Physical soil quality indicators for monitoring British soils

The condition or quality of soils determines its ability to deliver a range of functions that support ecosystem services, human health and wellbeing. The increasing policy imperative to implement successful soil monitoring programmes has resulted in the demand for reliable soil quality indicators (SQIs) for physical, biological and chemical soil properties. The selection of these indicators needs to ensure that they are sensitive and responsive to pressure and change e.g. they change across space and time in relation to natural perturbations and land management practices. Using a logical sieve approach based on key policy-related soil functions, this research assessed whether physical soil properties can be used to indicate the quality of British soils in terms of its capacity to deliver ecosystem goods and services. The resultant prioritised list of physical SQIs were tested for robustness, spatial and temporal variability and expected rate of change using statistical analysis and modelling. Six SQIs were prioritised; packing density, soil water retention characteristics, aggregate stability, rate of erosion, depth of soil and soil sealing. These all have direct relevance to current and likely future soil and environmental policy and are appropriate for implementation in soil monitoring programs

Scaling Egocentric Vision: The EPIC-KITCHENS Dataset

First-person vision is gaining interest as it offers a unique viewpoint on people's interaction with objects, their attention, and even intention. However, progress in this challenging domain has been relatively slow due to the lack of sufficiently large datasets. In this paper, we introduce EPIC-KITCHENS, a large-scale egocentric video benchmark recorded by 32 participants in their native kitchen environments. Our videos depict nonscripted daily activities: we simply asked each participant to start recording every time they entered their kitchen. Recording took place in 4 cities (in North America and Europe) by participants belonging to 10 different nationalities, resulting in highly diverse cooking styles. Our dataset features 55 hours of video consisting of 11.5M frames, which we densely labeled for a total of 39.6K action segments and 454.3K object bounding boxes. Our annotation is unique in that we had the participants narrate their own videos (after recording), thus reflecting true intention, and we crowd-sourced ground-truths based on these. We describe our object, action and anticipation challenges, and evaluate several baselines over two test splits, seen and unseen kitchens. Dataset and Project page: http://epic-kitchens.github.ioComment: European Conference on Computer Vision (ECCV) 2018 Dataset and Project page: http://epic-kitchens.github.i

A comparison of placebo and nocebo effects on objective and subjective postural stability: a double-edged sword?

Background: Positive expectations (i.e., placebo effect) can improve postural control during quiet standing. This raises an important question: if postural control is susceptible to positive expectations, is it possible to elicit the opposite, a decline in postural stability, simply by suggesting a performance impairment (i.e., nocebo) will take place? Yet no studies have examined the nocebo effect on balance performance. To better understand both phenomena, comparative studies, which include both placebo and nocebo conditions, are needed. Method: Forty-two healthy adults were initially assessed for objective (center of pressure movement) and subjective (perceived) postural stability and performance expectations. Participants were then randomly assigned in equal numbers to a placebo (positive expectation), nocebo (negative expectation) or control (no suggestion) group. Participants in the placebo/nocebo groups were deceptively administered an inert capsule described as a potent supplement which would either positively or negatively influence their balance performance. Objective and subjective postural stability, and performance expectations were reassessed 20 min later. Results: The nocebo procedure evoked an increase in COP sway movements and reduced perceived stability compared to a control group. The placebo group presented with reductions COP sway movements and increased perceived stability following expectation manipulation. Compared to the control group, the placebo group showed a significantly higher performance expectation whilst the nocebo group showed a significantly lower performance expectation. Regression analyses also revealed that performance expectations following the placebo/nocebo procedure significantly predicted perceptions of postural instability (i.e., perceived performance), accounting for around 50% of the variance. These results remained even when controlling for actual performance (i.e., objective postural stability). Conclusion: Our findings indicate that positive and negative performance expectations evoked by instructional manipulation can profoundly influence both objective and subjective postural stability. Postural control—and perceptions regarding such—are clearly susceptible to expectation manipulation, which could have important practical implications and repercussions on testing, training interventions and rehabilitation programs. Positive and negative expectancies are a double-edged sword for postural control

Is a specialist breathlessness service more effective and cost-effective for patients with advanced cancer and their carers than standard care? Findings of a mixed-method randomised controlled trial.

