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Surface nuclear magnetic resonance (NMR) is a unique technique to study groundwater, as it provides direct insights into water content and pore-scale properties. However, surface NMR suffers from an extremely weak signal that limits mapping speeds and can prohibit measurements in high ambient noise environments. It has recently been demonstrated that steady-state sequences can deliver orders of magnitude signal-to-noise ratio (S/N) enhancement in comparison with standard methods. Most notably, the steady-state approach collapses the surface NMR signal into an extremely narrow frequency band, which leads to vastly improved noise rejection. In this article, we develop the signal processing chain for steady-state surface NMR data. Each step in the signal processing chain, transient culling, pulse windowing, de-spiking, powerline harmonics subtraction, and spectral analysis are explained in detail. We demonstrate how error estimation can be efficiently performed using the power spectral density in the vicinity of the transmitting frequency. We also demonstrate how off-resonance excitation can be determined by locating the peak spectrum of surface NMR signal with an array of phase-corrected discrete Fourier transforms (DFTs). The presented signal processing methods can be easily implemented and applied to extract signal features for quality control and inversion procedures. We give a field example where data collected with steady-state pulse sequences are processed and inverted.

In efforts to map water at depth, steady-state free precession (SSFP) sequences promise to rapidly increase data acquisition rates in the practice of surface nuclear magnetic resonance (NMR). Unlike conventional surface NMR excitation schemes, pulses in SSFP are transmitted so frequently that the nuclear magnetization of hydrogen in water cannot return to its natural alignment with the Earth’s ambient magnetic field, and instead achieve a steady-state; a dynamic equilibrium between pulses. Unfortunately, the traditional formulations of SSFP sequences and the full surface NMR forward models are not immediately compatible with each other. First, the traditional analysis of SSFP sequences assumes that relaxation during pulse (RDP) effects is negligible, which is not always valid in surface NMR. Second, even for single-pulse measurement, the surface NMR forward model can be computationally demanding; this challenge scales with the number of pulses. Here, we investigate the incorporation of RDP effects on the dynamic equilibrium of SSFP measurement. This is then incorporated into the full surface NMR forward model by deriving the analytical expressions to directly predict processed surface NMR data. The model is validated by jointly inverting an extensive and diverse suite of SSFP measurement, 12 distinct sequences each with 16 pulse moments. The inverted model has a data misfit of 0.99 and is consistent with models derived from standard NMR data. The ability of our forward model to reproduce diverse signals and jointly invert them is a strong indication of its validity.

Poems.

To scrutinize georgic’s position between progress and tradition, this article will focus on the way those forces become legible in poems composed between the end of the First and Second World Wars. I will examine Vita Sackville-West’s long georgics “The Land” (1926) and The Garden (1946) to argue that they indicate the scope of what is possible in the genre given the challenges of both modernity and modernism. Her poems demonstrate that, in seeking to navigate the changing material and cultural landscapes, the labour of maintaining an imaginative tradition can be both productive and problematic. The article will assess the way Sackville-West positions herself as a writer in relation to the figures of the agricultural labourer and gardener and to the classical tradition, as well as her claims about the language in which georgic can and should be written. Each poem will also be compared to the poetry and criticism of her modernist contemporary T.S. Eliot, with particular reference to “The Waste Land, Four Quartets” and his essay “Tradition and the Individual Talent.” Engaged in a struggle on both agricultural and cultural fronts, “The Land” and “The Garden” are prone to inconsistency and, even by their own standards, failure. But in these failures as well as their successes both poems are committed to finding a way of writing human engagement with the land and literature. As such, they can be instructively read in the present moment to prompt questions about the way we engage with land and language in the Anthropocene, negotiating between competing modes of writing and more broadly between natural and human agency., Para examinar la posición geórgica entre el progreso y la tradición, este artículo se centrará en cómo esas fuerzas se hacen legibles en poemas compuestos entre el final de la Primera y la Segunda Guerra Mundial. Examinaré los largos geórgicos de Vita Sackville-West, “The Land” (1926) y “The Garden” (1946) para argumentar su lugar en el género ante los desafíos, tanto de la modernidad como del modernismo. Sus poemas demuestran que, al navegar por un paisaje cambiante, tanto material como cultural, la labor de mantener una tradición imaginativa es a la vez productiva y problemática. El artículo evaluará cómo Sackville-West se posiciona como escritora en relación con las figuras del trabajador agrícola y el jardinero y con la tradición clásica, así como sus declaraciones sobre el lenguaje en el que el geórgico puede y debe escribirse. Cada poema se comparará también con la poesía y la crítica de su contemporáneo modernista T.S. Eliot, con especial referencia a “The Waste Land, Four Quartets” y su ensayo “Tradition and the Individual Talent”. Comprometidos en un doble frente, agrícola y cultural, “The Land” and “The Garden” tienden a la inconsistencia e, incluso para sus propios estándares, al fracaso. Pero tanto en estos fracasos como en sus éxitos, ambos poemas se comprometen a encontrar una forma de escribir el compromiso humano con la tierra y la literatura. Como tales, pueden leerse de manera instructiva en el momento presente para plantear preguntas sobre cómo nos relacionamos con la tierra y el lenguaje en el Antropoceno, negociando entre modos de escritura que compiten entre sí y, más ampliamente, entre la agencialidad natural y la humana.

