A new analysis of debris mitigation and removal using networks

Modelling studies have shown that the implementation of mitigation guidelines, which aim to reduce the amount of new debris generated on-orbit, is an important requirement of future space activities but may be insufficient to stabilise the near-Earth debris environment. The role of a variety of mitigation practices in stabilising the environment has been investigated over the last decade, as has the potential of active debris removal (ADR) methods in recent work. We present a theoretical approach to the analysis of the debris environment that is based on the study of networks, composed of vertices and edges, which describe the dynamic relationships between Earth satellites in the debris system. Future projections of the 10 cm and larger satellite population in a non-mitigation scenario, conducted with the DAMAGE model, are used to illustrate key aspects of this approach. Information from the DAMAGE projections are used to reconstruct a network in which vertices represent satellites and edges encapsulate conjunctions between collision pairs. The network structure is then quantified using statistical measures, providing a numerical baseline for this future projection scenario. Finally, the impact of mitigation strategies and active debris removal, which can be mapped onto the network by altering or removing edges and vertices, can be assessed in terms of the changes from this baseline. The paper introduces the network methodology, highlights the ways in which this approach can be used to formalise criteria for debris mitigation and removal. It then summarises changes to the adopted network that correspond to an increasing stability and changes that represent a decreasing stability of the future debris environment

Assessing the use of network theory as a method for developing a targeted approach to Active Debris Removal

This thesis reports on the application of network theory to data representing space debris in Low Earth Orbit. The research was designed with a view to developing a targeted approach to Active Debris Removal (ADR). The need for remediation, via ADR, of the space debris environment is regarded as the only means by which we can control the growth of the future debris population to maintain use of Earth orbit. A targeted approach to ADR is required to remove the objects that pose the greatest risk in terms of the creation of further debris by explosions or collisions in the future. Methods of determining target criteria are debated in the literature. Network theory is introduced here as an alternative method that, unlike other methods, does not treat debris-producing events in isolation and examines the role of objects in series of conjunctions. The research involved using networks to represent various aspects of the space debris environment. Network theory analysis was carried out on the datasets to determine specific characteristics such as the presence of clustering and the extent of disassortative mixing. Once general characteristics of the 'space debris networks' were determined, two case studies were used as preliminary investigations to assess the use of network theory for targeting objects for removal. The research shows that network theory can be used to determine that `space debris networks' are robust and disassortative. Although there are limitations due to the uncertainties in the data used to create the networks, the findings suggest that careful development and application of target criteria would result in successful ADR

The space debris environment: future evolution

Space debris represents a significant risk to satellite operations, due to the possibility of damaging or catastrophic collisions. Consequently, many satellite operators screen the orbiting population for close approaches with their on-orbit assets and a public conjunction assessment service, Satellite Orbital Conjunction Reports Assessing Threatening Encounters in Space (SOCRATES), generates close approach predictions on a daily basis for all satellite payloads in the catalogue. These screening capabilities are used to inform operational decisions relating to risk mitigation but it is anticipated that the demands placed on these services will increase as debris becomes more prolific. This hypothesis is explored in a preliminary analysis of conjunction data for the years 2004 to 2009 and a new ‘Business As Usual’ study using the Debris Analysis and Monitoring Architecture for the Geosynchronous Environment (DAMAGE) model. The results suggest a 50% increase in the number of close approaches reported by SOCRATES (or its equivalent) within the next ten years. By 2059, daily conjunction reports could contain over 50,000 close approaches below 5 km, affecting the demands placed on tracking facilities and satellite resources

The Family Model Stress and Maternal Psychological Symptoms: Mediated Pathways From Economic Hardship to Parenting Family Life Project Key Investigators

