid-walled homes in the UK to calculate the heat loss and the sensitivity coefficient per building fabric feature, after which a metric Heat Loss Sensitivity (HLS) index was established to guide the selection of retrofit features for each archetype. The building fabric features' inputs were then adjusted to establish both lower and upper bounds, simulating low and high performance levels, to predict the how space heating energy demand varies. The analysis was extended by replicating the process with various scenarios considering climates, window-to-wall ratios, and overshadowing. The findings highlight the external wall as the primary consideration in retrofitting due to its high HLS index, even at high window-to-wall ratios. It was also established that dwelling type is important in retrofit decision-making, with floor and loft retrofits having a high HLS index in bungalows. Furthermore, the analysis underlines the necessity for Standard Assessment Procedure assessors to evaluate loft U-value and air permeability rates prior to implementing retrofit measures, given the significance of these factors in the lower and upper bounds analysis. Researchers globally can replicate the HLS index approach, facilitating the implementation of housing retrofit policies worldwide. [ABSTRACT FROM AUTHOR]

Land surface models are an important tool in the study of climate change and its impacts, but their use can be hampered by uncertainties in input parameter settings and by errors in the models. We apply uncertainty quantification (UQ) techniques to constrain the input parameter space and corresponding historical simulations of JULES-ES-1.0 (Joint UK Land Environment Simulator Earth System), the land surface component of the UK Earth System Model, UKESM1.0. We use an ensemble of historical simulations of the land surface model to rule out ensemble members and corresponding input parameter settings that do not match modern observations of the land surface and carbon cycle. As JULES-ES-1.0 is computationally expensive, we use a cheap statistical proxy termed an emulator, trained on the ensemble of model runs, to rule out parts of the parameter space where the simulator has not yet been run. We use history matching, an iterated approach to constraining JULES-ES-1.0, running an initial ensemble and training the emulator, before choosing a second wave of ensemble members consistent with historical land surface observations. We successfully rule out 88 % of the initial input parameter space as being statistically inconsistent with observed land surface behaviour. The result is a set of historical simulations and a constrained input space that are statistically consistent with observations. Furthermore, we use sensitivity analysis to identify the most (and least) important input parameters for controlling the global output of JULES-ES-1.0 and provide information on how parameters might be varied to improve the performance of the model and eliminate model biases. [ABSTRACT FROM AUTHOR]

Purpose: Algal research has been dominated by the use of marine biomass (mainly microalgae) as feedstock in the production of second-generation biofuels, albeit with limited economic success. A promising alternative strategy is the valorisation of seaweed (macroalgae), with the cascaded extraction of its high-value components, as well as lower-value components further downstream, under the 'biorefinery concept'. The goal of this study was to assess the environmental performance of one such marine biorefinery situated in the UK. Methods: Attributional life cycle assessment (LCA) was conducted on a hypothetical marine biorefinery coproducing fucoidan, laminarin, protein and alginate/cellulose packaging material (target product), from cultivated Saccharina latissima. The functional unit was the production of 1 kg of packaging material. A total of 6 scenarios were modelled, varying in coproduct management methodology (system expansion, mass allocation or economic allocation) and applied energy mix (standard or green energy). Sensitivity analysis was also conducted, evaluating the systems response to changes in allocation methodology; product market value; biomass composition and transport mode and distance. LCA calculations were performed using OpenLCA (version 1.10.3) software, with background processes modelled using the imported Ecoinvent 3.6 database. Environmental impacts were quantified under ReCiPe methodology at the midpoint level, from the 'Heirarchist' (H) perspective. Results and discussion: The overall global warming impacts ranged from 1.2 to 4.52 kg CO2 eq/kg biopolymer, with the application of economic allocation; 3.58 to 7.06 kg CO2eq/kg with mass allocation and 14.19 to 41.52 kg CO2eq/kg with system expansion — the lower limit representing the instance where green electricity is used and the upper where standard electricity is employed. While implementing the green energy mix resulted in a 67% reduction in global warming impacts, it also incurred a 2–9 fold increase in overall impacts in the categories of terrestrial acidification, human non-carcinogenic toxicity, land-use and terrestrial ecotoxicity. Economic allocation resulted in burden shifting most favourable to the packaging material pathway. Conclusions: This study demonstrates that the road to environmental optimisation in marine biorefineries is fraught with trade-offs. From the perspective of LCA — and by extension, the eco-design process that LCA is used to inform — when evaluating such product systems, it serves to strike a balance between performance across a broad spectrum of environmental impact categories, along with having consideration for the nature of energy systems incorporated and LCA methodological elements. [ABSTRACT FROM AUTHOR]

This study focuses on the specific types of supply chain strategies throughout the UK textile industry as extant literature has either emphasised on the fashion apparel industry or on sub-industry of fast fashion. A combination of normalised local priority weights of criteria and sub-criteria is used with respect to successive hierarchical levels which modelled in an Analytical Hierarchy Process (AHP) at different levels. This helped in obtaining global composite priority weights for all the sub-criteria at third level of AHP model. The changes in different factors are observed with respect to digitalisation in sensitivity analysis at different levels of variations in the weight for which marginal changes are noted in the following variables: development of key suppliers, supplier capability auditing, and long-term orientation with suppliers. Supply base optimisation and purchasing integration showed changes at all levels of variations. Purchasing and production strategy was crucial as primary criteria for accomplishing the goal of the supply chain management future. There was substantial evidence from the three companies participating in the research that purchasing and production strategies play equally significant roles in successful digitalisation, identification, and delivery. [ABSTRACT FROM AUTHOR]

We conducted a Mendelian randomization study to evaluate the potential causal effects of attending religious groups on the prevalence of depression, generalized anxiety disorders, anxiety disorders, and suicide and self-harm. Data from the UK Biobank and the FinnGen project were processed by inverse variance weighting (IVW), weighted median, and MR-Egger regression methods. Despite certain pleiotropic risks, we found that attending religious groups was potentially associated with a reduced risk of anxiety disorders (OR = 0.213, p =.028). The pleiotropies were largely controlled and the effect on anxiety disorders became more significant in our sensitivity analysis (OR = 0.162; p =.006). Additionally, attending religious groups was associated with a reduced risk of suicide and self-harm (OR = 0.231, p =.0006). However, we did not observe any substantial protection against depression. In conclusion, our study adds to the existing literature and sheds light on the potential health benefits of religious activities from a novel perspective. [ABSTRACT FROM AUTHOR]