Summary Background Electrosurgery makes dissection with simultaneous haemostasis possible. The produced heat can cause injury to the surrounding tissue. The PEAK PlasmaBlade™(PPB) is a new electrosurgery device which may overcome this by having the ability to operate on a lower temperature, therefore reducing collateral thermal damage. Method A single-centre, double-blinded, randomised controlled trial (RCT) was conducted which included 108 abdominal-based free-flap breast reconstruction patients who had their flap raise performed using either the PPB (n = 56) or the conventional diathermy (n = 52). Data were collected during their in-patient stay and out-patient appointments. The primary outcome value was the number of days the abdominal drains were required. Results Baseline characteristics were similar between the groups, except a significantly lower flap weight in the PPB group. The median number of days the drains were required did not differ significantly (p = 0.48; 6.0 days for the diathermy and 5.0 days for the PPB). The total drain output (p = 0.68), the inflammatory cytokine in the drain fluid (p>0.054) and complications (p>0.24) did not differ significantly between the two groups. At the 2-week follow-up appointment, there was a trend towards less abdominal seromas on abdominal ultrasound (p = 0.09) in the PPB group which were significantly smaller (p = 0.04). Conclusion The use of the PPB did not result in a significant reduction of drain requirement, total drain output or inflammatory cytokines but did reduce the size of seroma collections at the 2-week follow-up appointment. Therefore, the use of the PPB device could reduce early seroma formation after drain removal.

This article explores the way that the practices of copy-editing technical journals, composing poetry, and ecocritical research can complement one another, drawing on individual professional, creative, and academic experience. It reports on an exercise devised to generate material for a poem by collating edits from technical copy, and works through this to compose a piece based on the UK government’s 2018 environment plan. Critical reflections are then offered on the resultant text and the value of the process, with some proposals for further application.

Background: Histopathology assessments of cancers require highly skilled pathologists, are labor intensive and prone to errors without proper training or fatigue. Machine learning can assist pathologists by increasing efficiency and minimizing individual variability. This study adapted a deep learning model to reliably identify 3 cell types from triple negative breast cancers fixed on H&E slides and verified performance with an expert pathologist. Methods: We apply the U-Net architecture to analyse pathology slides fixed with triple negative breast cancer (TNBC) tissue. The public dataset NuCLS was used for training. Semantic segmentation was used to identify single cells of 3 types: tumor cells, fibroblasts, and tumor infiltrating lymphocyte (TILs). For validation, the pathologist annotated 8 random H&E tiles. The 3 cell types accuracy for NuCLS and the model was evaluated by our pathologist. Results: Overall, there was a 73% agreement with the pathologists (Pathologist vs. NuCLS). A set of 1,555 (90%) TNBC slides were used for training and 173 for validation (10%; unseen data). Table 1 outlines the accuracy metrics for each cell type and for each comparison. Compared to our pathologist, the model accurately identified TILs (62%), followed by fibroblasts (42%) and lastly tumor cells (26%). A significant source of discrepancy was variation in labeled single cell boundaries. The model was better at identifying TILs. The pathologist took 1.5 hours to annotate 8 tiles for the 3 cells and our model 644ms. Conclusion: It is possible to develop a deep learning model to identify breast cancer cells, fibroblasts and TILs from H&E stained slides, with similar accuracy levels as a trained pathologist. The model performed better than a pathologist in identifying TILs, but both struggled with fibroblasts. Accuracy of 71% overall and 87% for TILs, motivates expansion to further datasets and other cancer types. Table 1. - Accuracy metrics. Quality assessment8 H&E tiles Pathologist vs. NuCLS U-Net model vs. NuCLs U-Net model vs. Pathologist U-Net model vs. NuCLs (Full) Background 86% 71% 62% 73% Tumour 43% 35% 26% 71% Fibroblast 45% 39% 42% 31% TILs 34% 96% 62% 87% Overall 73% 74% 61% 71% Citation Format: Luiz Augusto Zillmann da Silva, Alistair R. Williams, Aidan Kubeyev, Andrea Giorni, Jordan Laurie, Prabu Sivasubramaniam, Matthew Foster, Matthew Griffiths, Uzma Asghar. A deep learning approach (AI) which accurately identifies breast tumor cells, tumor infiltrating lymphocytes (TILS) and fibroblasts from H&E slides. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5424.