Although much of the extant research on low-income families has targeted parental depression as the predominant psychological response to economic hardship, the current study examined a range of maternal psychological symptoms that may mediate the relations between early economic pressure and later parenting behaviors. A family stress model was examined using data from 1,142 mothers living in 2 areas of high rural poverty, focusing on the infancy through toddlerhood period. Maternal questionnaires and observations of mother-child interactions were collected across 4 time points (6, 15, 24, and 36 months). Results from structural equation analyses indicated that early economic pressure was significantly related to a variety of symptoms (depression, hostility, anxiety, and somatization), but only depression and somatization were significantly related to decreased levels of sensitive, supportive parenting behaviors. In contrast, anxiety was positively associated with sensitive parenting. Depression and anxiety were both found to mediate the relations between economic pressure and sensitive parenting behaviors. Results further suggest that mothers did not experience change in objective economic hardship over time but did experience a small decrease in economic pressure. Discussion centers on the apparent indirect influence of early economic hardship on later psychological symptoms and parenting behaviors, as well as detailing the need for broader and more complex perspectives on maternal psychological responses that arise as a result of economic disadvantage

Identifying critically ill children at high risk of acute kidney injury and renal replacement therapy

Acute kidney injury (AKI), a common complication in paediatric intensive care units (PICU), is associated with increased morbidity and mortality. In this single centre, prospective, observational cohort study, neutrophil gelatinase-associated lipocalin in urine (uNGAL) and plasma (pNGAL) and renal angina index (RAI), and combinations of these markers, were assessed for their ability to predict severe (stage 2 or 3) AKI in children and young people admitted to PICU. In PICU children and young people had initial and serial uNGAL and pNGAL measurements, RAI calculation on day 1, and collection of clinical data, including serum creatinine measurements. Primary outcomes were severe AKI and renal replacement therapy (RRT). Secondary outcomes were length of stay, hospital acquired infection and mortality. The area under the Receiver Operating Characteristic (ROC) curves and Youden index was used to determine biomarker performance and identify optimum cut-off values. Of 657 children recruited, 104 met criteria for severe AKI (15∙8%) and 47 (7∙2%) required RRT. Severe AKI was associated with increased length of stay, hospital acquired infection, and mortality. The area under the curve (AUC) for severe AKI prediction for Day 1 uNGAL, Day 1 pNGAL and RAI were 0.75 (95% Confidence Interval [CI] 0∙69, 0∙81), 0∙64 (95% CI 0∙56, 0∙72), and 0.73 (95% CI 0∙65, 0∙80) respectively. The optimal combination of measures was RAI and day 1 uNGAL, giving an AUC of 0∙80 for severe AKI prediction (95% CI 0∙71, 0∙88). In this heterogenous PICU cohort, urine or plasma NGAL in isolation had poorer prediction accuracy for severe AKI than in previously reported homogeneous populations. However, when combined together with RAI, they produced good prediction for severe AKI

Procalcitonin, C-reactive protein, neutrophil gelatinase-associated lipocalin, resistin and the APTT waveform for the early diagnosis of serious bacterial infection and prediction of outcome in critically ill children.

ObjectiveBacterial Infections remains a leading cause of death in the Paediatric Intensive Care Unit (PICU). In this era of rising antimicrobial resistance, new tools are needed to guide antimicrobial use. The aim of this study was to investigate the accuracy of procalcitonin (PCT), neutrophil gelatinase-associated lipocalin (NGAL), resistin, activated partial thromboplastin time (aPTT) waveform and C-reactive protein (CRP) for the diagnosis of serious bacterial infection (SBI) in children on admission to PICU and their use as prognostic indicators.SettingA regional PICU in the United Kingdom.PatientsConsecutive PICU admissions between October 2010 and June 2012.MeasurementsBlood samples were collected daily for biomarker measurement. The primary outcome measure was performance of study biomarkers for diagnosis of SBI on admission to PICU based on clinical, radiological and microbiological criteria. Secondary outcomes included durations of PICU stay and invasive ventilation and 28-day mortality. Patients were followed up to day 28 post-admission.Main resultsA total of 657 patients were included in the study. 92 patients (14%) fulfilled criteria for SBI. 28-day mortality was 2.6% (17/657), but 8.7% (8/92) for patients with SBI. The combination of PCT, resistin, plasma NGAL and CRP resulted in the greatest net reclassification improvement compared to CRP alone (0.69, pConclusionCombinations of biomarkers, including PCT, may improve accurate and timely identification of SBI on admission to PICU