Physical activity is a potential protective factor against gout, but the role of exercise intensity in this context remains unclear. To overcome the limitations of observational studies in causal inference, this study employed a two-sample Mendelian randomization approach to explore the impact of different genetically proxied/predicted intensities of physical activity on serum urate concentration and the incidence of gout. Our data related to physical activity, serum urate, and gout were obtained from the UK Biobank, the Global Urate Genetics Consortium (GUGC), and the FinnGen dataset, respectively. Walking was included as representative of typical low-intensity physical activity in the analysis, and the other two types were moderate and vigorous physical activities. The estimation methods we used included the inverse-variance-weighted (IVW) method, MR-Egger regression, weighted-median method, simple-mode method, and weighted-mode method. Sensitivity analyses involved Rucker's framework, Cochran's Q test, funnel plots, MR-PRESSO outlier correction, and leave-one-out analysis. We found suggestive evidence from the inverse-variance-weighted method that moderate physical activity was a potential factor in reducing the incidence of gout (OR = 0.628, p = 0.034), and this association became more substantial in our subsequent sensitivity analysis (OR = 0.555, p = 0.006). However, we observed no distinctive effects of physical activity on serum urate concentration. In conclusion, our study supports some findings from observational studies and emphasizes the preventive role of moderate physical activity against gout. Given the limitations of the existing datasets, we call for future reexamination and expansion of our findings using new GWAS data. [ABSTRACT FROM AUTHOR]

A cohort study conducted in the UK Biobank found no significant association between the use of statins and the risk of uterine leiomyoma (fibroids) in premenopausal women. The study analyzed data from over 60,000 participants and examined different types of statins. The results were consistent across various subgroup and sensitivity analyses, suggesting that statins do not appear to reduce the risk of uterine leiomyoma. However, caution should be exercised when interpreting the findings due to potential biases. [Extracted from the article]

Platelet count has been associated with blood pressure, but whether this association reflects causality remains unclear. To strengthen the evidence, we conducted a traditional observational analysis in the Lifelines Cohort Study (n = 167,785), and performed bi-directional Mendelian randomization (MR) with summary GWAS data from the UK Biobank (n = 350,475) and the International Consortium of Blood Pressure (ICBP) (n = 299,024). Observational analyses showed positive associations between platelet count and blood pressure (OR = 1.12 per SD, 95% CI: 1.10 to 1.14 for hypertension; B = 0.07, 95% CI: 0.07 to 0.08 for SBP; B = 0.07 per SD, 95% CI: 0.06 to 0.07 for DBP). In MR, a genetically predicted higher platelet count was associated with higher SBP (B = 0.02 per SD, 95% CI = 0.00 to 0.04) and DBP (B = 0.03 per SD, 95% CI = 0.01 to 0.05). IVW models and sensitivity analyses of the association between platelet count and DBP were consistent, but not all sensitivity analyses were statistically significant for the platelet count-SBP relation. Our findings indicate that platelet count has modest but significant effects on SBP and DBP, suggesting causality and providing further insight into the pathophysiology of hypertension. [ABSTRACT FROM AUTHOR]

Researchers and engineers employ machine learning (ML) tools to detect pipe bursts and prevent significant non-revenue water losses in water distribution systems (WDS). Nonetheless, many approaches developed so far consider a fixed number of sensors, which requires the ML model redevelopment and collection of sufficient data with the new sensor configuration for training. To overcome these issues, this study presents a novel approach based on Long Short-Term Memory neural networks (NNs) that leverages transfer learning to manage a varying number of sensors and retain good detection performance with limited training data. The proposed detection model first learns to reproduce the normal behavior of the system on a dataset obtained in burst-free conditions. The training process involves predicting flow and pressure one-time step ahead using historical data and time-related features as inputs. During testing, a post-prediction step flags potential bursts based on the comparison between the observations and model predictions using a time-varied error threshold. When adding new sensors, we implement transfer learning by replicating the weights of existing channels and then fine-tune the augmented NN. We evaluate the robustness of the methodology on simulated fire hydrant bursts and real-bursts in 10 district metered areas (DMAs) of the UK. For real bursts, we perform a sensitivity analysis to understand the impact of data resolution and error threshold on burst detection performance. The results obtained demonstrate that this ML-based methodology can achieve Precision of up to 98.1% in real-life settings and can identify bursts, even in data scarce conditions. [ABSTRACT FROM AUTHOR]

Background: Observational studies have suggested associations between serum urate levels and sarcopenia, but the causality underlying this correlation remains uncertain. The principal objective of this study is to investigate a causal relationship of serum urate levels with sarcopenia-related traits (hand grip strength, lean mass, walking pace) using bidirectional two-sample Mendelian randomization (MR) approach. The utilization of MR methodology serves to minimize bias caused by reverse causality and confounding factors from observational studies. Methods: The summary statistics of serum urate levels were derived from a cohort consisting of 288,659 individuals participating in CKDGen study. The parameters of right-hand grip strength (N=461,089), left-hand grip strength (N=461,026), appendicular lean mass (ALM) (N=450,243), whole-body lean mass(N=454,850), right-leg fat-free mass(FFM;N=454,835), left-leg FFM (N=454,805), right-arm FFM(N=454,753), left-arm FFM(N=454,672) and walking pace (N=459,915)were sourced from the UK Biobank. MR analysis was conducted utilizing inverse variance weighted (IVW), weighted median, and MR-Egger to evaluate causality. Sensitivity analysis was performed using Cochran's Q test, MR-Egger intercept test, leave-one-out analysis and the funnel plot. Results: IVW estimates demonstrated that serum urate levels exhibited no causal association with sarcopenia-related traits. In the inverse MR investigation, we had exclusively discerned an inverse correlation between walking pace and serum urate levels. No compelling evidence had surfaced to substantiate any association of other sarcopenia-related traits with serum urate. Supplemental MR methods consistently validated the findings obtained from the primary analysis. Sensitivity analysis demonstrated the robustness of findings. Conclusion: Our MR study revealed the absence of the bidirectional causal relationship between serum urate levels and sarcopenia. It is imperative to acknowledge that advanced age and an individual's health status are pivotal determinants influencing urate level and the initiation and advancement of sarcopenia. However, it is worth underscoring that these aspects remain unexamined within the purview of this study. Thus, future investigations should delve deeper into these intricate facets. [ABSTRACT FROM AUTHOR]

The post-effects of COVID-19 have begun to emerge in the long term in society. Stroke has become one of the most common side effects in the post-COVID community. In this study, to examine the relationship between COVID-19 and stroke, a fractional-order mathematical model has been constructed by considering the fear effect of being infected. The model's positivity and boundedness have been proved, and stability has been examined for disease-free and co-existing equilibrium points to demonstrate the biological meaningfulness of the model. Subsequently, the basic reproduction number (the virus transmission potential ( R 0 )) has been calculated. Next, the sensitivity analysis of the parameters according to R 0 has been considered. Moreover, the values of the model parameters have been calculated using the parameter estimation method with real data originating from the United Kingdom. Furthermore, to underscore the benefits of fractional-order differential equations (FODEs), analyses demonstrating their relevance in memory trace and hereditary characteristics have been provided. Finally, numerical simulations have been highlighted to validate our theoretical findings and explore the system's dynamic behavior. From the findings, we have seen that if the screening rate in the population is increased, more cases can be detected, and stroke development can be prevented. We also have concluded that if the fear in the population is removed, the infection will spread further, and the number of people suffering from a stroke may increase. [ABSTRACT FROM AUTHOR]