Background: Accurate modelling of the impact of patient-specific features and cancer treatments on survival allows the assignment of targeted therapy. There has not been any effort to build a multi-source model for the survival analysis of breast cancer. We show in this study a prognostic model, which integrates genetic (DNA), clinical and therapy inputs to predict survival for early breast cancer (stages 1-3) for all breast cancer subtypes. Methods: We used a data-driven Random Survival Forest approach, a statistical non-parametric ensemble learning method, that incorporates censor and time-to-event data. The learning is performed by creating numerous decision trees and selecting the model based on the correct responses in unseen data. We used The Cancer Genome Atlas Breast Cancer (TCGA) dataset and observed improvements in the accuracy when more sources of data were used, in line with the previous research. Integrating the impact of non-silent somatic tumor mutations (whole exome) and gene copy number variation (CNV) were analyzed on all mutations and per particular mutation. Results: Data from 1096 women with stage 1-3 early breast cancer were inputs to the model n=437 ER+ve HER2-ve, n=123 HER2+ve ER+ve, n=40 HER2+ ER-ve and n=126 TNBC. Pathological stage 1, n=183; stage 2, n=620; and stage 3, n=249. The following chemotherapy and hormonal treatments were used in the analysis: anthracycline, taxanes, platinum, alkylating and anti-metabolite agents, anti-oestrogen, aromatase inhibitors, ovarian suppression and HER2 antibody treatment. The model accuracy for predicting survival for early breast cancer using only clinical data was 0.78 for Area Under Curve (AUC) and c-index. The predictive accuracy improved stepwise by adding hormone, genetic and treatment data to AUC of 0.86 and c-index to 0.85. We observed the same trend if the proportion of test data increased from 0.25 to 0.75. Changes in median genes FGFR2 and CDKN2A copy number were strongly prognostic with p=0.0001 and p=0.002, and weaker signals for CBFB p=0.05, HRAS p=0.06, AKT p=0.07. Conclusion: Using public datasets, we developed a predictive survival model for an individual with early breast cancer up to 5 years from diagnosis using multi-source and patient-specific data. We show that using this approach for survival analysis yields good accuracy. Citation Format: Aidan (Amanzhol) Kubeyev, Andrea Giorni, Prabu Siva, Luiz Silva, Jordan Laurie, Matthew Foster, Matthew Griffiths, Uzma Asghar. A prognostic machine learning model for early breast cancer which combines clinical and genetic data in patients treated with neo/adjuvant chemotherapy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5696.

Background: Predicting tissue of origin (ToO) using clinical and molecular data improves diagnostic accuracy up to 95% in patients with Cancer of Unknown Primary (CUP). It is hypothesized that better treatment stratification of CUP patients using omics and machine learning (ML) classifiers may improve prognosis. Methods: We used publicly available whole exome somatic mutation data from 4733 primary solid tissue samples, across 11 tumor types from the TCGA database, and employed a ML classifier to predict their ToO. We used 5 sets of modeling features: 1) Non-silent somatic mutation burden of 230 cancer-related genes 2) Frequency of SNP substitution type 3) Trinucleotide mutation frequency 4) Copy number variation of the 230 cancer-related genes 5) Presence of hotspot mutations. We trained a Support Vector Machine on a training subset (80% of samples) and tuned the hyperparameters maximizing a 5-fold cross-validation F1-score. We then tested the model performance on a validation subset (20% of samples) and on a limited (n=6) dataset of metastatic samples present in the TCGA database. Results: On the primary tumor validation set, we achieved an average AUC of 0.98(std: 0.02) and top 1, top 2 and top 3 accuracies of 80%(std: 0.11), 90%(std: 0.08) and 95%(std: 0.04) respectively, across 11 tumor types. The classification accuracy plateaus after ~300 samples, suggesting further data collection may benefit low performing tumor types. The 2 worst performers: esophageal and stomach cancers were mostly misclassified with colorectal cancers, reflecting their relative similarity. On metastatic samples (n=6) the model achieved a 67% accuracy, this is work in progress. Conclusion: Our study confirms the potential for a DNA-based machine learning approach to improve prognosis in CUP patients by aiding diagnosis of ToO. To this end, we plan to take this study further by applying this approach to large, independent datasets derived from metastatic samples and liquid biopsies from CUP patient cohorts. Table 1. Top_1_acc Top_2_acc Top_3_acc Precision Recall F1_score Training_size Breast 0.88 0.97 0.99 0.88 0.84 0.86 756 Colorectal 0.85 0.97 0.98 0.83 0.83 0.83 460 Oesophagus 0.5 0.75 0.89 0.51 0.5 0.51 144 Liver 0.83 0.92 0.96 0.82 0.89 0.85 288 Lung 0.86 0.91 0.94 0.98 0.81 0.88 396 Ovary 0.87 0.94 0.97 0.77 0.9 0.83 312 Pancreas 0.73 0.79 0.85 0.62 0.7 0.66 132 Prostate 0.88 0.94 0.98 0.75 0.88 0.81 380 Sarcoma 0.78 0.84 0.96 0.8 0.82 0.81 180 Stomach 0.73 0.91 0.95 0.68 0.58 0.62 340 Endometrial 0.9 0.97 0.99 0.86 0.87 0.87 400 Mean 80.09% 90.09% 95.09% 0.77 0.78 0.78 344 Top_1_acc_n Top_2_acc_n Top_3_acc_n n samples Metastatic breast 2 2 2 2 Metastatic prostate 0 0 0 1 Metastatic pancreas 0 0 0 1 Metastatic sarcoma 1 1 1 1 Metastatic oesophagus 1 1 1 1 Mean accuracy 67% 67% 67% Citation Format: Andrea Giorni, Prabu Sivasubramiam, Aidan Kubeyev, Jordan Laurie, Luiz Silva, Matthew Foster, Uzma Asghar, Matthew Griffiths. Using machine learning to predict tissue of origin from somatic mutation features. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5429.