BACKGROUND: Breathlessness is common in advanced cancer. The Breathlessness Intervention Service (BIS) is a multi-disciplinary complex intervention theoretically underpinned by a palliative care approach, utilising evidence-based non-pharmacological and pharmacological interventions to support patients with advanced disease. We sought to establish whether BIS was more effective, and cost-effective, for patients with advanced cancer and their carers than standard care. METHODS: A single-centre Phase III fast-track single-blind mixed-method randomised controlled trial (RCT) of BIS versus standard care was conducted. Participants were randomised to one of two groups (randomly permuted blocks). A total of 67 patients referred to BIS were randomised (intervention arm n = 35; control arm n = 32 received BIS after a two-week wait); 54 completed to the key outcome measurement. The primary outcome measure was a 0 to 10 numerical rating scale for patient distress due to breathlessness at two-weeks. Secondary outcomes were evaluated using the Chronic Respiratory Questionnaire, Hospital Anxiety and Depression Scale, Client Services Receipt Inventory, EQ-5D and topic-guided interviews. RESULTS: BIS reduced patient distress due to breathlessness (primary outcome: -1.29; 95% CI -2.57 to -0.005; P = 0.049) significantly more than the control group; 94% of respondents reported a positive impact (51/53). BIS reduced fear and worry, and increased confidence in managing breathlessness. Patients and carers consistently identified specific and repeatable aspects of the BIS model and interventions that helped. How interventions were delivered was important. BIS legitimised breathlessness and increased knowledge whilst making patients and carers feel 'not alone'. BIS had a 66% likelihood of better outcomes in terms of reduced distress due to breathlessness at lower health/social care costs than standard care (81% with informal care costs included). CONCLUSIONS: BIS appears to be more effective and cost-effective in advanced cancer than standard care. TRIAL REGISTRATION: RCT registration at ClinicalTrials.gov NCT00678405 (May 2008) and Current Controlled Trials ISRCTN04119516 (December 2008).The study was supported by the following funders: NIHR Research for Patient Benefit (for Phase III RCT funding); Macmillan Cancer Support (MF’s post-doctoral fellowship); The Gatsby Foundation for the initial funding of BIS; and AT Prevost was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The study sponsor was CUHNFT.This is the final published version. It first appeared at http://www.biomedcentral.com/1741-7015/12/194

Analysis of thrombogenicity under flow reveals new insights into the prothrombotic state of patients with post-COVID syndrome

Background: Post-COVID syndrome (PCS) affects millions of people worldwide, causing a multitude of symptoms and impairing quality of life months or even years after acute COVID-19. A prothrombotic state has been suggested; however, underlying mechanisms remain to be elucidated. / Objectives: To investigate thrombogenicity in PCS using a microfluidic assay, linking microthrombi, thrombin generation, and the von Willebrand factor (VWF):a Disintegrin and Metalloproteinase with a Thrombospondin Type 1 motif, member 13 (ADAMTS13) axis. / Methods: Citrated blood was perfused through microfluidic channels coated with collagen or an antibody against the VWF A3 domain, and thrombogenicity was monitored in real time. Thrombin generation assays were performed and α(2)-antiplasmin, VWF, and ADAMTS13 activity levels were also measured. / Results: We investigated thrombogenicity in a cohort of 21 patients with PCS with a median time following symptoms onset of 23 months using a dynamic microfluidic assay. Our data show a significant increase in platelet binding on both collagen and anti-VWF A3 in patients with PCS compared with that in controls, which positively correlated with VWF antigen (Ag) levels, the VWF(Ag):ADAMTS13 ratio (on anti-VWF A3), and inversely correlated with ADAMTS13 activity (on collagen). Thrombi forming on collagen presented different geometries in patients with PCS vs controls, with significantly increased thrombi area mainly attributable to thrombi length in the patient group. Thrombi length positively correlated with VWF(Ag):ADAMTS13 ratio and thrombin generation assay results, which were increased in 55.5% of patients. α(2)-Antiplasmin levels were normal in 89.5% of patients. / Conclusion: Together, these data present a dynamic assay to investigate the prothrombotic state in PCS, which may help unravel the mechanisms involved and/or establish new therapeutic strategies for this condition

Rescaling Egocentric Vision:Collection Pipeline and Challenges for EPIC-KITCHENS-100

