923 research outputs found

    Industry solutions on Smart Farming Technology

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    Smart AKIS project aims at examining the suitability and use of Smart Farming Technologies (SFT) in the EU Agriculture involving farmers, the agricultural machinery industry, academia, research centers, agricultural engineering and public bodies. The purpose of this document is to present the report on methodology, standards and current findings within the Smart-AKIS project. The report provides a selection guide, detailing the issues that have to be taken into account in order to ensure the collection of data in a homogeneous way, and avoid misconceptions. This document is an update on the progress made in the data assessment that is currently ongoing on captuing industrial products related to SFTs that have not yet reached mainstreaming agriculture. This report is organized in three chapters. The first chapter will introduce current work on the Smart-Akis project as well as the objective of this document in the overall smart-akis framework. The second chapter will present the methodological approach that has taken to reach the industrial partners, the specific questions and the analysis procedure, wjhile the last chapter will present the interim results. The last chapter summarizes conclusion

    Yield sensing technologies for perennial and annual horticultural crops: a review

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    Yield maps provide a detailed account of crop production and potential revenue of a farm. This level of details enables a range of possibilities from improving input management, conducting on-farm experimentation, or generating profitability map, thus creating value for farmers. While this technology is widely available for field crops such as maize, soybean and grain, few yield sensing systems exist for horticultural crops such as berries, field vegetable or orchards. Nevertheless, a wide range of techniques and technologies have been investigated as potential means of sensing crop yield for horticultural crops. This paper reviews yield monitoring approaches that can be divided into proximal, either direct or indirect, and remote measurement principles. It reviews remote sensing as a way to estimate and forecast yield prior to harvest. For each approach, basic principles are explained as well as examples of application in horticultural crops and success rate. The different approaches provide whether a deterministic (direct measurement of weight for instance) or an empirical (capacitance measurements correlated to weight for instance) result, which may impact transferability. The discussion also covers the level of precision required for different tasks and the trend and future perspectives. This review demonstrated the need for more commercial solutions to map yield of horticultural crops. It also showed that several approaches have demonstrated high success rate and that combining technologies may be the best way to provide enough accuracy and robustness for future commercial systems

    Elevated Baseline C-Reactive Protein as a Predictor of Outcome After Aneurysmal Subarachnoid Hemorrhage: Data From the Simvastatin in Aneurysmal Subarachnoid Hemorrhage (STASH) Trial.

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    BACKGROUND: There remains a proportion of patients with unfavorable outcomes after aneurysmal subarachnoid hemorrhage, of particular relevance in those who present with a good clinical grade. A forewarning of those at risk provides an opportunity towards more intensive monitoring, investigation, and prophylactic treatment prior to the clinical manifestation of advancing cerebral injury. OBJECTIVE: To assess whether biochemical markers sampled in the first days after the initial hemorrhage can predict poor outcome. METHODS: All patients recruited to the multicenter Simvastatin in Aneurysmal Hemorrhage Trial (STASH) were included. Baseline biochemical profiles were taken between time of ictus and day 4 post ictus. The t-test compared outcomes, and a backwards stepwise binary logistic regression was used to determine the factors providing independent prediction of an unfavorable outcome. RESULTS: Baseline biochemical data were obtained in approximately 91% of cases from 803 patients. On admission, 73% of patients were good grade (World Federation of Neurological Surgeons grades 1 or 2); however, 84% had a Fisher grade 3 or 4 on computed tomographic scan. For patients presenting with good grade on admission, higher levels of C-reactive protein, glucose, and white blood cells and lower levels of hematocrit, albumin, and hemoglobin were associated with poor outcome at discharge. C-reactive protein was found to be an independent predictor of outcome for patients presenting in good grade. CONCLUSION: Early recording of C-reactive protein may prove useful in detecting those good grade patients who are at greater risk of clinical deterioration and poor outcome.Financial support: British Heart Foundation. None of the authors have any personal or institutional financial interest in drugs or materials in the manuscript. PJK and PJH are supported by the Cambridge NIHR BRC and PJH is supported by a NIHR Research Professorship. We also acknowledge the support of the Cambridge Clinical Trials Unit, UK Clinical Research Network and all 35 participating sites.This is the final version of the article. It first appeared from Wolters Kluwer via http://dx.doi.org/10.1227/NEU.000000000000096