We review Skilling's nested sampling (NS) algorithm for Bayesian inference and more broadly multi-dimensional integration. After recapitulating the principles of NS, we survey developments in implementing efficient NS algorithms in practice in high-dimensions, including methods for sampling from the so-called constrained prior. We outline the ways in which NS may be applied and describe the application of NS in three scientific fields in which the algorithm has proved to be useful: cosmology, gravitational-wave astronomy, and materials science. We close by making recommendations for best practice when using NS and by summarizing potential limitations and optimizations of NS., Comment: 20 pages + supplementary information, 5 figures. preprint version; published version at https://www.nature.com/articles/s43586-022-00121-x

Treatment wetlands can reduce nitrogen (N) pollution in waterways. However, the shortage of information on their cost-effectiveness has resulted in their relatively slow uptake in tropical and subtropical Australia, including the catchments of the Great Barrier Reef and Moreton Bay. We assessed the performance of constructed treatment wetlands (CW) and vegetated drains (VD) that treat agricultural runoff, and of sewage treatment plant wetlands (STPW), which polish treated effluent. Treatment performance was estimated as changes in concentration (dissolved inorganic nitrogen, DIN, and total nitrogen, TN; mg L−1) and annual load reductions (kg N ha−1 yr−1). We calculated their cost-effectiveness by comparing their N removal against the costs incurred in their design, construction, and maintenance. Overall, CWs and VDs reduced DIN concentrations by 44% (0.52 to 0.29 mg L−1), and STPW reduced them by 91% (2.3 to 0.2 mg L−1); STPWs also reduced TN concentrations by 72%. The efficiency varied among sites, with the best performing CWs and VDs being those with relatively high inflow concentrations (>0.2 mg L−1 of DIN, >0.7 mg L−1 of TN), low suspended solids, high vegetation cover and high length: width ratio. These high performing CWs and VDs removed N for less than USD 37 kg−1 DIN (AUD 50 kg−1 DIN), less than the end-of-catchment benchmark for the Great Barrier Reef of USD 110 kg−1 DIN (AUD 150 kg−1 DIN). When adequately located, designed, and managed, treatment wetlands can be cost-effective and should be adopted for reducing N in tropical and subtropical Australia.

In determining a corpus of recent British writing to be pastoral, Deborah Lilley eschews epithets such as ‘dark’ or ‘post’ for a more generous ‘new’, explaining that she intends her ‘usage to encom...

A major trend in academia and data science is the rapid adoption of Bayesian statistics for data analysis and modeling, leading to the development of probabilistic programming languages (PPL). A PPL provides a framework that allows users to easily specify a probabilistic model and perform inference automatically. PyAutoFit is a Python-based PPL which interfaces with all aspects of the modeling (e.g., the model, data, fitting procedure, visualization, results) and therefore provides complete management of every aspect of modeling. This includes composing high-dimensionality models from individual model components, customizing the fitting procedure and performing data augmentation before a model-fit. Advanced features include database tools for analysing large suites of modeling results and exploiting domain-specific knowledge of a problem via non-linear search chaining. Accompanying PyAutoFit is the autofit workspace (see https://github.com/Jammy2211/autofit_workspace), which includes example scripts and the HowToFit lecture series which introduces non-experts to model-fitting and provides a guide on how to begin a project using PyAutoFit. Readers can try PyAutoFit right now by going to the introduction Jupyter notebook on Binder (see https://mybinder.org/v2/gh/Jammy2211/autofit_workspace/HEAD) or checkout our readthedocs(see https://pyautofit.readthedocs.io/en/latest/) for a complete overview of PyAutoFit's features., Published in the Journal of Open Source Software

A survey of known gold-containing chemical vapour deposition (CVD) and atomic layer deposition (ALD) precursors, with a focus on collecting their volatilization and decomposition data. These data were applied to a figure of merit (σ) developed to easily assess the thermal characteristics.

Summary Introduction This study evaluates COVID-19 related patient risk, when undergoing management within one of the largest specialist centres in Europe, which rapidly implemented national COVID-19 safety guidelines. Method A prospective cohort study was undertaken in all patients who underwent surgical (n = 1429) or non-operative (n = 191) management during the UK COVID-19 pandemic peak (April–May 2020); all were evaluated for 30-day COVID-19 related death. A representative sample of elective/trauma/burns patients (surgery group, n = 729) were selected and also sub-analysed within a controlled cohort study design. Comparison was made to a random selection of non-operatively managed (non-operative group, n = 100) or waiting list (control group, n = 250) patients. These groups were prospectively followed-up and telephoned from the end of June (control group) or at 30 days post-first assessment (non-operative group)/post-operatively (surgery group). Results Complex general (9.2%, 136/1483) or regional (5.0%, 74/1483) anaesthesia cases represented 14.2% (210/1483) of operations undertaken. There were no 30-day post-operative (0/1429)/first assessment (0/191) COVID-19 related deaths. Neither the three sub-speciality plastic surgery, or non-operative groups, displayed increases in post-operative/first assessment symptoms in comparison to each other, or to control. The proportion of COVID-19 positive tests were: 7.1% (1/14) (non-operative), 5.9% (2/34) (burns) and 3.0% (3/99) (trauma); there were however no significant differences between these groups, the elective (0%, 0/54) and control (0%, 0/24) groups (p = 0.236). Conclusion We demonstrate that even heterogeneous sub-speciality patient groups, who required operative/non-operative management, did not incur an increased COVID-19 risk compared to each other or to control. These highly encouraging results were achieved with described, rapidly implemented service changes that were tailored to protect each patient group and staff.

