Low thrust orbit determination program

Logical flow and guidelines are provided for the construction of a low thrust orbit determination computer program. The program, tentatively called FRACAS (filter response analysis for continuously accelerating spacecraft), is capable of generating a reference low thrust trajectory, performing a linear covariance analysis of guidance and navigation processes, and analyzing trajectory nonlinearities in Monte Carlo fashion. The choice of trajectory, guidance and navigation models has been made after extensive literature surveys and investigation of previous software. A key part of program design relied upon experience gained in developing and using Martin Marietta Aerospace programs: TOPSEP (Targeting/Optimization for Solar Electric Propulsion), GODSEP (Guidance and Orbit Determination for SEP) and SIMSEP (Simulation of SEP)

Mission Analysis Program for Solar Electric Propulsion (MAPSEP). Volume 1: Analytical manual

The mission analysis program for solar electric propulsion (MAPSEP) is comprised of the basic modes: TOPSEP (trajectory generation), GODSEP (linear error analysis), and SIMSEP (simulation). The program is designed to analyze any low thrust mission with respect to trajectory performance, guidance and navigation, and to provide system related requirements for the purpose of vehicle design. The MAPSEP organization is described along with all models and algorithms. Topics discussed include: trajectory and error covariance propagation methods, orbit determination processes, thrust modeling, and trajectory correction (guidance) schemes

Mission Analysis Program for Solar Electric Propulsion (MAPSEP). Volume 3: Program manual

The internal structure of MAPSEP is described. Topics discussed include: macrologic, variable definition, subroutines, and logical flow. Information is given to facilitate modifications to the models and algorithms of MAPSEP

Mission Analysis Program for Solar Electric Propulsion (MAPSEP). Volume 2: User's manual

A user's manual which describes input/output routines and recommended operating procedures relating to MAPSEP is presented. Samples runs are included

Metacognition, Social Cognition, and Mentalizing In Psychosis: Are These Distinct Constructs When It Comes To Subjective Experience Or Are We Just Splitting Hairs?

Research using the integrated model of metacognition has suggested that the construct of metacognition could quantify the spectrum of activities that, if impaired, might cause many of the subjective disturbances found in psychosis. Research on social cognition and mentalizing in psychosis, however, has also pointed to underlying deficits in how persons make sense of their experience of themselves and others. To explore the question of whether metacognitive research in psychosis offers unique insight in the midst of these other two emerging fields, we have offered a review of the constructs and research from each field. Following that summary, we discuss ways in which research on metacognition may be distinguished from research on social cognition and mentalizing in three broad categories: (1) experimental procedures, (2) theoretical advances, and (3) clinical applications or indicated interventions. In terms of its research methods, we will describe how metacognition makes a unique contribution to understanding disturbances in how persons make sense of and interpret their own experiences within the flow of life. We will next discuss how metacognitive research in psychosis uniquely describes an architecture which when compromised – as often occurs in psychosis – results in the loss of persons’ sense of purpose, possibilities, place in the world and cohesiveness of self. Turning to clinical issues, we explore how metacognitive research offers an operational model of the architecture which if repaired or restored should promote the recovery of a coherent sense of self and others in psychosis. Finally, we discuss the concrete implications of this for recovery-oriented treatment for psychosis as well as the need for further research on the commonalities of these approaches

Diabetes medications and associations with Covid-19 outcomes in the N3C database: A national retrospective cohort study

Background While vaccination is the most important way to combat the SARS-CoV-2 pandemic, there may still be a need for early outpatient treatment that is safe, inexpensive, and currently widely available in parts of the world that do not have access to the vaccine. There are in-silico, in-vitro, and in-tissue data suggesting that metformin inhibits the viral life cycle, as well as observational data suggesting that metformin use before infection with SARS-CoV2 is associated with less severe COVID-19. Previous observational analyses from single-center cohorts have been limited by size. Methods Conducted a retrospective cohort analysis in adults with type 2 diabetes (T2DM) for associations between metformin use and COVID-19 outcomes with an active comparator design of prevalent users of therapeutically equivalent diabetes monotherapy: metformin versus dipeptidyl-peptidase-4-inhibitors (DPP4i) and sulfonylureas (SU). This took place in the National COVID Cohort Collaborative (N3C) longitudinal U.S. cohort of adults with +SARS-CoV-2 result between January 1 2020 to June 1 2021. Findings included hospitalization or ventilation or mortality from COVID-19. Back pain was assessed as a negative control outcome. Results 6,626 adults with T2DM and +SARS-CoV-2 from 36 sites. Mean age was 60.7 +/- 12.0 years; 48.7% male; 56.7% White, 21.9% Black, 3.5% Asian, and 16.7% Latinx. Mean BMI was 34.1 +/- 7.8kg/m2. Overall 14.5% of the sample was hospitalized; 1.5% received mechanical ventilation; and 1.8% died. In adjusted outcomes, compared to DPP4i, metformin had non-significant associations with reduced need for ventilation (RR 0.68, 0.32–1.44), and mortality (RR 0.82, 0.41–1.64). Compared to SU, metformin was associated with a lower risk of ventilation (RR 0.5, 95% CI 0.28–0.98, p = 0.044) and mortality (RR 0.56, 95% CI 0.33–0.97, p = 0.037). There was no difference in unadjusted or adjusted results of the negative control. Conclusions There were clinically significant associations between metformin use and less severe COVID-19 compared to SU, but not compared to DPP4i. New-user studies and randomized trials are needed to assess early outpatient treatment and post-exposure prophylaxis with therapeutics that are safe in adults, children, pregnancy and available worldwide

