Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations

Accurate determination of thermospheric neutral density holds crucial importance for satellite drag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and three physicsâ based models of the ionosphereâ thermosphere are compared with the neutral densities along the Challenging Microâ Satellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias), (2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set of metrics for the neutral density.Plain Language SummaryThermospheric neutral density is the largest source of uncertainty in atmospheric drag calculations. Consequently, mission and maneuver planning, satellite lifetime predictions, collision avoidance, and orbit determination depend on the accurate estimation of the thermospheric neutral density. Thermospheric neutral density varies in different timescales. In short timescales, the largest variations occur due to the geomagnetic storms. Several empirical and physicsâ based models of the ionosphereâ thermosphere system are used for estimating the variations in the neutral density. However, the storm time responses from the models are clouded by the climatology (background variations), upon which the effect of geomagnetic storms is superimposed. In this work, we show that it is critical to use reference levels for the neutral density to extract the true performance of the models for the evaluation of the storm time performances. We demonstrate that mean absolute error, prediction efficiency, and normalized root mean square error should be considered together for the performance evaluations, since each of them provides different aspects of the error.Key PointsUsing the average and maximum values of neutral densities to determine the model performances can be misleadingRemoving the quiet time trend from the neutral density reveals the actual performance of the model in simulating the storm time variationsMean absolute error, prediction efficiency, and normalized root mean square error should be considered together for the evaluationsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/1/swe20816_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/2/swe20816-sup-0001-2018SW002033-SI.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/3/swe20816.pd

FLT1 and transcriptome-wide polyadenylation site (PAS) analysis in preeclampsia

Maternal symptoms of preeclampsia (PE) are primarily driven by excess anti-angiogenic factors originating from the placenta. Chief among these are soluble Flt1 proteins (sFlt1s) produced from alternatively polyadenylated mRNA isoforms. Here we used polyadenylation site sequencing (PAS-Seq) of RNA from normal and PE human placentae to interrogate transcriptome-wide gene expression and alternative polyadenylation signatures associated with early-onset PE (EO-PE; symptom onset 34 weeks) cohorts. While we observed no general shift in alternative polyadenylation associated with PE, the EO-PE and LO-PE cohorts do exhibit gene expression profiles distinct from both each other and from normal placentae. The only two genes upregulated across all transcriptome-wide PE analyses to date (microarray, RNA-Seq and PAS-Seq) are NRIP1 (RIP140), a transcriptional co-regulator linked to metabolic syndromes associated with obesity, and Flt1. Consistent with sFlt1 overproduction being a significant driver of clinical symptoms, placental Flt1 mRNA levels strongly correlate with maternal blood pressure. For Flt1, just three mRNA isoforms account for > 94% of all transcripts, with increased transcription of the entire locus driving Flt1 upregulation in both EO-PE and LO-PE. These three isoforms thus represent potential targets for therapeutic RNA interference (RNAi) in both early and late presentations

MRI Indices of Cortical Development in Young People With Psychotic Experiences: Influence of Genetic Risk and Persistence of Symptoms

Background Psychotic experiences (PEs) are considered part of an extended psychosis phenotype and are associated with an elevated risk of developing a psychotic disorder. Risk of transition increases with persistence of PEs, and this is thought to be modulated by genetic and environmental factors. However, it is unclear if persistence is associated with progressive schizophrenia-like changes in neuroanatomy. Methods We examined cortical morphometry using MRI in 247 young adults, from a population-based cohort, assessed for the presence of PEs at ages 18 and 20. We then incorporated a polygenic risk score for schizophrenia (PRS) to elucidate the effects of high genetic risk. Finally, we used atlas-based tractography data to examine the underlying white matter. Results Individuals with persisting PEs showed reductions in gyrification (local gyrification index: lGI) in the left temporal gyrus as well as atypical associations with brain volume (TBV) in the left occipital and right prefrontal gyri. No main effect was found for the PRS, but interaction effects with PEs were identified in the orbitofrontal, parietal, and temporal regions. Examination of underlying white matter did not provide strong evidence of further disturbances. Conclusions Disturbances in lGI were similar to schizophrenia but findings were mostly limited to those with persistent PEs. These could reflect subtle changes that worsen with impending psychosis or reflect an early vulnerability associated with the persistence of PEs. The lack of clear differences in underlying white matter suggests our findings reflect early disturbances in cortical expansion rather than progressive changes in brain structure

Packages of Care for Depression in Low- and Middle-Income Countries

In the first in a series of six articles on packages of care for mental disorders in low- and middle-income countries, Neerja Chowdary and colleagues discuss the treatment of depression

Cost-effectiveness of nurse-led self-help for recurrent depression in the primary care setting: design of a pragmatic randomized trial