BACKGROUND Portable high-frequency ultrasound is a useful adjunct to a plastic surgeon's practice. With a short learning curve, this patient-friendly imaging modality has a variety of uses that aid patient management/treatment plans. The authors describe clinical cases and review the literature regarding ultrasound performed by the surgeon. METHODS The Sonosite S-Nerve machine with the L25X transducer was used (depth, 4.3 cm). Clinical cases that ordinarily would have been referred to the radiology department were taken from the day-to-day practice of the senior author (M.G.). The clinical scenarios ranged from acute presentations to planned elective settings. RESULTS Ultrasound was a useful adjunct in a variety of applications, ranging from acute hand trauma visualizing neurovascular bundles and tendons, to elements of reconstructive breast surgery such as fat grafting over an implant and scar release. The ultrasound machine was also used for determination of the depth and size of collections such as seromas to facilitate drainage, for identification of lymph nodes before transfer, and for acute presentations of conditions ranging from undiagnosed swelling to foreign body localization. CONCLUSIONS The portable ultrasound machine has become an invaluable tool in the senior author's practice. In a short time and with a short learning curve, the authors' unit identified numerous applications for its use. From a patient perspective, it is noninvasive/nonpainful and has no deleterious radiation effects, and treatment plans can be enacted without delay. It is highly recommended that surgeons become familiar with this imaging modality and assimilate it into their daily practice. CLINICAL QUESTION/LEVEL OF EVIDENCE Therapeutic, V.

This handsome new edition of J.H. Prynne’s 1983 poem makes it freshly accessible – I’m tempted to say consumable – whether readers have previously encountered his work or not. The thoughtful appara...

When Michael Malay begins his incisive, well-written analysis of animal poetry by discussing the prose of Thoreau, Stanley Cavell and J.M. Coetzee, one wonders whether he has doubts about his chose...

In Australia, declining water quality in the Great Barrier Reef (GBR) is a threat to its marine ecosystems and nitrate (NO3−) from sugar cane-dominated agricultural areas in the coastal catchments of North Queensland is a key pollutant of concern. Woodchip bioreactors have been identified as a potential low-cost remediation technology to reduce the NO3− runoff from sugar cane farms. This study aimed to trial different designs of bioreactors (denitrification walls and beds) to quantify their NO3− removal performance in the distinct tropical climates and hydrological regimes that characterize sugarcane farms in North Queensland. One denitrification wall and two denitrification beds were installed to treat groundwater and subsurface tile-drainage water in wet tropics catchments, where sugar cane farming relies only on rainfall for crop growth. Two denitrification beds were installed in the dry tropics to assess their performance in treating irrigation tailwater from sugarcane. All trialled bioreactors were effective at removing NO3−, with the beds exhibiting a higher NO3− removal rate (NRR, from 2.5 to 7.1 g N m−3 d−1) compared to the wall (0.15 g N m−3 d−1). The NRR depended on the influent NO3− concentration, as low influent concentrations triggered NO3− limitation. The highest NRR was observed in a bed installed in the dry tropics, with relatively high and consistent NO3− influent concentrations due to the use of groundwater, with elevated NO3−, for irrigation. This study demonstrates that bioreactors can be a useful edge-of-field technology for reducing NO3− in runoff to the GBR, when sited and designed to maximise NO3− removal performance.