This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M frames, 90K actions in 700 variable-length videos, capturing long-term unscripted activities in 45 environments, using head-mounted cameras. Compared to its previous version (Damen in Scaling egocentric vision: ECCV, 2018), EPIC-KITCHENS-100 has been annotated using a novel pipeline that allows denser (54% more actions per minute) and more complete annotations of fine-grained actions (+128% more action segments). This collection enables new challenges such as action detection and evaluating the “test of time”—i.e. whether models trained on data collected in 2018 can generalise to new footage collected two years later. The dataset is aligned with 6 challenges: action recognition (full and weak supervision), action detection, action anticipation, cross-modal retrieval (from captions), as well as unsupervised domain adaptation for action recognition. For each challenge, we define the task, provide baselines and evaluation metrics.Published versionResearch at Bristol is supported by Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Program (DTP), EPSRC Fellowship UMPIRE (EP/T004991/1). Research at Catania is sponsored by Piano della Ricerca 2016-2018 linea di Intervento 2 of DMI, by MISE - PON I&C 2014-2020, ENIGMA project (CUP: B61B19000520008) and by MIUR AIM - Attrazione e Mobilita Internazionale Linea 1 - AIM1893589 - CUP E64118002540007

Indicators of soil quality - Physical properties (SP1611). Final report to Defra

The condition of soil determines its ability to carry out diverse and essential functions that support human health and wellbeing. These functions (or ecosystem goods and services) include producing food, storing water, carbon and nutrients, protecting our buried cultural heritage and providing a habitat for flora and fauna. Therefore, it is important to know the condition or quality of soil and how this changes over space and time in response to natural factors (such as changing weather patterns) or to land management practices. Meaningful soil quality indicators (SQIs), based on physical, biological or chemical soil properties are needed for the successful implementation of a soil monitoring programme in England and Wales. Soil monitoring can provide decision makers with important data to target, implement and evaluate policies aimed at safeguarding UK soil resources. Indeed, the absence of agreed and well-defined SQIs is likely to be a barrier to the development of soil protection policy and its subsequent implementation. This project assessed whether physical soil properties can be used to indicate the quality of soil in terms of its capacity to deliver ecosystem goods and services. The 22 direct (e.g. bulk density) and 4 indirect (e.g. catchment hydrograph) physical SQIs defined by Loveland and Thompson (2002) and subsequently evaluated by Merrington et al. (2006), were re-visited in the light of new scientific evidence, recent policy drivers and developments in sampling techniques and monitoring methodologies (Work Package 1). The culmination of these efforts resulted in 38 direct and 4 indirect soil physical properties being identified as potential SQIs. Based on the gathered evidence, a ‘logical sieve’ was used to assess the relative strengths, weaknesses and suitability of each potential physical SQI for national scale soil monitoring. Each soil physical property was scored in terms of: soil function – does the candidate SQI reflect all soil function(s)? land use - does the candidate SQI apply to all land uses found nationally? soil degradation - can the candidate SQI express soil degradation processes? does the candidate SQI meet the challenge criteria used by Merrington et al. (2006)?This approach enabled a consistent synthesis of available information and the semi-objective, semi-quantitative and transparent assessment of indicators against a series of scientific and technical criteria (Ritz et al., 2009; Black et al., 2008). The logical sieve was shown to be a flexible decision-support tool to assist a range of stakeholders with different agenda in formulating a prioritised list of potential physical SQIs. This was explored further by members of the soil science and soils policy community at a project workshop. By emphasising the current key policy-related soil functions (i.e. provisioning and regulating), the logical sieve was used to generate scores which were then ranked to identify the most qualified SQIs. The process selected 18 candidate physical SQIs. This list was further filtered to move from the ‘narrative’ to a more ‘numerical’ approach, in order to test the robustness of the candidate SQIs through statistical analysis and modelling (Work Package 2). The remaining 7 physical SQIs were: depth of soil; soil water retention characteristics; packing density; visual soil assessment / evaluation; rate of erosion; sealing; and aggregate stability. For these SQIs to be included in a robust national soil monitoring programme, we investigated the uncertainty in their measurement; the spatial and temporal variability in the indicator as given by observed distributions; and the expected rate of change in the indicator. Whilst a baseline is needed (i.e. the current state of soil), it is the rate of change in soil properties and the implications of that change in terms of soil processes and functioning that are key to effective soil monitoring. Where empirical evidence was available, power analysis was used to understand the variability of indicators as given by the observed distributions. This process determines the ability to detect a particular change in the SQI at a particular confidence level, given the ‘noise’ or variability in the data (i.e. a particular power to detect a change of ‘X’ at a confidence level