Background: Online studies offer an efficient method of recruiting participants and collecting data. Whilst delivering an online randomised trial, we detected unusual recruitment activity. We describe our approach to detecting and managing suspected fraud and share lessons for researchers. Methods: Our trial investigated the single and combined effects of different ways of presenting clinical audit and feedback. Clinicians and managers who received feedback from one of five United Kingdom national clinical audit programmes were emailed invitations that contained a link to the trial website. After providing consent and selecting their relevant audit, participants were randomised automatically to different feedback versions. Immediately after viewing their assigned feedback, participants completed a questionnaire and could request a financial voucher by entering an email address. Email addresses were not linked to trial data to preserve participant anonymity. We actively monitored participant numbers, questionnaire completions, and voucher claims. Results: Following a rapid increase in trial participation, we identified 268 new voucher claims from three email addresses that we had reason to believe were linked. Further scrutiny revealed duplicate trial completions and voucher requests from 24 email addresses. We immediately suspended the trial, improved security measures, and went on to successfully complete the study. We found a peak in questionnaires completed in less than 20 seconds during a likely contamination period. Given that study and personal data were not linked, we could not directly identify the trial data from the 268 duplicate entries within the 603 randomisations occurring during the same period. We therefore excluded all 603 randomisations from the primary analysis, which was consequently based on 638 randomisations. A sensitivity analysis, including all 961 randomisations over the entire study except for questionnaire completions of less than 20 seconds, found only minor differences from the primary analysis. Conclusion: Online studies offering incentives for participation are at risk of attempted fraud. Systematic monitoring and analysis can help detect such activity. Measures to protect study integrity include linking participant identifiers to study data, balancing study security and ease of participation, and safeguarding the allocation of participant incentives. Trial registration: International Standard Randomised Controlled Trial Number: ISRCTN41584028. Registration date is August 17, 2017. [ABSTRACT FROM AUTHOR]

The end of the 20th century brought about drastic changes in the tropospheric ozone (O3) around the globe. It is, therefore, highly important to gain insight into O3 formation mechanisms and their key precursors in order to assist policymaking to combat O3 pollution. This article synthesizes a bibliometric analysis of O3 formation sensitivity from 1965 to 2022, reported in English language journals available in the Web of Science Core Collection. This study shows that constant expansion in the number of publications has occurred since 2008, with the highest number occurring in 2021. Most publications are from the United States of America (USA), with 406 papers (42.7%), followed by China with 128 papers (13.5%), and the United Kingdom (UK) with 87 papers (9.1%). Citation burst analysis and significant and highly cited research work analysis are used to discover and assess evolving research tendencies. The thematic evolution of author-supplied keywords indicates that the terms "volatile organic compounds" and "ozone precursors" have recently emerged with a higher frequency. This suggests that there is a growing trend in research focused on these topics in the future. The objective of this study is to provide research primacies and future prospects for better analysis of O3 sensitivity, thereby helping to manage O3 pollution. [ABSTRACT FROM AUTHOR]

Many partial identification problems can be characterized by the optimal value of a function over a set where both the function and set need to be estimated by empirical data. Despite some progress for convex problems, statistical inference in this general setting remains to be developed. To address this, we derive an asymptotically valid confidence interval for the optimal value through an appropriate relaxation of the estimated set. We then apply this general result to the problem of selection bias in population-based cohort studies. We show that existing sensitivity analyses, which are often conservative and difficult to implement, can be formulated in our framework and made significantly more informative via auxiliary information on the population. We conduct a simulation study to evaluate the finite sample performance of our inference procedure, and conclude with a substantive motivating example on the causal effect of education on income in the highly selected UK Biobank cohort. We demonstrate that our method can produce informative bounds using plausible population-level auxiliary constraints. We implement this method in the |$\texttt{R}$| package |$\texttt{selectioninterval}$|⁠. [ABSTRACT FROM AUTHOR]

Background: The Surgical Outcome Risk Tool (SORT) was derived and validated in the UK to improve preoperative prediction of postoperative risk. The aim of this study was to validate the SORT in a European mixed-case surgical population outside of the UK. Methods: The study included patients aged at least 18 years with ASA Physical Status (ASA-PS) grades I-V who underwent non-cardiac surgery at four tertiary hospitals in Sweden between November 2015 and February 2016. Exclusion criteria were surgery under local anaesthesia and missing data on the SORT predictors (ASA-PS, surgical urgency, high-risk surgery, surgical severity, malignancy, age over 65 years). The outcome was 30-day mortality. Discrimination and calibration of the SORT were assessed using area under the receiver operating curve (AUROC) statistics and calibration plots. A sensitivity analysis was done in a high-risk subgroup (ASAPS III or higher; surgical complexity major to Xmajor according to the SORT; gastrointestinal, orthopaedic, urogenital/obstetric surgery; and age at least 18 years). Results: The validation cohort included 17 965 patients; median age was 58 (i.q.r. 40-70) years, 43.2 per cent were men, and the mortality rate at 30 days was 1.6 per cent. The SORT had excellent discrimination, with an AUROC of 0.91 (95 per cent c.i. 0.89 to 0.92), and good calibration. The high-risk subgroup (1807 patients) had a 30-day mortality rate of 5.6 per cent; in the sensitivity analysis, the SORT had good discrimination, with an AUROC of 0.79 (0.74 to 0.83), and calibration remained good. Conclusion: The estimates of the original the SORT for prediction of 30-day mortality were valid and reliable in a mixed-case surgical population in a non-UK European setting. [ABSTRACT FROM AUTHOR]

Background: Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH, and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems. Methods: Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p<0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR (MVMR) controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels. Results: Our results identified seven disease traits reaching Bonferroni-corrected significance in both the discovery (p<1.92 × 10-5) and replication analyses (p<2.26 × 10-4), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p=2.47 × 10-13). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p<0.05), identifying plasma TG levels as a novel potential risk factor for nine non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p=1.17 × 10-5). Conclusions: Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies. [ABSTRACT FROM AUTHOR]

This paper analyses and compares the performance between a bifacial and a monofacial PV system based on the tests conducted at Heriot-Watt University, UK. The module's performance was observed on different ground reflective surfaces: concrete, white tiles, soil, and white pebbles. The rear side irradiance and bifacial energy gains are analysed. The power output is examined for a sunny and cloudy days, and yearly energy mapping is shown. Correlation studies are performed, and empirical model are developed between (i) clearness index and rear irradiance gain: (ii) rear irradiance gain and bifacial energy gain; (iii) total irradiance and power output. Based on the annual rear irradiance gain analysis, the highest gain range is found for white pebbles and white tiles ground surface (>30 % gain) and lowest for soil surface within the 5 %–10 % range and for concrete, >20 %. Regardless of the ground reflective surface, the probability is low that the bifacial energy gain is more than 30 %. Finally, a case study is discussed to perform a sensitivity analysis of a bifacial PV project's Levelized cost of electricity (LCOE). The sensitivity analysis shows that by using an enhanced ground albedo surface, the LCOE of the bifacial PV project can be reduced to 7.15p/kWh. The results show consistency with simulations output ran in PVSyst for different locations across the UK and the reported bifacial gain worldwide. [ABSTRACT FROM AUTHOR]