Background: NACT is a standard option for BC (T2-4, N0-3, M0) and certain BC phenotypes. The choice of AT based on the pre-NACT biomarkers status may not be optimum for individual patient because dynamic phenotypic changes induced by NACT may alter the response to treatment. Aim: The aim of this study is to determine the incidence of changes in the receptor status (ER, PR and HER2) and other proliferation biomarkers (Ki67 and SPAG5) before and after NACT and to assess the clinical significance of such changes. Methods Immunohistochemistry staining of ER, PR, HER2, Ki67 and SPAG5 in pre and post NACT tumors tissues from a consecutive series of 850 of BC (T2-4, N0-3, M0) treated at the Nottingham University Hospital (NUH) from 2000 to 2018, have been centrally evaluated according to ASCO guidelines. All cases with conversion in HER2 status had also been retested by HER2-FISH. The results were validated in an external cohort of 250 cases. Treatment options and patients characteristics are the same between the centres: (68%) received anthracycline plus Taxane (AC+T) NACT and 32% of patients have received NACT Anthracycline only (AC). Neoadjuvant HER2 targeting agents (Trastuzumab) or (Trastuzumab + Petruzumab) had been prescribed to 16% of patients in addition to AC+T followed by adjuvant Trastuzumab (total=18 cycles). All pre-NACT ER+ patients were given at least 5 year of adjuvant endocrine therapy (ET). In 2013 NUH started a prospective audit of retesting of receptor status in all post NACT surgical tumour samples. The results of the tests were presented to the weekly tumour board meeting and any change in the receptor status (ER and HER2) from negative (in the pre NACT core biopsies) to positive (in the post NACT surgical specimen) being considered for additional AT (ET for ER+ and Trastuzumab for HER2+ cases).The primary end points for this study are the % changes of biomarker changes and the disease free survival (DFS). The median follow up was 72 months. Results In pre NACT core biopsies 32% and 68% were HER2+ and HER2-; respectively. Twelve percent (12%) of the pre NACT HER2- tumours had a conversion to HER2+ in the post NACT surgical specimens. In this group of patients who subsequently received adjuvant Trastuzumab, 95% 3-year DFS was reported; which was similar to those patients who achieved pCR (3-year DFS; 90%) and was superior to cases which remained HER- in post NACT specimens (3-year DFS; 41%); (p Citation Format: Tarek M. a. Abdel-Fatah, Rebekah Webb, Jennifer Walker, Jun Lim, A. Graham Pockley, Graham Ball, Matthew Griffiths, Ian Ellis, Emad Rakhah, Zsolt Hodi, Andrew Lee, Arlene Chan, Stephen Chan. Clinically significant changes of receptors status (ER, PR and HER2) after receiving neoadjuvant chemotherapy (NACT) in breast cancer (BC) predicts the prognosis and guides the choice of the optimal adjuvant therapy (AT): Retesting of the receptor status should be mandatory [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-06-06.

Wetlands can increase resilience to extreme climatic events and have a key role in protection and water quality improvement in coastal ecosystems. Studies in tropical coastal wetlands at a catchment scale are scarce, and most work has been undertaken on small, temperate wetlands. In this study, we tested whether natural coastal wetlands in a tropical catchment (Tully-Murray, Queensland, Australia) could ameliorate nitrogen (N) exported to the Great Barrier Reef during a flood event. We measured denitrification rates in different types of coastal wetlands (mangroves, saltmarshes, waterbodies with macrophytes, and floodplain wetlands dominated by Melaleuca spp.) to assess their potential contribution to N losses during the 6-day duration of a flood in March 2018. Denitrification potential was variable across the landscape, and we identified “hotspots” in sub-catchments with high NO3--N concentrations (0.4–0.6 mg L−1) and large areas of wetlands (>800 ha, >40% of the sub-catchment). These hotspots can denitrify up to 10 t of NO3--N per day during a flood. We used our measured denitrification rates to provide input parameters for a model that includes the main biogeochemical processes affecting N transformations within wetlands (nitrification, denitrification, plant uptake, sedimentation, anammox, and mineralization), and accounts for transport via the duration, depth, and flow of water. Model simulations of a sub-catchment of the Tully-Murray indicate that flood inundation of large areas of natural wetlands (>40% of the sub-catchment area) could potentially remove 70% of the incoming NO3--N load in the first 24 h of the flood. The management and restoration of coastal tropical wetlands could play a critical role in sustaining the health of coastal ecosystems through water quality improvement.

We report an embarrassingly parallel method for the evaluation of thermodynamic properties over an energy landscape exhibiting broken ergodicity, nested is the likelihood of the observed data D givenbasin-sampling (NBS). We also introduce the No Galilean U-Turn Sampler (NoGUTS), a new sampling scheme based on the No U-Turn Sampler (NUTS) introduced by Hoffman and Gelman (2014) that works with the Galilean Monte Carlo scheme introduced by Betancourt (2012) to aid the efficient generation of new live points. NoGUTS can be thought of as a form of reflective slice sampling with an automatic stopping criterion. We apply this approach to a benchmark atomic cluster of 31 Lennard-Jones atoms, which exhibits a low temperature solid-solid heat capacity peak. The calculated heat capacity is compared with results generated by parallel tempering (PT), basin-sampling parallel tempering (BSPT), and standard nested sampling (NS) simulations. NBS reproduces the full heat capacity curve predicted by PT and BSPT, while the NS calculation with similar computational cost fails to resolve the low-temperature solid-solid phase transition.

Critical examination of Ian Fleming’s James Bond fiction has so far concentrated on its Cold War political context, and little has been written about the author’s engagement with the natural environment. However, his 1960 short story "The Hildebrand Rarity" is a valuable, early illustration of writing ecological crisis at the moment environmentalism is coming into being in its modern form. By reading the story ecocritically, this article will identify the resources that genre fiction offers for representing such crises, as well as the problems it raises. Comparison with Rachel Carson’s 1962 nonfiction work Silent Spring will help elucidate the techniques that environmental writing exploits to achieve global resonance. The article reads the story in terms of incident, gender relations, international relations, and the ecosystem in order to explain the peculiarity of James Bond’s lack of agency in this narrative, which is shown to evidence a twinned anxiety about the environment and the impotence of British masculinity in the Cold War era. In failing to resolve the problem of Bond’s inaction, Fleming’s text inadvertently dramatises the helplessness of the contemporary reader to engage meaningfully with environmental crisis.