of ‘Y%’ would require ‘N’ samples). However, the evidence base for analysing the candidate SQIs is poor: data are limited in spatial and temporal extent for England and Wales, in terms of a) the degree (magnitude) of change in the SQI which significantly affects soil processes and functions (i.e. ‘meaningful change’), and b) the change in the SQI that is detectable (i.e. what sample size is needed to detect the meaningful signal from the variability or noise in the signal). This constrains the design and implementation of a scientifically and statistically rigorous and reliable soil monitoring programme. Evidence that is available suggests that what constitutes meaningful change will depend on soil type, current soil state, land use and the soil function under consideration. However, when we tested this by analysing detectable changes in packing density and soil depth (because data were available for these SQIs) over different land covers and soil types, no relationships were found. Schipper and Sparling (2000) identify the challenge: “a standardised methodology may not be appropriate to apply across contrasting soils and land uses. However, it is not practical to optimise sampling and analytical techniques for each soil and land use for extensive sampling on a national scale”. Despite the paucity in data, all seven SQIs have direct relevance to current and likely future soil and environmental policy, because they can be related (qualitatively) to soil processes, soil functions and delivery of ecosystem goods and services. Even so, meaningful and detectable changes in physical SQIs may be out of time with any soil policy change and it is not usually possible to link particular changes in SQIs to particular policy activities. This presents challenges in ascertaining trends that can feed into policy development or be used to gauge the effectiveness of soil protection policies (Work Package 3). Of the seven candidate physical SQIs identified, soil depth and surface sealing are regarded by many as indicators of soil quantity rather than quality. Visual soil evaluation is currently not suited to soil monitoring in the strictest sense, as its semi-qualitative basis cannot be analysed statistically. Also, few data exist on how visual evaluation scores relate to soil functions. However, some studies have begun to investigate how VSE might be moved to a more quantified scale and the method has some potential as a low cost field technique to assess soil condition. Packing density requires data on bulk density and clay content, both of which are highly variable, so compounding the error term associated with this physical SQI. More evidence is needed to show how ‘meaningful’ change in aggregate stability affects soil processes and thus soil functions (for example, using the limited data available, an equivocal relationship was found with water regulation / runoff generation). The analysis of available data has given promising results regarding the prediction of soil water retention characteristics and packing density from relatively easy to measure soil properties (bulk density, texture and organic C) using pedotransfer functions. Expanding the evidence base is possible with the development of rapid, cost-effective techniques such as NIR sensors to measure soil properties. Defra project SP1303 (Brazier et al., 2012) used power analyses to estimate the number of monitoring locations required to detect a statistically significant change in soil erosion rate on cultivated land. However, what constitutes a meaningful change in erosion rates still requires data on the impacts of erosion on soil functions. Priority cannot be given amongst the seven SQIs, because the evidence base for each varies in its robustness and extent. Lack of data (including uncertainty in measurement and variability in observed distributions) applies to individual SQIs; attempts at integrating more than one SQI (including physical, biological and chemical SQIs) to improve associations between soil properties and processes / functions are only likely to propagate errors. Whether existing monitoring programmes can be adapted to incorporate additional measurement of physical SQIs was explored. We considered options where one or more of the candidate physical SQIs might be implemented into soil monitoring programmes (e.g. as a new national monitoring scheme; as part of the Countryside Survey; and as part of the National Soil Inventory). The challenge is to decide whether carrying out soil monitoring that is not statistically robust is still valuable in answering questions regarding current and future soil quality. The relationship between physical (and other) SQIs, soil processes and soil functions is complex, as is how this influences ecosystem services’ delivery. Important gaps remain in even the realisation of a conceptual model for these inter-relationships, let alone their quantification. There is also a question of whether individual quantitative SQIs can be related to ecosystem services, given the number of variables

Diamond Line - Fall 2020

In following up the premier issue of The Diamond Line, the fall 2020 editorial staff had big shoes to fill. We took on the challenge of creating something that would uphold the framework of Issue 1 while simultaneously branching out from its margins. Like the editors before us, we had a vision, but ours took a new form — bright, warm colors. Sunset colors. Moons. Playful lines. Isolation and introspection. A stroll through an art gallery. A coming-of-age story bound between two groovy orange bookends. While Issue 2 does not have an overarching theme, we chose the cover art, “Pandemic Prom” by Autumn Blaylock, because it beautifully encompassed the pages within and the vision we were working toward