Access to detailed data sets which can enable detailed hydraulic modelling of the river around a bridge structure is not always possible and may require extensive surveys. It is important for infrastructure managers to decide whether additional data availability that may increase the accuracy of scour risk assessments may be worthwhile. In this regard, this paper aims to examine the scour risk assessment of bridges under different model resolutions by using two commonly used scour risk assessment procedures for railway bridges in the UK and investigate the sensitivity of a number of hydraulic parameters used in the scour prediction equations. These procedures are applied to four case study railway bridges coupled with four data availability scenarios capturing different levels of topographical and hydrological data available for the bridge/river site. The results show that the estimations of hydraulic parameters based on the simple empirical equations recommended by EX2502 for data scarcity conditions have a tendency to cause a significant disparity compared to the estimates from 1D and 2D HEC-RAS models. Particularly 2D models with bathymetric representation of river can provide more reliable results and improve the accuracy of scour risk assessments, especially for bridges that are close to the thresholds distinguishing different scour risk categories, i.e. medium to high risk. Sensitivity analysis of hydraulic parameters suggests that the most influential parameter that causes significant variations in total scour depth and scour risk is average velocity, followed by mean flow depth, mean floodplain depth, and mean floodplain width. [ABSTRACT FROM AUTHOR]

With many of the world's governments committing to achieve net-zero greenhouse gas (GHG) emissions by mid-century, with well-defined milestones along the road, it is important to investigate how each sector can contribute towards achieving this global goal. The manufacturing sector, with its energy-intensive processes, large amounts of wastes, and hazardous and harmful emissions, is one of the main contributors to global GHG emissions, as well as other sustainability aspects, and, thus, it has great potential to contribute substantially to achieve net-zero objectives. This paper presents a techno-environmental-economic analysis of technologies that can play a key, enabling and leading role in the quest towards net-zero. Such technologies typically bring modest improvement in the environmental performance; however, the aim of this paper is to demonstrate how such small changes, when implemented in an industrial setting, can contribute significantly to the collective improvement in the environmental performance. In order to put the potential improvements into perspective, a real case study from the UK aerospace manufacturing sector is conducted. In the case study, metrics measuring potential improvements from the installation of a low-to-medium waste heat recovery system, and the upgrade of electric motors in the shopfloor to more energy efficient ones, are calculated through environmental and economic models. The models are then subject to a series of sensitivity analyses experiments to help understand the impact of different sources of uncertainty on the perceived GHG emissions, and economic and energy savings. The techno-environmental-economic analysis results revealed that these small changes, when implemented in an industrial setting, can indeed bring valuable improvements in the environmental performance of a manufacturing institute. Further, the sensitivity analysis experiments demonstrated how the environmental and economic performances are not adversely affected by different levels of fluctuations in key, likely to fluctuate, input parameters. [ABSTRACT FROM AUTHOR]

With the increasing size and number of genome-wide association studies, individual single nucleotide polymorphisms are increasingly found to associate with multiple traits. Many different mechanisms could result in proposed genetic IVs for an exposure of interest being associated with multiple non-exposure traits, some of which could bias MR results. We describe and illustrate, through causal diagrams, a range of scenarios that could result in proposed IVs being related to non-exposure traits in MR studies. These associations could occur due to five scenarios: (i) confounding, (ii) vertical pleiotropy, (iii) horizontal pleiotropy, (iv) reverse causation and (v) selection bias. For each of these scenarios we outline steps that could be taken to explore the underlying mechanism and mitigate any resulting bias in the MR estimation. We recommend MR studies explore possible IV—non-exposure associations across a wider range of traits than is usually the case. We highlight the pros and cons of relying on sensitivity analyses without considering particular pleiotropic paths versus systematically exploring and controlling for potential pleiotropic or other biasing paths via known traits. We apply our recommendations to an illustrative example of the effect of maternal insomnia on offspring birthweight in UK Biobank. [ABSTRACT FROM AUTHOR]

Although no human papillomavirus (HPV) vaccine is indicated for single-dose administration, some observational evidence suggests that a 1-dose regimen might reduce HPV infection risk to that achieved with 2 doses. This study estimated the potential health and economic outcomes associated with switching from a 2-dose HPV vaccination program for girls and boys aged 13–14 years to an off-label 9-valent (9vHPV), 1-dose regimen, accounting for the uncertainty of the effectiveness and durability of a single dose. A dynamic HPV transmission infection and disease model was adapted to the United Kingdom and included a probabilistic sensitivity analysis using estimated distributions for duration of protection of 1-dose and degree of protection of 1 relative to 2 doses. One-way sensitivity analyses of key inputs were performed. Outcomes included additional cancer and disease cases and the difference in net monetary benefit (NMB). The 1-dose program was predicted to result in 81,738 additional HPV-related cancer cases in males and females over 100 years compared to the 2-dose program, ranging from 36,673 to 134,347 additional cases (2.5% and 97.5% quantiles, respectively), and had a 7.8% probability of being cost-effective at the £20,000/quality-adjusted life years willingness-to-pay (WTP) threshold. In one-way sensitivity analyses, the number of additional cancer cases was sensitive to the median of the duration of protection distribution and coverage rates. The differences in NMBs were sensitive to the median of the duration of protection distribution, dose price and discount rate, but not coverage variations. Across sensitivity analyses, the probability of 1 dose being cost-effective vs 2 doses was < 50% at the standard WTP threshold. Adoption of a 1-dose 9vHPV vaccination program resulted in more vaccine-preventable HPV-related cancer and disease cases in males and females, introduced substantial uncertainty in health and economic outcomes, and had a low probability of being cost-effective compared to the 2-dose program. [ABSTRACT FROM AUTHOR]

New powertrain technologies, such as those used in Hybrid Electric Vehicles, have a price premium which is often offset by lower running costs. Total Cost of Ownership (TCO) combines these purchase and operating expenses to identify the most economical vehicles overall. This is a valuable assessment for both private and fleet purchasers. To date, no studies have compared Total Cost of Ownership across more than two vehicle markets or analysed historic costs. To address this gap, this research provides a more extensive assessment of TCO in three industrialized countries — the U.S.A. (California specifically), the UK, and Republic of Korea — for the time period from 2015 ∼ 2019. As an early analysis of the regional characteristics of TCO, this study aims to examine how TCO varies across different geographic regions and develop an analysis methodology for future analysis of environmental vehicles. To analyze the TCO under identical conditions for each region, the TCO result is calculated using data from conventional vehicles by utilizing sufficient statistical data. The TCO model includes registration and road taxes as well as insurance, fuel, financial interest, depreciation, and maintenance costs. To represent the local features, the research considers four vehicles from different manufacturers. Using the proposed TCO model, the regional characteristic is analyzed and a sensitivity analysis is performed with the parameters constituting the TCO model. This research has implications for both fleet purchasers and private owners considering new vehicles. The findings are also relevant for carmakers aiming to develop vehicle sales strategies optimized for specific regions. [ABSTRACT FROM AUTHOR]