We compare and contrast the volatility and thermal stability of a family of twelve organometallic gold(I) compounds using a combination of X-ray crystallography, thermogravimetric analysis (TGA), and density functional theory (DFT) techniques. Pentafluorophenyl is used as a new ligand for vapor deposition which produces rather low volatility, but very thermally stable compounds when combined with PMe3 and N,N'-di-tert-butylimidazolidin-2-ylidene. We introduce a precursor figure of merit that can be used to rank precursor usefulness. Using DFT, we find a linear correlation between Au-L bond strength and thermal stability, which demonstrates the power of computational techniques to predict successful synthetic targets for future precursor design studies.

Based on the theory of independently scattered random measures, we introduce a natural generalisation of Gaussian space-time white noise to a Levy-type setting, which we call Levy-valued random measures. We determine the subclass of cylindrical Levy processes which correspond to Levy-valued random measures, and describe the elements of this subclass uniquely by their characteristic function. We embed the Levy-valued random measure, or the corresponding cylindrical Levy process, in the space of general and tempered distributions. For the latter case, we show that this embedding is possible if and only if a certain integrability condition is satisfied. Similar to existing definitions, we introduce Levy-valued additive sheets, and show that integrating a Levy-valued random measure in space defines a Levy-valued additive sheet. This relation is manifested by the result, that a Levy-valued random measure can be viewed as the weak derivative of a Levy-valued additive sheet in the space of distributions.

Since the advent of microsurgical free tissue transfer in the 1960s, it has now become an indispensable part of limb salvage surgery. However, its application in children was initially met with concerns regarding vessel diameter, increased potential for vasospasm and its potential impact on normal growth and development. This resulted in its restriction to specialist paediatric facilities. With improvements and greater confidence in microsurgical techniques, more units are starting to rewrite the initially popularised narrative regarding free tissue transfer in paediatric limb salvage following trauma. A systematic review was undertaken, using the PRISMA criteria for systematic reviews, of all published literature relating to the use of free flaps in paediatric lower limb salvage following trauma.Inclusion and exclusion criteria were defined and Medline, Embase, PubMed and Google Scholar databases were searched from inception to September 2014 with the following search terms: "free tissue transfer", "free flaps", "microvascular free tissue transfer", "paediatric/pediatric", "children", "lower limb", "trauma" and "reconstruction".A total of 375 studies were retrieved following the electronic database search, of which 23 studies met the inclusion criteria. Two further studies were found via a hand-search of the reference lists of the retrieved studies. A total of 25 studies were, thus, included in the review.This study presents a synthesis of the literature available on the indications, timing, selection, viability, complications and functional outcome of free tissue transfer following lower limb trauma in paediatric patients. Limitations of current studies with potential areas for further research are also discussed.

To identify what is particular to the poetry of collapse, we can compare it with more widely known discourses. Jared Diamond for instance confronts the conundrum of scale in defining the term in Collapse: How SocietiesChoose to Fail or Survive, when he describes the phenomenon as “an extreme form of several milder types of decline, and it becomes arbitrary to decide how drastic the decline of a society must be before it qualifies to be labeled as a collapse”. In colony collapse disorder, or CCD, can witness at a smaller scale this failure to contain collapse. Poets taking up or taking on the theme of CCD work in a rich tradition of poetry about bees, a tradition in which the hive has always proved fertile for analogies with human society. One of the earliest texts in this tradition is Virgil’s Georgics, a Roman handbook of agricultural best practice in verse, itself attending to and written in a moment of collapse.

Objectives: To review internationally recognized models of police interactions with people experiencing mental health crises that are sometimes complex and associated with adverse experience for the person in crisis, their family and emergency service personnel. To develop, implement and review a partnership model trial between mental health and emergency services that offers alternative response pathways with improved outcomes in care. Methods: Three unique models of police and mental health partnership in the USA were reviewed and used to develop the PACER (Police Ambulance Crisis Emergency Response) model. A three month trial of the model was implemented and evaluated. Results: Significant improvements in response times, the interactions with and the outcomes for people in crisis were some of the benefits shown when compared with usual services. Conclusions: The pilot showed that a partnership involving mental health and police services in Melbourne, Australia could be replicated based on international models. Initial data supported improvements compared with usual care. Further data collection regarding usual care and this new model is required to confirm observed benefits.

Patrick D. Murphy’s latest book argues that ‘literary and cultural criticism […] is an academic form of persuasion’ (160), and, as a result, that ecocriticism could constitute a form of activism. I...

