The Complexity of the Practice of Ecosystem-Based Management.

In the United States, there are more than 20 federal agencies that manage over 140 ocean statutes (Crowder et al., 2006). A history of disjointed, single sector management has resulted in a one-dimensional view of ecosystems, administrative systems, and the socio-economic drivers that affect them. In contrast, an ecosystem-based approach to management is inherently multi-dimensional. Ecosystem-based approaches to management (EBM) are at the forefront of progressive science and policy discussions. Both the U.S. Commission on Ocean Policy (USCOP, 2004) and the Pew Oceans Commission (POC, 2003) reports called for a better understanding of the impact of human activities on the coastal ocean and the result was President Obama’s National Policy for the Stewardship of the Ocean, our Coasts, and the Great Lakes (2010). EBM is holistic by seeking to include all stakeholders affected by marine policy in decision-making. Stakeholders may include individuals from all levels of government, academia, environmental organizations, and marine-dependent businesses and industry. EBM processes require decision-makers to approach marine management differently and more comprehensively to sufficiently require a more sophisticated conceptual understanding of the process and the people involved. There are implicit cognitive, interpersonal, and intra-personal demands of EBM that are not addressed by current literature. This research seeks to understand the mental demands of EBM. A constructive developmental framework is used to illuminate how decision-makers reason or make sense of the ideals and values underlying EBM, the mutual relationships that must be built among natural resource management agencies, and the personal experiences and emotions that accompany change

A Novel and Automated Approach to Classify Radiation Induced Lung Tissue Damage on CT Scans

Radiation-induced lung damage (RILD) is a common side effect of radiotherapy (RT). The ability to automatically segment, classify, and quantify different types of lung parenchymal change is essential to uncover underlying patterns of RILD and their evolution over time. A RILD dedicated tissue classification system was developed to describe lung parenchymal tissue changes on a voxel-wise level. The classification system was automated for segmentation of five lung tissue classes on computed tomography (CT) scans that described incrementally increasing tissue density, ranging from normal lung (Class 1) to consolidation (Class 5). For ground truth data generation, we employed a two-stage data annotation approach, akin to active learning. Manual segmentation was used to train a stage one auto-segmentation method. These results were manually refined and used to train the stage two auto-segmentation algorithm. The stage two auto-segmentation algorithm was an ensemble of six 2D Unets using different loss functions and numbers of input channels. The development dataset used in this study consisted of 40 cases, each with a pre-radiotherapy, 3-, 6-, 12-, and 24-month follow-up CT scans (n = 200 CT scans). The method was assessed on a hold-out test dataset of 6 cases (n = 30 CT scans). The global Dice score coefficients (DSC) achieved for each tissue class were: Class (1) 99% and 98%, Class (2) 71% and 44%, Class (3) 56% and 26%, Class (4) 79% and 47%, and Class (5) 96% and 92%, for development and test subsets, respectively. The lowest values for the test subsets were caused by imaging artefacts or reflected subgroups that occurred infrequently and with smaller overall parenchymal volumes. We performed qualitative evaluation on the test dataset presenting manual and auto-segmentation to a blinded independent radiologist to rate them as 'acceptable', 'minor disagreement' or 'major disagreement'. The auto-segmentation ratings were similar to the manual segmentation, both having approximately 90% of cases rated as acceptable. The proposed framework for auto-segmentation of different lung tissue classes produces acceptable results in the majority of cases and has the potential to facilitate future large studies of RILD

Ba4Ru3O10.2(OH)1.8 : a new member of the layered hexagonal perovskite family crystallised from water

A new barium ruthenium oxyhydroxide Ba4Ru3O10.2(OH)1.8 crystallises under hydrothermal conditions at 200 °C: powder neutron diffraction data show it adopts an 8H hexagonal perovskite structure with a new stacking sequence, while high resolution electron microscopy reveals regions of ordered layers of vacant Ru sites, and magnetometry shows antiferromagnetism with TN = 200(5) K

Quantitative Analysis of Radiation-Associated Parenchymal Lung Change

We present a novel classification system of the parenchymal features of radiation-induced lung damage (RILD). We developed a deep learning network to automate the delineation of five classes of parenchymal textures. We quantify the volumetric change in classes after radiotherapy in order to allow detailed, quantitative descriptions of the evolution of lung parenchyma up to 24 months after RT, and correlate these with radiotherapy dose and respiratory outcomes. Diagnostic CTs were available pre-RT, and at 3, 6, 12 and 24 months post-RT, for 46 subjects enrolled in a clinical trial of chemoradiotherapy for non-small cell lung cancer. All 230 CT scans were segmented using our network. The five parenchymal classes showed distinct temporal patterns. Moderate correlation was seen between change in tissue class volume and clinical and dosimetric parameters, e.g., the Pearson correlation coefficient was ≤0.49 between V30 and change in Class 2, and was 0.39 between change in Class 1 and decline in FVC. The effect of the local dose on tissue class revealed a strong dose-dependent relationship. Respiratory function measured by spirometry and MRC dyspnoea scores after radiotherapy correlated with the measured radiological RILD. We demonstrate the potential of using our approach to analyse and understand the morphological and functional evolution of RILD in greater detail than previously possible

Elbow joint variability for different hand positions of the round off in gymnastics.

The aim of the present study was to conduct within-gymnast analyses of biological movement variability in impact forces, elbow joint kinematics and kinetics of expert gymnasts in the execution of the round-off with different hand positions. Six international level female gymnasts performed 10 trials of the round-off from a hurdle step to a back-handspring using two hand potions: parallel and T-shape. Two force plates were used to determine ground reaction forces. Eight infrared cameras were employed to collect the kinematic data automatically. Within gymnast variability was calculated using biological coefficient of variation (BCV) discretely for ground reaction force, kinematic and kinetic measures. Variability of the continuous data was quantified using coefficient of multiple correlations (CMC). Group BCV and CMC were calculated and T-test with effect size statistics determined differences between the variability of the two techniques examined in this study. The major observation was a higher level of biological variability in the elbow joint abduction angle and adduction moment of force in the T-shaped hand position. This finding may lead to a reduced repetitive abduction stress and thus protect the elbow joint from overload. Knowledge of the differences in biological variability can inform clinicians and practitioners with effective skill selection

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relaps

Agricultural Management and Climatic Change Are the Major Drivers of Biodiversity Change in the UK

Action to reduce anthropogenic impact on the environment and species within it will be most effective when targeted towards activities that have the greatest impact on biodiversity. To do this effectively we need to better understand the relative importance of different activities and how they drive changes in species’ populations. Here, we present a novel, flexible framework that reviews evidence for the relative importance of these drivers of change and uses it to explain recent alterations in species’ populations. We review drivers of change across four hundred species sampled from a broad range of taxonomic groups in the UK. We found that species’ population change (~1970–2012) has been most strongly impacted by intensive management of agricultural land and by climatic change. The impact of the former was primarily deleterious, whereas the impact of climatic change to date has been more mixed. Findings were similar across the three major taxonomic groups assessed (insects, vascular plants and vertebrates). In general, the way a habitat was managed had a greater impact than changes in its extent, which accords with the relatively small changes in the areas occupied by different habitats during our study period, compared to substantial changes in habitat management. Of the drivers classified as conservation measures, low-intensity management of agricultural land and habitat creation had the greatest impact. Our framework could be used to assess the relative importance of drivers at a range of scales to better inform our policy and management decisions. Furthermore, by scoring the quality of evidence, this framework helps us identify research gaps and needs