The asset allocation decision is one of the most important decisions made by defined benefit pension schemes, with a major effect on the scheme contribution rate, funding ratio and financial position of the sponsoring company. We investigate the determinants of the equity allocation of UK pension funds using a panel of 1,304 observations on 125 companies that were members of the FTSE 100 over the 2003–2019 period. We find that seven variables have a significant effect on the allocation between equities and bonds – maturity (as measured by the effective duration of scheme liabilities), default risk, leverage of the sponsor, size of the sponsor (or the scheme), whether the scheme is closed to future contributions, whether the scheme has significant overseas liabilities, and a time trend. Our sensitivity analysis finds that the biggest effects on the asset allocation come from scheme maturity, the scheme's funding ratio and a time trend. [ABSTRACT FROM AUTHOR]

Calibration of the rating curve is a challenge due to uncertainty in the parameters. This problem increases in an area with considerable seasonal vegetation diversity. In this study, the generalized likelihood uncertainty estimation (GLUE) method was combined with the proposed stage-discharge model, introduced by Maghrebi et al., to compute the parameter uncertainty of the rating curve in the Main River in the UK and the Colorado River in Argentina. In GLUE methodology, the sensitivity and uncertainty analysis of each parameter were investigated by comparing the prior and posterior distribution of the effective parameters in the proposed method. It should be noted that all the parameters studied in the proposed model, such as power function parameters (a1, a2, and a3) and Manning's roughness coefficient can be acquired with an optimal parameter domain using the calibration method. The results demonstrated low sensitivity of roughness parameters and high sensitivity of power function parameter a1 in comparison with other parameters. In order to evaluate the uncertainty results, two average relative interval length (ARILCI) and the percent of observations bracketed by the 95CI (PCI95%) factors at 95% confidence level were used. The results showed that if the observational data were selected from the middle level, a more favorable result would be obtained and demonstrated less uncertainty in the output range of the model. [ABSTRACT FROM AUTHOR]

Background: This systematic review aimed to identify, compare and contrast outcome domains and outcome instruments reported in studies investigating interventions that seek to restore bilateral (two-sided) and/or binaural (both ears) hearing in adults with single-sided deafness (SSD). Findings can inform the development of evidence-based guidance to facilitate design decisions for confirmatory trials.Methods: Records were identified by searching MEDLINE, EMBASE, PubMed, CINAHL, ClinicalTrials.gov, ISRCTN, CENTRAL, WHO ICTRP and the NIHR UK clinical trials gateway. The search included records published from 1946 to March 2020. Included studies were those as follows: (a) recruiting adults aged 18 years or older diagnosed with SSD of average threshold severity worse than 70 dB HL in the worse-hearing ear and normal (or near-normal) hearing in the better-hearing ear, (b) evaluating interventions to restore bilateral and/or binaural hearing and (c) enrolling those adults in a controlled trial, before-and-after study or cross-over study. Studies that fell just short of the participant eligibility criteria were included in a separate sensitivity analysis.Results: Ninety-six studies were included (72 full inclusion, 24 sensitivity analysis). For fully included studies, 37 exclusively evaluated interventions to re-establish bilateral hearing and 29 exclusively evaluated interventions to restore binaural hearing. Overall, 520 outcome domains were identified (350 primary and 170 secondary). Speech-related outcome domains were the most common (74% of studies), followed by spatial-related domains (60% of studies). A total of 344 unique outcome instruments were reported. Speech-related outcome domains were measured by 73 different instruments and spatial-related domains by 43 different instruments. There was considerable variability in duration of follow-up, ranging from acute (baseline) testing to 10 years after the intervention. The sensitivity analysis identified no additional outcome domains.Conclusions: This review identified large variability in the reporting of outcome domains and instruments in studies evaluating the therapeutic benefits and harms of SSD interventions. Reports frequently omitted information on what domains the study intended to assess, and on what instruments were used to measure which domains.Trial Registration: The systematic review protocol is registered on PROSPERO (International Prospective Register of Systematic Reviews): Registration Number CRD42018084274 . Registered on 13 March 2018, last revised on 7th of May 2019. [ABSTRACT FROM AUTHOR]

The coronavirus (COVID-19) outbreak started in December 2019 and rapidly spread around the world affecting millions of people. With the growth of infection rate, many countries adopted different policies to control the spread of the disease. The UK implemented strict rules instructing individuals to stay at home except in some special circumstances starting from 23 March 2020. Accordingly, this study focuses on sensitivity analysis of transmissibility of the infection as the effects of removing restrictions, for example by returning different occupational groups to their normal working environment and its effect on the reproduction number in the UK. For this reason, available social contact matrices are adopted for the population of UK to account for the average number of contacts. Different scenarios are then considered to analyse the variability of total contacts on the reproduction number in the UK as a whole and each of its four nations. Our data-driven retrospective analysis shows that if more than 38.5% of UK working-age population return to their normal working environment, the reproduction number in the UK is expected to be higher than 1. However, analysis of each nation, separately, shows that local reproduction number in each nation may be different and requires more adequate analysis. Accordingly, we believe that using statistical methods and historical data can provide good estimation of local transmissibility and reproduction number in any region. As a consequence of this analysis, efforts to reduce the restrictions should be implemented locally via different control policies. It is important that these policies consider the social contacts, population density, and the occupational groups that are specific to each region. [ABSTRACT FROM AUTHOR]

Objectives: Cost-effectiveness analyses (CEA) are based on the value judgment that health outcomes (eg, quantified in quality-adjusted life-years; QALYs) are all equally valuable irrespective of their context. Whereas most published CEAs perform extensive sensitivity analysis on various parameters and assumptions, only rarely is the influence of the QALY-equivalence assumption on cost-effectiveness results investigated. We illustrate how the integration of alternative social value judgments in CEA can be a useful form of sensitivity analysis.Methods: Because varicella-zoster virus (VZV) vaccination affects 2 distinct diseases (varicella zoster and herpes zoster) and likely redistributes infections across different age groups, the program has an important equity dimension. We used a cost-effectiveness model and disentangled the share of direct protection and herd immunity within the total projected QALYs resulting from a 50-year childhood VZV program in the UK. We use the UK population's preferences for QALYs in the vaccine context to revalue QALYs accordingly.Results: Revaluing different types of QALYs for different age groups in line with public preferences leads to a 98% change in the projected net impact of the program. The QALYs gained among children through direct varicella protection become more important, whereas the QALYs lost indirectly through zoster in adults diminish in value. Weighting of vaccine-related side effects made a large difference.Conclusions: Our study shows that a sensitivity analysis in which alternative social value judgments about the value of health outcomes are integrated into CEA of vaccines is relatively straightforward and provides important additional information for decision makers to interpret cost-effectiveness results. [ABSTRACT FROM AUTHOR]