Studies are underway to determine if a large amount gas discharged through the downcomer pipes in the pressure suppression chamber during the blowdown of Loss of Coolant Accident (LOCA) can potentially be entrained into the Emergency Core Cooling System (ECCS) suction piping of BWR. This may result in degraded ECCS pumps performance which could affect the ability to maintain or recover the water inventory level in the Reactor Pressure Vessel (RPV) during a LOCA. Therefore, it is very important to understand the void behavior in the pressure suppression chamber during the blowdown period of a LOCA. To address this issue, a set of experiments is conducted using the Purdue University Multi-Dimensional Integral Test Assembly for ESBWR applications (PUMA-E) facility. The geometry of the test apparatus is determined based on the basic geometrical scaling analysis from a prototypical BWR containment (MARK I) with a consideration of downcomer size, downcomer water submergence depth and Suppression Pool (SP) water level. Several instruments are installed in the test facility to measure the required experimental data such as the steam mass flow rate, void fraction, pressure and temperature. In the experiments, sequential flows of air, steam–air mixture and pure steam-each with the various flow rate conditions are injected from the Drywell (DW) through a downcomer pipe in the SP. Eight tests with two different downcomer sizes, various initial gas volumetric fluxes at the downcomer, and two different initial non-condensable gas concentration conditions in the DW are conducted. Three distinct phases, namely, an initial phase, a quasi-steady, and a chugging phase are observed. The maximum void penetration depth is observed in the initial phase. A reduction in the void penetration depth is observed in the quasi-steady phase. As a result of low non-condensable gas concentration, chugging is observed at the tail end of the experiment. Chugging provides renewed void penetrations comparable to those in the initial phase. It is determined that the void distribution and area of void penetration in the SP is governed by the gas volumetric flux at the downcomer and the non-condensable gas concentration in the downcomer.

Finding the optimal alignment between two structures is important for identifying the minimum root-mean-square distance (RMSD) between them and as a starting point for calculating pathways. Most current algorithms for aligning structures are stochastic, scale exponentially with the size of structure, and the performance can be unreliable. We present two complementary methods for aligning structures corresponding to isolated clusters of atoms and to condensed matter described by a periodic cubic supercell. The first method (Go-PERMDIST), a branch and bound algorithm, locates the global minimum RMSD deterministically in polynomial time. The run time increases for larger RMSDs. The second method (FASTOVERLAP) is a heuristic algorithm that aligns structures by finding the global maximum kernel correlation between them using fast Fourier transforms (FFTs) and fast SO(3) transforms (SOFTs). For periodic systems, FASTOVERLAP scales with the square of the number of identical atoms in the system, reliably finds the best alignment between structures that are not too distant, and shows significantly better performance than existing algorithms. The expected run time for Go-PERMDIST is longer than FASTOVERLAP for periodic systems. For finite clusters, the FASTOVERLAP algorithm is competitive with existing algorithms. The expected run time for Go-PERMDIST to find the global RMSD between two structures deterministically is generally longer than for existing stochastic algorithms. However, with an earlier exit condition, Go-PERMDIST exhibits similar or better performance.

AimsReports into standards in the National Health Service and quality in pathology have focused on the way we work in pathology and how to provide assurance that this is of a high standard. There are a number of external quality assurance schemes covering pathology and histopathology specifically; however, there is no scheme covering the process of histological surgical dissection. This is an area undergoing development, emerging from the sole preserve of medically qualified pathologists to a field populated by a number of highly trained biomedical scientists, but remains without any formal quality assurance.MethodsThis work builds on Barnes, taking the guidance of the Royal College of Pathologists (RCPath)and Institute of Biomedical Science (IBMS)to form a series of key performance indicators relating to dissection. These were developed for use as an indicator of individual practice, highlighting areas of variation, weakness or strength. Once identified, a feedback event provided opportunities to address these errors and omissions, or to enable areas of strength to be shared.ResultsThe data obtained from the checklists demonstrate a large variation in practice at the outset of this study. The use of the checklists alone served to reduce this variation in practice, the addition of the training event showed further reduction in variation. The combination of these two tools was an effective method for enhancing standardisation of practice.ConclusionsThe results of this work show that training events serve to reduce variation in practice by, and between, dissectors, driving up standards in dissection—directly addressing the needs of the modern pathology service.

During the initial blowdown period of a Loss of Coolant Accident (LOCA), the non-condensable gas initially contained in the BWR containment is discharged to the pressure suppression chamber through the blowdown pipes. The performance of Emergency Core Cooling System (ECCS) can be degraded due to the released gas ingestion into the suction intakes of the ECCS pumps. The understanding of the relevant phenomena in the pressure suppression chamber is important in analyzing potential gas intrusion into the suction intakes of ECCS pumps. To obtain the basic understanding of the relevant phenomena and the generic data of void distribution in the pressure suppression chamber during the initial blowdown period of a LOCA, tests with various blowdown conditions were conducted using the existing Suppression Pool (SP) tank of the integral test facility, called Purdue University Multi-Dimensional Integral Test Assembly for ESBWR applications (PUMA-E) facility, a scaled downcomer pipe installed in the PUMA-E SP, and air discharge pipe system. Two different diameter sizes of air injection pipe (0.076 and 0.102 m), a range of air volumetric flux (7.9–24.7 m/s), initial void conditions in an air injection pipe (fully void, partially void, and fully filled with water) and different air velocity ramp rates (1.0, 1.5, and 2.0 s) are used to investigate the impact of the blowdown conditions to the void distribution in the SP. Two distinct phases of experiments, namely, an initial and a quasi-steady phase were observed. The maximum void penetration depth was experienced during the initial phase. The quasi-steady phase provided less void penetration depth and was categorized by oscillations in the void penetration. The initial void conditions in an air injection pipe and air volumetric fluxes were only found to significantly impact on the void distribution in the SP.