1,259 research outputs found

    Equipping for risk: Lessons learnt from the UK shale-gas experience on assessing environmental risks for the future geoenergy use of the deep subsurface

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    \ua9 2024 The Authors. Summary findings are presented from an investigation to improve understanding of the environmental risks associated with developing an unconventional-hydrocarbons industry in the UK. The EQUIPT4RISK project, funded by UK Research Councils, focused on investigations around Preston New Road (PNR), Fylde, Lancashire, and Kirby Misperton Site A (KMA), North Yorkshire, where operator licences to explore for shale gas by hydraulic fracturing (HF) were issued in 2016, although exploration only took place at PNR. EQUIPT4RISK considered atmospheric (greenhouse gases, air quality), water (groundwater quality) and solid-earth (seismicity) compartments to characterise and model local conditions and environmental responses to HF activities. Risk assessment was based on the source-pathway-receptor approach. Baseline monitoring of air around the two sites characterised the variability with meteorological conditions, and isotopic signatures were able to discriminate biogenic methane (cattle) from thermogenic (natural-gas) sources. Monitoring of a post-HF nitrogen-lift (well-cleaning) operation at PNR detected the release of atmospheric emissions of methane (4.2 \ub1 1.4 t CH4). Groundwater monitoring around KMA identified high baseline methane concentrations and detected ethane and propane at some locations. Dissolved methane was inferred from stable-isotopic evidence as overwhelmingly of biogenic origin. Groundwater-quality monitoring around PNR found no evidence of HF-induced impacts. Two approaches for modelling induced seismicity and associated seismic risk were developed using observations of seismicity and operational parameters from PNR in 2018 and 2019. Novel methodologies developed for monitoring include use of machine learning to identify fugitive atmospheric methane, Bayesian statistics to assess changes to groundwater quality, a seismicity forecasting model seeded by the HF-fluid injection rate and high-resolution monitoring of soil-gas methane. The project developed a risk-assessment framework, aligned with ISO 31000 risk-management principles, to assess the theoretical combined and cumulative environmental risks from operations over time. This demonstrated the spatial and temporal evolution of risk profiles: seismic and atmospheric impacts from the shale-gas operations are modelled to be localised and short-lived, while risk to groundwater quality is longer-term

    A Carbon Nanofilament-Bead Necklace

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    Carbon nanofilaments with carbon beads grown on their surfaces were successfully synthesized reproducibly by a floating catalyst CVD method. The nanofilaments hosting the pearl-like structures typically show an average diameter of about 60 nm, which mostly consists of low-ordered graphite layers. The beads with diameter range 150−450 nm are composed of hundreds of crumpled and random graphite layers. The mechanism for the formation of these beaded nanofilaments is ascribed to two nucleation processes of the pyrolytic carbon deposition, arising from a temperature gradient between different parts of the reaction chamber. Furthermore, the Raman scattering properties of the beaded nanofilaments have been measured, as well as their confocal Raman G-line images. The Raman spectra reveal that that the trunks of the nanofilaments have better graphitic properties than the beads, which is consistent with the HRTEM analysis. The beaded nanofilaments are expected to have high potential applications in composites, which should exhibit both particle- and fiber-reinforcing functions for the host matrixes

    Pain outcomes in patients with bone metastases from advanced cancer: assessment and management with bone-targeting agents

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    Bone metastases in advanced cancer frequently cause painful complications that impair patient physical activity and negatively affect quality of life. Pain is often underreported and poorly managed in these patients. The most commonly used pain assessment instruments are visual analogue scales, a single-item measure, and the Brief Pain Inventory Questionnaire-Short Form. The World Health Organization analgesic ladder and the Analgesic Quantification Algorithm are used to evaluate analgesic use. Bone-targeting agents, such as denosumab or bisphosphonates, prevent skeletal complications (i.e., radiation to bone, pathologic fractures, surgery to bone, and spinal cord compression) and can also improve pain outcomes in patients with metastatic bone disease. We have reviewed pain outcomes and analgesic use and reported pain data from an integrated analysis of randomized controlled studies of denosumab versus the bisphosphonate zoledronic acid (ZA) in patients with bone metastases from advanced solid tumors. Intravenous bisphosphonates improved pain outcomes in patients with bone metastases from solid tumors. Compared with ZA, denosumab further prevented pain worsening and delayed the need for treatment with strong opioids. In patients with no or mild pain at baseline, denosumab reduced the risk of increasing pain severity and delayed pain worsening along with the time to increased pain interference compared with ZA, suggesting that use of denosumab (with appropriate calcium and vitamin D supplementation) before patients develop bone pain may improve outcomes. These data also support the use of validated pain assessments to optimize treatment and reduce the burden of pain associated with metastatic bone disease

    Phytoplankton dynamics in relation to seasonal variability and upwelling and relaxation patterns at the mouth of Ria de Aveiro (West Iberian Margin) over a four-year period