Background: Cannabidiol (CBD) is a novel therapy for the treatment of Lennox-Gastaut Syndrome (LGS), a rare, treatment-refractory epileptic encephalopathy. Two pivotal trials found CBD 20 mg/kg/day conferred a reduction from baseline in median drop seizure frequency of 44% and 42%, respectively, compared with 22% and 17%, respectively, in the usual care arms. No economic evaluations have been published to date. This analysis assessed the cost effectiveness of CBD adjunct therapy compared with usual care alone in LGS from the US payer perspective. Methods: We developed a lifetime horizon Markov decision analytic model. Efficacy, healthcare costs (2020 US$), and health state utilities were ascertained from published clinical trials, retrospective analyses, and time trade-off interviews conducted in the UK, respectively. Fifteen-year-old patients entering the model transitioned to states representing a percentage reduction in drop seizure frequency from baseline, where they remained until reverting back to baseline drop seizure frequency, or death. One-way and probabilistic sensitivity analyses were conducted to evaluate parameter uncertainty, and scenario analyses investigated the impact of various assumptions. Costs and outcomes were discounted at 3%. Results: Compared with usual care alone, CBD yielded 0.7 additional quality-adjusted life-years (QALYs) and $314,900 additional healthcare expenditure, resulting in $451,800 per QALY. Uncertainty in health state utilities were the largest contributor to uncertainty in the results. Results from the 5000-simulation probabilistic sensitivity analysis indicated a 0% chance of CBD being cost effective at a $150,000 per QALY willingness-to-pay threshold, with a 95% credible range for the incremental cost-effectiveness ratio of $325,300–$690,000 per QALY. Conclusion: CBD does not appear to be a cost-effective therapeutic option in LGS patients at a willingness-to-pay threshold of $150,000/QALY. [ABSTRACT FROM AUTHOR]

This paper examines the possible effects of corporate governance (GC) on audit quality (AQ) among the FTSE 350 companies. Using a sample of 180 companies from 2012 to 2017 (i.e. 1080 firm-year observations) a binary logistic model has been employed to investigate the CG-AQ nexus. This analysis was supported by conducting a probit logistic model as a sensitivity analysis. Our findings are associative of a heterogeneous impact of CG on AQ post the implementation of the 2012 CG reforms in the UK. For example, although institutional ownership and management ownership can predict AQ, board independence, non-executive directors and audit committee are not attributed to AQ in the UK. This implies that corporate compliance with good CG practices has a limited impact on the decision to select a Big4 auditor in the UK. Despite the limitations of our study, we hope it can motivate further investigations in this area. [ABSTRACT FROM AUTHOR]

A key contribution to the latest generation of climate projections for the UK (UKCP18) was a perturbed parameter ensemble (PPE) of global coupled models based on HadGEM3-GC3.05. Together with 13 CMIP5 simulations, this PPE provides users with a dataset that samples modelling uncertainty and is ideal for use in impacts studies. Evaluations of global mean surface temperatures for this PPE have shown twenty-first century warming rates consistently at the top end of the CMIP5 range. Here we investigate one potential contributory factor to this lack of spread: that the methodology to select plausible members from a larger, related PPE of atmosphere-only experiments preferentially ruled out those predicted to have more negative climate feedbacks (i.e. lower climate sensitivities). We confirm that this is indeed the case. We show that performance in extratropical long-wave cloud forcing played a key role in this by constraining ice cloud parameters, which in turn constrained the feedback distribution (though causal links are not established). The relatively weak relationship driving this constraint is shown to arise from stronger relationships for the long-wave and short-wave cloud feedback components, which largely cancel out due to changes in tropical high clouds. Moreover, we show that the strength of these constraints is due to a structural bias in extratropical long-wave cloud forcing across the PPE. We discuss how choices made in the methodology to pick the plausible PPE members may result in an overly strong constraint when there is a structural bias and possible improvements to this methodology for the future. [ABSTRACT FROM AUTHOR]

The UK government is committed to reducing carbon dioxide emission levels by 80%, comparative to the 1990 baseline, by 2050. 'Nearly-zero-energy buildings' (nZEBs) were introduced by the Energy Performance Building Directive (recast) in 2010 as a realistic solution to the intrinsic environmental debt associated with most existing buildings. This paper aims to carry out a life-cycle cost (LCC) analysis to identify what is a cost-optimal level and how best to achieve this by examining and focusing on the exploration of realistically applicable energy-efficient measures and retrofit scenarios for a typical UK dwelling. A sensitivity analysis is used to identify uncertainty and provide the expected economic benefits and losses of the applied scenarios over their respective lifetimes. It was established that the total LCCs of all the retrofit scenarios were in fact lower than that of the baseline scenario (i.e. not retrofitting the property) over the 30-year study period. Furthermore, it was found that the cost-optimal level for the retrofit of a typical UK residential dwelling is 75 (kWh/m2)/year; meanwhile, the UK's current nZEB target stands at 44 (kWh/m2)/year, meaning that there is a gap between the current nZEB target and the calculated cost-optimal level. [ABSTRACT FROM AUTHOR]

Although we have known anecdotally that insects have been declining in Great Britain for more than 100 years, insect declines have only been statistically estimated over the last 20 years. Estimation of the rate of those declines is still hotly debated, fuelled by a lack of standardised, systematically collected data.More than 24 million individual moths and aphids collected from 112 light traps and 25 12.2 m suction‐traps, respectively, were analysed using mixed models. Our objective was to estimate the long‐term trends in both groups based on annual totals recorded every year between 1969 and 2016.The models showed that two paradigms existed: Over 47 years, long‐term linear trends showed that moths had declined significantly by −31%, but short‐term trends indicated that there were periods of significant decline and recovery in most decades since the 1960s. Conversely, despite aphid annual totals fluctuating widely, this group was in a steady state over the long‐term, with a non‐significant decline of −7.6%. Sensitivity analysis revealed that moth trends were not driven by a group of abundant species, but the sign of the overall aphid trends may have been driven by three of the most abundant species.The spatial extent of moth trends suggests that they are extremely heterogeneous. Uniquely, moth declines were different among several habitat types, with robust significant declines found in coastal, urban and woodland habitats, but notably not in agricultural, parkland and scrubland habitats. Conversely, aphid trends showed spatial synchrony extending to 338 km, albeit with local variation. [ABSTRACT FROM AUTHOR]