<p>Abstract</p> <p>Background</p> <p>Major Depressive Disorder is a leading cause of disability, tends to run a recurrent course and is associated with substantial economic costs due to increased healthcare utilization and productivity losses. Interventions aimed at the prevention of recurrences may reduce patients' suffering and costs. Besides antidepressants, several psychological treatments such as preventive cognitive therapy (PCT) are effective in the prevention of recurrences of depression. Yet, many patients find long-term use of antidepressants unattractive, do not want to engage in therapy sessions and in the primary care setting psychologists are often not available. Therefore, it is important to study whether PCT can be used in a nurse-led self-help format in primary care. This study sets out to test the hypothesis that usual care plus nurse-led self-help for recurrent depression in primary care is feasible, acceptable and cost-effective compared to usual care only.</p> <p>Design</p> <p>Patients are randomly assigned to ‘nurse-led self-help treatment plus usual care’ (134 participants) or ‘usual care’ (134 participants). Randomisation is stratified according to the number of previous episodes (2 or 3 previous episodes versus 4 or more). The primary clinical outcome is the cumulative recurrence rate of depression meeting DSM-IV criteria as assessed by the Structured-Clinical-Interview-for-DSM-IV- disorders at one year after completion of the intervention. Secondary clinical outcomes are quality of life, severity of depressive symptoms, co-morbid psychopathology and self-efficacy. As putative effect-moderators, demographic characteristics, number of previous episodes, type of treatment during previous episodes, age of onset, self-efficacy and symptoms of pain and fatigue are assessed. Cumulative recurrence rate ratios are obtained under a Poisson regression model. Number-needed-to-be-treated is calculated as the inverse of the risk-difference. The economic evaluation is conducted from a societal perspective, both as a cost-effectiveness analysis (costs per depression free survival year) and as a cost-utility analysis (costs per quality adjusted life-year).</p> <p>Discussion</p> <p>The purpose of this paper is to outline the rationale and design of a nurse-led, cognitive therapy based self-help aimed at preventing recurrence of depression in a primary care setting. Only few studies have focused on psychological self-help interventions aimed at the prevention of recurrences in primary care patients.</p> <p>Trial registration</p> <p>NTR3001 (<url>http://www.trialregister.nl</url>)</p

The Earth: Plasma Sources, Losses, and Transport Processes

This paper reviews the state of knowledge concerning the source of magnetospheric plasma at Earth. Source of plasma, its acceleration and transport throughout the system, its consequences on system dynamics, and its loss are all discussed. Both observational and modeling advances since the last time this subject was covered in detail (Hultqvist et al., Magnetospheric Plasma Sources and Losses, 1999) are addressed

Cooperation between Russian research organizations and industrial companies: factors and problems

The study is focused on the cooperation of Russian companies with research organizations in implementing R&D projects during technological innovation. Taking into account behavioral changes, authors carry out a micro-level analysis based on empirical data of executive survey of over 600 Russian industrial firms (2011—2012) and about 350 research organizations and universities (2012). The authors emphasize the key factors of firms’ demand for outsourcing R&D reveal the main barriers to the development of university-industry cooperation and their particularities for different cooperation actors. The analysis shows that there is a positive relation between the size of a company and R&D outsourcing. As for the factor of age, the highest cooperation activity of Russian firms is observed among enterprises founded over 20 years ago. As far as concernes cooperation activity of research organizations, large ones are significantly more likely to cooperate with business. A common prerequisite for research organizations' R&D cooperation with business is sufficient academic ranking. Business and science evaluate differently various obstacles to effective cooperation. For firms, the main problems are the inflated costs of national R&Ds, insufficient research organizations’ orientation at company needs, and low quality of developments. As for representatives of research organizations, they mention as barriers primarily the lack of companies' receptivity to innovation and inadequate information about promising developments. Businesses are more optimistic about cooperation with science if they already have a relevant experience of interaction. In the case of research organizations we observe a different pattern: most problems seem more significant to organizations conducting R&D in business interests

Retrieving climate change dependent Sea Surface Temperature (SST) in Southern Turkey by using Landsat thermal imagery

597-605Sea Surface Temperature (SST) is one of the most significant parameters in oceanography. SST data can be used to analyse the ocean and marine environments. SST is required to study Marine Protected Areas (MPAs), identification of invasive species spreading areas, climate change, sea-level rise and pollution predictions. For more than 30 years, satellites have provided images that can assist in understanding changes in marine ecosystems. Remote data can be used as a real-time instrument for creating SST datasets. In this study, Landsat thermal data is used to retrieve sea surface temperatures. The study area of the research includes 1025 points belonging to four cross-sections of Gökova Bay in Southern Turkey. SST values were retrieved using satellite measurements for the first time in Gökova Bay. Landsat 4-5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager/Thermal Infrared Sensor imagery were analysed, covering the period from 1987 to 2017. Using geographical information systems, the satellite images were processed with algorithms, and changes in sea surface temperature were evaluated in spatiotemporal terms. As a result, a temperature anomaly of about 3 °C above average was observed in 2011 and 2015. Climate change has been shown to cause fishing losses in Gökova Bay. A relationship was identified between invasive species entering Gökova Bay and sea surface temperature data. The study method has become a useful alternative method in cases where there is a lack of in-situ data