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    From June 2004 to December 2007, samples were weekly collected at a fixed station located at the mouth of Ria de Aveiro (West Iberian Margin). We examined the seasonal and inter-annual fluctuations in composition and community structure of the phytoplankton in relation to the main environmental drivers and assessed the influence of the oceano-graphic regime, namely changes in frequency and intensity of upwelling events, over the dynamics of the phytoplankton assemblage. The samples were consistently handled and a final subset of 136 OTUs (taxa with relative abundance > 0.01%) was subsequently submitted to various multivariate analyses. The phytoplankton assemblage showed significant changes at all temporal scales but with an overriding importance of seasonality over longer-(inter-annual) or shorter-term fluctuations (upwelling-related). Sea-surface temperature, salinity and maximum upwelling index were retrieved as the main driver of seasonal change. Seasonal signal was most evident in the fluctuations of chlorophyll a concentration and in the high turnover from the winter to spring phytoplankton assemblage. The seasonal cycle of production and succession was disturbed by upwelling events known to disrupt thermal stratification and induce changes in the phytoplankton assemblage. Our results indicate that both the frequency and intensity of physical forcing were important drivers of such variability, but the outcome in terms of species composition was highly dependent on the available local pool of species and the timing of those events in relation to the seasonal cycle. We conclude that duration, frequency and intensity of upwelling events, which vary seasonally and inter-annually, are paramount for maintaining long-term phytoplankton diversity likely by allowing unstable coexistence and incorporating species turnover at different scales. Our results contribute to the understanding of the complex mechanisms of coastal phytoplankton dynamics in relation to changing physical forcing which is fundamental to improve predictability of future prospects under climate change.Portuguese Foundation for Science and Technology (FCT, Portugal) [SFRH/BPD/ 94562/2013]; FEDER funds; national funds; CESAM [UID/AMB/50017]; FCT/MEC through national funds; FEDERinfo:eu-repo/semantics/publishedVersio

    Multiple populations in globular clusters. Lessons learned from the Milky Way globular clusters

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    Recent progress in studies of globular clusters has shown that they are not simple stellar populations, being rather made of multiple generations. Evidence stems both from photometry and spectroscopy. A new paradigm is then arising for the formation of massive star clusters, which includes several episodes of star formation. While this provides an explanation for several features of globular clusters, including the second parameter problem, it also opens new perspectives about the relation between globular clusters and the halo of our Galaxy, and by extension of all populations with a high specific frequency of globular clusters, such as, e.g., giant elliptical galaxies. We review progress in this area, focusing on the most recent studies. Several points remain to be properly understood, in particular those concerning the nature of the polluters producing the abundance pattern in the clusters and the typical timescale, the range of cluster masses where this phenomenon is active, and the relation between globular clusters and other satellites of our Galaxy.Comment: In press (The Astronomy and Astrophysics Review

    CT Scan Screening for Lung Cancer: Risk Factors for Nodules and Malignancy in a High-Risk Urban Cohort

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    Low-dose computed tomography (CT) for lung cancer screening can reduce lung cancer mortality. The National Lung Screening Trial reported a 20% reduction in lung cancer mortality in high-risk smokers. However, CT scanning is extremely sensitive and detects non-calcified nodules (NCNs) in 24-50% of subjects, suggesting an unacceptably high false-positive rate. We hypothesized that by reviewing demographic, clinical and nodule characteristics, we could identify risk factors associated with the presence of nodules on screening CT, and with the probability that a NCN was malignant.We performed a longitudinal lung cancer biomarker discovery trial (NYU LCBC) that included low-dose CT-screening of high-risk individuals over 50 years of age, with more than 20 pack-year smoking histories, living in an urban setting, and with a potential for asbestos exposure. We used case-control studies to identify risk factors associated with the presence of nodules (n=625) versus no nodules (n=557), and lung cancer patients (n=30) versus benign nodules (n=128).The NYU LCBC followed 1182 study subjects prospectively over a 10-year period. We found 52% to have NCNs >4 mm on their baseline screen. Most of the nodules were stable, and 9.7% of solid and 26.2% of sub-solid nodules resolved. We diagnosed 30 lung cancers, 26 stage I. Three patients had synchronous primary lung cancers or multifocal disease. Thus, there were 33 lung cancers: 10 incident, and 23 prevalent. A sub-group of the prevalent group were stable for a prolonged period prior to diagnosis. These were all stage I at diagnosis and 12/13 were adenocarcinomas.NCNs are common among CT-screened high-risk subjects and can often be managed conservatively. Risk factors for malignancy included increasing age, size and number of nodules, reduced FEV1 and FVC, and increased pack-years smoking. A sub-group of screen-detected cancers are slow-growing and may contribute to over-diagnosis and lead-time biases

    Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

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    BACKGROUND: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored. METHODOLOGY: This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. CONCLUSIONS: Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets
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