Background: In the CELESTIAL trial for patients with advanced hepatocellular carcinoma (HCC), cabozantinib showed improved survival compared with placebo but comes at a price. We aimed to investigate the cost‐effectiveness of cabozantinib for sorafenib‐resistant HCC from the payer's perspective of the USA, UK and China. Methods: We developed Markov models to simulate the patients pre‐treated with first‐line sorafenib following the CELESTIAL trial. Quality‐adjusted life‐years (QALYs) and incremental cost‐effectiveness ratio (ICER) were calculated for the treatment with cabozantinib or best supportive care. The list price for drugs was acquired from the Red Book, the British National Formulary, West China hospital and reported literature. Adverse events, utilities weights, and transition likelihood between states were sourced from the published randomized phase III trial. A willing‐to‐pay threshold was set $150 000/QALY in the USA, $70 671/QALY (£50 000/QALY) in the UK and $26 481/QALY (3x GDP per capita) in China. Deterministic and probabilistic sensitivity analyses were developed to test the models' uncertainty. Results: In the base case, treatment with cabozantinib increased effectiveness by 0.13 QALYs, resulting in an ICER vs best supportive care of $833 497/QALY in the USA, $304 177/QALY in the UK and $156 437/QALY in China. The models were most sensitive to assumptions about transitions to progression with both cabozantinib and best supportive care, the utility associated with being progression free. These results were robust across a range of scenarios and sensitivity analyses, including deterministic and probabilistic analyses. Conclusions: Cabozantinib at its current cost would not be a cost‐effective treatment option for patients with sorafenib‐resistant HCC from the payer's perspective in the USA, UK or China. Substantial discounts are necessary to meet conventional cost‐effectiveness thresholds. [ABSTRACT FROM AUTHOR]

The initial state sensitivity of high-impact extratropical cyclones over the North Atlantic and United Kingdom is investigated using an adjoint modeling system that includes moist processes. The adjoint analysis indicates that the 48-h forecast of precipitation and high winds associated with the extratropical cyclone "Desmond" was highly sensitive to mesoscale regions of moisture at the initial time. Mesoscale moisture and potential vorticity structures along the poleward edge of an atmospheric river at the initialization time had a large impact on the development of Desmond as demonstrated with precipitation, kinetic energy, and potential vorticity response functions. Adjoint-based optimal perturbations introduced into the initial state exhibit rapidly growing amplitudes through moist energetic processes over the 48-h forecast. The sensitivity manifests as an upshear-tilted structure positioned along the cold and warm fronts. Perturbations introduced into the nonlinear and tangent linear models quickly expand vertically and interact with potential vorticity anomalies in the mid- and upper levels. Analysis of adjoint sensitivity results for the winter 2013/14 show that the moisture sensitivity magnitude at the initial time is well correlated with the kinetic energy error at the 36-h forecast time, which supports the physical significance and importance of the mesoscale regions of high moisture sensitivities. [ABSTRACT FROM AUTHOR]

Numerical weather models such as weather research and forecasting (WRF) are increasingly used in studies on water resources. However, they have suffered from relatively poor performance in rainfall estimation. Among the various influential factors, a critical parameter in the WRF model rainfall retrieval is raindrop size distribution (DSD), which has not been fully explored. The analysis of sensitivity and uncertainty of the DSD model accuracy is significant for rainfall forecasts based on mesoscale numerical weather prediction (NWP) models. A WRF-disdrometer integrated error assessment framework is developed to analyze the accuracy and sensitivity of DSD parameterizations of gamma distribution in WRF rainfall simulation. This study adopts three different microphysics parameterizations (Morrison, WDM6, and Thompson aerosol-aware) to simulate the DSD of approximately 100 rainfall events in Chilbolton, UK that are categorized into 12 scenarios based on the season, rainfall evenness, and rainfall rate. The Thompson aerosol-aware microphysics scheme shows the best performance among the three. In comparisons of WRF rainfall simulations across different scenarios of evenness and rainfall rate, a higher accuracy is obtained with more even rain and a higher rainfall rate. The sensitivity results of different DSD parameterizations indicate that the sensitivity to the intercept parameter N 0 is pronouncedly higher than those to the shape parameter μ and slope parameter λ for all studied schemes. The overall WRF rainfall shows a trend of slight underestimation followed by overestimation as μ increases; further, the rainfall is overestimated when log 10 N 0 or λ decreases and is underestimated when it increases and then remains constant. Comparisons of different scenarios reveal that variations of DSD parameters of even rain have a relatively high impact on rainfall recognizability, and the DSD parameterizations show a higher sensitivity for rainfall with a low rate. Moreover, the sensitivity discrimination is not clear among the rainfall of different seasons. The uncertainty assessment of the WRF rainfall retrieval caused by the shape parameter suggests that a gamma DSD model with a variable shape parameter should be developed according to the evenness, rainfall rate, and microphysics parameterizations by using the WRF model. Some modified algorithms of the WRF gamma DSD model for achieving better accuracy in WRF rainfall retrievals will be explored in future studies with various climatic regimes by adjusting the DSD parameterization based on the assimilation of measured data. • A higher accuracy of WRF rainfall simulation is obtained with more even rain and a higher rainfall rate. • The sensitivity to the intercept parameter N 0 is obviously higher than those to the shape parameter μ and slope parameter λ. • The DSD parameterizations show a higher sensitivity for the precipitation with a low rate. • A gamma DSD model with a variable shape parameter should be developed by using the WRF model. [ABSTRACT FROM AUTHOR]

• We use exploratory modelling to address uncertainty of transitions in the UK's mobility sector using the MATISSE model. • This allows the behaviour of complex, non-linear transitions to be mapped out. • Our analysis shows transitions to a public transport mobility regime in the UK. • Exploratory modelling enables the systematic analysis of stochastic behavioural changes. Modelling is an important approach for analysing the behaviour of sustainability transitions. However, the presence of uncertainty challenges the usefulness of models and our inference from model results. We use the example of the MATISSE agent-based model to examine conditions for a transition to a public transport mobility regime under uncertainty in the UK. We use 'exploratory modellingö to investigate the regions of model uncertainty in a structured way. Model results are generated from a wider range of input values compared to that applied normally in transitions modelling. A stochastic description of the pathways of adoption of different mobility lifestyles is developed. Our approach identifies possible transition pathways under an uncertain future in response to ranges of behavioural changes of households. A sensitivity analysis over the critical behavioural parameters also shows how the interactions between households and mobility lifestyle niches are determined by the dynamics of household behaviours. [ABSTRACT FROM AUTHOR]

