Prospects for gulf of Mexico environmental recovery and restoration

Previous oil spills provide clear evidence that ecosystem restoration efforts are challenging, and recovery can take decades. Similar to the Ixtoc 1 well blowout in 1979, the Deepwater Horizon (DWH) oil spill was enormous both in volume of oil spilled and duration, resulting in environmental impacts from the deep ocean to the Gulf of Mexico coastline. Data collected during the National Resource Damage Assessment showed significant damage to coastal areas (especially marshes), marine organisms, and deep-sea habitat. Previous spills have shown that disparate regions recover at different rates, with especially long-term effects in salt marshes and deepsea habitat. Environmental recovery and restoration in the northern Gulf of Mexico are dependent upon fundamental knowledge of ecosystem processes in the region. PostDWH research data provide a starting point for better understanding baselines and ecosystem processes. It is imperative to use the best science available to fully understand DWH environmental impacts and determine the appropriate means to ameliorate those impacts through restoration. Filling data gaps will be necessary to make better restoration decisions, and establishing new baselines will require long-term studies. Future research, especially via NOAA’s RESTORE Science Program and the state-based Centers of Excellence, should provide a path to understanding the potential for restoration and recovery of this vital marine ecosystem

Navigating spaces between conservation research and practice: are we making progress?

1. Despite aspirations for conservation impact, mismatches between research and implementation have limited progress towards this goal. There is, therefore, an urgent need to identify how we can more effectively navigate the spaces between research and practice. 2. In 2014, we ran a workshop with conservation researchers and practitioners to identify mismatches between research and implementation that needed to be overcome to deliver evidence‐informed conservation action. Five mismatches were highlighted: spatial, temporal, priority, communication, and institutional. 3. Since 2014, thinking around the ‘research–implementation gap’ has progressed. The term ‘gap’ has been replaced by language around the dynamic ‘spaces’ between research and action, representing a shift in thinking around what it takes to better align research and practice. 4. In 2019, we ran a follow‐up workshop reflecting on this shift, whether the five mismatches identified in the 2014 workshop were still present in conservation, and whether progress had been made to overcome these mismatches during the past 5 years. We found that while there has been progress, we still have some way to go across all dimensions. 5. Here, we report on the outcomes of the 2019 workshop, reflect on what has changed over the past 5 years, and offer 10 recommendations for strengthening the alignment of conservation research and practice

AI segmentation as a quality improvement tool in radiotherapy planning for breast cancer

AI segmentation has been recently introduced in the local department for delineation of targets and organs-at-risk (OAR) for a wide range of tumour sites. For breast radiotherapy, AI segmentation can provide target delineation (breast and lymph nodes) and required OAR, and this has enabled a stepwise series of improvements to the local planning technique.Clinician feedback deemed 67 - 89 % of nodal target volumes required no edits or only minor edits, so AI breast and lymph nodes volumes were first used to guide tangent and supraclavicular field placement, instead of a bony-anatomy based technique.Next, evolution from anatomical field-placement to true inverse optimised planning was introduced using AI to create the required target volumes. For internal mammary node (IMN) treatments, the previous 3-field technique prohibited Deep Inspiration breath-hold (DIBH), due to the couch rotation used to match field edges. The roll-out of VMAT (volumetric-modulated arc therapy) with DIBH enabled by AI therefore resulted in a dose reduction to ipsi-lateral lung, and in mean heart dose compared to the old 3-field technique. Median time from CT scan to VMAT IMN plan approval reduced from 12 days (with manual contouring) to 7 days using reviewed and edited AI-generated volumes.Consistent, high-quality contours for 9 OAR and breast PTVs for all patients facilitates comparison with NHS-E scorecards as a benchmark for plan quality. Workflows have been simplified, with significant time-savings. DIBH radiotherapy is now available to more patients, further improving dose sparing for heart and lung

Optimization of metal/phosphor screens for on-line portal imaging

NRC publication: Ye

A Concept of Power Generator using Wind Turbine, Hydrodynamic Retarder, and Organic Rankine Cycle Drive

This paper describes a concept of electric power generating system that uses a wind turbine to generate kinetic energy which converts heat through a hydrodynamic retarder. The heat so generated is utilized to drive an organic Rankine cycle that converts thermal energy into electricity power for continuous and undisrupted supply during the year. A hydrodynamic retarder converts kinetic energy into heat through hot fluid by directing the flow of the fluid into the hydrodynamic retarder in a manner that resists rotation of blades of the wind turbine. The hot fluid circulating in the hydrodynamic retarder is a thermal heat source for vapor regeneration of organic heat exchange fluid mixture(s) used in the Rankine cycle. The expansion of the organic heat exchange fluid gets converted into rotation of the generator rotor

Divergent Fe-Mediated C–H Activation Paths Driven by Alkali Cations

The association of the ferrous complex FeIICl2(dmpe)2 (1) with alkali bases M(hmds) (M = Li, Na, K) proves to be an efficient platform for the activation of Ar–H bonds. Two mechanisms can be observed, leading to either Ar–FeII species by deprotonative ferration or hydrido species Ar–FeII–H by oxidative addition of transient Fe0(dmpe)2 generated by reduction of 1. Importantly, the nature of the alkali cation in M(hmds) has a strong influence on the preferred path. Starting from the same iron precursor, diverse catalytic applications can be explored by a simple modulation of the MI cation. Possible strategies enabling cross-coupling using arenes as pro-nucleophiles, reductive dehydrocoupling, or deuteration of B–H bonds are discussed

Divergent Fe-Mediated C–H Activation Paths Driven by Alkali Cations

The association of the ferrous complex FeIICl2(dmpe)2 (1) with alkali bases M(hmds) (M = Li, Na, K) proves to be an efficient platform for the activation of Ar–H bonds. Two mechanisms can be observed, leading to either Ar–FeII species by deprotonative ferration or hydrido species Ar–FeII–H by oxidative addition of transient Fe0(dmpe)2 generated by reduction of 1. Importantly, the nature of the alkali cation in M(hmds) has a strong influence on the preferred path. Starting from the same iron precursor, diverse catalytic applications can be explored by a simple modulation of the MI cation. Possible strategies enabling cross-coupling using arenes as pro-nucleophiles, reductive dehydrocoupling, or deuteration of B–H bonds are discussed