Non-Unique Machine Learning Mapping in Data-Driven Reynolds Averaged Turbulence Models

Recent growing interest in using machine learning for turbulence modelling has led to many proposed data-driven turbulence models in the literature. However, most of these models have not been developed with overcoming non-unique mapping (NUM) in mind, which is a significant source of training and prediction error. Only NUM caused by one-dimensional channel flow data has been well studied in the literature, despite most data-driven models having been trained on two-dimensional flow data. The present work aims to be the first detailed investigation on NUM caused by two-dimensional flows. A method for quantifying NUM is proposed and demonstrated on data from a flow over periodic hills, and an impinging jet. The former is a wall-bounded separated flow, and the latter is a shear flow containing stagnation and recirculation. This work confirms that data from two-dimensional flows can cause NUM in data-driven turbulence models with the commonly used invariant inputs. This finding was verified with both cases, which contain different flow phenomena, hence showing that NUM is not limited to specific flow physics. Furthermore, the proposed method revealed that regions containing low strain and rotation or near pure shear cause the majority of NUM in both cases - approximately 76% and 89% in the flow over periodic hills and impinging jet, respectively. These results led to viscosity ratio being selected as a supplementary input variable (SIV), demonstrating that SIVs can reduce NUM caused by data from two-dimensional flows

Building energy consumption prediction for campus accommodation buildings based on spatial temporal graph convolution networks

The Net Zero Building (NZB) strategy has been regarded as the fundamental pathway to achieve sustainable cities and communities and to amend climate change. This necessitates an accurate understanding of the energy consumption of buildings which serves as a baseline reference for any energy planning or building retrofit. Artificial Intelligence (AI) approaches have been well documented in predicting energy consumption of buildings with credits of accuracy and efficiency. However, most of the studies focused on a single building which ignored or overlooked the interdependencies of buildings, especially for those buildings with the same group of users such as educational campuses where students and university staffs usually share the facilities and infrastructures across buildings. Predicting energy consumption independently significantly affects the accuracy of AI models. To fill this research gap, this study proposes a spatial-temporal graph convolutional network (STGCN) algorithm to predict the hourly energy consumption of campus buildings in northern England. To evaluate the feasibility of the STGCN algorithm, several popular AI algorithms were also employed for comparison. The results indicated that STGCN can significantly improve the prediction performance that conventional machine learning algorithms

Effects of higher-than-expected control population allele frequency on classification of loss-of-function variants in cancer susceptibility genes

A query was sent to the cancer predisposition gene variant database Cancer Variant Interpretation Group UK, on the nonsense variant in NM_032043.3( BRIP1):c.2392C&gt;T,p.(Arg798Ter). The submitter classified this as a variant of uncertain significance, providing very strong variant effect evidence with the intention of adding supporting pedigree information, according to the guidelines used for classification. However, the relatively high population frequency in the UKB cohort of 367/439 920 (0.083%) was a concern as it is higher than expected for the disease frequency, which would reduce the predicted pathogenicity score. This situation highlights the increasing concerns over the use of population data in pathogenicity classification of truncating/loss-of-function (LoF) variants in known cancer predisposition genes, particularly since the addition of UKB control data. Here, we have conducted a series of case-control comparisons for common truncating variants in known breast/ovarian cancer-associated genes, as well as LZTR1-related schwannomatosis, to address this issue using our Manchester cancer screening population compared with controls in UKB data.Our data show strong ORs for these common truncating variants. We propose that for truncating variants in cancer susceptibility genes with a significant case-control OR, apparently conflicting population frequency evidence criteria should be avoided. </p

A novel classifier of radiographic knee osteoarthritis for use on knee DXA images is predictive of joint replacement in UK Biobank