    The relationships between golf and health:A scoping review

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    OBJECTIVE: To assess the relationships between golf and health. DESIGN: Scoping review. DATA SOURCES: Published and unpublished reports of any age or language, identified by searching electronic databases, platforms, reference lists, websites and from consulting experts. REVIEW METHODS: A 3-step search strategy identified relevant published primary and secondary studies as well as grey literature. Identified studies were screened for final inclusion. Data were extracted using a standardised tool, to form (1) a descriptive analysis and (2) a thematic summary. RESULTS AND DISCUSSION: 4944 records were identified with an initial search. 301 studies met criteria for the scoping review. Golf can provide moderate intensity physical activity and is associated with physical health benefits that include improved cardiovascular, respiratory and metabolic profiles, and improved wellness. There is limited evidence related to golf and mental health. The incidence of golfing injury is moderate, with back injuries the most frequent. Accidental head injuries are rare, but can have serious consequences. CONCLUSIONS: Practitioners and policymakers can be encouraged to support more people to play golf, due to associated improved physical health and mental well-being, and a potential contribution to increased life expectancy. Injuries and illnesses associated with golf have been identified, and risk reduction strategies are warranted. Further research priorities include systematic reviews to further explore the cause and effect nature of the relationships described. Research characterising golf's contribution to muscular strengthening, balance and falls prevention as well as further assessing the associations and effects between golf and mental health are also indicated

    Regional pressure and temperature differences across the injured human brain : comparisons between intraparenchymal and ventricular measurements

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    Introduction: Intraparenchymal, multimodality sensors are commonly used in the management of patients with severe traumatic brain injury (TBI). The ‘gold standard’, based on accuracy, reliability and cost for intracranial pressure (ICP) monitoring is within the cerebral ventricle (external strain gauge). There are no standards yet for intracerebral temperature monitoring and little is known of temperature differences between brain tissue and ventricle. The aim of the study therefore was to determine pressure and temperature differences at intraparenchymal and ventricular sites during five days of continuous neurominitoring. Methods: Patients with severe TBI requiring emergency surgery. Inclusion criteria: patients who required ICP monitoring were eligible for recruitment. Two intracerebral probe types were used: a) intraventricular, dual parameter sensor (measuring pressure, temperature) with inbuilt catheter for CSF drainage: b) multiparameter intraparenchymal sensor measuring pressure, temperature and oxygen partial pressure. All sensors were inserted during surgery and under aseptic conditions. Results: Seventeen patients, 12 undergoing neurosurgery (decompressive craniectomy n=8, craniotomy n=4) aged 21–78 years were studied. Agreement of measures for 9540 brain tissue-ventricular temperature ‘pairs’ and 10,291 brain tissue-ventricular pressure ‘pairs’ were determined using mixed model to compare mean temperature and pressure for longitudinal data. There was no significant overall difference for mean temperature (p=0.92) or mean pressure readings (p=0.379) between tissue and ventricular sites. With 95.8% of paired temperature readings within 2SD (−0.4 to 0.4°C) differences in temperature between brain tissue and ventricle were clinically insignificant. For pressure, 93.5% of readings pairs fell within the 2SD range (−9.4756 to 7.8112 mmHg) (Fig. 2). However, for individual patients, agreement for mean tissue-ventricular pressure differences was poor on occasions. Conclusions: There is good overall agreement between paired temperature measurements obtained from deep white matter and brain ventricle in patients with and without early neurosurgery. For paired ICP measurements, 93.5% of readings were within 2SD of mean difference. Whilst the majority of paired readings were comparable (within 10mmHg) clinically relevant tissue-ventricular dissociations were noted. Further work is required to unravel the events responsible for short intervals of pressure dissociation before tissue pressure readings can be definitively accepted as a reliable surrogate for ventricular pressure.</p

    Mapping the Steroid Response to Major Trauma From Injury to Recovery : A Prospective Cohort Study