Vaccination Against SARS-CoV-2 Is Associated With a Lower Viral Load and Likelihood of Systemic Symptoms

Background: Data conflict on whether vaccination decreases severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load. The objective of this analysis was to compare baseline viral load and symptoms between vaccinated and unvaccinated adults enrolled in a randomized trial of outpatient coronavirus disease 2019 (COVID-19) treatment. Methods: Baseline data from the first 433 sequential participants enrolling into the COVID-OUT trial were analyzed. Adults aged 30-85 with a body mass index (BMI) ≥25 kg/m2 were eligible within 3 days of a positive SARS-CoV-2 test and <7 days of symptoms. Log10 polymerase chain reaction viral loads were normalized to human RNase P by vaccination status, by time from vaccination, and by symptoms. Results: Two hundred seventy-four participants with known vaccination status contributed optional nasal swabs for viral load measurement: median age, 46 years; median (interquartile range) BMI 31.2 (27.4-36.4) kg/m2. Overall, 159 (58%) were women, and 217 (80%) were White. The mean relative log10 viral load for those vaccinated <6 months from the date of enrollment was 0.11 (95% CI, -0.48 to 0.71), which was significantly lower than the unvaccinated group (P = .01). Those vaccinated ≥6 months before enrollment did not differ from the unvaccinated with respect to viral load (mean, 0.99; 95% CI, -0.41 to 2.40; P = .85). The vaccinated group had fewer moderate/severe symptoms of subjective fever, chills, myalgias, nausea, and diarrhea (all P < .05). Conclusions: These data suggest that vaccination within 6 months of infection is associated with a lower viral load, and vaccination was associated with a lower likelihood of having systemic symptoms

Randomized Trial of Metformin, Ivermectin, and Fluvoxamine for Covid-19

BACKGROUND Early treatment to prevent severe coronavirus disease 2019 (Covid-19) is an important component of the comprehensive response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. METHODS In this phase 3, double-blind, randomized, placebo-controlled trial, we used a 2-by-3 factorial design to test the effectiveness of three repurposed drugs - metformin, ivermectin, and fluvoxamine - in preventing serious SARS-CoV-2 infection in nonhospitalized adults who had been enrolled within 3 days after a confirmed diagnosis of infection and less than 7 days after the onset of symptoms. The patients were between the ages of 30 and 85 years, and all had either overweight or obesity. The primary composite end point was hypoxemia (≤93% oxygen saturation on home oximetry), emergency department visit, hospitalization, or death. All analyses used controls who had undergone concurrent randomization and were adjusted for SARSCoV-2 vaccination and receipt of other trial medications. RESULTS A total of 1431 patients underwent randomization; of these patients, 1323 were included in the primary analysis. The median age of the patients was 46 years; 56% were female (6% of whom were pregnant), and 52% had been vaccinated. The adjusted odds ratio for a primary event was 0.84 (95% confidence interval [CI], 0.66 to 1.09; P=0.19) with metformin, 1.05 (95% CI, 0.76 to 1.45; P=0.78) with ivermectin, and 0.94 (95% CI, 0.66 to 1.36; P=0.75) with fluvoxamine. In prespecified secondary analyses, the adjusted odds ratio for emergency department visit, hospitalization, or death was 0.58 (95% CI, 0.35 to 0.94) with metformin, 1.39 (95% CI, 0.72 to 2.69) with ivermectin, and 1.17 (95% CI, 0.57 to 2.40) with fluvoxamine. The adjusted odds ratio for hospitalization or death was 0.47 (95% CI, 0.20 to 1.11) with metformin, 0.73 (95% CI, 0.19 to 2.77) with ivermectin, and 1.11 (95% CI, 0.33 to 3.76) with fluvoxamine. CONCLUSIONS None of the three medications that were evaluated prevented the occurrence of hypoxemia, an emergency department visit, hospitalization, or death associated with Covid-19