ObjectivesDXA scans may offer a novel means of evaluating radiographic knee OA (rKOA) in large population studies and through opportunistic screening. We aimed to develop and apply a semi-automated method for assessing rKOA using ≈20 000 knee DXA images from UK Biobank (UKB) and assess its face validity by checking for expected relationships with clinical outcomes.MethodsRight knee DXA scans were manually annotated for osteophytes to derive corresponding grades. Joint space narrowing (JSN) grades in the medial joint compartment were determined from automatically measured minimum joint space width. Overall rKOA grade (0–4) was determined by combining osteophyte and JSN grades. Logistic regression was employed to investigate the associations of osteophyte, JSN and rKOA grades with knee pain and hospital-diagnosed KOA. Cox proportional hazards modelling was used to examine the associations of these variables with risk of subsequent total knee replacement (TKR).ResultsOf the 19 595 participants included (mean age 63.7 years), 19.5% had rKOA grade ≥1 (26.1% female, 12.5% male). Grade ≥1 osteophytes and grade ≥1 JSN were associated with knee pain, hospital-diagnosed KOA and TKR. Higher rKOA grades were linked to stronger associations with these clinical outcomes, with the most pronounced effects observed for TKR. Hazard ratios for the association of rKOA grades with TKR were 3.28, 8.75 and 28.63 for grades 1, 2 and 3–4, respectively.ConclusionsOur DXA-derived measure of rKOA demonstrated a progressive relationship with clinical outcomes. These findings support the use of DXA for classifying rKOA in large epidemiological studies and in future population-based screening

Deccan Volcanic Province volatile data compilation

This is a supplementary file to the Journal of Volcanology and Geothermal Research review article on Volatile Emissions from Deccan Volcanic Eruptions and their Effects on Climate across the K-Pg Boundary. This document hosts the updated compilation of literature data on the volatile content of the Deccan Traps magmas (Capriolo et al., 2024; Callegaro et al., 2023; Choudhary et al., 2019; Hernandez Nava et al., 2021; Sano, 2001; Self et al., 2008). The melt inclusion analysis has been carried out using several techniques, including NanoSIMS, Raman Spectroscopy, EPMA and FTIR. The majority of the analysed inclusions preserved in olivine, plagioclase and clinopyroxene phenocrysts and glomerocrysts form different lava flows that erupted across the Cretaceous-Paleogene (K-Pg) boundary 66 million years ago were glassy (Hernandez Nava et al., 2021; Sano, 2001; Self et al., 2008), with some being partially rehomogenised (Choudhary et al., 2019). CO2 concentration in the melt is also calculated using the CO2 density in the vapour bubble using Raman Spectroscopy and bubble volume fraction in melt inclusions (Capriolo et al., 2024; Hernandez Nava et al., 2021). This spreadsheet further contains the formation-specific melt S and F content data calculated based on experimentally derived clinopyroxene-equilibrium melt partitioning (Callegaro et al., 2023). This dataset intends to highlight the gaps in our current knowledge of volatile content measurements in Deccan magmas across the K-Pg boundary

Management of Small Testicular Masses:A Delphi Consensus Study

BACKGROUND AND OBJECTIVE: The majority of small testicular masses (STMs) are benign and therefore radical orchidectomy (RO) may represent overtreatment. In appropriately selected patients, surveillance or testis-sparing surgery (TSS) is an alternative option to preserve testicular function. Since there are no clear guidelines, we aimed to develop consensus recommendations on the management of STMs.METHODS: A four-round Delphi study was conducted by 24 experts representing multiple subspecialties to reach consensus. Consensus was defined as ≥75% of the participants scoring within the same 3-point grouping (1-3, disagree; 4-6, uncertain; 7-9, agree.). The first two rounds were survey based, the third round was an online meeting to discuss uncertainties from the first two rounds, and the fourth round was a review of the final consensus statements from rounds 1-3.KEY FINDINGS AND LIMITATIONS: The initial survey consisted of 126 statements. Following the four rounds of assessment, a list of 96 statements were produced, which focused on clinical and biochemical assessment, colour Doppler ultrasound (CDUS) characteristics, and management options including surveillance, RO, and TSS. Management should be personalised according to risk factors for testicular cancer, fertility status, uni- or bilateral tumours, status of the contralateral testis, and CDUS characteristics, with solid lesions displaying vascularity and hypoechogenicity being more suspicious for malignancy. The consensus statements are prone to a bias, and some may not reflect robust, randomised evidence.CONCLUSIONS AND CLINICAL IMPLICATIONS: The expert panel has produced consensus recommendations on the management of STMs, and TSS should be considered in patients with an STM. The recommendations could aid in the dissemination of best practice.PATIENT SUMMARY: There are no clear guidelines on the management of small testicular masses. Excising the whole testicle (radical orchidectomy) with a small or an indeterminate mass may affect fertility and hormonal function. A panel of experts was formed, and consensus recommendations were developed on how to deal with small and indeterminate testicular masses, which include surveillance or testis-sparing surgery.</p