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    CONTEXT: Survival rates after severe injury are improving, but complication rates and outcomes are variable. OBJECTIVE: This cohort study addressed the lack of longitudinal data on the steroid response to major trauma and during recovery. DESIGN: We undertook a prospective, observational cohort study from time of injury to 6 months postinjury at a major UK trauma centre and a military rehabilitation unit, studying patients within 24 hours of major trauma (estimated New Injury Severity Score (NISS) > 15). MAIN OUTCOME MEASURES: We measured adrenal and gonadal steroids in serum and 24-hour urine by mass spectrometry, assessed muscle loss by ultrasound and nitrogen excretion, and recorded clinical outcomes (ventilator days, length of hospital stay, opioid use, incidence of organ dysfunction, and sepsis); results were analyzed by generalized mixed-effect linear models. FINDINGS: We screened 996 multiple injured adults, approached 106, and recruited 95 eligible patients; 87 survived. We analyzed all male survivors <50 years not treated with steroids (N = 60; median age 27 [interquartile range 24-31] years; median NISS 34 [29-44]). Urinary nitrogen excretion and muscle loss peaked after 1 and 6 weeks, respectively. Serum testosterone, dehydroepiandrosterone, and dehydroepiandrosterone sulfate decreased immediately after trauma and took 2, 4, and more than 6 months, respectively, to recover; opioid treatment delayed dehydroepiandrosterone recovery in a dose-dependent fashion. Androgens and precursors correlated with SOFA score and probability of sepsis. CONCLUSION: The catabolic response to severe injury was accompanied by acute and sustained androgen suppression. Whether androgen supplementation improves health outcomes after major trauma requires further investigation

    Measurement of substructure-dependent jet suppression in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

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    The ATLAS detector at the Large Hadron Collider has been used to measure jet substructure modification and suppression in Pb+Pb collisions at a nucleon–nucleon center-of-mass energy √sNN = 5.02 TeV in comparison with proton–proton (pp) collisions at √s = 5.02 TeV. The Pb+Pb data, collected in 2018, have an integrated luminosity of 1.72 nb−1, while the ppdata, collected in 2017, have an integrated luminosity of 260 pb−1. Jets used in this analysis are clustered using the anti-kt algorithm with a radius parameter R = 0.4. The jet constituents, defined by both tracking and calorimeter information, are used to determine the angular scale rg of the first hard splitting inside the jet by reclustering them using the Cambridge–Aachen algorithm and employing the soft-drop grooming technique. The nuclear modification factor, RAA, used to characterize jet suppression in Pb+Pb collisions, is presented differentially in rg, jet transverse momentum, and in intervals of collision centrality. The RAA value is observed to depend significantly on jet rg. Jets produced with the largest measured rg are found to be twice as suppressed as those with the smallest rg in central Pb+Pb collisions. The RAA values do not exhibit a strong variation with jet pT in any of the rg intervals. The rg and pT dependence of jet RAA is qualitatively consistent with a picture of jet quenching arising from coherence and provides the most direct evidence in support of this approach

    Anomaly detection search for new resonances decaying into a Higgs boson and a generic new particle X in hadronic final states using Formula Presented pp collisions with the ATLAS detector

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    A search is presented for a heavy resonance Formula Presented decaying into a Standard Model Higgs boson Formula Presented and a new particle Formula Presented in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at Formula Presented collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of Formula Presented. The search targets the high Formula Presented-mass region, where the Formula Presented and Formula Presented have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted Formula Presented particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark Formula Presented decay into two quarks, covering topologies where the Formula Presented is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into Formula Presented, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section Formula Presented) for signals with Formula Presented between 1.5 and 6 TeV and Formula Presented between 65 and 3000 GeV. A search is presented for a heavy resonance Y decaying into a Standard Model Higgs boson H and a new particle X in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at √ s = 13     TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139     fb − 1 . The search targets the high Y -mass region, where the H and X have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted X particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark X decay into two quarks, covering topologies where the X is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into b ¯ b , and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section σ ( p p → Y → X H → q ¯ q b ¯ b ) for signals with m Y between 1.5 and 6 TeV and m X between 65 and 3000 GeV
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