Limiting the global temperatures to +1.5 °C from pre-industrial levels requires achieving net-zero greenhouse gas emissions by 2050. This should be achieved across all sectors, and for electrical and electronic equipment (EEE) the promotion of repair, lifetime extension and other Circular Economy (CE) strategies are often proposed as the main areas for intervention. However, few studies have quantified and compared the effectiveness of different CE strategies at reducing emissions at a national level and into the future. To fill this gap, an extended dynamic stock model was combined with a device energy consumption model to anticipate the embodied, operational, and repair energy requirements arising from the stocks and flows of seven devices up to 2050 in the United Kingdom (UK). To understand the relative influence of all model inputs on device energy demand in 2050, a variance-based sensitivity analysis was performed using the Sobol method. The results show that device size is the most significant variable for six out of the seven devices. Whereas substantial increases in device lifetime and repair rates were shown not to be significant in reducing energy demand. A reduction of 30% of energy demand by 2050 is possible for almost all EEE devices, except laptops and TVs. However, delivering these savings requires significant changes to consumption behaviours such as decreasing device size by about 40% or decreasing ownership rates by approximately two thirds through shared ownership. This analysis prioritises the most impactful strategies to reduce the total energy demand of EEE in the UK. • Impacts of various strategies are tested for seven household electronics. • The influence of these strategies on future energy demand is quantified. • Device size is a significant lever across most devices to reduce energy demand. • Operational efficiency should be prioritised for white goods. [ABSTRACT FROM AUTHOR]

The article discusses research which investigated how tumor necrosis factor inhibitor (TNFi) therapy influenced need for total hip and total knee replacement procedures in patients with rheumatoid arthritis (RA). Topics explored include the clinical characteristics, progression, and risk factors for RA, comparison of outcomes from TNFi and conventional synthetic disease-modifying antirheumatic drugs (DMARD) administration, and the reduction in total hip replacement in older patients.

Seismic data made available by the UK OGA (Oil & Gas Authority) has been used to constrain a model of crustal structure and heat-flow history for the UK Rockall Basin. Top basement/base sediment has been interpreted around the full extent of the seismic dataset. This has produced a model for the thickness of the sediment fill within the basin which is thicker than previous published estimates. The new sediment-thickness model has been incorporated into a 3D backstripping study, producing maps of subsidence and thinning factor. Analysis of backstripped subsidence shows the thinning factor reaching peak values of c. 0.8-0.85 (β factor >5) in the south-central axial area, reducing in magnitude northwards to c. 0.7. The new sediment-thickness model has also been incorporated into a 3D gravity-inversion study, mapping Moho depth, crustal thickness and thinning/stretching factor. The results show crustal-basement thickness reduced to c. 6 km, thinning factor c. 0.8, in the south-central area, while it spans the range c. 6-10 km further north. The results are compatible with previous seismic refraction work in both the UK and Irish sectors of the Rockall Basin.We believe that the extension which created the basin was non-magmatic and that the axial region is underlain by highly-thinned continental crust. The results from the gravity inversion have been used to make predictions about the top-basement heat-flow history. Heat flow in the basin centre is predicted to have been initially high, reducing with time, associated with cooling of the transient synrift heat-flow anomaly. On the basin flanks heat flow was less variable over time, its magnitude controlled primarily by constant radiogenic heat input from the basement, rather than by the transient geotherm anomaly. There remain considerable uncertainties associated with our interpretation and analysis. These uncertainties have been addressed with sensitivity analyses. A regional gravity-inversion model, using the new sediment-thickness data spliced into regional public-domain information, shows that structural and stretching continuity can be mapped at the crustal scale along the full length of the UK/Irish Rockall Basin, contrary to conclusions from some previous studies. [ABSTRACT FROM AUTHOR]

Abstract In order to reduce the cost of energy per MWh in wind energy sector and support investment decisions, an optimisation methodology is developed and applied on Round 3 offshore zones, which are specific sites released by the Crown Estate for offshore wind farm deployments, and for each zone individually in the UK. The 8-objective optimisation problem includes five techno-economic Life Cycle Cost factors that are directly linked to the physical aspects of each location, where three different wind farm layouts and four types of turbines are considered. Optimal trade-offs are revealed by using NSGA II and sensitivity analysis is conducted for deeper insight for both industrial and policy-making purposes. Four optimum solutions were discovered in the range between £1.6 and £1.8 billion; the areas of Seagreen Alpha, East Anglia One and Hornsea Project One. The highly complex nature of the decision variables and their interdependencies were revealed, where the combinations of site-layout and site-turbine size captured above 20% of total Sobol indices in total cost. The proposed framework could also be applied to other sectors in order to increase investment confidence. Highlights • Four optimal solutions were found between £1.6 and £1.8 billion of the total cost. • Norfolk Boreas includes the highest total costs per MW. • High-order interdependencies of more than two variables govern problem's complexity. • Site-layout & site-turbine size account for 20% of the variability in expenditures. [ABSTRACT FROM AUTHOR]

Energy systems modellers often resort to simplified system representations and deterministic model formulations (i.e. , not considering uncertainty) to preserve computational tractability. However, reduced levels of detail and neglected uncertainties can both lead to sub-optimal system designs. Herein, we present a novel method that quantitatively compares the impact of detail and uncertainty to guide model development and help prioritisation of the limited computational resources. By considering modelling choices as an additional 'uncertain' parameter in a global sensitivity analysis, the method determines their qualitative ranking against conventional input parameters. As a case study, the method is applied to a peer-reviewed heat decarbonisation model for the United Kingdom with the objective of assessing the importance of spatial resolution. The results show that while for the optimal total system cost the impact of spatial resolution is negligible, it is the most important factor determining the capacities of electricity, gas and heat networks. • Quantitative method to define the appropriate level of detail in energy models. • Global sensitivity analysis method to compare the importance of detail vs uncertainty. • Data: uncertainty ranges are derived for key parameters of the UK energy system. • Application to a heat decarbonisation model to study the impact of spatial resolution. • Spatial resolution does not impact total cost but is important for system design. [ABSTRACT FROM AUTHOR]

Agricultural soils are the primary source of nitrous oxide emissions due to management practices including fertiliser application. While fertiliser rates are one of the main drivers of nitrous oxide emissions, emissions are also dependent on other variables such as climate and soil properties. To understand the spatial and inter-annual variations in emission rate, simulations of N 2 O emissions were made from 2000 to 2010 for UK grass and croplands. In addition, the sensitivity of these emissions to soil and climate inputs was also tested. Emissions of between 0.3 to 3.5 kg N ha −1 yr −1 and 0.7–7 kg N ha −1 yr −1 were simulated across UK croplands and grasslands, respectively. While inter-annual variations can be attributed to climate influences, the primary driver of spatial variations in emissions was soil clay content. However, when the sensitivity of nitrous oxide emissions to soil clay content alone was tested, it was not always the best predictor of emissions, when soil texture is altered outside of the normal range used as inputs to the model from different databases. [ABSTRACT FROM AUTHOR]

We explore the sensitivity of time varying confounding adjusted estimates to different dropout mechanisms. We extend the Heckman correction to two time points and explore selection models to investigate situations where the dropout process is driven by unobserved variables and the outcome respectively. The analysis is embedded in a Bayesian framework which provides several advantages. These include fitting a hierarchical structure to processes that repeat over time and avoiding exclusion restrictions in the case of the Heckman correction. We adopt the decision theoretic approach to causal inference which makes explicit the no-regime-dropout dependence assumption. We apply our methods to data from the 'Counterweight programme' pilot: a UK protocol to address obesity in primary care. A simulation study is also implemented. [ABSTRACT FROM AUTHOR]