¹⁰Be evidence for extensive, low-elevation Late Pleistocene glaciation in far eastern (Arunachal) Himalayas - timing and palaeoclimate reconstruction

The glacial history of the eastern Himalayas has remained undocumented compared to its western and central regions. In this study, we present 63 Be-10 exposure ages from glacial deposits in the Dri Valley, situated at the eastern extremity of the Himalayas, to reconstruct the first Pleistocene glaciation history of the ~900 km long Arunachal Himalayas. The most extensive glaciation occurred before ~48 ka (and possibly earlier than ~58 ka), when the (inferred) trunk glacier reached 100 km in length and descended to around 1500 to 1300 m above sea level (a.s.l) – among the lowest elevations recorded for glaciers in the Himalayan-Tibetan Orogen. The main valley glacier remained substantial during the Last (Global) Glacial Maximum (LGM) and had a length of ~76 km and terminated around 1680 m a.s.l. Despite dense forest cover, paraglacial and postglacial erosion obscuring (prominent) glacial landforms in the Dri Valley, an integrated approach combining geomorphological evidence and high-resolution satellite imagery with cosmogenic-based geochronological data has enabled a detailed reconstruction of its Pleistocene glaciation. Glacial deposits covering elevations from 3700 to 1600 m a.s.l were subdivided based on morphostratigraphy, revealing four periods of postglacial exposure dating to ≥58 ka, ~48 ka, ~19 ka and ~13 ka. The results indicate that the Dri Valley cirques (elevations ~3700 to ~3800 m a.s.l) became ice free between ~14 – 13 ka. Reconstruction of the cirque glacier yields an equilibrium line altitude (ELA) of approximately 3750 m, corresponding to a ∆ELA of ~900 m compared to today which is among the largest ELA depressions in the Himalayas for this period (~14 ka to present). Our findings reveal that Late Quaternary glaciation in the Dri Valley was primarily temperature-driven, influenced by long-term orbital forcing. With approximately 90% of the region’s abundant annual precipitation today occurring in summer, a positive mass balance for the Dri glacier is maintained up to a temperature-sensitive threshold. Beyond this threshold, even minimal warming would have caused glacier retreat (or collapse) due to a larger percentage of the summer precipitation falling as rain rather than snow, reducing the glacier’s accumulation. This is reflected in the termination of Dri Valley glacial phases correlating with known regional warm periods. This study offers critical insights into the climate-glacier interactions in the understudied eastern Himalayas and enhances our understanding of broader Himalayan-Tibetan palaeoclimate

Imposter participants?:Towards a reflexive epistemology of ‘suspected participants’

There is an increased reliance, since COVID-19, on online methods in qualitative research for participant recruitment and data collection. While online methods have some clear advantages, they have also raised ‘new’ concerns about fraudulent participation in qualitative research that can hamper research rigour. Drawing on a case study of two of our own UK-based projects which investigated intersections of health, sexuality, and social connections during and after the COVID-19 pandemic, this paper critically examines the challenges posed by terms like "imposter” and “fraudulent” participants and suggests instead the use of "suspected participants" to acknowledge the researchers' role in judging if participants are authentic or not. We argue for a reflexive epistemology that questions normative assumptions about authentic participation and advocate an inclusive but separate analysis of suspect data as an interpretive tool that ca enhance rigour, rather rejecting such data as a problem that needs ‘screening out’. <br/